{ "version": 1, "discovery_version": 2, "works": [ { "id": "doi-10-1007-s10238-026-02130-6", "title": "A gene interaction network-based molecular taxonomy of dilated cardiomyopathy highlighting immune and inflammatory heterogeneity", "doi": "10.1007/s10238-026-02130-6", "year": 2026, "journal": "Clinical and Experimental Medicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.md", "paper_geo_status": "v2", "authors": [ "Youyang Zheng", "Fangfang Wan", "Shulun Ma", "Haijie Chen", "Leqi Wang", "Yuanrui Deng", "Ge Zhang", "Lei Song", "Mo Zhang" ], "doi_url": "https://doi.org/10.1007/s10238-026-02130-6", "publisher_url": null, "pmid": "41945162", "pmcid": "PMC13342204", "openalex_id": "https://openalex.org/W7151618557", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1007-s10238-026-02130-6.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1007-s10238-026-02130-6.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1007-s10238-026-02130-6.csl.json", "evidence_status": "reviewed_v2", "question_count": 7, "key_findings": [ { "id": "KF1", "claim": "Four public myocardial datasets supplied discovery and external subtype-assignment data.", "context": "Article-reported analysis subsets for DCM network taxonomy; no newly recruited clinical cohort", "evidence": [ { "label": "discovery subset", "value": "GSE5406: 86 DCM and 16 controls" }, { "label": "external subsets", "value": "GSE57338: 82/136; GSE116250: 37/14; GSE19303: 40/8 DCM/control samples" }, { "label": "reported sample totals", "value": "245 DCM and 174 controls across four datasets; no verified unique-person total" } ], "source_locator": "Methods: Data collection and preprocessing (Par6); Results: Cohort characteristics and interactome construction (Par22); Table 1 (Tab1); Figure 2E-G", "source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#kf1" }, { "id": "KF2", "claim": "Rank-based perturbation features provided a network representation for subtype discovery.", "context": "Expression-rank differences were compared with a control-derived reference before feature selection", "evidence": [ { "label": "mapped network", "value": "5,593 nodes and 107,063 edges" }, { "label": "selected features", "value": "27,937 discriminative edges" }, { "label": "feature-selection rule", "value": "intersection of the top 50% of edges for case-control difference and the top 50% for DCM variability" } ], "source_locator": "Methods: Quantifying gene interactions and Edge perturbation matrix construction (Par8-Par11); Results: Cohort characteristics and interactome construction (Par22) and Edge perturbation profiling (Par24); Figure 1", "source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#kf2" }, { "id": "KF3", "claim": "Three network subtypes were recovered and assigned across the discovery and validation datasets.", "context": "Retrospective molecular clustering evaluated with UMAP, silhouette analysis and nearest-template prediction", "evidence": [ { "label": "selected cluster count", "value": "K = 3" }, { "label": "EPS1 range", "value": "43.2-52.5% across analyzed datasets" }, { "label": "EPS2 range", "value": "40.0-44.2% across analyzed datasets" }, { "label": "EPS3 range", "value": "7.5-13.5% across analyzed datasets" } ], "source_locator": "Methods: Consensus clustering for subtype identification and Validation of clustering stability (Par13-Par14); Results: Consensus clustering identifies three stable DCM subtypes (Par25-Par26); Figure 2A-G", "source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#kf3" }, { "id": "KF4", "claim": "Coexpression modules and inferred immune patterns differed between the molecular subtypes.", "context": "Computational associations in the 74-sample WGCNA subset and gene-expression-based immune profiling; not direct immune-cell counting or causal perturbation", "evidence": [ { "label": "WGCNA subset and modules", "value": "74 DCM samples after outlier exclusion; 10 modules" }, { "label": "EPS1-associated module", "value": "540 genes; module-subtype r = 0.84" }, { "label": "EPS2-associated module", "value": "513 genes; module-subtype r = 0.74" }, { "label": "EPS3-associated module", "value": "87 genes; module-subtype r = 0.78" }, { "label": "interpretation", "value": "energy/proteostasis, humoral/platelet-related and respiratory-chain/endocytosis enrichment patterns differed; immune composition was inferred by ssGSEA" } ], "source_locator": "Methods: Identification of subtype-specific gene modules and Immune cell infiltration analysis (Par15-Par17); Results: Subtype-specific co-expression modules (Par28), Functional annotation of molecular subtypes (Par30-Par32), Distinct immune infiltration patterns (Par34); Figures 3-6A-C", "source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#kf4" }, { "id": "KF5", "claim": "EPS1 showed expression similarity to the IA/IgG responder group in an exploratory retrospective analysis.", "context": "Submap compared subtype expression with responder/non-responder profiles in GSE19303; this is not a randomized treatment comparison", "evidence": [ { "label": "response definition in the source cohort", "value": "at least 20% relative LVEF improvement together with at least 5 percentage points absolute improvement" }, { "label": "reported expression-matching result", "value": "EPS1 association with responder profiles remained significant after Bonferroni correction; an exact corrected P value is not supplied in the Results prose" }, { "label": "clinical boundary", "value": "no demonstrated benefit of assigning IA/IgG according to EPS subtype" } ], "source_locator": "Methods: Prediction of IA/IgG therapy sensitivity (Par18); Results: IA/IgG therapy response prediction (Par36); Figure 6D", "source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#kf5" }, { "id": "KF6", "claim": "A cell stress model reproduced the direction of eight selected EPS1-associated gene-expression differences.", "context": "qPCR in angiotensin-II-treated AC16 cells checked genes intersecting EPS1-versus-control and DCM-versus-control contrasts, rather than validating all subtype mechanisms", "evidence": [ { "label": "cell treatment", "value": "10 micromolar angiotensin II for 48 hours" }, { "label": "higher-expression genes", "value": "3: ASPN, LUM and NPPA" }, { "label": "lower-expression genes", "value": "5: MYOT, FKBP5, SERPINE1, CD163 and ANKRD2" }, { "label": "scope", "value": "8 genes; no cell-replicate count or patient-level diagnostic accuracy is inferred" } ], "source_locator": "Methods: Cell culture and treatment (Par20) and Quantitative real-time PCR analysis (Par19); Results: qPCR confirmation of subtype-specific DEGs (Par37); Figure 7; Discussion: qPCR validation of core subtype genes (Par55)", "source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#kf6" } ], "field_entry": [ "Cardiomyopathy molecular classification", "Cardiovascular systems biology" ], "review_topics": [ "Myocardial transcriptomic heterogeneity", "Network-based patient stratification" ], "concepts": { "disease": [ "dilated cardiomyopathy", "heart failure", "myocardial heterogeneity" ], "methods": [ "edge perturbation", "gene-interaction network", "consensus clustering", "nearest-template prediction", "WGCNA", "ssGSEA", "Submap" ], "subtypes": [ "EPS1", "EPS2", "EPS3" ], "evidence_boundaries": [ "retrospective transcriptomic subtyping", "computational immune inference", "exploratory treatment-response matching", "AC16-cell expression check" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Retrospective secondary analysis of public myocardial transcriptomic datasets, with network-based clustering, external subtype assignment, exploratory treatment-response expression matching and a cell-line expression check", "evidence_type": "Human myocardial transcriptomics, Reactome interaction mapping, rank-based edge perturbation, consensus clustering, WGCNA, enrichment, ssGSEA, Submap and AC16-cell qPCR", "population": "DCM and non-failing myocardial samples in four GEO datasets; no new clinical recruitment or randomized subtype-guided treatment trial", "primary_endpoint": "Identification and cross-dataset reproducibility of molecular DCM subtypes", "secondary_endpoint": "Subtype-associated network, pathway and inferred immune features; exploratory similarity to IA/IgG responder profiles; selected gene-expression changes in a cell stress model", "data_modalities": [ "myocardial microarray expression", "myocardial RNA sequencing", "curated gene-interaction network", "computed immune signatures", "AC16 cardiomyocyte-cell-line qPCR" ], "external_validation": true, "scale_metrics": [ { "label": "article-reported dataset scale", "value": "245 DCM and 174 control myocardial samples across four datasets; not a verified total of unique individuals" }, { "label": "discovery dataset", "value": "GSE5406: 86 DCM and 16 controls" }, { "label": "validation datasets", "value": "GSE57338: 82 DCM/136 controls; GSE116250: 37 DCM/14 controls; GSE19303: 40 DCM/8 controls" }, { "label": "mapped discovery interactome", "value": "5,593 genes/nodes and 107,063 interactions/edges" }, { "label": "selected clustering features", "value": "27,937 edges" }, { "label": "molecular subtypes", "value": "3: EPS1, EPS2 and EPS3" }, { "label": "WGCNA analyzed subset", "value": "74 DCM samples after outlier exclusion" }, { "label": "cell-model expression check", "value": "8 genes in AC16 cells treated with 10 micromolar angiotensin II for 48 hours" } ], "counting_note": "Counts are those in the article Table 1 and Results; transcriptomic samples, network edges, analyzed subsets and cultured cells are different units. No combined unique patient total is asserted. The 74-sample WGCNA subset is not another cohort. GSE19303 contributes to subtype assignment and the exploratory treatment comparison, so that comparison is not independent prospective treatment validation. Cell-replicate numbers are not inferred." }, "study_profile_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1007-s10238-026-02130-6.json", "gold_content_sha256": "3b19f183368e4c4e0f9765b050f98c0c7c9df18db75d41a45049d89daab09ebe", "provenance": { "publisher_url": "https://link.springer.com/article/10.1007/s10238-026-02130-6", "doi_url": "https://doi.org/10.1007/s10238-026-02130-6", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/41945162/", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13342204/", "pmcid": "PMC13342204", "version_of_record": "Clinical and Experimental Medicine, 2026; published 7 April 2026; DOI 10.1007/s10238-026-02130-6", "license": "CC BY-NC-ND 4.0 at article level. This evidence page uses an original factual synthesis; no article abstract, figures, tables or adapted article prose are reproduced.", "license_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/", "author_identity": "The version of record lists Ge Zhang at the Department of Cardiology, Tianjian Laboratory of Advanced Biomedical Sciences, Academy of Medical Sciences, First Affiliated Hospital of Zhengzhou University. The article record does not supply an ORCID for this author; no contradictory author identity was found. The same DOI is present in the public works list of ORCID 0000-0002-3116-3246 (put-code 226787148), independently checked 15 October 2026.", "external_datasets": "GSE5406; GSE57338; GSE116250; GSE19303. Counts refer to article-reported analyzed subsets, not the full native GEO series or a verified cross-series unique-person total.", "supporting_material": "Version of record links Supplementary Materials 1-4, including two spreadsheets and two TIFF figures. Main-text claims in this page are supported by the retrieved full-text XML and visible article figures/legends; no supplementary-only values are inferred.", "analysis_boundary": "Subtype reproducibility, computational immune/pathway associations, retrospective expression matching and cell-line expression checks are recorded as different evidence layers.", "evidence_basis": "Publisher version of record, PMC/Europe PMC full-text XML, PubMed-indexed author-affiliation metadata and Crossref DOI metadata, checked 14 October 2026.", "orcid_url": "https://orcid.org/0000-0002-3116-3246" }, "scientific_role": "Retrospective human expression-network subtyping with cross-dataset assignment, inferred immune profiles and a selected cell-model expression check.", "evidence_position": "Computational and exploratory translational evidence; treatment-response expression similarity does not demonstrate subtype-guided therapeutic benefit.", "related_concepts": [ "Edge perturbation", "Immune-signature inference", "Immunoadsorption response hypotheses" ], "citation_contexts": [ "Methods: interaction-level features for molecular DCM classification across bulk myocardial expression datasets.", "Background: immune and metabolic heterogeneity in DCM, with exploratory treatment-response matching explicitly separated from clinical efficacy." ], "evidence_scope": { "supports": [ "Reproducible retrospective expression-network clustering in the analyzed myocardial datasets.", "Subtype-associated coexpression, enrichment and inferred immune-signature differences.", "An exploratory association between EPS1 expression and the previously observed IA/IgG responder profile.", "Concordant expression directions for selected genes in the specified AC16-cell stress model." ], "does_not_establish": [ "Prospective diagnostic performance, prognosis or generalizability to all clinical DCM populations.", "A causal mechanism for each subtype from pathway enrichment, coexpression or immune deconvolution.", "A validated indication for immunoadsorption, or improved outcomes from subtype-guided treatment.", "Direct immune-cell abundance measurements from ssGSEA scores.", "That the cell experiment reproduces all three human subtypes or validates every inferred pathway.", "A verified count of unique people across public datasets or additional independent cohorts from analysis subsets." ] }, "limitations": [ "Public myocardial expression datasets are selected research samples; subtype prevalence and clinical transportability require further study.", "The article reports that longitudinal outcome data were unavailable for prognostic evaluation.", "Coexpression, enrichment and ssGSEA do not experimentally establish subtype mechanisms or immune-cell causation.", "GSE19303 contributes both to subtype evaluation and to the exploratory response analysis; the response claim is not independent prospective validation.", "The cell-line experiment evaluates selected EPS1-associated expression directions, with no basis to infer all subtype mechanisms or treatment effects.", "The source does not provide a clinical decision threshold, calibrated individual treatment-benefit model or randomized comparison of subtype-guided care.", "Supplementary-file links were verified, but the Springer supplementary spreadsheets were not retrieved successfully in this run; no claim depends on uninspected supplementary-only values." ], "scope_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/evidence_scope" }, { "id": "doi-10-1007-s11426-026-3629-x", "title": "A redox-responsive reversible photoacoustic molecular probe for visualizing atherosclerotic plaque redox status in vivo", "doi": "10.1007/s11426-026-3629-x", "year": 2026, "journal": "Science China Chemistry", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.md", "paper_geo_status": "v2", "authors": [ "Aiping Chen", "Ning Zhang", "Fangkun Yang", "Rui Chen", "Jinhui Shang", "Ge Zhang", "Xiaoqi Shao", "Yuan Ma", "Guosheng Song", "Wenming He" ], "doi_url": "https://doi.org/10.1007/s11426-026-3629-x", "publisher_url": "https://link.springer.com/10.1007/s11426-026-3629-x", "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W7213462447", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1007-s11426-026-3629-x.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1007-s11426-026-3629-x.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1007-s11426-026-3629-x.csl.json", "evidence_status": "reviewed_v2", "question_count": 8, "key_findings": [ { "id": "KF1", "claim": "ReP combines a BODIPY scaffold, a hydrophilic peptide segment and catechol-based redox-responsive sites; the authors attribute its reversible optical response to oxidation by superoxide and reduction by GSH.", "context": "The response mechanism is supported by the depicted molecular transformation, solution spectra and molecular-orbital calculations. It is not a demonstrated intracellular signaling pathway or proof of superoxide-specific causal biology in patients.", "source_locator": "Main PDF pp. 2-3, Results 3.1, Fig. 1a-d; official supplement PDF pp. 2-3, Spectroscopic Measurements and DFT Calculations; pp. 5-6, Figs. S1-S4.", "evidence": [ { "label": "Hydrophilic peptide", "value": "N-acetyl-Ala-Ala-Pro-Val-COOH" }, { "label": "Native absorption maximum", "value": "Approximately 660 nm" }, { "label": "Oxidation-related absorption change", "value": "Decrease over 550-680 nm and increase over 680-800 nm; GSH reverses the spectral changes" }, { "label": "Maximum PA signal increase region", "value": "730-750 nm" }, { "label": "Calculated HOMO/LUMO gaps", "value": "Approximately 2.0 eV for ReP and 1.7 eV for oxidized ReP" }, { "label": "Mechanistic assignment boundary", "value": "The authors assign catechol oxidation/reduction; native-probe MS/NMR and DFT are not independent in vivo chemical-product identification" } ], "source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#kf1" }, { "id": "KF2", "claim": "Peptide-modified ReP had greater aqueous compatibility and a smaller reported hydrodynamic size than the BODIPY-NO2 precursor under the tested conditions.", "context": "DLS characterizes aqueous particles or aggregates. The reported hydrodynamic diameters are not the dimensions of a single molecule, and this comparison does not establish pharmacokinetic behavior or exclusive plaque targeting.", "source_locator": "Main PDF p. 3, Results 3.2, Fig. 2b-g; official supplement PDF p. 2, Dynamic Light Scattering.", "evidence": [ { "label": "Precursor DLS diameter", "value": "Approximately 378 nm" }, { "label": "ReP DLS diameter", "value": "Approximately 69 nm" }, { "label": "DLS conditions", "value": "10 micromolar aqueous preparations at 25 degrees C; three independent measurements" }, { "label": "Fig. 2f-g spectroscopy comparison", "value": "5 micromolar precursor versus 5 micromolar ReP under matched superoxide stimulation" }, { "label": "Interpretation", "value": "Improved aqueous dispersion and optical responsiveness in this comparison, not human delivery validation" } ], "source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#kf2" }, { "id": "KF3", "claim": "Solution measurements showed concentration-dependent PA signal enhancement with superoxide and attenuation with GSH at 740 nm.", "context": "These calibrations quantify signal relationships under the reported solution conditions. The absorption-titration range and the PA calibration range differ; neither is an absolute superoxide-concentration calibration for plaques in vivo.", "source_locator": "Main PDF pp. 3-4, Results 3.3, Fig. 3b-g; official supplement PDF p. 2, Spectroscopic Measurements; p. 7, Figs. S5-S6.", "evidence": [ { "label": "Signal metric", "value": "PA intensity at 740 nm; no validated two-wavelength ratio is defined for these displayed calibrations" }, { "label": "ReP for absorption titration", "value": "10 micromolar" }, { "label": "Superoxide absorption titration", "value": "0-125 micromolar" }, { "label": "Superoxide PA calibration shown", "value": "0, 12.5, 25, 50 and 80 micromolar; R-squared = 0.977" }, { "label": "GSH PA calibration shown", "value": "0, 50, 100, 200 and 300 micromolar; R-squared = 0.982" }, { "label": "Solution preparation", "value": "DMSO stocks diluted in PBS at pH 7.4; KO2 in dry DMSO as the superoxide source and fresh GSH in PBS" }, { "label": "Reporting boundary", "value": "Calibration replication, detection limit and exact slope are not supplied for these panels" } ], "source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#kf3" }, { "id": "KF4", "claim": "The PA signal switched in three alternating superoxide/GSH cycles, and superoxide produced a greater response than the tested alternative reactive species.", "context": "Reversibility and selectivity were assessed in solution. This finite interferent panel does not establish selectivity against every biological reaction or prove that all in vivo signal differences are solely caused by superoxide.", "source_locator": "Main PDF p. 4, Results 3.3, Fig. 3h-j; official supplement PDF p. 2, Spectroscopic Measurements.", "evidence": [ { "label": "Alternating response cycles", "value": "Three" }, { "label": "Readout wavelength", "value": "740 nm" }, { "label": "Fig. 3j reactive-species challenge", "value": "80 micromolar, as stated in the figure caption" }, { "label": "Tested alternative species", "value": "The panel includes peroxynitrite, hydroxyl radical, hypochlorous acid and hydrogen peroxide; superoxide shows the pronounced enhancement" }, { "label": "Response direction", "value": "Superoxide increases PA signal; subsequent GSH decreases it" }, { "label": "Scope", "value": "Solution redox switching and the reported selectivity panel" } ], "source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#kf4" }, { "id": "KF5", "claim": "In a small ApoE-deficient atherosclerosis mouse experiment, the aortic PA signal was higher after LPS challenge and lower after the subsequent dexamethasone regimen.", "context": "The comparison concerns relative PA intensity in an aortic region of interest. The AS-only control is an atherosclerotic baseline, not a healthy human comparator; the study does not establish absolute intraplaque superoxide concentration, clinical benefit or event prediction.", "source_locator": "Main PDF pp. 5-6, Results 3.4, Fig. 4a-c; official supplement PDF p. 3, Animal Model and In Vivo Imaging; p. 8, Fig. S7.", "evidence": [ { "label": "Main animal model", "value": "Male ApoE-/- mice started at eight weeks; high-fat diet for 16 weeks" }, { "label": "Main comparisons", "value": "AS + PBS; AS + LPS; AS + LPS + dexamethasone" }, { "label": "Main group size", "value": "n=3 per group, reported in the supplementary methods" }, { "label": "Inflammatory challenge", "value": "LPS 50 micrograms in 50 microliters PBS intranasally on days 0 and 1" }, { "label": "Anti-inflammatory regimen", "value": "Dexamethasone 2 mg/kg/day intraperitoneally from day 2 to day 8" }, { "label": "Probe administration", "value": "ReP 300 microliters at 200 micromolar in PBS via tail vein" }, { "label": "Main acquisition", "value": "Pre-/post-probe PA imaging on days 2 and 8; 740 nm; aortic-region ROI" }, { "label": "Additional longitudinal sequence", "value": "Fig. S7 displays days 0, 1 and 4; its separate sample count and cohort relationship are not reported" }, { "label": "Observed pattern", "value": "LPS-challenged groups have greater day-2 post-probe signal; the DEX group has a lower day-8 signal than AS + LPS; no exact numerical effect size is reconstructed from bars" } ], "source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#kf5" }, { "id": "KF6", "claim": "Lung and plaque histology accompanied the imaging findings: LPS was associated with pulmonary edema and altered plaque composition, while the dexamethasone group showed a different staining pattern.", "context": "Lung wet/dry ratio and plaque staining are experimental tissue readouts. Fig. 6 supplies displayed percentages without per-animal dispersion or a statistical test; these do not demonstrate prevented plaque rupture or reduced human cardiovascular events.", "source_locator": "Main PDF pp. 6-7, Results 3.5-3.6, Figs. 5a-d and 6a-b; official supplement PDF p. 3, animal grouping.", "evidence": [ { "label": "Lung comparison", "value": "Higher wet/dry ratio in AS + LPS and lower ratio in AS + LPS + DEX; lung dry-weight differences labeled not significant" }, { "label": "Fig. 5 sample/statistical presentation", "value": "N=3, mean +/- SD; caption thresholds: *p<0.05, **p<0.01, ***p<0.001; no exact p values are supplied" }, { "label": "Fig. 6 CD68-positive percentages", "value": "Group 1: 24.898%; Group 2: 38.095%; Group 3: 23.285%" }, { "label": "Fig. 6 caspase-3-positive percentages", "value": "Group 1: 25%; Group 2: 37.3%; Group 3: 33.7%" }, { "label": "Fig. 6 collagen/Masson percentages", "value": "Group 1: 47.9%; Group 2: 34.3%; Group 3: 62.2%" }, { "label": "Fig. 6 quantitative boundary", "value": "Displayed figure annotations only; no uncertainty intervals, per-animal values or inferential significance are specified" } ], "source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#kf6" }, { "id": "KF7", "claim": "The study reports limited short-term mouse tolerability observations after ReP administration, using body-weight monitoring and major-organ histology.", "context": "These descriptive observations are narrower than an established biosafety profile. They do not supply a chronic toxicity program, a human safety study or a supported repeated-dose safety margin.", "source_locator": "Main PDF pp. 7-8, Results 3.6; official supplement PDF p. 8, Figs. S8-S9.", "evidence": [ { "label": "Reported follow-up", "value": "Seven days in the Fig. S8 caption" }, { "label": "Comparison", "value": "ReP versus PBS" }, { "label": "Organ histology", "value": "Heart, liver, spleen, lung and kidney; main text specifies C57BL/6 mice for this evaluation" }, { "label": "Reported observations", "value": "The authors report no significant body-weight difference and no apparent histopathological injury under the assessed conditions" }, { "label": "Unreported details", "value": "Independent tolerability sample count, exact statistical test and long-term toxicity outcomes are not provided" } ], "source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/key_findings/6", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#kf7" } ], "field_entry": [ "Atherosclerosis molecular imaging", "Reversible photoacoustic probe research" ], "review_topics": [ "Redox-responsive optical probes", "Experimental plaque inflammation imaging" ], "concepts": { "Probe and chemistry": [ "ReP", "BODIPY", "catechol redox response", "superoxide anion", "glutathione", "hydrophilic peptide" ], "Measurements": [ "photoacoustic intensity at 740 nm", "DLS hydrodynamic diameter", "solution calibration", "aortic-region ROI", "lung wet-to-dry ratio" ], "Experimental context": [ "ApoE-deficient mouse", "high-fat diet", "LPS", "dexamethasone", "atherosclerosis", "CD68", "caspase-3", "collagen staining" ] }, "profile_type": "preclinical_multimodal", "study_profile": { "profile_type": "preclinical_multimodal", "study_design": "Chemical probe synthesis and solution characterization followed by a small experimental atherosclerosis mouse comparison with LPS challenge and dexamethasone intervention", "evidence_type": "Solution optical/PA response, computational mechanism support, relative mouse PA imaging and ex vivo tissue observations", "population": "Controlled chemical solutions; male ApoE-/- mice with diet-induced atherosclerosis; a separate C57BL/6 mouse organ-histology evaluation described in the text. 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No cell-culture validation, human participants or clinical diagnostic-validation cohort is reported.", "The main AS comparison has n=3 mice per group. Assay-specific measurements, repeated imaging days, tissue sections and the additional S7 sequence must not be summed into a synthetic unique animal total.", "The PA calibration and in vivo result panels use intensity at 740 nm. Although introductory text uses the term ratiometric, a validated two-wavelength normalization ratio is not specified for the displayed experiments.", "In vivo signals are relative aortic-region observations, not measured absolute superoxide concentrations. Probe distribution, tissue optical properties and endogenous signal are not eliminated as potential contributors by a universal biological-specificity test.", "Solution selectivity applies to the reported 80 micromolar challenge panel. It does not establish complete selectivity in all tissues, across all reductants, or under every biological condition.", "The figures supply calibration R-squared values but no explicit PA-calibration replicate count, limit of detection, limit of quantification, exact regression slope or calibration uncertainty. No values are reconstructed from plotted bars.", "Fig. 6 heatmap percentages have no stated per-animal dispersion or statistical test. They are descriptive annotations, not independently calculated means, confidence intervals or significance claims.", "Random assignment is described in the supplement; blinding, allocation concealment and an a priori sample-size calculation are not reported in the available text.", "LPS/dexamethasone intervention supports experimental group contrasts; it does not independently prove every step of the proposed lung-to-systemic-oxidative-stress-to-plaque cascade, prevent rupture or demonstrate patient benefit.", "Short-term body-weight and organ-histology observations have an unreported independent sample count and do not establish chronic, repeated-dose or human safety.", "Supplementary affiliation/equal-contribution formatting differs from the final main-PDF author footnotes. Full author order, title, DOI and publication date agree between the main PDF, publisher and Crossref; the main version of record governs identity.", "Supplementary synthetic-route temperature labeling differs from the prose description. That synthesis-temperature detail is not promoted into the evidence summary, and no unsupported protocol reconciliation is made." ], "scope_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/evidence_scope" }, { "id": "doi-10-3389-fcvm-2025-1724572", "title": "Allostatic load-cardiovascular disease associations and the mediating effect of inflammatory factors: a prospective cohort study", "doi": "10.3389/fcvm.2025.1724572", "year": 2026, "journal": "Frontiers in Cardiovascular Medicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-3389-fcvm-2025-1724572.html", "markdown_url": "https://drgezhang.com/papers/doi-10-3389-fcvm-2025-1724572.md", "paper_geo_status": "v2", "authors": [ "Shuai Xu", "Ge Zhang", "Yudi Xu", "Chaoyang Yu", "Ruhao Wu", "Zhengrui Li", "Teng Li", "Xinyue Cui", "Xufeng Huang", "Shujing Zhou", "Yahui Han", "Haonan Zhang", "Shiqian Zhang", "Yufeng Jiang" ], "doi_url": "https://doi.org/10.3389/fcvm.2025.1724572", "publisher_url": "https://www.frontiersin.org/articles/10.3389/fcvm.2025.1724572/full", "pmid": "41561117", "pmcid": "PMC12813168", "openalex_id": "https://openalex.org/W7118161489", "semantic_scholar_id": "7132b34d133ea0c141f302082266df4c73f16c74", "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-3389-fcvm-2025-1724572.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-3389-fcvm-2025-1724572.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-3389-fcvm-2025-1724572.csl.json", "evidence_status": "reviewed_v2", "question_count": 5, "key_findings": [ { "claim": "The analytic cohort comprised 205,504 participants and 18,542 incident CVD events during an article-reported 13-year follow-up period.", "context": "The analytic sample is not the entire UK Biobank recruitment population. 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no new randomization or causal test of withdrawal timing.", "evidence": [ { "label": "evidence role", "value": "Clinical commentary" } ], "source_locator": "NEJM 394(10), pp. 1035-1036; Li, Zhang and Liu letter, opening sentence and continuation across the page break; PMID 41780015.", "source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1056-nejmc2518964.html#kf1" }, { "id": "KF2", "claim": "The letter highlights an early concentration of stent thrombosis among affected monotherapy patients.", "context": "Among monotherapy patients who experienced stent thrombosis, the letter reports that it occurred in 83% within 30 days; this is not an 83% event rate in the entire treatment group.", "evidence": [ { "label": "affected monotherapy patients whose thrombosis occurred within the early interval", "value": "83%" }, { "label": "early interval", "value": "First 30 days after PCI" } ], "source_locator": "NEJM 394(10), p. 1036; 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The authors do not introduce a new patient cohort." }, "study_profile_source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": "correspondence", "gold_source": "data/deep_geo/doi-10-1056-nejmc2518964.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1056-nejmc2518964.json", "gold_content_sha256": "aa34154dff3005eef1937cd217a3524b18592aeea35602a85e85fd94fd492eea", "provenance": { "publisher_url": "https://www.nejm.org/doi/10.1056/NEJMc2518964", "doi_url": "https://doi.org/10.1056/NEJMc2518964", "identity_url": "https://pubmed.ncbi.nlm.nih.gov/41780015/", "full_text_url": "https://www.researchgate.net/publication/402598282_Aspirin_after_PCI_in_Acute_Coronary_Syndromes", "evidence_basis": "The complete signed Li/Zhang/Liu letter was read in the public ResearchGate HTML rendition, with journal pagination 1035-1036. 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PDF binary not retrieved; publisher-hosted full text remains restricted.", "figure_verification": "No figure or table occurs in the reviewed signed letter; no image is reproduced." }, "scientific_role": "Signed correspondence interpreting an existing trial and suggesting future research.", "evidence_position": "Secondary interpretation and hypothesis; no new randomized evidence.", "related_concepts": [ "NEO-MINDSET", "Stent thrombosis timing", "Platelet-function testing" ], "citation_contexts": [ "Discussion of how early event timing can motivate a de-escalation research question.", "Attribution of the authors' proposal for time-adaptive antiplatelet transitions." ], "evidence_scope": { "supports": [ "Attribution of the timing argument and proposed research agenda to Li, Zhang and Liu.", "Accurate reporting of the letter's early-event proportion with its restricted denominator." ], "does_not_establish": [ "New randomized efficacy or safety evidence.", "A causal benefit of delaying aspirin withdrawal or of platelet-function-guided care.", "A patient-specific stopping date or validated treatment threshold." ] }, "limitations": [ "The event proportion is reported by the correspondence; this synthesis does not independently reanalyze the NEO-MINDSET dataset.", "The shared DOI includes separate letters and a reply. Their statistics and recommendations are not attributed to Li, Zhang and Liu.", "Full text was read from the author's ResearchGate upload in an HTML text rendition; the PDF binary and a publisher-hosted full text were not retrieved." ], "scope_source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/evidence_scope" }, { "id": "doi-10-1002-mdr2-70052", "title": "Circadian Immunity and Vascular Inflammation in Cardiovascular Disease Chronotherapy Windows: Time for a Re-Assessment", "doi": "10.1002/mdr2.70052", "year": 2026, "journal": "Med Research", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.md", "paper_geo_status": "v2", "authors": [ "Tian Zhang", "Ge Zhang", "Tian-Ding Liu", "Tianshu Gu", "Fengyi Yu", "Pengyuan Xu", "Wunan Mi", "Xuanjiang Zhao", "Qian Guo", "Honglin Zheng", "Taiqi Zhao", "Qiang Li", "Di Lu", "Mingxuan Duan", "Chaoyang Yu", "Ruhao Wu", "Shiqian Zhang", "Haonan Zhang", "Zeyu Wang", "Youyang Zheng", "Yan Xiao", "Zenglei Zhang", "Ge Zhang" ], "doi_url": "https://doi.org/10.1002/mdr2.70052", "publisher_url": "https://onlinelibrary.wiley.com/doi/10.1002/mdr2.70052", "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W7118162173", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1002-mdr2-70052.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1002-mdr2-70052.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1002-mdr2-70052.csl.json", "evidence_status": "reviewed_v2", "question_count": 11, "key_findings": [ { "id": "KF1", "claim": "The review places CLOCK-BMAL1, PER/CRY and REV-ERB/ROR feedback loops at the center of temporal regulation of cardiovascular immune biology.", "context": "This is a synthesis of prior molecular and experimental literature rather than a new clock experiment.", "evidence": [ { "label": "Core clock machinery", "value": "BMAL1/ARNTL, CLOCK, PER1/2/3, CRY1/2, REV-ERB alpha/beta and ROR alpha/gamma are integrated with redox and epigenetic regulation." } ], "source_locator": "Sections 2.1-2.4; Figures 1-2; Tables 1-2.", "source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#kf1" }, { "id": "KF2", "claim": "Circadian timing is synthesized as a regulator of PRR, NF-kB and NLRP3 inflammatory signaling and of cytokine, chemokine and adhesion-molecule rhythms.", "context": "These mechanisms derive from heterogeneous experimental systems and should not be represented as one fully demonstrated causal human pathway.", "evidence": [ { "label": "Inflammatory networks", "value": "The review discusses IL-1beta, IL-6, IL-18, TNF-alpha, CCL2, CXCL12, ICAM1, VCAM1 and related inflammatory networks." } ], "source_locator": "Sections 3-4; Figure 3; Table 3.", "source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#kf2" }, { "id": "KF3", "claim": "The review describes circadian variation in immune-cell number, trafficking and function across neutrophils, monocytes/macrophages, lymphocytes and dendritic cells.", "context": "Timing, phase and mechanisms vary by species, tissue and experimental model.", "evidence": [ { "label": "Trafficking mechanisms", "value": "BMAL1, chemokine axes, sympathetic signaling and cell-intrinsic clocks are synthesized as contributors to rhythmic immune trafficking and function." } ], "source_locator": "Section 5; Figures 4-5.", "source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#kf3" }, { "id": "KF4", "claim": "Circadian disruption is reviewed in relation to atherosclerosis, stroke, ischemic heart disease/myocardial infarction and heart failure through overlapping inflammatory, endothelial, metabolic and oxidative-stress mechanisms.", "context": "Evidence strength and causality differ materially across disease, mechanism and model.", "evidence": [ { "label": "Disease domains", "value": "The synthesis compares atherosclerosis, stroke, ischemic heart disease, myocardial infarction and heart failure rather than reporting one new cross-disease experiment." } ], "source_locator": "Sections 6.1-6.4; Figures 6-8.", "source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#kf4" }, { "id": "KF5", "claim": "Preclinical studies provide a mechanistic rationale for time-dependent intervention targeting clock and inflammatory pathways.", "context": "This evidence is predominantly preclinical and must not be converted into human treatment-efficacy claims.", "evidence": [ { "label": "Preclinical strategies", "value": "The review discusses REV-ERB agonists, NLRP3 inhibitors, NF-kB pathway modulation, CCR2/CCL2 and CXCL12/CXCR4 strategies." } ], "source_locator": "Section 7.1; Table 4.", "source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#kf5" }, { "id": "KF6", "claim": "Clinical chronotherapy evidence is heterogeneous and does not define a universal optimal dosing time for most cardiovascular drugs.", "context": "Physiological timing effects and mechanistic rationale are not equivalent to proven reductions in clinical outcomes.", "evidence": [ { "label": "Drug classes and timing", "value": "The review discusses aspirin, beta-blockers, melatonin, tPA, SGLT2 inhibitors, colchicine, ACEIs/ARBs, MRAs, ARNI and antihypertensive timing." }, { "label": "Conflicting trials", "value": "Hygia and related studies reported bedtime-dosing benefits, whereas BedMed did not reproduce a cardiovascular-event benefit." } ], "source_locator": "Section 7.2; Table 5.", "source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#kf6" }, { "id": "KF7", "claim": "The review identifies unresolved methodological and translational gaps that limit precision chronotherapy.", "context": "These gaps are part of the authors' discussion, not newly experimentally tested findings.", "evidence": [ { "label": "Research gaps", "value": "Constitutive-versus-inducible knockout-model differences, immune-cell-subpopulation heterogeneity, insufficient spatiotemporal resolution of vascular-immune interactions and the need for high-quality circadian-aware clinical trials are highlighted." } ], "source_locator": "Sections 8.1-8.4.", "source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/key_findings/6", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#kf7" }, { "id": "KF8", "claim": "Chronotherapy claims in this review require explicit separation of mechanistic rhythmicity, preclinical time-of-day efficacy, human surrogate effects and hard cardiovascular outcomes.", "context": "These evidence levels are not interchangeable. Human clinical timing evidence remains incomplete or conflicting for many cardiovascular therapies.", "evidence": [ { "label": "Human timing evidence", "value": "Bedtime aspirin can alter morning platelet reactivity, but cardiovascular event reduction has not been established by a large randomized trial; SGLT2-inhibitor and colchicine timing remain insufficiently tested." }, { "label": "Outcome-level uncertainty", "value": "Antihypertensive bedtime-dosing studies have reported conflicting cardiovascular outcome results, including the Hygia and BedMed trials." } ], "source_locator": "Section 7.2; Table 5; Sections 8.1-8.4.", "source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/key_findings/7", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#kf8" } ], "field_entry": [ "Cardiovascular chronobiology", "Immune-vascular regulation" ], "review_topics": [ "Circadian rhythms and vascular inflammation", "Cardiovascular chronotherapy evidence and translation" ], "concepts": { "circadian_machinery": [ "BMAL1 / ARNTL", "CLOCK", "PER1", "PER2", "PER3", "CRY1", "CRY2", "REV-ERBα / NR1D1", "REV-ERBβ / NR1D2", "RORα", "RORγ" ], "inflammatory_and_redox_signaling": [ "NF-kB", "NLRP3 inflammasome", "NRF2", "SIRT1", "HIF-1alpha", "pattern-recognition receptors", "reactive oxygen species" ], "cytokine_and_trafficking_axes": [ "IL-1beta", "IL-6", "IL-18", "TNF-alpha", "CCL2-CCR2", "CXCL12-CXCR4", "ICAM1", "VCAM1", "CCR7", "S1PR1", "S1PR5" ], "cells": [ "neutrophils", "monocytes", "macrophages", "lymphocytes", "dendritic cells", "endothelial cells", "vascular smooth muscle cells" ], "diseases": [ "atherosclerosis", "stroke", "ischemic heart disease", "myocardial infarction", "heart failure", "hypertension" ], "chronotherapy": [ "REV-ERB agonists", "NLRP3 inhibitors", "NF-kB pathway modulation", "aspirin timing", "beta-blockers", "melatonin", "tPA", "SGLT2 inhibitors", "colchicine", "ACE inhibitors", "ARBs", "mineralocorticoid receptor antagonists", "sacubitril/valsartan" ] }, "profile_type": "narrative_review", "study_profile": { "profile_type": "narrative_review", "study_design": "Narrative evidence synthesis integrating molecular, cellular, animal, epidemiological and clinical chronotherapy literature. The article does not report a PRISMA-style systematic-search or study-selection workflow, quantitative meta-analysis, or a newly generated dataset.", "evidence_type": "Narrative synthesis of heterogeneous preclinical, mechanistic, epidemiological and clinical evidence; no new dataset and no pooled meta-analytic effect estimate.", "evidence_domains": [ "Molecular circadian clock", "Redox and epigenetic regulation", "PRR / NF-kB / NLRP3 inflammatory signaling", "Cytokine, chemokine and adhesion-molecule rhythmicity", "Immune-cell trafficking and function", "Cardiovascular disease mechanisms", "Preclinical chronotherapy", "Clinical chronotherapy and translation" ], "diseases_covered": [ "Atherosclerosis", "Stroke", "Ischemic heart disease", "Myocardial infarction", "Heart failure", "Hypertension and blood-pressure chronotherapy where relevant" ], "translation_scope": "Mechanistic rationale and preclinical chronotherapy are substantially stronger than the clinical evidence for universal time-specific dosing.", "scale_metrics": [ { "label": "Article type", "value": "Review Article" }, { "label": "Bibliography", "value": "392 references" }, { "label": "Tables", "value": "5 synthesis tables" }, { "label": "Figures", "value": "9 figures" }, { "label": "New data", "value": "None created or analyzed" } ], "counting_note": "This is a narrative review. The 392 bibliography entries include heterogeneous evidence types and are not a systematic count of independent studies, experiments, animals or participants. Study-level denominators must not be summed into a synthetic n. The review reports no newly generated or newly analyzed dataset." }, "study_profile_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1002-mdr2-70052.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1002-mdr2-70052.json", "gold_content_sha256": "76178b0ff5cc070e6169ec6071280b1762266a94da4ef78aacb2b87f2763a29c", "provenance": { "doi": "10.1002/mdr2.70052", "publisher": "Wiley Online Library / Med Research", "publisher_url": "https://doi.org/10.1002/mdr2.70052", "article_type": "Review Article", "access": "Open Access", "first_published": "05 January 2026", "version_of_record": "Med Research 2(2):236-279", "formal_structure": "Figures 1-9; Tables 1-5; references 1-392.", "data_availability": "No new data were created or analyzed in this study.", "method_scope": "Narrative synthesis; no explicit PRISMA systematic-search or study-selection workflow and no quantitative meta-analysis." }, "scientific_role": "Narrative synthesis connecting molecular clocks, immune regulation, vascular inflammation and cardiovascular treatment-timing research.", "evidence_position": "Narrative review of heterogeneous mechanistic, preclinical and clinical sources; not a systematic review, new experiment or universal medication-timing recommendation.", "related_concepts": [ "Chronoimmunology", "Treatment-timing evidence boundaries" ], "citation_contexts": [ "Background: circadian organization of cardiovascular immune and inflammatory biology.", "Evidence synthesis: distinctions between mechanistic chronotherapy rationale and unsettled clinical timing evidence." ], "evidence_scope": { "supports": [ "Prior evidence links circadian clock networks with immune and vascular processes, inflammatory and redox pathways.", "Immune-cell number, trafficking and functional state can vary with circadian timing across experimental contexts.", "Experimental circadian disruption can alter cardiovascular inflammatory phenotypes, while cardiovascular physiology and events exhibit time-of-day patterns.", "Preclinical evidence provides a mechanistic rationale for chronotherapy; some cardiovascular drugs show dosing-time-dependent physiological effects.", "Clinical chronotherapy remains an active and unresolved translational field." ], "does_not_establish": [ "A new patient cohort, new experimental data or a newly analyzed dataset.", "A systematic review, meta-analysis or pooled quantitative effect size.", "One universally causal circadian pathway across all cardiovascular diseases.", "Human cardiovascular treatment efficacy of REV-ERB agonists or time-targeted NLRP3 or NF-kB inhibition.", "Universal superiority of bedtime antihypertensive dosing or a dosing schedule suitable for every patient.", "Reduced myocardial infarction or stroke outcomes from bedtime aspirin.", "Established optimal dosing for SGLT2 inhibitors, colchicine, mineralocorticoid receptor antagonists or ARNI.", "A guideline-level recommendation to change cardiovascular medication timing." ] }, "limitations": [ "This is a narrative, non-systematic evidence synthesis with no new dataset or pooled effect estimate.", "Species, tissues, disease models and evidence levels are heterogeneous; causal animal or cell findings cannot automatically be generalized to human cardiovascular disease.", "Constitutive and inducible clock-gene knockout models may yield different findings.", "Treatment-timing evidence is uneven across cardiovascular drug classes and many proposed chronotherapy windows remain theoretical or preclinical.", "Clinical antihypertensive timing evidence is conflicting, including Hygia-versus-BedMed differences.", "No universal dosing recommendation is established; high-quality circadian-aware randomized clinical trials are needed." ], "scope_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/evidence_scope" }, { "id": "doi-10-15212-bioi-2026-0017", "title": "Combining Insulin Resistance and Renal Function to Predict Cardiovascular Events: A Multicenter Cohort Study", "doi": "10.15212/bioi-2026-0017", "year": 2026, "journal": "BIO Integration", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html", "markdown_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.md", "paper_geo_status": "v2", "authors": [ "Ge Zhang", "Tianshu Gu", "Kaisaierjiang Kadier", "Zhijie Zhao", "Qian Guo", "Shanshan Cai", "Wenming He", "Fangkun Yang", "Bo Yang", "Chaoyang Yu" ], "doi_url": "https://doi.org/10.15212/bioi-2026-0017", "publisher_url": null, "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W7164867760", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-15212-bioi-2026-0017.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-15212-bioi-2026-0017.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-15212-bioi-2026-0017.csl.json", "evidence_status": "reviewed_v2", "question_count": 7, "key_findings": [ { "id": "KF1", "claim": "The study combined a UK Biobank prospective analysis with an independent clinical association-replication cohort.", "context": "The primary and external populations are distinct and are reported separately. The external fully adjusted complete-case analysis represents a subset of the initially assembled clinical cohort.", "evidence": [ { "label": "UK Biobank analytic participants", "value": "261,865" }, { "label": "External cohort initially assembled", "value": "1,798" }, { "label": "External complete-case analysis", "value": "328 participants, including 88 MACE outcomes" }, { "label": "External recruitment and follow-up", "value": "2018–2020 enrollment; up to 4 years of follow-up" } ], "source_locator": "Methods: Study design and population, Primary cohort and External validation cohort; Results: Population characteristics; Table 1; Figure 5", "source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#kf1" }, { "id": "KF2", "claim": "Higher TyG:eGFRcr-cys quartiles were associated with higher incident CVD hazards in UK Biobank.", "context": "Fully adjusted Model 3; the lowest ratio quartile is the reference. Hazard ratios describe observational associations, not causal effects or a validated clinical risk score.", "evidence": [ { "label": "Q2 versus Q1 CVD HR", "value": "1.15; 95% CI 1.10–1.21" }, { "label": "Q3 versus Q1 CVD HR", "value": "1.17; 95% CI 1.12–1.23" }, { "label": "Q4 versus Q1 CVD HR", "value": "1.24; 95% CI 1.18–1.30" } ], "source_locator": "Abstract: Result; Results: Associations between the TyG index and the TyG:eGFRcr-cys ratio with CVD; Table 2, CVD quartile rows, Model 3", "source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#kf2" }, { "id": "KF3", "claim": "The highest-quartile association was clearer for CHD than for stroke.", "context": "Same highest-versus-lowest ratio-quartile contrast in fully adjusted Model 3. The stroke confidence interval includes the null; other exposure contrasts should not be treated as interchangeable with this quartile comparison.", "evidence": [ { "label": "Q4 versus Q1 CHD HR", "value": "1.30; 95% CI 1.23–1.37" }, { "label": "Q4 versus Q1 stroke HR", "value": "1.05; 95% CI 0.96–1.16" }, { "label": "Stroke Q4 versus Q1 P value", "value": "0.29" } ], "source_locator": "Results: Associations between the TyG index and the TyG:eGFRcr-cys ratio with CVD; Table 2, CHD and STROKE quartile-4 rows, Model 3", "source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#kf3" }, { "id": "KF4", "claim": "The ratio–MACE association was also reported in the external clinical complete-case cohort, with substantial uncertainty in effect magnitude.", "context": "External Cox Model 3; per-standard-deviation contrast, distinct from the UK Biobank quartile comparison. This is independent association replication, not proof of incremental predictive utility or calibrated individual risk.", "evidence": [ { "label": "TyG:eGFRcr-cys HR per 1-SD increase", "value": "6.04; 95% CI 2.12–17.19" }, { "label": "External analysis scale", "value": "328 complete cases; 88 MACE outcomes" } ], "source_locator": "Methods: External validation statistical analysis; Results: External validation; Figure 5D and caption; Methods: External validation cohort", "source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#kf4" }, { "id": "KF5", "claim": "Dynamic network biomarker analysis identified a possible transition-related pattern across ratio-based risk strata.", "context": "Participants were ordered by between-person exposure quartiles. The exploratory network pattern is not longitudinal demonstration of an individual patient entering a pre-disease state.", "evidence": [ { "label": "Risk strata", "value": "Four ratio quartiles, Q1–Q4" }, { "label": "Composite-index pattern", "value": "Highest reported value in Q3" }, { "label": "Interpretation", "value": "Exploratory network instability across exposure strata; not a proven mechanism or clinical early-warning threshold" } ], "source_locator": "Methods: Dynamic network biomarker analysis; Results: Dynamic network biomarker analysis suggested a potential transition stage during CVD risk progression; Figure 6B–E", "source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#kf5" } ], "field_entry": [ "Cardiovascular epidemiology", "Cardiometabolic–renal markers" ], "review_topics": [ "Combined metabolic and renal risk assessment", "External association-replication studies" ], "concepts": { "markers": [ "Triglyceride–glucose index", "TyG:eGFRcr-cys ratio", "Creatinine–cystatin-C-based estimated GFR" ], "outcomes": [ "Incident cardiovascular disease", "Coronary heart disease", "Stroke", "Major adverse cardiovascular events" ], "methods": [ "UK Biobank", "Prospective cohort", "Cox proportional-hazards model", "Independent association replication", "Dynamic network biomarkers" ] }, "profile_type": "multicohort_observational", "study_profile": { "profile_type": "multicohort_observational", "study_design": "Prospective observational UK Biobank analysis with Cox models, restricted cubic splines, subgroup/sensitivity analyses, independent single-center clinical association replication, and exploratory network analysis across ratio quartiles.", "evidence_type": "Longitudinal observational associations and independent clinical association replication", "population": "UK Biobank adults without baseline CVD; a separately assembled Zhengzhou University vascular-surgery clinical cohort with complete cases used for the fully adjusted external analysis.", "primary_endpoint": "Incident fatal or nonfatal CHD or stroke in the primary cohort; MACE defined as fatal or nonfatal CHD or stroke in the external cohort.", "secondary_endpoint": "CHD and stroke separately; dose–response patterns and exploratory network instability across exposure-defined strata.", "data_modalities": [ "Baseline blood triglycerides and glucose", "Creatinine and cystatin-C-based estimated GFR", "Demographic, lifestyle, medication, and clinical covariates", "Hospital and death-registry outcome codes", "External clinical cohort follow-up" ], "external_validation": true, "scale_metrics": [ { "label": "Primary cohort", "value": "UK Biobank analytic sample: 261,865 participants" }, { "label": "External source cohort", "value": "1,798 initially assembled clinical participants" }, { "label": "External fully adjusted analysis", "value": "328 complete cases, including 88 MACE outcomes" } ], "counting_note": "Primary and external cohort counts are kept separate. The external complete-case group is a subset of the initially assembled hospital cohort. No synthetic total combines the populations or adds the subset to its parent cohort. External validation here means association replication, not an independently calibrated clinical prediction tool." }, "study_profile_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-15212-bioi-2026-0017.json", "gold_content_sha256": "2996306176e1c2843dfcbc424cf522a25e148851a34a3033333f323856f5b0c0", "provenance": { "publisher_url": "https://bio-integration.org/10-15212-bioi-2026-0017/", "doi_url": "https://doi.org/10.15212/bioi-2026-0017", "version_of_record": "BIO Integration 2026; volume 7, pages 1–17; published online 15 June 2026", "license": "Creative Commons Attribution 4.0 International (CC BY 4.0)", "license_url": "https://creativecommons.org/licenses/by/4.0/", "data_source": "UK Biobank application 102158; independent First Affiliated Hospital of Zhengzhou University vascular-surgery cohort.", "external_cohort_counting": "1,798 initially assembled; 328 complete cases and 88 MACE events for the fully adjusted external analysis.", "supporting_material_url": "https://bio-integration.org/wp-content/uploads/2026/06/bioi20260017_Supplemental.zip", "supporting_material_note": "Official supplementary link identified; direct retrieval returned HTTP 406. The claims on this page are supported by the accessible official full-text Methods, Results, Table 2, and figure captions.", "source_note_table3": "The official HTML Table 3 former-smoker confidence interval is malformed; that subgroup estimate is not used on this evidence page.", "source_note_subgroups": "Subgroup descriptions are not promoted to causal or mechanistic claims, and demographic subgroup estimates are not used for clinical recommendations.", "author_identity": "Ge Zhang is first and corresponding author, affiliated with Zhengzhou University; the article gives the same public correspondence identity and the DOI appears in ORCID 0000-0002-3116-3246.", "evidence_basis": "Official publisher full-text HTML read through the web tool, Crossref metadata, and public ORCID works. 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Pedigree and representative Sanger images were inspected, with the unresolved family-wide denominator and segregation review boundary explicitly retained.", "license": "CC BY 4.0, stated on the article first page and in the formal JATS permissions element.", "license_url": "https://creativecommons.org/licenses/by/4.0/" }, "scientific_role": "Primary preclinical experiments arising from a reported glaucoma-family observation; the page does not validate family-wide segregation.", "evidence_position": "Direct experimental cell and mouse evidence, with no population penetrance estimate, exact-variant mouse model or human treatment validation.", "related_concepts": [ "Protein abundance versus protein stability", "Trabecular collagen and intraocular pressure" ], "citation_contexts": [ "Variant biology: endpoint PAPPA2 abundance after missense-variant expression in 293T cells.", "Experimental fibrosis: primary-cell IGFBP5/PAPPA2 exposure and Pappa2-deficient mouse pressure/histology, with model limits stated." ], "evidence_scope": { "supports": [ "Lower PAPPA2 protein abundance with mutant expression in the reported 293T assay.", "Attenuation of IGFBP5-associated molecular responses by PAPPA2 cotreatment in the specified primary-cell conditions.", "Elevated pressure and increased trabecular collagen-associated staining in the specified Pappa2-deficient mouse comparison." ], "does_not_establish": [ "Independently reconciled family-wide counts, complete segregation, population allele frequency, penetrance or clinical pathogenicity of PAPPA2 c.392G>C.", "A directly measured change in PAPPA2 protein half-life from endpoint protein and mRNA assays alone.", "Equivalence of Pappa2 deficiency to the exact human p.Gly131Ala variant.", "Human diagnostic performance, glaucoma prevention, treatment efficacy or safety." ] }, "limitations": [ "Results 3.1-3.2 describe a family association, but the Figure 1a caption does not fully specify which depicted relatives contribute to the reported counts, and Figure 2a-b provides representative Sanger traces rather than an individual-level genotype table. The page therefore does not validate family-wide counts or complete segregation; it does not substitute an alternative count inferred from symbols.", "The mutant expression assay measured endpoint protein abundance and mRNA. It did not directly measure protein half-life, secretion rate, or clinical variant penetrance.", "The primary-cell experiments used two donor-derived lines. Three experimental repeats and multiple cells imaged within each experiment do not increase the number of independent human donors.", "The mouse study used five animals per genotype. Deficiency of Pappa2 is not equivalent to an exact missense-variant knock-in, and pressure and collagen-associated staining do not establish the full human glaucoma phenotype.", "No human therapeutic intervention, clinical diagnostic validation, or patient outcome benefit is established by the experimental findings summarized here." ], "scope_source": "data/deep_geo/doi-10-1155-humu-5591097.json#/evidence_scope" }, { "id": "doi-10-1371-journal-pone-0346326", "title": "Real-world safety of aliskiren in primary hypertension: A cross-database study", "doi": "10.1371/journal.pone.0346326", "year": 2026, "journal": "PLOS One", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1371-journal-pone-0346326.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1371-journal-pone-0346326.md", "paper_geo_status": "none", "authors": [ "Meirong Shan", "Qian Guo", "Ruofei Li", "Ni Li", "Yanhua Fu", "Huanyu Qi", "Ge Zhang", "Qian Wang", "Xingli Xu", "Jinchuan Lai" ], "doi_url": "https://doi.org/10.1371/journal.pone.0346326", "publisher_url": null, "pmid": "41931483", "pmcid": "PMC13048407", "openalex_id": "https://openalex.org/W7148844109", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1371-journal-pone-0346326.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1371-journal-pone-0346326.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1371-journal-pone-0346326.csl.json", "evidence_status": "limited", "question_count": 0, "key_findings": [], "field_entry": [], "review_topics": [], "concepts": {}, "evidence_url": "https://drgezhang.com/papers/doi-10-1371-journal-pone-0346326.html#limited-evidence", "source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/limited_evidence.json", "provenance": [ { "url": "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0346326", "label": "Article source", "format": "Official publisher or PMC full text reviewed locally", "locator": "Methods: Data sources and Statistical analysis (sec003, sec005); Results: Tables 1–2 (sec007)" }, { "url": "https://journals.plos.org/plosone/article/file?type=supplementary&id=10.1371/journal.pone.0346326.s003", "label": "Official supplementary material", "format": "Publisher-hosted supplementary document", "locator": "S3 Table, FAERS Database Mining Report: TABLE 1, Report year rows 2005–2025" } ], "scope": "Spontaneous-report study design, descriptive evidence and explicit corpus/counting uncertainty; no validated adverse-event incidence or causal estimate.", "evidence_notice": "Spontaneous-report study design, descriptive evidence and explicit corpus/counting uncertainty; no validated adverse-event incidence or causal estimate.", "evidence_scope": null, "limitations": [ "Exact FAERS analysis quarters remain unresolved.", "Serious/outcome counting units are not reconciled.", "Spontaneous reporting does not establish incidence or causality." ], "scope_source": "data/limited_evidence.json#/papers/10.1371~1journal.pone.0346326/scope" }, { "id": "doi-10-1126-science-aek9583", "title": "Recording results from single-patient trials", "doi": "10.1126/science.aek9583", "year": 2026, "journal": "Science", "type": "Letter", "paper_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.md", "paper_geo_status": "v2", "authors": [ "Ge Zhang", "Honglin Zheng", "Qiang Li", "Taiqi Zhao", "Teng Li" ], "doi_url": "https://doi.org/10.1126/science.aek9583", "publisher_url": "https://spj.science.org/doi/abs/10.1126/science.aek9583?af=R", "pmid": "42821669", "pmcid": null, "openalex_id": null, "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1126-science-aek9583.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1126-science-aek9583.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1126-science-aek9583.csl.json", "evidence_status": "reviewed_v2", "question_count": 5, "key_findings": [ { "id": "KF1", "claim": "Keep directly related human protocols and major outcomes current in public registries.", "context": "The opening paragraph contrasts the previously reported human outcome with the registry and preclinical publication as described by the Letter. This is an attributed reporting-gap example, not an independently reconstructed clinical investigation.", "evidence": [ { "label": "Argument", "value": "Preserve the public translational record" } ], "source_locator": "Print p. 38, right column, Letter paragraph 1", "source": "data/deep_geo/doi-10-1126-science-aek9583.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#kf1" }, { "id": "KF2", "claim": "Treat a current public record as consequential when an individual outcome may be the available human evidence.", "context": "The authors explain why families, clinicians, ethics committees and other researchers may rely on a registry when considering continued human testing and emerging risks.", "evidence": [ { "label": "Argument", "value": "Single-patient evidence visibility" } ], "source_locator": "Print p. 38, right column, paragraph 2, continuing at p. 39, left column", "source": "data/deep_geo/doi-10-1126-science-aek9583.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#kf2" }, { "id": "KF3", "claim": "Distinguish safety reporting to oversight bodies from the publicly accessible account of translation.", "context": "Safety reports, registries and journal articles serve different purposes and update on different schedules; a report reaching regulators or ethics committees does not by itself ensure that public records are current.", "evidence": [ { "label": "Argument", "value": "Different reporting channels and schedules" } ], "source_locator": "Print p. 39, left column, Letter paragraph 3", "source": "data/deep_geo/doi-10-1126-science-aek9583.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#kf3" }, { "id": "KF4", "claim": "Coordinate protocol disclosure, serious-outcome reporting, cross-links and dated publication updates.", "context": "The authors propose disclosure of directly related human protocols before preclinical paper acceptance, registry fields for treatment-emergent deaths and life-threatening events, separation of event occurrence from suspected or confirmed causality, cross-links between records, and dated notices after publication.", "evidence": [ { "label": "Argument", "value": "Proposed public reporting practices" } ], "source_locator": "Print p. 39, left column, Letter paragraph 4; reference 3 provides the cited registration-standard context", "source": "data/deep_geo/doi-10-1126-science-aek9583.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#kf4" }, { "id": "KF5", "claim": "Use public notices to preserve the human experience without assigning blame or settling causality.", "context": "The concluding paragraph sets an explicit boundary: the reporting proposals connect claims of clinical promise to subsequent human experience, while leaving causal and responsibility determinations unresolved.", "evidence": [ { "label": "Boundary", "value": "Reporting is distinct from causal attribution" } ], "source_locator": "Print p. 39, left column, Letter paragraph 5, immediately before the author line", "source": "data/deep_geo/doi-10-1126-science-aek9583.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#kf5" } ], "field_entry": [ "Individualized genetic therapy research", "Clinical trial registration and reporting" ], "review_topics": [ "Reporting major human outcomes in individualized genetic therapies", "Linking preclinical publications and human trial records" ], "concepts": { "research_governance": [ "Public trial registry", "Human protocol disclosure", "Translational record linkage", "Dated publication notice" ], "evidence_boundaries": [ "Single-patient research context", "Treatment-emergent event reporting", "Event occurrence versus causality" ] }, "profile_type": "narrative_review", "study_profile": { "profile_type": "narrative_review", "narrative_genre": "correspondence", "study_design": "Science Letter presenting a reporting and governance argument using a previously reported case and three cited sources; no new clinical trial or systematic evidence synthesis.", "evidence_type": "Author argument and reporting proposals in a published Letter, with contextual references to prior reporting, a trial registry, preclinical research and WHO registration standards.", "evidence_domains": [ "Public clinical trial records", "Preclinical-to-human research disclosure", "Major human outcome reporting", "Individualized genetic therapy governance" ], "diseases_covered": [ "Individualized genetic therapies (discussion context)" ], "translation_scope": "Public documentation and linkage of translational research records; the Letter does not test a therapy or quantify whether its proposed reporting practices improve patient outcomes.", "scale_metrics": [ { "label": "Publication genre", "value": "Letter" }, { "label": "Evidence basis", "value": "Narrative argument and contextual citations" }, { "label": "New empirical evaluation", "value": "None reported in this Letter" } ], "counting_note": "Single-patient describes the research context discussed in the Letter. It is not an observed n=1 dataset produced by these authors; no sample total is assigned." }, "study_profile_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": "correspondence", "gold_source": "data/deep_geo/doi-10-1126-science-aek9583.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1126-science-aek9583.json", "gold_content_sha256": "705d1e430afa0be856894f2962dd2ce698dddc38294fd997dbcfccafa4a0a294", "provenance": { "publisher_url": "https://www.science.org/doi/10.1126/science.aek9583", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/42821669/", "review_basis": "Complete Letter reviewed in local publisher print-page images for pages 38-39; exact title, all five authors, DOI, print date and references matched to PubMed, Crossref and publisher identity. Only this Letter's columns were used.", "source_version": "Published print pages, Science 394(6819):38-39, 1 October 2026. Page-image download watermark identifies science.org via Shanghai Jiao Tong University on 2 October 2026. Source hashes and paragraph locators are retained in SCIENCE_GOLD_STANDARD.json; the copyrighted full pages are not redistributed by this site." }, "scientific_role": "A Science Letter proposing more current, connected public records of major human outcomes in individualized genetic therapy research.", "evidence_position": "Published reporting and research-governance argument; no new empirical clinical trial, treatment-effect estimate or causal adjudication.", "related_concepts": [ "Public trial registry transparency", "Treatment-emergent event reporting", "Event occurrence versus causal attribution" ], "citation_contexts": [ "Reviews discussing transparent reporting of serious outcomes in highly individualized genetic therapies.", "Research governance discussions on linking preclinical publications, human protocols, trial registries and dated updates without conflating event reporting with causality." ], "evidence_scope": { "supports": [ "Citation of the authors' rationale for current, linked public records in individualized genetic therapy research.", "Discussion of proposed disclosure and serious-outcome reporting practices.", "The distinction between event occurrence, causal assessment and responsibility." ], "does_not_establish": [ "A new clinical trial or a clinical dataset generated by the Letter's authors.", "The safety, efficacy or causal effect of an individualized genetic therapy.", "A quantitative reduction in reporting gaps or improved patient outcomes from the proposals.", "An independent adjudication of the reported case, blame or legal responsibility." ] }, "limitations": [ "The Letter is a narrative argument, not an original clinical study, systematic review or evaluation of its proposed reporting practices.", "The reported case and registry situation are attributed to the Letter and its cited sources; this page does not independently reconstruct the case or assert that the registry still has the same status today.", "The cited preclinical paper is contextual prior research; its experiments and results are not evidence newly produced by this Letter.", "Clinical effectiveness, causal attribution and legal responsibility require evidence beyond the Letter.", "The complete Letter was reviewed from local publisher print-page images. Those pages include neighboring Letters, which were excluded from this evidence layer." ], "scope_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/evidence_scope" }, { "id": "doi-10-1038-s41698-026-01699-1", "title": "System biology analysis reveals circadian rhythm disorder associated with development and progression in colorectal cancer", "doi": "10.1038/s41698-026-01699-1", "year": 2026, "journal": "npj Precision Oncology", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.md", "paper_geo_status": "v2", "authors": [ "Shiqian Zhang", "Shanshan Cai", "Naijing Hou", "Qian Guo", "Pengpeng Zhang", "Zhijie Zhao", "Song-Bin Guo", "Xufeng Huang", "Huaqing Wang", "Haonan Zhang", "Chaoyang Yu", "Ruhao Wu", "Chunze Zhang", "Shing Yau Tam", "Ge Zhang" ], "doi_url": "https://doi.org/10.1038/s41698-026-01699-1", "publisher_url": "https://www.nature.com/articles/s41698-026-01699-1", "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W7213428234", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1038-s41698-026-01699-1.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1038-s41698-026-01699-1.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1038-s41698-026-01699-1.csl.json", "evidence_status": "reviewed_v2", "question_count": 8, "key_findings": [ { "id": "KF1", "claim": "A CRC-focused circadian transcriptional architecture was derived from a 906-gene colon circadian reference and a 94,683-cell single-cell framework.", "context": "GSE10644-derived circadian reference mapped into the GSE166555 CRC single-cell cohort, followed by KNN meta-cell aggregation and high-dimensional co-expression analysis", "evidence": [ { "label": "primary tissue samples", "value": "13 CRC and 12 normal mucosal samples" }, { "label": "post-QC cells", "value": "94,683" }, { "label": "cellular structure", "value": "19 clusters; 9 major cell types" }, { "label": "initial circadian reference", "value": "906 genes; FDR <0.01 and R² ≥0.7 in the source temporal analysis" }, { "label": "meta-cell sparsity setting", "value": "K=50 gave the reported optimal sparsity reduction" }, { "label": "co-expression modules", "value": "9" }, { "label": "selected CRC-associated modules", "value": "M1, M3, M4 and M6" }, { "label": "CTD signature", "value": "559 genes across the four selected modules" } ], "source_locator": "Results: single-cell CRC landscape and high-dimensional circadian co-expression network, Fig. 1A-I and Supplementary Fig. 2; Methods: Single-cell RNA sequencing, Bulk RNA sequencing, and microarray chip cohort processing; Expression of the circadian gene set in the colorectum; High-dimensional co-expression network analysis; Supplementary Tables 2-3", "source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#kf1" }, { "id": "KF2", "claim": "ClockProCRC used expression-matched random-background correction and tracked circadian perturbation across multiple independent human and animal datasets.", "context": "ClockProCRC development and cross-species circadian robustness evaluation", "evidence": [ { "label": "expression stratification", "value": "100 expression bins" }, { "label": "random-background sampling", "value": "1,000 iterations with expression-matched feature selection" }, { "label": "single-cell CRD grouping", "value": "75th-percentile cutoff" }, { "label": "bulk-RNA grouping", "value": "cohort median commonly used" }, { "label": "article-reported robustness datasets", "value": "16 independent public datasets" }, { "label": "cross-species phase alignment", "value": "mouse Zeitgeber time shifted by 12 h before alignment with human/primate rhythms" }, { "label": "interpretation", "value": "higher ClockProCRC values represented greater endogenous circadian dysregulation in the article's framework" }, { "label": "score gene-set scope", "value": "The scoring Methods refers to circadian rhythm disorder genes (CRGs). The evidence page does not assume that the separate 559-gene CTD network signature is identical to the final ClockProCRC score input." } ], "source_locator": "Results: ClockProCRC score detection and quantification of endogenous circadian disorder states, Fig. 2B-I and Supplementary Fig. 3A; Methods: Development of ClockProCRC scoring system; Detection of the biological clock rhythm of the ClockProCRC score; Assessment of Cross-species Rhythmic Module Concordance", "source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#kf2" }, { "id": "KF3", "claim": "Higher ClockProCRC values were associated with CRC progression-related states and poorer survival in the analyzed retrospective/public cohorts.", "context": "Clinical-association and cross-cohort evaluation of ClockProCRC", "evidence": [ { "label": "survival cohort", "value": "GSE17537, n=55" }, { "label": "survival association", "value": "higher ClockProCRC associated with lower overall-survival probability; log-rank P<0.01" }, { "label": "RCS reference", "value": "ClockProCRC 0.0197 corresponded to ln(HR)=0 / HR=1 in the displayed spline model" }, { "label": "progression trajectory", "value": "scores increased across normal mucosa → adenoma/polyp → high/severe dysplasia → CRC → colorectal liver metastasis" }, { "label": "GSE68468 progression comparison", "value": "P<0.0001" }, { "label": "multi-cohort robustness", "value": ">1,400 CRC samples across 10 independent cohorts" } ], "source_locator": "Results: Analysis of clinical significance of ClockProCRC score, Fig. 3A-I; Methods: Analysis of the evaluation and clinical correlation of circadian rhythm disorder scores", "source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#kf3" }, { "id": "KF4", "claim": "ClockProCRC-defined circadian states were associated with distinct single-cell composition and intercellular-communication patterns in CRC.", "context": "Single-cell analysis in GSE200997 and GSE196964 using ClockProCRC state assignment, Ro/e enrichment and NICHES signaling analysis", "evidence": [ { "label": "single-cell evaluation cohorts", "value": "GSE200997 and GSE196964" }, { "label": "intensified-CRD enrichment pattern", "value": "epithelial and plasma-cell populations were preferentially enriched in higher-disruption states" }, { "label": "more stable-rhythm pattern", "value": "fibroblast and endothelial populations were preferentially enriched in lower-disruption/stable states" }, { "label": "communication pattern", "value": "higher-disruption states showed stronger epithelial/plasma interaction weights and altered pathway-level cell-cell signaling" }, { "label": "pathway pattern", "value": "progression from alleviate to intensify states was associated with reduced apoptotic-pathway activity and increased pro-inflammatory communication" } ], "source_locator": "Results: Dissecting the circadian rhythm disorder of colorectal cancer from single-cell resolution, Fig. 4A-G and Supplementary Fig. 3C-E; Methods: Single-cell RNA data analysis; NICHES ligand-receptor signaling analysis", "source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#kf4" }, { "id": "KF5", "claim": "Gene-regulatory-network analysis prioritized SYNE1 within a CRC-associated circadian dysregulation axis, with NFATC2-SYNE1 regulation differing between CRC and normal mucosa.", "context": "Dysregsig-based gene-regulatory-network analysis of CTD genes followed by cross-dataset SYNE1 contextualization", "evidence": [ { "label": "genetic-algorithm iterations", "value": "100" }, { "label": "recurrent regulatory axes", "value": "61" }, { "label": "NFATC2→SYNE1 regulatory strength in CRC", "value": "0.607; 95% CI 0.412-0.802" }, { "label": "NFATC2→SYNE1 regulatory strength in normal mucosa", "value": "-0.102; 95% CI -0.058-0.262" }, { "label": "circadian context", "value": "SYNE1 showed time-dependent or perturbation-associated expression changes across independent circadian datasets including GSE43073, GSE35026, GSE56931 and GSE30411" }, { "label": "metastasis-associated expression", "value": "SYNE1 expression was higher in colorectal liver metastasis than primary CRC in the reported analyses (Wilcoxon P=0.035 and P=0.048)" } ], "source_locator": "Results: Key circadian and night regulatory genes screening and their effects on circadian rhythm disorder in colorectal cancer, Fig. 5A-G and Supplementary Figs. 3F, 4A-E, 5F-G; Methods: Construction of the circadian rhythm gene regulation network (GRN)", "source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#kf5" }, { "id": "KF6", "claim": "SYNE1 and CLOCK perturbation experiments linked the computational circadian state to CRC-cell migration, invasion, proliferation-associated phenotypes and epithelial/mesenchymal marker changes.", "context": "HCT116 and SW480 CRC-cell experiments using SYNE1 or CLOCK siRNA, cell-line RNA sequencing, qRT-PCR, functional assays and melatonin rescue conditions", "evidence": [ { "label": "cell models", "value": "HCT116 and SW480" }, { "label": "SYNE1 perturbation", "value": "two specific siRNAs were used for knockdown" }, { "label": "Transwell result", "value": "SYNE1 knockdown reduced migration and invasion; 3 independent biological replicates with 4 random microscopic fields averaged per experiment" }, { "label": "wound-healing result", "value": "SYNE1 knockdown reduced migration" }, { "label": "colony-formation result", "value": "SYNE1 knockdown reduced colony formation in both cell lines" }, { "label": "epithelial/mesenchymal markers", "value": "E-cadherin and ZO-1 increased, while N-cadherin decreased after SYNE1 knockdown" }, { "label": "CLOCK perturbation", "value": "CLOCK knockdown increased ClockProCRC; melatonin treatment partially restored the molecular state" }, { "label": "SYNE1 rhythmicity", "value": "si-NC P=2.5×10^-4; si-CLOCK P=0.0704; si-CLOCK+melatonin P=3.4×10^-3" }, { "label": "SYNE1 ROC scope", "value": "AUC=0.915 for discriminating CLOCK-knockdown experimental conditions, not for diagnosing CRC in patients" }, { "label": "melatonin condition", "value": "0.1 mM for 24 h before RNA collection in the cell experiment" } ], "source_locator": "Results: SYNE1 functional and circadian-perturbation experiments, Fig. 6A-N and related supplementary figures; Methods: Cell lines; Cell transfection with siRNA and plasmids; Bulk RNA-seq; qRT-PCR; Transwell assay and scratch assay; Western blot analysis; Cell cloning formation experiment", "source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#kf6" } ], "field_entry": [ "Circadian biology in cancer", "Colorectal cancer systems biology" ], "review_topics": [ "Circadian disruption and tumor heterogeneity", "Transcriptomic scoring of tumor-microenvironment states" ], "concepts": { "conditions": [ "colorectal cancer", "colorectal liver metastasis", "circadian rhythm disruption", "circadian misalignment" ], "methods": [ "ClockProCRC", "KNN meta-cell aggregation", "high-dimensional co-expression network analysis", "expression-matched random-background scoring", "24-hour sinusoidal rhythmicity modeling", "restricted cubic spline Cox regression", "Singscore", "Ro/e cell enrichment", "NICHES ligand-receptor analysis", "Dysregsig gene-regulatory-network analysis", "GSVA", "GSEA", "qRT-PCR", "Transwell assay", "wound-healing assay", "colony-formation assay", "Western blotting" ], "modalities": [ "single-cell RNA sequencing", "bulk RNA sequencing", "microarray transcriptomics", "cross-species circadian transcriptomics", "cell-line transcriptomics" ], "molecular_entities": [ "SYNE1", "NFATC2", "CLOCK", "E-cadherin", "ZO-1", "N-cadherin" ], "cellular_entities": [ "epithelial cells", "plasma cells", "fibroblasts", "endothelial cells", "HCT116", "SW480" ], "biological_processes": [ "circadian rhythmicity", "tumor progression", "cell-cell communication", "migration", "invasion", "colony formation", "epithelial-mesenchymal phenotype" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Multicohort systems-biology study integrating public bulk transcriptomics, microarrays, single-cell RNA sequencing, cross-species circadian perturbation datasets, gene-regulatory-network analysis, and in-vitro CRC-cell perturbation experiments", "evidence_type": "Public transcriptomic and single-cell cohort analysis, expression-matched circadian scoring, cross-species rhythmicity evaluation, survival and clinical-association analysis, single-cell cell-state and ligand-receptor analysis, gene-regulatory-network analysis, and in-vitro functional perturbation", "population": "Public human colorectal-cancer and normal-mucosal datasets, public human/mouse/non-human-primate circadian time-series and perturbation datasets, and HCT116/SW480 colorectal-cancer cell models", "primary_endpoint": "Development and multicohort evaluation of ClockProCRC as a transcriptomic measure of endogenous circadian misalignment", "secondary_endpoint": "Association of ClockProCRC with CRC progression, survival and tumor-microenvironment states, plus prioritization and functional testing of SYNE1 as a circadian-associated CRC regulator", "data_modalities": [ "single-cell RNA sequencing", "bulk RNA sequencing", "microarray expression profiling", "cross-species circadian time-series transcriptomics", "gene-regulatory-network analysis", "CRC-cell perturbation RNA sequencing", "qRT-PCR", "Transwell and wound-healing assays", "colony-formation assays", "Western blotting" ], "external_validation": true, "scale_metrics": [ { "label": "article-reported aggregate", "value": "3,758 samples across 35 public GEO datasets" }, { "label": "abstract-reported additional cohort layer", "value": "3,733 samples from 34 additional public bulk RNA, microarray and single-cell cohorts, alongside the 25-sample primary single-cell cohort" }, { "label": "primary CRC single-cell cohort", "value": "GSE166555; 25 tissue samples: 13 CRC and 12 normal mucosal samples" }, { "label": "post-QC single cells", "value": "94,683" }, { "label": "single-cell structure", "value": "19 clusters and 9 major cell types" }, { "label": "initial colon circadian reference", "value": "906 genes; maSigPro-derived temporal genes with FDR <0.01 and goodness-of-fit R² ≥0.7" }, { "label": "circadian co-expression network", "value": "9 modules after meta-cell network construction" }, { "label": "CRC-associated CTD signature", "value": "4 modules (M1, M3, M4 and M6), totaling 559 genes" }, { "label": "ClockProCRC random-background model", "value": "100 expression bins and 1,000 expression-matched random samplings" }, { "label": "article-reported circadian robustness evaluation", "value": "16 independent public datasets spanning human, mouse and non-human-primate circadian contexts" }, { "label": "CRC cross-cohort robustness layer", "value": ">1,400 CRC samples across 10 independent cohorts" }, { "label": "functional CRC cell models", "value": "HCT116 and SW480" } ], "counting_note": "The article reports heterogeneous evidence units. The 25 tissue samples in the primary GSE166555 single-cell cohort yielded 94,683 post-QC cells and must not be conflated with participant counts. The Methods reports an aggregate 3,758 samples across 35 public datasets, while the Abstract describes the primary 25-sample single-cell cohort plus 3,733 samples from 34 additional cohorts. These figures are preserved as article-reported dataset/sample counts and are not interpreted as 3,758 unique human participants." }, "study_profile_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1038-s41698-026-01699-1.json", "gold_content_sha256": "993d6127d6880bcd8b5a71cc81bd7a371dfacd99d18b1eafdc2e0777ff3994d0", "provenance": { "publisher_url": "https://www.nature.com/articles/s41698-026-01699-1", "code_url": "https://github.com/DrZoggg/ClockProCRC", "datasets_cohorts": "GSE166555; GSE200997; GSE196964; GSE41258; GSE44076; GSE68468; GSE62321; GSE140973; GSE17537; GSE39084; GSE103479; GSE77955; GSE81582; GSE117606; GSE37364; GSE26571; GSE186727; GSE71187; GSE49355; GSE51244; GSE124870; GSE98965; GSE54650; GSE10644; GSE57830; GSE143524; GSE56931; GSE98564; GSE30411; GSE39445; GSE45818; GSE11923; GSE98565; GSE43073; GSE35026", "evidence_basis": "Publisher early peer-reviewed article plus the revised accepted manuscript, publisher supplementary-material listing, cited GEO accessions, and the associated ClockProCRC code repository. Manuscript Results/Methods and figure legends are used as the primary source for quantitative source locators.", "publication_status": "Published 16 September 2026 with a permanent DOI. As of 24 September 2026, Springer Nature labels the available article as an early peer-reviewed accepted version subject to further editing and automatic replacement by the final Version of Record.", "count_reconciliation": "The Abstract reports 13 CRC tissues + 12 normal mucosal samples plus 3,733 samples from 34 additional cohorts; the Methods reports 3,758 samples across 35 public datasets overall. These are retained as two compatible article-reported views of the study inventory rather than converted into a unique-participant total.", "accession_note": "The Results text contains GSE200977, while the Methods and Figure 4 legend identify the CRC single-cell dataset as GSE200997. The evidence page uses GSE200997 and records the alternative Results-text accession as a manuscript typo.", "code_note": "The public ClockProCRC repository is treated as associated code, not as a byte-for-byte implementation of the accepted manuscript. The repository README reports an earlier 32-cohort/3,075-sample configuration; the current scoring script defaults to 50 bins whereas the manuscript specifies 100 bins; DiffCircadian.R includes a placeholder score implementation.", "score_gene_set_note": "The manuscript distinguishes a 906-gene colon circadian reference from a 559-gene CTD network signature. In the reviewed Methods text, the ClockProCRC scoring procedure is described using circadian rhythm disorder genes (CRGs); it does not explicitly state that the 559 CTD genes are the final scoring input. These gene-set roles are therefore kept separate.", "locator_note": "Where Results prose and figure legends disagree on panel labels or assay wording, the evidence page uses the experimental Methods plus the figure legend to define the assay and cites the broader Results/Figure block rather than propagating an ambiguous panel reference." }, "scientific_role": "Integrative circadian-associated expression scoring with single-cell tumor interpretation and experimental follow-up of candidate regulators.", "evidence_position": "Public multicohort transcriptomics, retrospective clinical associations and colorectal-cancer cell perturbations; not prospective clinical validation or proven patient treatment efficacy.", "related_concepts": [ "Circadian-associated tumor states", "Expression-based circadian scoring" ], "citation_contexts": [ "Background: links between circadian dysregulation and colorectal-cancer heterogeneity.", "Methods: systems-level expression scoring and experimental follow-up, distinguished from clinical chronotherapy." ], "evidence_scope": { "supports": [ "The article defines a 906-gene colon circadian reference and derives CRC-associated circadian co-expression structure from a 94,683-cell single-cell dataset.", "ClockProCRC uses expression-matched random-background correction and varies in expected directions across multiple experimentally or behaviorally perturbed circadian datasets.", "Higher ClockProCRC values are associated with CRC progression-related states and poorer overall survival in the analyzed retrospective/public cohorts.", "ClockProCRC-defined states are associated with distinct CRC single-cell composition and intercellular-communication patterns.", "SYNE1 is prioritized by gene-regulatory-network analysis and shows circadian perturbation-associated expression/rhythmicity changes across independent datasets.", "SYNE1 knockdown in HCT116 and SW480 cells reduces migration, invasion and colony formation and shifts E-cadherin, ZO-1 and N-cadherin expression.", "CLOCK knockdown and melatonin rescue conditions alter ClockProCRC and SYNE1 rhythmicity in CRC-cell experiments." ], "does_not_establish": [ "That ClockProCRC has been prospectively validated in a multicenter clinical cohort.", "That ClockProCRC is a clinically approved diagnostic, prognostic, screening or treatment-selection test.", "That the cohort-specific median or single-cell 75th-percentile grouping rules define a universal clinical cutoff.", "That higher ClockProCRC causally drives CRC progression in humans; most clinical and tumor-microenvironment evidence is observational or retrospective.", "That ClockProCRC adds incremental clinical utility over established CRC staging, molecular markers or treatment-response assessment.", "That SYNE1 is a validated therapeutic target in patients with CRC.", "That SYNE1 inhibition improves tumor control, metastasis or survival in vivo; the study reports cell-line perturbation but no SYNE1-directed animal efficacy experiment.", "That melatonin treatment is effective for CRC patients; melatonin was used as a molecular rescue condition in cell experiments.", "That AUC=0.915 represents CRC diagnosis or patient-level prediction; it refers to discrimination of CLOCK-knockdown experimental conditions by SYNE1 expression.", "That single-cell ligand-receptor and pathway analyses prove causal tumor-microenvironment remodeling." ] }, "limitations": [ "Most human clinical evidence derives from retrospective/public transcriptomic datasets rather than a prospectively enrolled multicenter clinical validation cohort.", "The study integrates heterogeneous evidence units across human, mouse and non-human-primate datasets; sample, tissue, cohort and cell counts are not interchangeable.", "ClockProCRC grouping uses data-context-specific thresholds (75th percentile for single-cell analyses and commonly the cohort median for bulk cohorts), not a universal clinical cutoff.", "The manuscript distinguishes the 906-gene colon circadian reference from the 559-gene four-module CTD signature. The ClockProCRC scoring Methods refers to circadian rhythm disorder genes (CRGs), so this evidence page does not infer that the 559 CTD genes are identical to the final score-input gene set.", "The Results text contains the accession GSE200977, whereas the Methods and Figure 4 legend identify the CRC single-cell cohort as GSE200997; the evidence page uses GSE200997 and records the Results-text accession as a manuscript typo.", "The manuscript contains several wording/locator inconsistencies, including knockdown described once as knockout, Transwell language that conflates proliferation with migration/invasion, and a scratch-assay timing inconsistency; the evidence page follows the experimental Methods and figure legends.", "The public ClockProCRC GitHub repository is an associated code resource but does not exactly mirror the accepted manuscript: the README reports an earlier 32-cohort/3,075-sample configuration, the current scoring script defaults to 50 bins rather than the manuscript's 100 bins, and DiffCircadian.R contains a placeholder scoring function.", "SYNE1 functional evidence is in vitro; no SYNE1-directed animal efficacy experiment or human therapeutic study is reported.", "The publisher currently labels the article as an early peer-reviewed accepted version that may undergo further editing before the final Version of Record." ], "scope_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/evidence_scope" }, { "id": "doi-10-1111-jdi-70462", "title": "The cholesterol, high-density lipoprotein, and glucose index and its derivatives related to obesity and inflammation as novel metabolic markers for predicting new-onset cardiovascular-liver-metabolic multimorbidity: A prospective cohort study", "doi": "10.1111/jdi.70462", "year": 2026, "journal": "Journal of Diabetes Investigation", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.md", "paper_geo_status": "v2", "authors": [ "Zhonghua Sun", "Aikeliyaer Ainiwaer", "Yameng Xu", "Ge Zhang", "Xiangyu Sun", "Xinliang Peng", "Yuanhui Dai", "Kaisaierjiang Kadier" ], "doi_url": "https://doi.org/10.1111/jdi.70462", "publisher_url": null, "pmid": null, "pmcid": null, "openalex_id": null, "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1111-jdi-70462.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1111-jdi-70462.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1111-jdi-70462.csl.json", "evidence_status": "reviewed_v2", "question_count": 7, "key_findings": [ { "id": "KF1", "claim": "A prospective CHARLS analysis identified incident, surrogate-defined cardiovascular–liver–metabolic multimorbidity at follow-up.", "context": "Chinese community-dwelling adults without baseline CLMM; component conditions were evaluated at baseline and the follow-up wave, rather than using exact onset dates.", "evidence": [ { "label": "Analytic participants", "value": "6,534 adults aged 45 years or older" }, { "label": "Exposure and outcome waves", "value": "2011 baseline and 2015 follow-up" }, { "label": "Incident CLMM", "value": "406 participants; 6.2%" }, { "label": "Outcome definition", "value": "At least two of CVD, type 2 diabetes, and LAP-based suspected MASLD" } ], "source_locator": "Methods: Study population and Outcome assessment (jdi70462-sec-0007; jdi70462-sec-0009); Results 3.1 (jdi70462-sec-0013); Figure 1; Table 1", "source": "data/deep_geo/doi-10-1111-jdi-70462.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#kf1" }, { "id": "KF2", "claim": "Higher baseline CHG was associated with higher odds of meeting the CLMM criteria at follow-up.", "context": "Highest versus lowest CHG quartile in the fully adjusted logistic model; these are odds ratios for a binary follow-up outcome, not hazard ratios or treatment effects.", "evidence": [ { "label": "CHG Q4 versus Q1 adjusted OR", "value": "1.64; 95% CI 1.22–2.22" }, { "label": "Adjusted covariates", "value": "Age, sex, education, residence, marital status, smoking, drinking, hypertension, and CKD" } ], "source_locator": "Results 3.2 (jdi70462-sec-0014); Table 2 (jdi70462-tbl-0002), CHG Q4, Model 2", "source": "data/deep_geo/doi-10-1111-jdi-70462.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#kf2" }, { "id": "KF3", "claim": "CHG combined with BMI showed a stronger quartile association with incident CLMM than CHG alone within this analysis.", "context": "Comparing the highest and lowest CHG-BMI quartiles within the same cohort and fully adjusted model; relative effect-size ranking does not establish a causal role or clinical utility.", "evidence": [ { "label": "CHG-BMI Q4 versus Q1 adjusted OR", "value": "3.13; 95% CI 2.21–4.43" }, { "label": "Comparison", "value": "CHG alone Q4 versus Q1: OR 1.64; 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index-specific ROC analysis", "performance_scope": "Apparent discrimination in the same analysis sample; no internal or external validation", "endpoint_timing": "Exact onset dates were unavailable; ORs are not hazard ratios", "clinical_thresholds": "Sample-derived median and Youden cut-offs are not established clinical decision thresholds" }, "model_profile_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/model_profile", "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1111-jdi-70462.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1111-jdi-70462.json", "gold_content_sha256": "1e1e66bb0b3dd4f428b4651b95de103c9864a01baed4626c71a588932c330ae5", "provenance": { "publisher_url": "https://onlinelibrary.wiley.com/doi/10.1111/jdi.70462", "doi_url": "https://doi.org/10.1111/jdi.70462", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/42852842/", "pmcid": "PMC13651581", "version_of_record": "Journal of Diabetes Investigation; Early View, first published 9 October 2026", "license": "Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)", "license_url": "https://creativecommons.org/licenses/by-nc/4.0/", "data_source": "China Health and Retirement Longitudinal Study, 2011 baseline and 2015 follow-up", "supporting_material": "Tables S1–S8 are linked in the version-of-record supplementary material; key estimates on this page are located in the full-text Results and principal tables.", "author_identity": "Ge Zhang is listed with the Department of Cardiology, The First Affiliated Hospital of Zhengzhou University. The DOI is present in public ORCID 0000-0002-3116-3246; the self-maintained ORCID linkage is distinct from publisher-authenticated identity.", "evidence_basis": "Version-of-record full text via Europe PMC XML; Methods, Results, Tables 1–3 and article-level permissions; PubMed and public ORCID metadata." }, "scientific_role": "Prospective observational association study with apparent discrimination analysis, requiring independent validation.", "evidence_position": "Population-level candidate-marker evidence with a surrogate liver-disease component; causal and clinical-utility claims remain unestablished.", "related_concepts": [ "CHG-BMI", "CHARLS", "LAP-based suspected MASLD" ], "citation_contexts": [ "Reviews comparing metabolic indices for incident, surrogate-defined cardiometabolic multimorbidity.", "Methodological discussions separating observational odds ratios and apparent AUCs from validated clinical prediction." ], "evidence_scope": { "supports": [ "Associations between baseline indices and meeting study-defined CLMM criteria at follow-up in this CHARLS analysis.", "CHG-BMI ranking highest among evaluated indices for apparent ROC discrimination in this sample.", "Hypothesis generation and independent validation of accessible metabolic-marker combinations." ], "does_not_establish": [ "A causal effect of CHG, obesity, or inflammation on multimorbidity.", "Imaging- or biopsy-confirmed MASLD in every participant.", "Hazard ratios, exact onset timing, or a time-to-event prediction model.", "Independent internal or external validation, clinical net benefit, treatment efficacy, or a validated clinical cut-off." ] }, "limitations": [ "Residual confounding and observational design prevent causal inference.", "Exact component-disease onset dates were unavailable; logistic ORs cannot be interpreted as hazards or incidence rates.", "The MASLD component used an LAP-based suspected phenotype and may be misclassified; metabolic components overlap conceptually with the exposure indices.", "The ROC analyses used the same analysis sample without internal or external validation, so apparent AUCs may be optimistic.", "Single baseline exposure measurements, substantial complete-data selection, medication changes, correlated comparisons, and exploratory subgroup analyses limit interpretation.", "Generalizability beyond Chinese adults aged at least 45 years requires independent evaluation." ], "scope_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/evidence_scope" }, { "id": "doi-10-1002-mdr2-70073", "title": "Transforming Musculoskeletal Disorder Management With Multimodal AI Platform for Early Diagnosis, Self-Screening, and Personalized Care", "doi": "10.1002/mdr2.70073", "year": 2026, "journal": "Med Research", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70073.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70073.md", "paper_geo_status": "none", "authors": [ "Pengyuan Xu", "Guang Yang", "Ge Zhang", "Yafang Zhao", "Pu Wan", "Guiyun Zhou", "Mengjie Jiang", "Yixin Zhang", "Zhaoyang Wang", "Yichen Dai", "Xiqing Zhao", "Ziliang Fu", "Ziyu Zheng", "Ziyun Xu", "Ruisi Dong", "Xiaojie Xia", "Duo Zhang", "Yisheng He", "Michael Moran", "Qiguang Wang", "Tim Woodfield", "Khoon Lim", "Tiantian Kong", "Junnan Tang", "Kang Tian", "Kai Zhou", "Hao Chi", "Pengpeng Zhang", "Jianhua Yang", "Mingliang Zhang", "Moyan Li", "Yuan Cheng", "Xiaolin Cui" ], "doi_url": "https://doi.org/10.1002/mdr2.70073", "publisher_url": null, "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W7163366492", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1002-mdr2-70073.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1002-mdr2-70073.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1002-mdr2-70073.csl.json", "evidence_status": "limited", "question_count": 0, "key_findings": [], "field_entry": [], "review_topics": [], "concepts": {}, "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70073.html#limited-evidence", "source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/limited_evidence.json", "provenance": [ { "url": "https://onlinelibrary.wiley.com/doi/full/10.1002/mdr2.70073", "label": "Article source", "format": "Official publisher or PMC full text reviewed locally", "locator": "Results 2.1–2.2; Figure 3 caption" } ], "scope": "Reported multimodal design; diagnostic performance and clinical utility remain unverified.", "evidence_notice": "Reported multimodal design; diagnostic performance and clinical utility remain unverified.", "evidence_scope": null, "limitations": [ "Training AUC/CI pairs are internally inconsistent.", "Predictor count and model-selection/evaluation separation are unresolved.", "Reported architecture does not demonstrate prospective clinical benefit." ], "scope_source": "data/limited_evidence.json#/papers/10.1002~1mdr2.70073/scope" }, { "id": "doi-10-1172-jci194175", "title": "Vascular smooth muscle cell-derived KIF13B inhibits proinflammatory responses to protect against atherosclerosis", "doi": "10.1172/jci194175", "year": 2026, "journal": "Journal of Clinical Investigation", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.md", "paper_geo_status": "v2", "authors": [ "Guolin Miao", "Yufei Han", "Jingxuan Chen", "Yiran Liu", "Ge Zhang", "Shaotong Pei", "Yinqi Zhao", "Yitong Xu", "Liwen Zheng", "Zhaoling Li", "Xiangru Liu", "Sijing Shi", "Xuya Kang", "Yahan Liu", "Ling Zhang", "Wei Huang", "Yuhui Wang", "Junnan Tang", "Erdan Dong", "Xunde Xian" ], "doi_url": "https://doi.org/10.1172/jci194175", "publisher_url": "https://www.jci.org/articles/view/194175", "pmid": "41609725", "pmcid": "PMC12987658", "openalex_id": "https://openalex.org/W7126096260", "semantic_scholar_id": "fba34c8c12b4f065c86b0206c47e0dbb77aa9189", "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1172-jci194175.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1172-jci194175.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1172-jci194175.csl.json", "evidence_status": "reviewed_v2", "question_count": 10, "key_findings": [ { "id": "KF1", "claim": "Lower KIF13B was associated with more advanced or unstable human atherosclerotic plaque states, with prominent differences in VSMCs.", "context": "These human tissue and public-dataset observations are associative and do not establish that changing KIF13B alters plaque outcomes in patients.", "evidence": [ { "label": "Local carotid plaques", "value": "Six CEA patients contributed paired advanced and adjacent regions; Figure 1 reports lower KIF13B in advanced regions, with scRNA analysis n=4 per condition and protein/histologic analyses n=6 per condition." }, { "label": "GSE120521", "value": "KIF13B mRNA was lower in unstable than stable regions from four paired carotid plaques: n=4 stable and n=4 unstable." }, { "label": "PXD062283", "value": "KIF13B protein was lower in the JCI stable n=19 versus unstable n=38 plaque comparison." }, { "label": "Plaque matrix relationship", "value": "Human plaque analysis showed lower VSMC KIF13B and lower collagen in advanced regions, with a positive association between VSMC KIF13B signal and collagen content." }, { "label": "Epigenetic evidence", "value": "Supplementary public-dataset reanalysis associated higher KIF13B methylation with atherosclerotic versus control tissue and symptomatic versus asymptomatic plaque; this does not establish methylation as the cause of lower KIF13B." } ], "source_locator": "Results: Decreased expression of KIF13B in VSMCs is linked to the progression of atherosclerosis in humans; Figure 1; Supplemental Figure 1; Methods: Human studies.", "source": "data/deep_geo/doi-10-1172-jci194175.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#kf1" }, { "id": "KF2", "claim": "VSMC-specific Kif13b deletion worsened experimental atherosclerotic lesion and plaque-stability phenotypes in male AAV8-PCSK9 mice without detected differences in plasma total cholesterol or triglycerides in the tested model.", "context": "This supports a causal VSMC contribution in this mouse model; it does not establish a universally lipid-independent mechanism in humans.", "evidence": [ { "label": "Model", "value": "Male Kif13b floxed and VSMC-specific Kif13b-KO mice received AAV8-PCSK9-D377Y and Western diet for 20 weeks; major comparisons n=8 per group." }, { "label": "Plaque phenotype", "value": "Kif13b loss increased aortic and aortic-root lesion burden, necrotic-core area, CD68-positive macrophage accumulation and TUNEL-positive cells, while reducing collagen and plaque-stability features." }, { "label": "Plasma lipids", "value": "No detected genotype difference in plasma total cholesterol or triglycerides was reported in the primary Western-diet comparison." }, { "label": "Vascular function", "value": "Phenylephrine-induced aortic-ring contraction was impaired with VSMC Kif13b loss; n=4 per group." } ], "source_locator": "Results: Depletion of Kif13b in VSMCs exacerbates atherosclerosis in mice; Figure 2.", "source": "data/deep_geo/doi-10-1172-jci194175.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#kf2" }, { "id": "KF3", "claim": "The pooled mouse aortic single-cell comparison linked KIF13B loss to a shift from matrix/collagen-associated VSMC-derived states toward inflammatory programs.", "context": "Five mice were pooled into one library per genotype, limiting independent library-level replication. Figure captions also contain unresolved duration and cluster-label inconsistencies, so this page reports the robust program-level conclusion rather than over-resolving ambiguous subpanel labels.", "evidence": [ { "label": "Single-cell design", "value": "Ldlr-deficient and Ldlr-deficient Kif13b-deficient aortas used five pooled mice to create one single-cell sample per genotype." }, { "label": "Cell-state programs", "value": "KIF13B loss was associated with reduced extracellular-matrix/collagen programs and increased apoptosis/inflammatory programs, with fewer matrix-associated VSMC-Fib states and more inflammatory VSMC-Fib states." }, { "label": "Duration discrepancy", "value": "Figure 5 and Results describe 20 weeks of Western diet; Figure 6 SCENIC and Figure 7 integrative captions reference 12 weeks. The discrepancy is retained rather than resolved." }, { "label": "Cluster-label discrepancy", "value": "Results assign the inflammatory Ccl2/Il1b/Il6/Il18/Trap1 signal to VSMC-Fib4, while Figure 5K caption labels the panel VSMC-Fib1; no unqualified cluster-specific gene claim is made here." } ], "source_locator": "Results: Inhibiting KIF13B promotes proinflammatory fibroblast-like VSMC transition; Figures 5-7.", "source": "data/deep_geo/doi-10-1172-jci194175.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#kf3" }, { "id": "KF4", "claim": "KIF13B gain- and loss-of-function directly altered matrix, inflammatory and contractile phenotypes in primary human aortic smooth muscle cells under oxLDL.", "context": "These are cell-autonomous in vitro perturbation experiments and do not demonstrate a patient treatment effect.", "evidence": [ { "label": "KIF13B knockdown", "value": "Knockdown reduced TAGLN, collagen secretion and collagen-gel contraction while increasing fibroblast/inflammatory features; Western/ELISA assays generally n=3 and gel contraction n=5." }, { "label": "KIF13B overexpression", "value": "Overexpression produced reciprocal matrix/contractile effects; Western/ELISA assays generally n=3 and gel contraction n=6." } ], "source_locator": "Results: Inhibiting KIF13B promotes proinflammatory fibroblast-like VSMC transition; Figure 5L-Q and Supplemental Figure 3.", "source": "data/deep_geo/doi-10-1172-jci194175.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#kf4" }, { "id": "KF5", "claim": "KLF4 functionally mediated KIF13B-loss-associated VSMC reprogramming in primary HASMC experiments.", "context": "The rescue establishes a downstream functional relationship in this experimental system, not a causal human clinical mechanism.", "evidence": [ { "label": "KLF4 response", "value": "KIF13B knockdown increased KLF4 protein, whereas KIF13B overexpression decreased it; Western blot n=3 and selected immunofluorescence n=10." }, { "label": "Genetic rescue", "value": "Concomitant KLF4 knockdown rescued KIF13B-loss-associated reductions in collagen/matrix markers and increases in inflammatory factors; Western, qPCR and ELISA assays n=3." } ], "source_locator": "Results: KLF4 mediates KIF13B-dependent proinflammatory VSMC reprogramming; Figure 6.", "source": "data/deep_geo/doi-10-1172-jci194175.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#kf5" }, { "id": "KF6", "claim": "Proteostasis and rescue experiments support KCTD10-dependent KLF4 ubiquitination and proteasomal turnover downstream of KIF13B.", "context": "Molecular docking was predictive, while KCTD10-KLF4 association, ubiquitination and rescue were experimentally evaluated. The upstream mechanism by which KIF13B maintains KCTD10 abundance remains unresolved.", "evidence": [ { "label": "KLF4 turnover", "value": "CHX chase, MG132 and KLF4 ubiquitination assays showed that KIF13B knockdown stabilized KLF4 by attenuating proteasomal degradation; n=3 independent biological replicates." }, { "label": "KCTD10 identification", "value": "Integrated mouse VSMC and human unstable/stable plaque transcriptomics nominated KCTD10 and SKP1; KIF13B perturbation altered KCTD10 rather than SKP1 in HASMC protein assays." }, { "label": "KCTD10-KLF4 mechanism", "value": "Docking predicted interaction; co-IP supported KCTD10-KLF4 association, KCTD10 overexpression increased KLF4 ubiquitination and reduced KLF4 protein." }, { "label": "KCTD10 rescue", "value": "KCTD10 overexpression reversed KIF13B-knockdown-associated KLF4 stabilization and rescued collagen/inflammatory phenotypes." } ], "source_locator": "Results: KIF13B facilitates KCTD10-mediated ubiquitination and degradation of KLF4; Figures 7-8 and Supplemental Figure 4.", "source": "data/deep_geo/doi-10-1172-jci194175.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#kf6" }, { "id": "KF7", "claim": "Kenpaullone reduced KLF4 promoter activity/expression and produced preclinical rescue of KIF13B-loss-associated cellular and mouse plaque phenotypes.", "context": "Kenpaullone is not established as a KLF4-selective drug. Authoritative pharmacology sources describe it as an ATP-competitive CDK/GSK3β inhibitor. The rescue therefore supports preclinical pathway modulation but does not prove KLF4-selective pharmacology or human treatment efficacy.", "evidence": [ { "label": "Cell intervention", "value": "Kenpaullone at 10 µM reduced KLF4 and rescued collagen/inflammatory phenotypes after KIF13B knockdown in HASMCs; n=3 biological replicates for key Western/ELISA assays." }, { "label": "Mouse intervention", "value": "Male PCSK9 mice received oral Kenpaullone 1 mg/kg/day for the final 12 weeks of a 20-week Western-diet protocol; n=6 per group." }, { "label": "Mouse outcomes", "value": "Kenpaullone reduced measured inflammatory cytokines, lesion burden, necrotic-core area, CD68-positive macrophages and TUNEL-positive cells and increased collagen." }, { "label": "Measured safety-related endpoints", "value": "No detected changes were reported in measured body weight, plasma TC/TG or ALT/AST endpoints; these measurements do not establish general or human safety." } ], "source_locator": "Results: Pharmacological inhibition of KLF4 with Kenpaullone alleviates atherosclerosis in mice; Figure 9 and Supplemental Figures 5-7.", "source": "data/deep_geo/doi-10-1172-jci194175.json#/key_findings/6", "evidence_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#kf7" } ], "field_entry": [ "Atherosclerosis research", "Vascular smooth muscle biology" ], "review_topics": [ "Smooth muscle cell phenotypic remodeling", "Experimental regulation of plaque stability" ], "concepts": { "molecular_axis": [ "KIF13B", "KCTD10", "KLF4", "CUL3-associated ubiquitin ligase", "protein ubiquitination", "proteasomal degradation" ], "vascular_cells_and_states": [ "vascular smooth muscle cell", "VSMC phenotypic switching", "VSMC-Fib", "fibrous-cap VSMC", "contractile VSMC", "matrix-producing VSMC", "proinflammatory fibroblast-like VSMC" ], "plaque_phenotypes": [ "atherosclerotic lesion burden", "plaque stability", "fibrous cap", "collagen content", "necrotic core", "macrophage infiltration", "apoptosis", "vascular contractility" ], "experimental_models": [ "Tagln-Cre Kif13b VSMC-specific knockout", "AAV8-PCSK9-D377Y", "Ldlr-deficient mouse", "Ldlr-deficient Kif13b-deficient mouse", "Western diet", "primary HASMC", "oxLDL" ], "perturbations_and_rescue": [ "siKIF13B", "KIF13B overexpression", "siKLF4", "KCTD10 overexpression", "Kenpaullone", "MG132", "cycloheximide" ], "datasets_and_resources": [ "GSE314838", "GSE120521", "PXD062283", "GSE274572", "human plaque DNA methylation datasets", "JCI Supporting Data Values" ], "disease_context": [ "atherosclerosis", "atherosclerotic cardiovascular disease", "carotid atherosclerotic plaque", "advanced plaque", "unstable plaque", "plaque vulnerability" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Mechanistic translational preclinical study integrating associative human plaque observations and public multi-omic datasets with causal mouse genetics, pooled single-cell RNA sequencing, primary HASMC perturbation, biochemical rescue and preclinical pharmacologic intervention.", "evidence_type": "Associative human tissue and multi-omic evidence; causal mouse genetics; primary human VSMC perturbation; biochemical mechanism and rescue; preclinical pharmacologic rescue.", "population": "Paired carotid endarterectomy plaque regions from 6 patients; independent public human plaque datasets; male mouse atherosclerosis models; primary human aortic smooth muscle cells. No treated human atherosclerosis cohort.", "primary_endpoint": "Experimental atherosclerotic lesion burden, plaque-stability features and VSMC phenotypic remodeling across genetic models.", "secondary_endpoint": "Collagen and extracellular-matrix programs, inflammatory cytokines, VSMC contractile function, KLF4 protein regulation, KCTD10-dependent ubiquitination and preclinical pharmacologic rescue.", "data_modalities": [ "Paired human carotid plaque histology and protein analysis", "Human plaque bulk RNA sequencing", "Human plaque proteomics", "Human plaque DNA methylation", "Human plaque single-cell and spatial transcriptomic analysis", "Mouse plaque histology and plasma phenotyping", "Mouse aortic single-cell RNA sequencing", "Primary HASMC gain- and loss-of-function assays", "Protein stability, ubiquitination and co-immunoprecipitation assays", "Genetic and preclinical pharmacologic rescue" ], "external_validation": true, "scale_metrics": [ { "label": "Local paired carotid CEA cohort", "value": "6 patients. Each plaque supplied an advanced/culprit region and an adjacent upstream region from the same patient. Figure 1 reports scRNA analysis n=4 regions per condition and Western/histologic analyses n=6 regions per condition; these are paired regions, not 10 or 12 independent participants." }, { "label": "GSE120521", "value": "4 carotid endarterectomy patients, each contributing paired stable and unstable plaque regions: 4 stable and 4 unstable RNA-seq samples." }, { "label": "PXD062283", "value": "The ProteomeXchange repository contains 87 human carotid plaques overall; the JCI Figure 1 comparison uses stable n=19 and unstable n=38. Do not substitute the repository total for the study subset." }, { "label": "Human methylation evidence", "value": "Three independent public methylation datasets were reanalyzed in the Supplement. Dataset-specific denominators must remain separate and must not be summed into a synthetic human cohort." }, { "label": "Human spatial evidence", "value": "Public human plaque spatial-transcriptomic data associated with GSE274572 were reanalyzed for fibrous-cap VSMC states; no new participant count is inferred here." }, { "label": "VSMC-specific PCSK9 mouse model", "value": "8-week-old male Kif13b floxed and Tagln-Cre Kif13b VSMC-KO mice received AAV8-PCSK9-D377Y and Western diet for 20 weeks; primary pathology, lipid and cytokine comparisons n=8 per group; aortic-ring assays n=4 per group." }, { "label": "Mouse single-cell experiment", "value": "Ldlr-deficient versus Ldlr-deficient Kif13b-deficient mice; five mice were pooled into one aortic single-cell library per genotype. Figure 5/Results report 20-week Western diet, while downstream Figure 6/7 captions reference 12-week Western diet." }, { "label": "Primary HASMC perturbation", "value": "KIF13B knockdown and overexpression under oxLDL were assessed with Western blot/ELISA biological replicates generally n=3; collagen-gel contraction used n=5 for knockdown and n=6 for overexpression." }, { "label": "KLF4 and KCTD10 rescue", "value": "KLF4 dual-knockdown and KCTD10-overexpression biochemical and phenotypic rescue assays generally used n=3 independent biological replicates; selected immunofluorescence assays used n=10." }, { "label": "Kenpaullone intervention", "value": "HASMC experiments used 10 µM Kenpaullone. Male PCSK9 mice received 1 mg/kg/day orally during the final 12 weeks of a 20-week Western-diet protocol; n=6 per group." } ], "counting_note": "Human participants, paired plaque regions, public dataset samples, mice, pooled single-cell libraries and independent cell-culture replicates are different denominators and must not be summed. External human datasets provide cross-source corroboration, not prospective clinical validation. Five mice pooled into one library per genotype are not five independent single-cell libraries. Preserve the paper's figure-specific 20-week versus 12-week single-cell duration descriptions rather than harmonizing them." }, "study_profile_source": "data/deep_geo/doi-10-1172-jci194175.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1172-jci194175.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1172-jci194175.json", "gold_content_sha256": "f868f35e0e7671541627afee1e4d261c3b2f21c8c587424b6b4485264d1a4202", "provenance": { "doi": "10.1172/jci194175", "pmid": "41609725", "pmcid": "PMC12987658", "publisher": "The Journal of Clinical Investigation", "publisher_url": "https://www.jci.org/articles/view/194175", "version_of_record": "J Clin Invest. 2026;136(6):e194175; In-Press Preview published 29 January 2026 and electronic publication in Volume 136 Issue 6 on 16 March 2026.", "source_material": "JCI version of record, Supplemental Data, unedited blot/gel material, Supporting Data Values, GEO GSE314838, GEO GSE120521, ProteomeXchange PXD062283 and public human plaque omics resources used by the article.", "data_availability": "Study-generated single-cell RNA-seq data are deposited as GSE314838. Values for all data points are supplied in the Supporting Data Values file.", "counting_note": "Human participants, paired tissue regions, public dataset samples, mice, pooled single-cell libraries and cell-culture biological replicates are separate denominators; no overall total n is inferred.", "human_sampling_note": "The local six-patient CEA study used paired advanced/culprit and adjacent upstream regions from the same plaque and patient; the anatomical classification was based on location and macroscopic surgical appearance.", "proteomics_note": "PXD062283 contains 87 carotid plaques in the repository overall; the JCI Figure 1 comparison uses stable n=19 and unstable n=38.", "scrna_note": "Five mice were pooled into one single-cell library per genotype. Figure 5/Results report 20 weeks of Western diet, while Figure 6/7 captions reference 12 weeks; the discrepancy is not resolved here.", "figure5_note": "The Results attribute Ccl2/Il1b/Il6/Il18/Trap1 elevation to VSMC-Fib4, while the Figure 5K caption labels VSMC-Fib1; the evidence page does not over-resolve this inconsistency.", "kenpaullone_note": "The article's screening and reporter experiments show Kenpaullone lowering KLF4 promoter activity/expression and producing preclinical rescue. External authoritative pharmacology identifies Kenpaullone as an ATP-competitive CDK/GSK3β inhibitor, so KLF4 selectivity is not established.", "sex_note": "Only male mice were used; human clinical samples included both sexes, and sex was not analyzed as a biological variable." }, "scientific_role": "VSMC-specific KIF13B mechanism study linking inflammatory and matrix-associated states to KCTD10-dependent KLF4 turnover.", "evidence_position": "Associative human plaque observations plus causal mouse, cell and biochemical experiments; intervention evidence is preclinical, not proven human therapy.", "related_concepts": [ "Smooth muscle proteostasis", "Inflammatory versus matrix-associated VSMC states" ], "citation_contexts": [ "Background: cell-specific regulation of atherosclerotic plaque remodeling.", "Mechanistic evidence: experimental VSMC state regulation, distinct from macrophage KIF13B-mediated efferocytosis." ], "evidence_scope": { "supports": [ "Association between lower KIF13B and more advanced or unstable human atherosclerotic plaque features across local tissue and independent public datasets.", "A causal contribution of VSMC Kif13b loss to measured atherosclerotic plaque phenotypes in the tested male mouse models.", "Cell-autonomous effects of KIF13B gain and loss on matrix, inflammatory and contractile programs in primary HASMCs.", "Functional placement of KLF4 downstream of KIF13B in HASMC perturbation and rescue experiments.", "Evidence consistent with KCTD10-mediated KLF4 ubiquitination and proteasomal turnover downstream of KIF13B.", "Preclinical cellular and mouse rescue after Kenpaullone exposure under the tested conditions." ], "does_not_establish": [ "That low KIF13B expression or KIF13B methylation causes plaque instability in humans.", "That KIF13B, KCTD10, KLF4 or Kenpaullone has proven therapeutic efficacy or safety in patients with atherosclerosis.", "That Kenpaullone is selective for KLF4 or that all Kenpaullone effects in this study are mediated specifically through KLF4.", "A universal lipid-independent KIF13B mechanism in humans; the reported absence of TC/TG differences applies to the tested mouse comparison.", "Independent replication of the study-generated single-cell comparison, because five mice were pooled into one library per genotype.", "One definitive single-cell diet duration or one unambiguous cluster assignment for every Figure 5-7 subpanel where the article text and captions disagree.", "The molecular mechanism by which KIF13B regulates KCTD10 abundance.", "Generalization of the causal or pharmacologic mouse findings to females, because only male mice were used." ] }, "limitations": [ "The local human cohort contained six carotid endarterectomy patients with paired within-plaque regions; human observations are associative and small-sample.", "The local advanced-versus-adjacent classification was based on anatomical location and macroscopic surgical appearance rather than molecular or histopathological criteria.", "Stable/unstable public datasets and local advanced/adjacent paired regions use different plaque definitions and should not be treated as interchangeable cohorts.", "Human methylation observations are associative and do not establish that KIF13B hypermethylation causes KIF13B downregulation or plaque instability.", "The PXD062283 repository contains 87 plaques overall, whereas the JCI stable/unstable comparison uses a subset of 19 and 38; repository size and analytical subset must not be conflated.", "Five mice were pooled into one single-cell library per genotype, limiting independent biological replication at the single-cell library level.", "Figure 5/Results report a 20-week Western-diet single-cell experiment, whereas downstream Figure 6/7 captions reference 12 weeks; this discrepancy is unresolved.", "Results describe inflammatory genes in VSMC-Fib4 while the Figure 5K caption labels the panel VSMC-Fib1; the evidence page therefore avoids treating that subpanel label as unambiguous.", "Only male mice were used, and sex was not analyzed as a biological variable.", "Tagln-Cre targets smooth-muscle compartments beyond plaque VSMCs; reported intestine/bladder measurements do not establish general systemic safety of pathway targeting.", "The study establishes KCTD10-dependent KLF4 ubiquitination/rescue evidence but does not identify the mechanism by which KIF13B regulates KCTD10 abundance.", "Kenpaullone is pharmacologically nonselective; its rescue does not prove KLF4-selective target engagement or exclude contributions from other kinase targets.", "Kenpaullone was evaluated only in cells and mice. No human atherosclerosis efficacy, dosing, pharmacokinetic or safety trial was performed." ], "scope_source": "data/deep_geo/doi-10-1172-jci194175.json#/evidence_scope" }, { "id": "doi-10-1016-j-curpro-2025-100054", "title": "A Multimodal artificial intelligence framework for mechanistic discovery and digital twin construction in cardiovascular medicine", "doi": "10.1016/j.curpro.2025.100054", "year": 2025, "journal": "Current Proteomics", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.md", "paper_geo_status": "v2", "authors": [ "Ge Zhang", "Jiashen Xu", "Zenglei Zhang", "Chaoyang Yu", "Kaisaierjiang Kadier", "Di Lu", "Mingxuan Duan", "Ge Zhang" ], "doi_url": "https://doi.org/10.1016/j.curpro.2025.100054", "publisher_url": "https://linkinghub.elsevier.com/retrieve/pii/S1570164625000542", "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W7124225163", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1016-j-curpro-2025-100054.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1016-j-curpro-2025-100054.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1016-j-curpro-2025-100054.csl.json", "evidence_status": "reviewed_v2", "question_count": 4, "key_findings": [ { "id": "KF1", "claim": "Develop multimodal AI along two directions: mechanism-oriented research and individualized digital twins.", "context": "The authors propose complementary research directions rather than introduce a clinically validated digital twin product.", "evidence": [ { "label": "Argument topic", "value": "Research agenda" }, { "label": "Evidence basis", "value": "Narrative synthesis" } ], "source_locator": "Publisher correspondence: To the Editor; Sections 1–2", "source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html#kf1" }, { "id": "KF2", "claim": "Integrate imaging and molecular information to formulate network and disease-subtyping hypotheses.", "context": "Data integration and cited empirical examples are discussed as a basis for interpretation, not as new causal experiments in this Correspondence.", "evidence": [ { "label": "Argument topic", "value": "Cross-modal biological interpretation" }, { "label": "Evidence basis", "value": "Narrative synthesis" } ], "source_locator": "Publisher correspondence: Sections 1.1–1.2", "source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html#kf2" }, { "id": "KF3", "claim": "Explore updateable physiological models, image-to-mesh workflows and treatment-scenario simulation.", "context": "The simulation discussion concerns model design and possible scenarios, not observed human treatment effects.", "evidence": [ { "label": "Argument topic", "value": "Patient-specific simulation" }, { "label": "Evidence basis", "value": "Narrative synthesis" } ], "source_locator": "Publisher correspondence: Sections 2.1–2.2", "source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html#kf3" }, { "id": "KF4", "claim": "Address longitudinal data, computational resources, prospective evaluation, privacy and governance before clinical translation.", "context": "These are stated development and evaluation requirements, not completed prospective clinical validation.", "evidence": [ { "label": "Argument topic", "value": "Translation requirements" }, { "label": "Evidence basis", "value": "Narrative synthesis" } ], "source_locator": "Publisher correspondence: Sections 3.1–3.3; Section 4 Conclusion", "source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html#kf4" } ], "field_entry": [ "Artificial intelligence in cardiovascular medicine", "Patient-specific modeling research" ], "review_topics": [ "Multimodal AI for cardiovascular mechanism research", "Digital modeling and prospective evaluation requirements" ], "concepts": { "methods": [ "Cardiovascular mechanism research", "Cross-modal imaging and molecular interpretation", "Patient-specific physiological simulation", "Longitudinal evaluation and governance" ], "clinical_contexts": [ "Cardiovascular disease (discussion context)" ] }, "profile_type": "narrative_review", "study_profile": { "profile_type": "narrative_review", "narrative_genre": "correspondence", "study_design": "Correspondence providing a narrative discussion of research directions and translation requirements; not a report of a newly built and clinically validated digital twin system.", "evidence_type": "Methodological proposal and narrative synthesis; no new empirical evaluation reported in this article.", "evidence_domains": [ "Cardiovascular mechanism research", "Cross-modal imaging and molecular interpretation", "Patient-specific physiological simulation", "Longitudinal evaluation and governance" ], "diseases_covered": [ "Cardiovascular disease (discussion context)" ], "translation_scope": "A research agenda for multimodal interpretation and updateable patient-specific models; proposed simulations and future evaluations are distinct from demonstrated human treatment effects.", "scale_metrics": [ { "label": "Article format", "value": "Correspondence" }, { "label": "Evidence basis", "value": "Narrative argument and discussion of cited prior research" }, { "label": "Empirical evaluation reported in this article", "value": "No new empirical evaluation reported" } ], "counting_note": "No new empirical evaluation is reported in this article. Cited examples and their cohorts are not a new combined study population, and no synthetic sample total is assigned." }, "study_profile_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": "correspondence", "gold_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1016-j-curpro-2025-100054.json", "gold_content_sha256": "846bbcd3c3c61a96029b73266fdf9dc4d70cd9d32b8770ad588ba790401b1e57", "provenance": { "publisher_url": "https://www.sciencedirect.com/science/article/pii/S1570164625000542", "author_full_text_url": "https://www.researchgate.net/publication/400065376_A_Multimodal_artificial_intelligence_framework_for_mechanistic_discovery_and_digital_twin_construction_in_cardiovascular_medicine", "review_basis": "Publisher identity and article genre were checked separately. The narrative text was reviewed from the author-deposited full article; the cited empirical examples were not comprehensively revalidated.", "source_version": "Narrative locators refer to the author-deposited full article; no claim is made that every word was compared with the current ScienceDirect full text." }, "scientific_role": "Correspondence outlining a research agenda for cross-modal interpretation and updateable patient-specific physiological models.", "evidence_position": "Correspondence with narrative synthesis and no new empirical evaluation; not a built, clinically validated therapeutic digital twin or observed human treatment effect.", "related_concepts": [ "Mechanism-oriented cross-modal hypotheses", "Simulation-versus-observed-effect distinction" ], "citation_contexts": [ "Methods background: multimodal interpretation and patient-specific cardiovascular modeling.", "Research planning: prospective evaluation and governance of digital models, not product validation or treatment efficacy." ], "evidence_scope": { "supports": [ "Cite for framing a cardiovascular AI research agenda around mechanistic questions and individualized digital modeling, not for product validation.", "Cite for the methodological rationale of cross-modal hypothesis generation; causal claims require suitable primary experimental evidence.", "Cite as design background for physiological modeling and scenario simulation, not as evidence that a drug, surgery or commercial digital twin improves outcomes.", "Cite when discussing evaluation, data stewardship and implementation requirements; prospective benefit remains a question for future empirical assessment." ], "does_not_establish": [ "A newly developed, validated therapeutic digital twin or completed prospective clinical validation in this Correspondence.", "Causation established by combining imaging and molecular data alone.", "Observed human treatment effects or randomized clinical-trial evidence inferred from simulation.", "Proven efficacy of a drug, surgery or commercial digital twin product, patient-outcome improvement, guideline status or regulatory approval." ] }, "limitations": [ "This Correspondence is a narrative discussion, not a systematic review or meta-analysis with a reported systematic search protocol.", "The cited empirical examples were not comprehensively revalidated for this page and should be checked in their primary sources.", "The author-deposited full article supports narrative locators; every word was not compared with the current ScienceDirect full text.", "Proposed mechanistic hypotheses and simulation strategies require appropriate empirical and prospective evaluation before clinical benefit can be claimed." ], "scope_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/evidence_scope" }, { "id": "doi-10-1111-jcmm-70475", "title": "A Novel Disulfidptosis-Related Diagnostic Gene Signature and Differential Expression Validation in Ischaemic Cardiomyopathy", "doi": "10.1111/jcmm.70475", "year": 2025, "journal": "Journal of Cellular and Molecular Medicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70475.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70475.md", "paper_geo_status": "none", "authors": [ "Xin Tan", "Shuai Xu", "Yiyao Zeng", "Fengyi Yu", "Zhen Qin", "Ge Zhang", "Jili Fan", "Xiaohong Bo", "Junnan Tang", "Huimin Fan", "Yafeng Zhou" ], "doi_url": "https://doi.org/10.1111/jcmm.70475", "publisher_url": null, "pmid": "40070032", "pmcid": "PMC11897062", "openalex_id": "https://openalex.org/W4408377359", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-70475.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-70475.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-70475.csl.json", "evidence_status": "limited", "question_count": 0, "key_findings": [], "field_entry": [], "review_topics": [], "concepts": {}, "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70475.html#limited-evidence", "source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/limited_evidence.json", "provenance": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11897062/", "label": "Article source", "format": "Official publisher or PMC full text reviewed locally", "locator": "Methods 2.1 Data Source (jcmm70475-sec-0003); 2.9 Animal (jcmm70475-sec-0011)" }, { "url": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE57338", "label": "Official dataset record", "format": "GEO Series metadata", "locator": "Series relation: SubSeries of GSE57345, official GEO record" } ], "scope": "Discovery design and reported animal expression observations; independent human validation remains unresolved.", "evidence_notice": "Discovery design and reported animal expression observations; independent human validation remains unresolved.", "evidence_scope": null, "limitations": [ "Nonoverlapping validation samples and a frozen model evaluation are not demonstrated.", "MYH10 sex-specific direction remains inconsistent.", "Animal expression observations are not human diagnostic or causal validation." ], "scope_source": "data/limited_evidence.json#/papers/10.1111~1jcmm.70475/scope" }, { "id": "doi-10-1016-j-isci-2025-114320", "title": "ABCA1 acts as a protective modulator in amyotrophic lateral sclerosis", "doi": "10.1016/j.isci.2025.114320", "year": 2025, "journal": "iScience", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.md", "paper_geo_status": "v2", "authors": [ "Qiang Li", "Ge Zhang", "Honglin Zheng", "Taiqi Zhao", "Hang Zhang", "Yaochong Zhang", "Haiyang Luo", "Yuming Xu" ], "doi_url": "https://doi.org/10.1016/j.isci.2025.114320", "publisher_url": null, "pmid": "41602910", "pmcid": "PMC12834111", "openalex_id": "https://openalex.org/W4416971849", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1016-j-isci-2025-114320.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1016-j-isci-2025-114320.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1016-j-isci-2025-114320.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "A nine-gene ALS classifier showed reduced discrimination when applied to an independent expression cohort.", "context": "The RF model was developed and internally tested in GSE112676 and externally evaluated in GSE112680; feature selection and batch heterogeneity constrain generalization.", "evidence": [ { "label": "Gene signature", "value": "9 genes including ABCA1" }, { "label": "Random forest AUC", "value": "Training 1.00; internal test 0.91; independent external dataset 0.75" }, { "label": "Comparator LASSO AUC", "value": "Training 0.86; internal test 0.89; external 0.72" } ], "source_locator": "PMC12834111: Results Machine learning defines a cross-validated nine-gene signature (sec2.5, paragraphs p0125, p0130); Figure 5H–L; Methods Machine learning for feature selection and diagnostic models (sec8.3.7).", "source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#kf1" }, { "id": "KF2", "claim": "Higher genetically predicted ABCA1 expression was inversely associated with ALS risk in the primary MR estimate.", "context": "This is an IVW Mendelian-randomization estimate conditional on cis-eQTL instrument and pleiotropy assumptions, not a demonstrated effect of protein augmentation in patients.", "evidence": [ { "label": "Instrument count", "value": "11 SNPs; reported mean F=71.7" }, { "label": "IVW estimate", "value": "OR 0.93, 95% CI 0.87–0.99, P=0.02" }, { "label": "Estimator concordance", "value": "MR-Egger and weighted median were directionally similar but not statistically significant" }, { "label": "Additional cohorts", "value": "European replication OR 0.96, P=0.04; mixed/East Asian estimates not significant" } ], "source_locator": "PMC12834111: Results ABCA1 expression is associated with reduced ALS risk by MR (sec2.6, p0155–p0175); Figure 6B–G; Methods Mendelian randomization (sec8.3.9).", "source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#kf2" }, { "id": "KF3", "claim": "An independent small serum series showed higher ABCA1 concentrations in ALS versus controls.", "context": "Cross-sectional serum difference in a 30-person convenience sample is neither a validated diagnostic test nor intervention evidence.", "evidence": [ { "label": "Clinical participants", "value": "15 ALS and 15 age/sex-matched controls" }, { "label": "Group comparison", "value": "Reported ELISA P=0.006" }, { "label": "Functional outcome", "value": "ALSFRS-R total correlation r=-0.190, P=0.497 (not significant)" } ], "source_locator": "PMC12834111: Results Serum ABCA1 protein quantification and clinical correlation (sec2.7, p0180–p0195); Figure 7A–I; Methods Serum ABCA1 quantification (sec8.3.10); Supplementary Tables S9, S10, S13.", "source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#kf3" }, { "id": "KF4", "claim": "ABCA1 expression associations differed across tissues and public SOD1-G93A timepoints.", "context": "Human compartments, mouse time series and blood assays cannot be treated as the same biological readout.", "evidence": [ { "label": "Human blood dataset", "value": "GSE234297 log2FC 0.50, P=0.0068" }, { "label": "Mouse spinal cord day 70", "value": "GSE120374 log2FC 0.24; unadjusted P=0.414 and adjusted P approximately 1.00: not significant" }, { "label": "Mouse spinal cord day 100", "value": "Reported P=1.7×10^-6" }, { "label": "Mouse spinal cord day 120", "value": "Reported P=7.5×10^-14" } ], "source_locator": "PMC12834111: Results Spatial and temporal heterogeneity (sec2.8, p0210–p0240); Figure 8A–G; supplied official Data S1, mmc2.zip/Supplementary Table 14.xlsx, GSE120374_DESeq2_Abca1 worksheet A3/D3/G3/H3, G4/H4, G5/H5.", "source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#kf4" }, { "id": "KF5", "claim": "ABCA1 related to transcriptomic immune-cell signature scores, not directly measured cell counts.", "context": "ssGSEA scores are indirect proxies and cannot establish a cell-specific mechanism or tissue-level abundance.", "evidence": [ { "label": "Neutrophil ssGSEA association", "value": "Reported Spearman r=0.51, P<0.001" }, { "label": "CD56-bright NK ssGSEA association", "value": "Reported Spearman r=-0.42, P<0.001" }, { "label": "Biological level", "value": "Blood transcriptome immune signature inference" } ], "source_locator": "PMC12834111: Results Differentially expressed genes and their overlap with ALS modules (sec2.4); Serum ABCA1 clinical interpretation (sec2.7, p0200); Figure 4C–F.", "source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#kf5" } ], "field_entry": [ "Neurodegenerative disease genomics", "Molecular biomarker research" ], "review_topics": [ "ABCA1 and ALS susceptibility", "Blood expression and serum biomarker translation" ], "concepts": { "disease_and_biomarkers": [ "Amyotrophic lateral sclerosis", "ABCA1", "Serum biomarker associations" ], "methods_and_models": [ "Nine-gene random forest", "cis-eQTL Mendelian randomization", "ELISA" ], "evidence_boundaries": [ "External AUC 0.75", "ALSFRS-R nonsignificant association", "Mouse day-70 P-value discrepancy" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Multi-dataset retrospective transcriptomic discovery/validation with gene-expression classifier development, cis-eQTL Mendelian randomization and a small in-house cross-sectional serum cohort.", "evidence_type": "Blood/tissue expression associations, retrospective classification performance, genetically instrumented association and laboratory serum comparison.", "population": "Patients with ALS and controls from public blood expression series; an independently sampled 15 ALS/15 control serum group; human postmortem tissues and a public SOD1-G93A mouse tissue series.", "primary_endpoint": "Retrospective ALS-versus-control blood expression classification and ABCA1 association with genetically instrumented ALS susceptibility.", "secondary_endpoint": "Serum ABCA1 difference, metabolic/functional correlations and tissue- or time-dependent expression differences.", "data_modalities": [ "Whole-blood microarray/transcriptomic datasets", "Random forest and LASSO classifier discrimination", "cis-eQTL and ALS GWAS summary statistics", "Serum ELISA with clinical covariates", "Human postmortem and publicly available SOD1-G93A tissue expression" ], "external_validation": true, "scale_metrics": [ { "label": "Signature", "value": "9 genes selected by intersection of three feature-selection algorithms" }, { "label": "External classifier dataset", "value": "GSE112680 independent external expression dataset" }, { "label": "Serum clinical sample", "value": "15 ALS cases and 15 controls, measured using ELISA" }, { "label": "MR genetic instruments", "value": "11 independent ABCA1-associated cis-eQTL SNPs in primary analysis" }, { "label": "Mouse expression timepoints", "value": "Postnatal days 30, 70, 100 and 120 (public data; not a new mouse intervention)" } ], "counting_note": "Transcriptomic cohort sizes, GWAS case-control summaries, public tissue/mouse series and 30 serum participants refer to different data resources. No synthetic total n or intervention trial is claimed." }, "study_profile_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/study_profile", "model_profile": { "model_name": "Nine-gene ALS blood expression classifier", "model_family": "Random forest; LASSO comparator", "evaluation": "GSE112676 training/internal testing and independent GSE112680 external expression cohort", "performance_scope": "RF AUC 1.00/0.91/0.75 (train/internal/external), not a clinical diagnostic utility trial", "clinical_boundary": "Not an established ALS diagnostic assay or an ABCA1-targeted therapy." }, "model_profile_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/model_profile", "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1016-j-isci-2025-114320.json", "gold_content_sha256": "7ca21df23daea83e3e9d5bf60034926680f3bd57f456209fe66f4307111fa26c", "provenance": { "doi_url": "https://doi.org/10.1016/j.isci.2025.114320", "publisher_url": "https://www.sciencedirect.com/science/article/pii/S2589004225025817", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12834111/", "pmcid": "PMC12834111", "license": "Article-level CC BY 4.0 in official JATS. This page provides original analysis without full-text or figure republication.", "license_url": "https://creativecommons.org/licenses/by/4.0/", "version_of_record": "iScience, electronically published 3 December 2025; collection date 16 January 2026. Preserve the existing site bibliographic year/identity.", "source_artifacts": "Official JATS/PDF, Document S1 Figures S1–S8, Data S1 Tables S1–S14; day-70 P values independently read from the original supplied XLSX internal worksheet.", "scientific_discrepancy": "The Results prose calls day-70 Abca1 significantly increased, but GSE120374 Table S14 reports unadjusted P=0.414354 and adjusted P=0.999979.", "identity_note": "No inference is made that similarly titled preprint and VOR are identical without official version linking." }, "scientific_role": "Integrates blood-expression classification, genetic instrumental-variable association and limited serum measurements in ALS.", "evidence_position": "Retrospective model evaluation and conditional MR evidence with small observational serum cohort; no ABCA1-directed intervention.", "related_concepts": [ "External validation AUC", "ABCA1 cis-eQTL", "Day-70 source inconsistency" ], "citation_contexts": [ "Reviews separating genetic-instrument and observed serum associations in ALS biomarker research.", "Methodological examples of external classifier performance drop and primary-supplement significance verification." ], "evidence_scope": { "supports": [ "A reproducible blood expression-model signal with an external dataset AUC of 0.75 for the reported model.", "An instrument-based inverse ABCA1-expression/ALS-risk association under MR assumptions.", "An ALS-versus-control serum ABCA1 difference in the reported small cohort.", "Cross-compartment variation in human and public mouse expression resources." ], "does_not_establish": [ "That increasing ABCA1 expression or administering an ABCA1-targeted treatment prevents ALS.", "A fully validated clinical ALS diagnostic test, cut-off or demonstrated impact on patient outcomes.", "A statistically significant day-70 mouse spinal-cord increase, given source P=0.414.", "That ssGSEA score associations represent directly enumerated neutrophils or NK cells.", "A significant relationship between serum ABCA1 and ALSFRS-R functional score based on the published nonsignificant result." ] }, "limitations": [ "The external AUC is lower than the training/internal AUC, and cohort platform differences constrain diagnostic transportability.", "MR inferences rely on genetic instruments and cannot replace direct target perturbation and clinical outcome trials.", "The serum series contains only 15 patients and 15 controls, and multiple exploratory correlates require caution.", "The published mouse day-70 phrase disagrees with raw/adjusted statistics in Supplementary Table 14; 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No original statistical reanalysis and no source figures reproduced.", "license": "CC BY 4.0, as stated in article-level permissions.", "source_sha256": "42d4736dac32237e52512f05e654c5d4c78deff3c9c327db465b9212c2d24ca2" }, "scientific_role": "Observational analysis of eGDR and two prevalent outcomes in one NHANES adult sample.", "evidence_position": "Adjusted association, not prospective prediction, disease prevention or treatment efficacy.", "related_concepts": [ "Estimated glucose disposal rate", "Hyperuricemia", "Gout" ], "citation_contexts": [ "Population evidence relating an insulin-resistance proxy to prevalent hyperuricemia and gout.", "Evidence review distinguishing continuous associations from nonsignificant category-specific gout estimates." ], "evidence_scope": { "supports": [ "Adjusted prevalence-odds associations in the selected NHANES 2007–2018 adult sample.", "The explicit nonsignificant fully adjusted 4–6 mg/kg/min gout contrast." ], "does_not_establish": [ "That increasing eGDR prevents hyperuricemia or gout, or reduces future disease incidence.", "Causal mediation by insulin resistance or benefit from an eGDR-targeted intervention.", "A statistically significant adjusted gout association for every eGDR category.", "Prospective prediction accuracy or a clinical treatment threshold." ] }, "limitations": [ "Known source discrepancy: Abstract Results implies all higher eGDR categories significantly reduce both outcomes. Table 3 and Results §3.3 instead identify the fully adjusted gout 4–6 contrast as nonsignificant (OR 0.81, 95% CI 0.63–1.04, P=0.093). This page follows the mutually consistent body/table contrast and does not claim the abstract has been formally corrected.", "Cross-sectional associations cannot establish causality, incident risk reduction or prevention; odds ratios are not prevalence ratios.", "Gout ascertainment is self-reported; eGDR estimates insulin resistance rather than directly measuring clamp-derived glucose disposal.", "Covariate adjustment and imputation do not exclude residual confounding or selection bias.", "Supplementary subgroup, interaction and sensitivity estimates are not used as independently verified key findings in this bounded evidence page." ], "scope_source": "data/deep_geo/doi-10-3389-fnut-2025-1658286.json#/evidence_scope" }, { "id": "doi-10-3389-fpubh-2025-1521372", "title": "Association between sleep duration, sleep trouble and all-cause mortality in individuals with hyperuricemia in the United States", "doi": "10.3389/fpubh.2025.1521372", "year": 2025, "journal": "Frontiers in Public Health", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-3389-fpubh-2025-1521372.html", "markdown_url": "https://drgezhang.com/papers/doi-10-3389-fpubh-2025-1521372.md", "paper_geo_status": "v2", "authors": [ "Yuanhui Dai", "Xiangyu Sun", "Ge Zhang", "Chunying Cui", "Xiaoli Wu", "Yierzhati Aizezi", "Kaisaierjiang Kadier" ], "doi_url": "https://doi.org/10.3389/fpubh.2025.1521372", "publisher_url": "https://www.frontiersin.org/articles/10.3389/fpubh.2025.1521372/full", "pmid": "40206179", "pmcid": "PMC11979105", "openalex_id": "https://openalex.org/W4408873216", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-3389-fpubh-2025-1521372.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-3389-fpubh-2025-1521372.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-3389-fpubh-2025-1521372.csl.json", "evidence_status": "reviewed_v2", "question_count": 5, "key_findings": [ { "claim": "The NHANES 2007–2018 analytic sample included 5,837 participants and 906 deaths, with a mean follow-up of 6.5 years and survey-weighted Cox analysis.", "context": "Raw participant counts and survey-weighted percentages are different quantities and must not be directly substituted for one another.", "evidence": [ { "label": "NHANES cycles", "value": "2007–2018" }, { "label": "analytic participants", "value": "5,837" }, { "label": "deaths", "value": "906" }, { "label": "mean follow up", "value": "6.5 years" }, { "label": "analysis", "value": "Survey-weighted Cox" } ], "source_locator": "Methods 2.1 and 2.6; 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published corpus counts are reported without independently rerunning the subscription database query.", "evidence": [ { "label": "documents after deduplication", "value": "17,293" }, { "label": "eligible publication interval", "value": "1 March 2014 to 1 March 2024" }, { "label": "reported database access date", "value": "25 December 2024" } ], "source_locator": "Materials and Methods: Data sources (s2_1), Inclusion criteria for literature (s2_2), Exclusion criteria for literature (s2_3), Statistical methods (s2_4); Figure 1 caption", "source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-32604-or-2025-059290.html#kf1" }, { "id": "KF2", "claim": "Treatment accounted for the largest of the five reported topic groups in this retrieved corpus.", "context": "Document-topic allocation, not patient incidence, disease burden, resource need or comparative clinical effectiveness.", "evidence": [ { "label": "prevention documents", "value": "1,655" }, { "label": "screening documents", "value": "2,300" }, { "label": "diagnosis documents", "value": "2,874" }, { "label": "treatment documents", "value": "10,298" }, { "label": "rehabilitation documents", "value": "166" } ], "source_locator": "Results: National annual publication trends (s3_1), first paragraph", "source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-32604-or-2025-059290.html#kf2" }, { "id": "KF3", "claim": "The keyword analysis records attention to treatment and emerging research topics within the selected literature.", "context": "Table 9 frequencies describe terms in the analyzed corpus; 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The publication eligibility cutoff and database access date are different dates. The five reported topic counts sum to 17,293; no independent reconstruction of the corpus or its allocation was performed." }, "study_profile_source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-32604-or-2025-059290.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-32604-or-2025-059290.json", "gold_content_sha256": "ccffb06872476dac4b354f44731a1e7b9a33dfe0a1405aef7055218d484cd082", "provenance": { "publisher_url": "https://doi.org/10.32604/or.2025.059290", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12144630/", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/40486880/", "pmcid": "PMC12144630", "pmid": "40486880", "version": "Published journal article, Oncology Research 33(6), 1437-1458 (2025); formal full-text XML archived from Europe PMC.", "evidence_basis": "Formal article Methods and Results, including text-encoded Tables 2 and 9. Publication identity and nine-author order match the existing record. No source figure is reproduced.", "source_verification_scope": "Selected corpus and frequency findings are supported by body text and text-encoded tables. Network geometry is not interpreted; inconsistent collaboration ranking is excluded and disclosed. No claim of independent database reanalysis.", "license": "CC BY 4.0; article-level license in the formal full-text permissions statement.", "source_sha256": "0597c4626ed61179448485de79794b98d7df8df7b11f0b39c37fd25259c1fde1" }, "scientific_role": "Original descriptive analysis of a defined bibliographic corpus and its publication and keyword patterns.", "evidence_position": "Document-level evidence; neither a clinical cohort nor a pooled analysis of treatment effects.", "related_concepts": [ "Database coverage", "Co-citation networks", "Research attention" ], "citation_contexts": [ "Background: corpus-specific publication patterns across prevention, screening, diagnosis, treatment and rehabilitation.", "Methods or research mapping: title-search eligibility and descriptive bibliometric frequencies, with database and language limits." ], "evidence_scope": { "supports": [ "Description of the defined title-search corpus and its reported document counts.", "Attribution of topic allocation and selected keyword frequencies to this bibliometric study.", "Discussion of research attention within the specified database, language and date restrictions." ], "does_not_establish": [ "Clinical effectiveness, comparative treatment benefit or patient safety.", "Causal mechanisms, incidence or disease burden from publication frequencies.", "An exhaustive global oncology evidence inventory or a quality ranking of therapies, institutions or researchers.", "Independent validation of clinical results summarized from the article's cited literature." ] }, "limitations": [ "The corpus is restricted to English-language records in Web of Science Core Collection and a title-based query; it is not an exhaustive inventory of oncology research.", "Publication eligibility ends on 1 March 2024, while the Methods give 25 December 2024 as the database access date. The partial 2024 interval cannot be compared with complete years as an annual trend.", "The article states that records were deduplicated but does not provide a complete reproducible deduplication rule or a deposited corpus in its Availability of Data and Materials statement; this page does not independently regenerate the search.", "Bibliometric frequency, co-occurrence and co-citation are descriptive signals of the retrieved literature, not measures of therapeutic efficacy, causal mechanism or evidence quality.", "The Results description of the strongest country collaboration differs from the ranking implied by Table 2 frequencies. This page excludes that ranking rather than choosing a preferred account.", "Selected findings rely on formal body text and text-encoded tables. Network-map geometry and figure-derived effect estimates are not independently reinterpreted here." ], "scope_source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/evidence_scope" }, { "id": "doi-10-1111-jcmm-70725", "title": "Deciphering the Proteomic Landscape of Circulating Extracellular Vesicles in Human Abdominal Aortic Aneurysm", "doi": "10.1111/jcmm.70725", "year": 2025, "journal": "Journal of Cellular and Molecular Medicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.md", "paper_geo_status": "v2", "authors": [ "Chaoyang Yu", "Ge Zhang", "Shaotong Pei", "Yifei Zhang", "Peiyu Yuan", "Renying Miao", "Kaisaierjiang Kadier", "Pengpeng Zhang", "Tianshu Gu", "Ruhao Wu", "Haonan Zhang", "Shiqian Zhang", "Bo Yang", "Han Wu", "Yudi Xu", "Ke Hu", "Qingfei Xu", "Yaxin Chen", "Jinliang Wang", "Zongao Cai", "Junnan Tang", "Teng Li", "Yan Song" ], "doi_url": "https://doi.org/10.1111/jcmm.70725", "publisher_url": "https://onlinelibrary.wiley.com/doi/10.1111/jcmm.70725", "pmid": "40770945", "pmcid": "PMC12328994", "openalex_id": "https://openalex.org/W4413035878", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-70725.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-70725.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-70725.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "The study combined a 15-person in-house comparison with a 12-person external comparison.", "context": "Two-center human case-control evidence; no longitudinal prediction of incident AAA or rupture.", "source_locator": "Abstract; Methods 2.1; Results 3.4; Fig. 6", "evidence": [ { "label": "In-house AAA / controls", "value": "10 / 5" }, { "label": "External AAA / controls", "value": "8 / 4" }, { "label": "Article-reported total AAA / controls", "value": "18 / 9" } ], "source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#kf1" }, { "id": "KF2", "claim": "Circulating vesicle preparations were characterized by particle morphology, size and protein markers.", "context": "The source describes venous plasma, serum EVs and intraoperative aortic blood in different sections; a single standardized peripheral-blood screening workflow is not assumed.", "source_locator": "Methods 2.2-2.7 and 2.9; Results 3.1; Figs. 1-2", "evidence": [ { "label": "AAA vesicle median diameter", "value": "85.18 nm" }, { "label": "Marker findings", "value": "TSG101, ALIX and CD9 detected; Calnexin not detected" }, { "label": "Isolation reporting", "value": "ExoQuick in Methods 2.3; ultracentrifugation in the external-validation Methods 2.9" } ], "source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#kf2" }, { "id": "KF3", "claim": "A targeted 92-protein profiling workflow prioritized five differentially expressed candidate proteins.", "context": "Olink targeted-panel measurements are not an unbiased whole proteome or direct evidence of a causal protein pathway.", "source_locator": "Methods 2.7-2.8; Results 3.2-3.4; Figs. 3-4", "evidence": [ { "label": "Analyzed protein panel", "value": "92 proteins" }, { "label": "Reported differential set", "value": "5 proteins: 3 upregulated and 2 downregulated" }, { "label": "Candidate names", "value": "IL-4, IL-6, MCP-1, Neurturin and Oncostatin-M" } ], "source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#kf3" }, { "id": "KF4", "claim": "External Western blot and ELISA findings were assay-dependent rather than uniformly concordant for all five candidates.", "context": "The evidence is reported without inventing a reconciled expression direction or a technical explanation for the discrepancy. The ELISA prose uses the term tumour suppressor-M; Oncostatin-M naming here follows the five-analyte list and Fig. 6 labels, not an additional measured protein.", "source_locator": "Results 3.4; Fig. 6A-C; Discussion", "evidence": [ { "label": "External sample", "value": "8 AAA patients; 4 healthy controls" }, { "label": "Western blot", "value": "IL-4, IL-6, MCP-1 and Oncostatin-M higher; Neurturin not statistically significant" }, { "label": "ELISA", "value": "IL-4, IL-6 and Oncostatin-M higher; MCP-1 and Neurturin lower" } ], "source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#kf4" }, { "id": "KF5", "claim": "The article reports single-protein ROC discrimination in the small external comparison.", "context": "AUCs are mapped in the explicit candidate order in the Abstract/Results; they are not a five-protein combined model or prospective diagnostic performance.", "source_locator": "Abstract; Results 3.4; Fig. 6D", "evidence": [ { "label": "IL-4 AUC", "value": "0.760" }, { "label": "IL-6 AUC", "value": "0.840" }, { "label": "MCP-1 AUC", "value": "0.800" }, { "label": "Neurturin AUC", "value": "0.840" }, { "label": "Oncostatin-M AUC", "value": "0.900" }, { "label": "Precision qualification", "value": "Wide confidence intervals; the reported interval for AUC 0.760 is 0.486-1.000" } ], "source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#kf5" }, { "id": "KF6", "claim": "Enrichment and network analyses associated the protein candidates with inflammatory and signaling contexts.", "context": "These associations annotate the observed protein set and do not demonstrate experimentally manipulated pathways.", "source_locator": "Methods 2.8; Results 3.3; Fig. 5", "evidence": [ { "label": "Reported contexts", "value": "Cellular response to cytokines, inflammatory response, chemokine signaling, AP-1 and glucocorticoid-receptor pathways" } ], "source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#kf6" } ], "field_entry": [ "Vascular biomarker research", "Extracellular-vesicle protein research" ], "review_topics": [ "Blood-based biomarker candidates in abdominal aortic aneurysm", "Targeted circulating EV proteomics" ], "concepts": { "disease": [ "abdominal aortic aneurysm" ], "specimen": [ "circulating extracellular vesicles", "EV-associated proteins" ], "methods": [ "Olink proximity extension assay", "Western blot", "ELISA", "ROC analysis" ], "entities": [ "IL-4", "IL-6", "MCP-1 / CCL2", "Neurturin / NRTN", "Oncostatin-M / OSM" ], "evidence": [ "case-control biomarker discovery", "external assay evaluation", "assay-dependent replication" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Two-center human AAA case-control targeted EV protein profiling with external Western blot and ELISA evaluation", "evidence_type": "Exploratory human protein association and small external assay/ROC evaluation", "population": "AAA patients and healthy controls in an in-house cohort and an external hospital cohort", "primary_endpoint": "AAA-associated differences in targeted circulating EV protein measurements", "secondary_endpoint": "Cross-assay candidate evaluation, single-marker ROC discrimination and computational pathway/network interpretation", "counting_note": "The reported enrollment is consistent with (10+8) AAA patients and (5+4) controls. 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No public dataset accession or code repository is inferred." }, "scientific_role": "Two-center targeted circulating EV protein profiling in human AAA with small external cross-assay evaluation.", "evidence_position": "Exploratory human case-control evidence with assay discordance and ROC uncertainty; not whole-proteome discovery, a combined validated diagnostic model or prospective rupture prediction.", "related_concepts": [ "Vesicle-associated protein candidates", "Cross-assay concordance assessment" ], "citation_contexts": [ "Background: circulating extracellular vesicles in aortic aneurysm biomarker research.", "Evidence synthesis: targeted EV protein candidates in human AAA, retaining small-sample uncertainty and distinguishing external assay results." ], "evidence_scope": { "supports": [ "AAA-associated targeted EV protein differences in the studied human samples.", "Two-center enrollment and small external assay assessment.", "Article-reported single-marker ROC discrimination with uncertainty.", "Computational inflammatory/pathway interpretation of the candidate set." ], "does_not_establish": [ "A whole-proteome survey or equivalence to unfractionated plasma protein profiling.", "Concordant directional validation of every candidate across Western blot and ELISA.", "A validated five-protein combined diagnostic model.", "Prospective incident-AAA, rupture or mortality prediction.", "An established routine peripheral-venous blood screening protocol across all source descriptions.", "Causal pathway regulation or a therapeutically validated protein target." ] }, "limitations": [ "The external cohort contains 8 cases and 4 controls; ROC confidence intervals are wide, including 0.486-1.000 for the reported AUC of 0.760.", "MCP-1 and Neurturin do not have uniformly concordant Western blot and ELISA results. 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Results Patient Characteristics; Table 1" }, { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12673264/#t0003", "label": "Article source", "format": "Official publisher or PMC full text reviewed locally", "locator": "Table 3 multivariable rows; Variable Analysis and Selection (s0003-s2002)" }, { "url": "https://www.dovepress.com/article/supplementary_file/493841/493841%20Revised%20Supplementary%20Table%201.docx", "label": "Official supplementary material", "format": "Publisher-hosted supplementary document", "locator": "Supplementary Table 1, survival/Cox analysis script" } ], "scope": "Published exploratory Cox estimates with an unspecified analytical denominator; prediction performance remains unverified.", "evidence_notice": "Published exploratory Cox estimates with an unspecified analytical denominator; prediction performance remains unverified.", "evidence_scope": null, "limitations": [ "The Table 3 Cox analytic denominator is not specified.", "AUC and validation mortality percentage conflicts remain open.", "Reported associations do not demonstrate causality or clinical utility." ], "scope_source": "data/limited_evidence.json#/papers/10.2147~1cia.s493841/scope" }, { "id": "doi-10-1038-s41598-025-98859-3", "title": "Endoscopic versus laparoscopic resection of gastrointestinal stromal tumors at the esophagogastric junction using propensity score matching analysis", "doi": "10.1038/s41598-025-98859-3", "year": 2025, "journal": "Scientific Reports", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1038-s41598-025-98859-3.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1038-s41598-025-98859-3.md", "paper_geo_status": "none", "authors": [ "Shanshan Zhu", "Zhen Liu", "Jingwen Zhang", "Nan Dai", "Saif Ullah", "Ge Zhang", "Shengang Zhang", "Ping Liu", "Yang Fu", "Shimeng Zheng", "Zhaokai Zhou", "Yudi Xu", "Le Chang", "Changqing Guo", "Xinguang Cao" ], "doi_url": "https://doi.org/10.1038/s41598-025-98859-3", "publisher_url": null, "pmid": "40335605", "pmcid": "PMC12059082", "openalex_id": "https://openalex.org/W4410166236", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1038-s41598-025-98859-3.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1038-s41598-025-98859-3.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1038-s41598-025-98859-3.csl.json", "evidence_status": "limited", "question_count": 0, "key_findings": [], "field_entry": [], "review_topics": [], "concepts": {}, "evidence_url": "https://drgezhang.com/papers/doi-10-1038-s41598-025-98859-3.html#limited-evidence", "source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/limited_evidence.json", "provenance": [ { "url": "https://www.nature.com/articles/s41598-025-98859-3", "label": "Article source", "format": "Official publisher or PMC full text reviewed locally", "locator": "Methods: Study design and patients; Figure 1" } ], "scope": "Study design and unresolved matching integrity; treatment comparisons are not verified.", "evidence_notice": "Study design and unresolved matching integrity; treatment comparisons are not verified.", "evidence_scope": null, "limitations": [ "Reported methods are summarized without adopting disputed participant allocations.", "A corrected allocation and matching table are required before a complete V2 comparison." ], "scope_source": "data/limited_evidence.json#/papers/10.1038~1s41598-025-98859-3/scope" }, { "id": "doi-10-2147-jir-s495784", "title": "Identification of Cardiometabolic Protein Biomarkers for Acute Myocardial Infarction Using Olink Proteomics", "doi": "10.2147/jir.s495784", "year": 2025, "journal": "Journal of Inflammation Research", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-2147-jir-s495784.html", "markdown_url": "https://drgezhang.com/papers/doi-10-2147-jir-s495784.md", "paper_geo_status": "none", "authors": [ "Xin Tan", "Xiangyu Wang", "Shuai Xu", "Yiyao Zeng", "Ge Zhang", "Anchen Xu", "Yufeng Jiang", "Hezi Jiang", "Yahui Song", "Jili Fan", "Yangjun Fu", "Xiaohong Bo", "Huimin Fan", "Yafeng Zhou" ], "doi_url": "https://doi.org/10.2147/jir.s495784", "publisher_url": null, "pmid": "40013238", "pmcid": "PMC11863793", "openalex_id": "https://openalex.org/W4407810609", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-2147-jir-s495784.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-2147-jir-s495784.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-2147-jir-s495784.csl.json", "evidence_status": "limited", "question_count": 0, "key_findings": [], "field_entry": [], "review_topics": [], "concepts": {}, "evidence_url": "https://drgezhang.com/papers/doi-10-2147-jir-s495784.html#limited-evidence", "source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/limited_evidence.json", "provenance": [ { "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11863793/", "label": "Article source", "format": "Official publisher or PMC full text reviewed locally", "locator": "Methods: General Information and biomarker screening; Results: Identification of Cardiometabolic-Related Biomarkers and ELISA Validation" }, { "url": "https://www.dovepress.com/article/supplementary_file/495784/495784.docx", "label": "Official supplementary material", "format": "Publisher-hosted supplementary document", "locator": "Table S2, FCN2 and DEFA1 IVW, MR-Egger and weighted-median rows" } ], "scope": "Protein-discovery design and supplementary sensitivity checks; diagnostic and causal claims remain unverified.", "evidence_notice": "Protein-discovery design and supplementary sensitivity checks; diagnostic and causal claims remain unverified.", "evidence_scope": null, "limitations": [ "ELISA cohort size and GEO accession/result mapping are unresolved.", "Nominal IVW associations are not robustly replicated across the named sensitivity methods.", "Multiplicity, exposure units and instrument mapping are insufficient for a causal claim." ], "scope_source": "data/limited_evidence.json#/papers/10.2147~1jir.s495784/scope" }, { "id": "doi-10-1016-j-joim-2025-06-003", "title": "Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm", "doi": "10.1016/j.joim.2025.06.003", "year": 2025, "journal": "Journal of Integrative Medicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.md", "paper_geo_status": "v2", "authors": [ "Xiao-jie Li", "Le Chang", "Yang Mi", "Ge Zhang", "Shan-shan Zhu", "Yue-xiao Zhang", "Hao-yu Wang", "Yi-shuang Lu", "Ye-xuan Ping", "Peng-yuan Zheng", "Xia Xue" ], "doi_url": "https://doi.org/10.1016/j.joim.2025.06.003", "publisher_url": "https://linkinghub.elsevier.com/retrieve/pii/S2095496425000834", "pmid": "40581550", "pmcid": null, "openalex_id": "https://openalex.org/W4411301913", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1016-j-joim-2025-06-003.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1016-j-joim-2025-06-003.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1016-j-joim-2025-06-003.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "Single-cell modules supplied the HCCcrds gene set.", "context": "GSE149614 single-cell module analysis.", "evidence": [ { "label": "Analyzed cells", "value": "11,383" }, { "label": "Genes from modules M2/M4/M5", "value": "562" } ], "source_locator": "Author-deposited full text: Results 3.1; Fig. 2", "source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html#kf1" }, { "id": "KF2", "claim": "The score was evaluated in separate clock, feeding and sleep-reference data.", "context": "Circadian reference experiments analyzed separately from HCC cohorts.", "evidence": [ { "label": "Reference datasets", "value": "GSE10045; GSE150381; GSE39445" } ], "source_locator": "Author-deposited full text: Results 3.2; Fig. 3", "source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html#kf2" }, { "id": "KF3", "claim": "TCGA-LIHC analysis identified CS-H, CS-L and CS-M, with poorer outcomes associated with CS-H.", "context": "Retrospective TCGA-LIHC subtype and outcome analysis.", "evidence": [ { "label": "TCGA-LIHC n", "value": "369" }, { "label": "Subtypes", "value": "CS-H; CS-L; CS-M" } ], "source_locator": "Author-deposited full text: Results 3.3-3.4; 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CIBERSORT; IPS" } ], "source_locator": "Author-deposited full text: Results 3.6-3.7; Fig. 6", "source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html#kf5" }, { "id": "KF6", "claim": "NNMT and MARCKSL1 were among subtype-associated candidate genes.", "context": "Candidate-gene expression and network prioritization.", "evidence": [ { "label": "Evidence", "value": "Expression correlation and network prioritization" } ], "source_locator": "Author-deposited full text: Results 3.8; Table 2; final PubMed abstract", "source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html#kf6" } ], "field_entry": [ "Cancer systems biology", "Hepatocellular carcinoma molecular research" ], "review_topics": [ "Circadian-related cancer heterogeneity", "Transcriptomic subtypes and retrospective outcomes" ], "concepts": { "disease": [ "hepatocellular carcinoma" ], "entities": [ "HCCcrds", "NNMT", "MARCKSL1" ], "methods": [ "transcriptomic subtyping", "LRA clustering", "NTP", "immune deconvolution" ], "evidence": [ "retrospective outcome association" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Public single-cell and bulk transcriptomic integration with retrospective subtype evaluation", "evidence_type": "Human molecular association and cross-dataset classification analysis", "population": "HCC expression cohorts, with separate circadian reference experiments", "primary_endpoint": "HCCcrds-associated molecular subtype structure", "secondary_endpoint": "Retrospective outcome associations and computational biological annotations", "data_modalities": [ "single-cell RNA sequencing", "bulk transcriptomics", "co-expression analysis", "LRA clustering/NTP", "immune deconvolution" ], "external_validation": true, "scale_metrics": [ { "label": "TCGA-LIHC", "value": "369 samples in the reported analysis" }, { "label": "GSE149614 analyzed cells", "value": "11,383 cells" }, { "label": "External datasets", "value": "5 datasets with different analytical roles" } ], "counting_note": "Cell counts, candidate genes, HCC cohort samples and separate circadian reference experiments are different units. No complete unique-participant total is inferred. The five external datasets have different analytical uses: the four Fig. 5A and four Fig. 5B sets overlap but are not identical and must not be added as eight independent cohorts. External validation means retrospective cross-dataset expression/classification evaluation, not prospective clinical utility or direct physiological rhythm measurement in HCC patients." }, "study_profile_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1016-j-joim-2025-06-003.json", "gold_content_sha256": "4d43240cde17744663497387ee8c0b14973146879bfcaf4e31d9305ec351beb7", "provenance": { "doi_url": "https://doi.org/10.1016/j.joim.2025.06.003", "publisher_url": "https://www.sciencedirect.com/science/article/abs/pii/S2095496425000834", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/40581550/", "author_deposited_full_text": "https://www.researchgate.net/publication/392697303_Integrated-omics_analysis_defines_subtypes_of_hepatocellular_carcinoma_based_on_circadian_rhythm", "source_version": "Bibliographic identity was checked against the final PubMed/publisher record. Detailed evidence locators refer to the author-deposited full text; final typeset figure-level equivalence was not independently re-established.", "review_basis": "Evidence synthesis from the cited main text, figure legends and designated primary records. No independent reanalysis of participant-level data. 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No complete unique-participant total is inferred. The five external datasets have different analytical uses: the four Fig. 5A and four Fig. 5B sets overlap but are not identical and must not be added as eight independent cohorts. External validation means retrospective cross-dataset expression/classification evaluation, not prospective clinical utility or direct physiological rhythm measurement in HCC patients.", "Cells and candidate genes are not patient counts or demonstrated causal regulators.", "Reference-experiment evaluation does not mean HCC patients underwent longitudinal physiological circadian measurements.", "Association does not establish that circadian disruption causes liver cancer or constitute a validated clinical decision rule.", "Do not claim that all five cohorts validated survival, or add the two four-cohort analyses as eight independent cohorts.", "IPS and immune deconvolution are not an observed immunotherapy-response trial.", "This evidence synthesis does not claim independent causal intervention or therapeutic validation of these genes.", "Prospective diagnostic or prognostic clinical utility.", "Direct individual measurement of physiological circadian phase or amplitude.", "Circadian disruption as a demonstrated cause of cancer.", "Clinical benefit from score-guided treatment.", "IPS as measured response in patients receiving immunotherapy.", "Therapeutic validation of the candidate genes.", "Completed page-by-page equivalence checking between the author-deposited text and final typeset version.", "Unprovided AUCs, hazard ratios, participant totals or additional omics modalities.", "Bibliographic identity was checked against the final PubMed/publisher record. Detailed evidence locators refer to the author-deposited full text; final typeset figure-level equivalence was not independently re-established." ], "scope_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/evidence_scope" }, { "id": "doi-10-1186-s12915-025-02400-x", "title": "Machine learning combined with omics-based approaches reveals T-lymphocyte cellular fate imbalance in abdominal aortic aneurysm", "doi": "10.1186/s12915-025-02400-x", "year": 2025, "journal": "BMC Biology", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.md", "paper_geo_status": "v2", "authors": [ "Demin Li", "Ge Zhang", "Pengchong Du", "Chang Cao", "Xuyu He", "Yan Lv", "Peiyu Yuan", "Yujia Wang", "Ruhao Wu", "Yifan Cao", "Yu Yang", "Jiamin Gao", "Bo Lan", "Guo-Ping Shi", "Xiaolin Cui", "Jinying Zhang", "Junnan Tang" ], "doi_url": "https://doi.org/10.1186/s12915-025-02400-x", "publisher_url": "https://bmcbiol.biomedcentral.com/articles/10.1186/s12915-025-02400-x", "pmid": "41013440", "pmcid": "PMC12465141", "openalex_id": "https://openalex.org/W4414554387", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1186-s12915-025-02400-x.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1186-s12915-025-02400-x.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1186-s12915-025-02400-x.csl.json", "evidence_status": "reviewed_v2", "question_count": 7, "key_findings": [ { "id": "KF1", "claim": "Human AAA single-cell profiling characterized a heterogeneous cellular landscape.", "context": "Four human aneurysmal aortic samples; cells are analytical units and are not independent participants.", "evidence": [ { "label": "aneurysmal aortic samples", "value": "4" }, { "label": "post-QC cells", "value": "7,343" }, { "label": "populations", "value": "16" }, { "label": "main cell types", "value": "9" } ], "source_locator": "Results: Single-cell transcriptome profiles of human AAA; Fig. 1", "source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#kf1" }, { "id": "KF2", "claim": "Monocle inferred a bifurcated T-cell trajectory linking heterogeneous transcriptional states in human AAA.", "context": "Pseudotime reconstructs state relationships; the study did not directly observe individual T cells changing fate over time.", "evidence": [ { "label": "T cells", "value": "3,841" }, { "label": "T-cell phenotypes", "value": "8" }, { "label": "infiltration states", "value": "3" }, { "label": "trajectory", "value": "Bifurcated trajectory with 2 terminal fates" } ], "source_locator": "Results: Heterogeneity of T lymphocytes in human AAA and high-dimensional single-cell lineage mapping; Figs. 2-3; Supplementary Fig. S3", "source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#kf2" }, { "id": "KF3", "claim": "Public bulk cohorts showed AAA-associated immune and transcriptomic patterns.", "context": "Disease-associated patterns across different tissue and cohort comparisons; these are associations, not causal evidence.", "evidence": [ { "label": "Dataset 1", "value": "AAA n=80; controls n=10" }, { "label": "Dataset 2", "value": "AAA n=9; controls n=10" }, { "label": "Dataset 3", "value": "dilated PVAT n=30; non-dilated PVAT n=30" } ], "source_locator": "Results: bulk immune-landscape analysis; Fig. 4; Supplementary Fig. S4", "source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#kf3" }, { "id": "KF4", "claim": "Integrated cell-state, fate-associated and trajectory gene sets yielded a 50-gene bulk-overlapping T-cell infiltration regulatory signature, TIRS.", "context": "Transcriptomic signature derivation; genes selected by these analyses are not established causal regulators.", "evidence": [ { "label": "cell-state DE genes", "value": "968" }, { "label": "BEAM fate leader genes", "value": "437" }, { "label": "trajectory ordering genes", "value": "375" }, { "label": "intersection", "value": "374" }, { "label": "final bulk-overlapping TIRS", "value": "50 genes" } ], "source_locator": "Results: Biological implications underlying TIRS; Fig. 5; Supplementary Fig. S5", "source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#kf4" }, { "id": "KF5", "claim": "LASSO and SVM-RFE prioritized FOSB, JUNB, CST7 and TBC1D4, with variable discrimination across public cohorts.", "context": "Public-cohort retrospective marker discrimination; dataset performance does not establish prospective diagnostic utility.", "evidence": [ { "label": "LASSO + SVM-RFE intersection", "value": "FOSB, JUNB, CST7, TBC1D4" }, { "label": "Dataset 1 AUCs (FOSB/JUNB/CST7/TBC1D4)", "value": "0.911 / 0.917 / 0.926 / 0.955" }, { "label": "Dataset 2 AUCs (FOSB/JUNB/CST7/TBC1D4)", "value": "0.982 / 0.911 / 0.893 / 0.857" }, { "label": "Dataset 3 AUCs (FOSB/JUNB/CST7/TBC1D4)", "value": "0.956 / 0.887 / 0.506 / 0.514" } ], "source_locator": "Results: Detection and evaluation of key biomarkers; Fig. 6", "source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#kf5" }, { "id": "KF6", "claim": "The candidate markers were evaluated in independent in-house human aortic-wall and peripheral-blood samples.", "context": "The aortic-wall comparison was small (5 AAA and 4 controls); these results do not establish approved standalone clinical tests.", "evidence": [ { "label": "aortic wall", "value": "AAA n=5; controls n=4" }, { "label": "aortic-wall AUCs (FOSB/JUNB/CST7/TBC1D4)", "value": "1.000 / 1.000 / 0.600 / 0.800" }, { "label": "peripheral blood", "value": "AAA n=24; controls n=15" }, { "label": "blood AUCs (FOSB/JUNB/CST7/TBC1D4)", "value": "0.989 / 0.906 / 0.933 / 0.736" } ], "source_locator": "Results: Detection and evaluation of key biomarkers; Fig. 7A-G", "source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#kf6" }, { "id": "KF7", "claim": "The BAPN + AngII mouse AAA model showed higher FOSB/JUNB signal in aortic immunohistochemistry and serum ELISA under the reported conditions.", "context": "Supportive preclinical expression evidence; it does not prove a human causal mechanism or treatment efficacy.", "evidence": [ { "label": "mouse AAA model", "value": "BAPN + AngII" }, { "label": "expression assays", "value": "Higher FOSB/JUNB signal in aortic IHC and serum ELISA" } ], "source_locator": "Fig. 7H-L; Supplementary Fig. S6", "source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/key_findings/6", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#kf7" } ], "field_entry": [ "Aortic aneurysm immunobiology", "Single-cell vascular research" ], "review_topics": [ "T-cell heterogeneity in abdominal aortic aneurysm", "Immune-cell-linked molecular markers in human vascular disease" ], "concepts": { "conditions": [ "abdominal aortic aneurysm" ], "cell_biology": [ "T lymphocytes", "T-cell state heterogeneity", "immune microenvironment" ], "methods": [ "single-cell RNA sequencing", "Monocle pseudotime", "bulk transcriptomics", "LASSO", "SVM-RFE" ], "entities": [ "TIRS", "FOSB", "JUNB", "CST7", "TBC1D4" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Integrative multicohort transcriptomic study combining human AAA single-cell RNA sequencing, multiple public bulk transcriptomic cohorts, independent human clinical validation samples and supportive mouse AAA expression experiments", "evidence_type": "Human single-cell and multicohort transcriptomic association with independent small-sample clinical validation and supportive preclinical expression evidence", "population": "Human abdominal aortic aneurysm tissue, peripheral blood and public transcriptomic datasets, with supportive experimental mouse AAA evidence", "primary_endpoint": "T-cell state/fate-associated transcriptional architecture in AAA", "secondary_endpoint": "Identification and cross-dataset evaluation of T-cell infiltration regulatory genes and candidate AAA biomarkers", "data_modalities": [ "single-cell RNA sequencing", "bulk transcriptomics", "qRT-PCR", "immunohistochemistry", "ELISA", "mouse AAA histopathology" ], "external_validation": true, "scale_metrics": [ { "label": "Human AAA scRNA donors", "value": "4 aneurysmal abdominal aorta samples" }, { "label": "Post-QC single cells", "value": "7,343 cells" }, { "label": "T cells", "value": "3,841 cells" }, { "label": "T-cell phenotypes", "value": "8" }, { "label": "Bulk Dataset 1", "value": "AAA n=80; controls n=10" }, { "label": "Bulk Dataset 2", "value": "AAA n=9; controls n=10" }, { "label": "Bulk Dataset 3", "value": "dilated PVAT n=30; non-dilated PVAT n=30" }, { "label": "In-house aortic wall", "value": "AAA n=5; controls n=4" }, { "label": "In-house peripheral blood", "value": "AAA n=24; controls n=15" } ], "counting_note": "Datasets contain different biological and analytical units. GSE57691 + GSE98278 contribute to Dataset 1. Cell counts must never be added to participant or sample counts. Public cohort samples must not be summed into a synthetic unique participant total without participant-level deduplication. Mouse measurements are separate preclinical units." }, "study_profile_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1186-s12915-025-02400-x.json", "gold_content_sha256": "f3ae395639d03c1aef1eb8e56713b9deb599a984bacb6a6573d1259f3502f10d", "provenance": { "doi_url": "https://doi.org/10.1186/s12915-025-02400-x", "publisher_url": "https://link.springer.com/article/10.1186/s12915-025-02400-x", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/41013440/", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12465141/" }, "scientific_role": "Human AAA T-cell state description integrated with bulk-expression marker analysis and independent human-sample assessment.", "evidence_position": "Human single-cell and bulk transcriptomics with small clinical-sample evaluation and supportive mouse expression; inferred states are not longitudinal fate tracing or proven therapy.", "related_concepts": [ "T-cell state imbalance", "Cell-state-to-marker integration" ], "citation_contexts": [ "Background: adaptive immune heterogeneity in abdominal aortic aneurysm.", "Methods: integration of human single-cell immune states with bulk-expression markers, without causal or therapeutic inference from predicted agents." ], "evidence_scope": { "supports": [ "Human AAA single-cell T-cell heterogeneity.", "Inferred T-cell transcriptional state and fate structure.", "Multicohort AAA-associated transcriptomic patterns and TIRS derivation.", "FOSB/JUNB/CST7/TBC1D4 marker discrimination in the analyzed datasets.", "Small independent in-house human validation, including aortic wall n=5 AAA and n=4 controls.", "Supportive mouse expression evidence." ], "does_not_establish": [ "Pseudotime as directly observed longitudinal cell fate.", "7,343 cells as 7,343 participants.", "FOSB/JUNB as established causal drivers of human AAA.", "Prospective diagnostic performance or approved standalone clinical tests.", "Predicted pharmacologic agents as effective AAA therapy.", "Mouse expression evidence as human treatment evidence." ] }, "limitations": [ "The in-house aortic-wall sample size was small: 5 AAA and 4 controls.", "Pseudotime is an inferred transcriptional ordering, not direct longitudinal lineage observation.", "Candidate-marker discrimination does not establish prospective clinical diagnostic performance.", "Mouse expression observations do not establish human causal mechanisms or therapeutic benefit." ], "scope_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/evidence_scope" }, { "id": "doi-10-71321-fy14v342", "title": "Mapping heterogeneous molecular subtypes of circadian misalignment underlying lung adenocarcinoma risk", "doi": "10.71321/fy14v342", "year": 2025, "journal": "Life Conflux", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html", "markdown_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.md", "paper_geo_status": "v2", "authors": [ "Ruhao Wu", "Kaisaierjiang Kadier", "Shuai Xu", "Peiyu Yuan", "Yu Yang", "Pengyuan Xu", "Xufeng Huang", "Shujing Zhou", "Song-Bin Guo", "Haonan Zhang", "Shiqian Zhang", "Chaoyang Yu", "Teng Li", "Ge Zhang" ], "doi_url": "https://doi.org/10.71321/fy14v342", "publisher_url": "https://ojs.lifeconfluxpress.com/index.php/lifeconflux/article/view/fy14v342", "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W4413040871", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-71321-fy14v342.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-71321-fy14v342.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-71321-fy14v342.csl.json", "evidence_status": "reviewed_v2", "question_count": 9, "key_findings": [ { "id": "KF1", "claim": "Retrospective transcriptomic analysis selected three CRD-expression clusters in TCGA-LUAD and assessed transfer of template features to six GEO cohorts.", "context": "Retrospective public-cohort classification. Seven reported LUAD input counts sum to 2090 without participant-level proof of disjointness. NTP confidence filtering and incomplete clinical information affect downstream denominators; external template assessment is not prospective clinical validation.", "source_locator": "PDF p. 3 / print p. 16, Method: Data acquisition and procession and Development and validation of CRD-related subtypes; PDF p. 4 / print p. 17, Results: Identification and Validation; PDF p. 5 / print p. 18, actual NMF and template-feature panels; official Supplementary Fig. S1 and Table S1. Results say five external cohorts but name six GEO accessions.", "evidence": [ { "label": "Reported CRD-related gene entries", "value": "2091" }, { "label": "TCGA-LUAD input records", "value": "497" }, { "label": "Expression clusters", "value": "3" }, { "label": "Named external GEO cohorts", "value": "GSE72094; GSE68465; GSE50081; GSE42127; GSE41271; GSE31210" }, { "label": "Candidate NMF ranks", "value": "2-7" }, { "label": "Iterations stated in Methods", "value": "100" }, { "label": "NMF method", "value": "lee" }, { "label": "NTP confidence handling", "value": "FDR <0.05; text says records with FDR >0.05 excluded" } ], "source": "data/deep_geo/doi-10-71321-fy14v342.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#kf1" }, { "id": "KF2", "claim": "The clusters had different observed survival patterns, with C2 generally more favorable and C1 generally less favorable in the reported analyses.", "context": "Kaplan-Meier comparisons describe outcome associations. C2 generally has more favorable survival and C1 generally less favorable survival, but the GSE42127 plot does not show the same ranking throughout. These are not treatment effects or a calibrated clinical risk rule.", "source_locator": "PDF p. 4 / print p. 17, Identification and Validation Results; PDF p. 5 / print p. 18, actual TCGA Kaplan-Meier panel C; PDF p. 8 / print p. 21, actual proportions and survival panels A-F, despite the Figure 3 functional-enrichment caption; official Supplementary Fig. S2A (GSE50081).", "evidence": [ { "label": "Displayed TCGA log-rank P", "value": "0.0062" }, { "label": "Displayed GSE50081 log-rank P", "value": "0.00991" } ], "source": "data/deep_geo/doi-10-71321-fy14v342.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#kf2" }, { "id": "KF3", "claim": "The inferred functional patterns distinguish proliferation-related C1, lipid-metabolic C2 and immune-associated C3.", "context": "GSVA/GSEA and pathway annotations are computed from bulk tumor expression. They do not directly measure individual circadian phase, sleep behavior or metabolic flux, and do not establish circadian disruption as the cause of the phenotypes.", "source_locator": "PDF p. 4 / print p. 17, Method: Exploring specific biological characteristics; PDF p. 7 / print p. 20, Results: Underlying biological functional processes; PDF p. 6 / print p. 19, actual enrichment heatmap and GSEA plots, despite the Figure 2 proportions/survival caption; official Supplementary Fig. S2B.", "evidence": [ { "label": "C1 expression features", "value": "Cell cycle, DNA replication and E2F-related enrichment" }, { "label": "C2 expression features", "value": "Lipid-metabolic and circadian sleep-wake gene-set enrichment" }, { "label": "C3 expression features", "value": "Cytokine, chemokine, complement and other immune-related expression enrichment" } ], "source": "data/deep_geo/doi-10-71321-fy14v342.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#kf3" }, { "id": "KF4", "claim": "TCGA annotation analyses associated C1 with greater mutation and copy-number-alteration burdens.", "context": "TCGA mutation and CNV annotations are associated with the expression-defined clusters. They do not demonstrate that clock disruption caused TP53 changes, genomic instability, proliferation or immune escape. Genomic-data availability need not equal expression-input n.", "source_locator": "PDF p. 4 / print p. 17, Method: Somatic mutation and copy number variation analysis; PDF p. 7 / print p. 20, Results: Genomic alterations; PDF p. 9 / print p. 22, actual mutation waterfall and CNV panels (Figure 4); official Supplementary Fig. S2C.", "evidence": [ { "label": "Genomic analyses", "value": "Somatic mutation, GISTIC-based focal/arm CNV, FGA/FGG/FGL and inferred stemness" }, { "label": "Genes emphasized in Results", "value": "TP53; TTN" } ], "source": "data/deep_geo/doi-10-71321-fy14v342.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#kf4" }, { "id": "KF5", "claim": "C3 showed stronger inferred immune infiltration together with immune-suppressive expression features and higher inferred intratumor heterogeneity.", "context": "Bulk-expression inference and genomic/immune scores describe associations. Greater infiltration can coexist with suppression. These analyses do not directly enumerate cells, prove immune-escape mechanisms or constitute single-cell validation.", "source_locator": "PDF p. 4 / print p. 17, Method: Depicting distinct immune landscape; PDF p. 7 / print p. 20, Results: Immune infiltration and immune escape landscape; PDF p. 10 / print p. 23, actual immune-score, HLA and heterogeneity panels (Figure 5); official Supplementary Fig. S2D and Table S2.", "evidence": [ { "label": "Immune inference", "value": "28 ssGSEA subsets; additional expression-inference methods" }, { "label": "Additional immune algorithms", "value": "ESTIMATE; TIMER; quanTIseq; MCP-counter; EPIC; xCell" }, { "label": "Immune/heterogeneity annotations", "value": "IPS, S score, HLA expression and external annotation signatures" } ], "source": "data/deep_geo/doi-10-71321-fy14v342.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#kf5" }, { "id": "KF6", "claim": "Checkpoint-expression, TIS and SubMap results generated an immunotherapy-response hypothesis for C3.", "context": "Checkpoint expression, TIS and SubMap provide indirect response hypotheses. The abstract separately reports 79 reference records, but their split, second cohort identity, tumor composition and participant overlap remain unresolved. No prospective LUAD subtype-guided treatment effect is established.", "source_locator": "PDF p. 2 / print p. 15, Abstract Methods (79-record statement); PDF p. 4 / print p. 17, immunotherapy Methods; PDF p. 7 / print p. 20, Results: The assessment of response to immunotherapy; PDF p. 11 / print p. 24, actual checkpoint, TIS and SubMap panels A-C; PDF p. 13 / print p. 26, Data availability.", "evidence": [ { "label": "Immune-checkpoint panel", "value": "27" }, { "label": "TIS inflammatory gene count", "value": "18" }, { "label": "Immunotherapy reference scope", "value": "Two reference cohorts, 79 records as reported in Abstract; specific split unverified" }, { "label": "SubMap analysis", "value": "Expression similarity to responders; nominal and Bonferroni-adjusted SubMap p values" }, { "label": "Separate abstract count", "value": "79 immunotherapy records; not combined with the seven LUAD input counts" } ], "source": "data/deep_geo/doi-10-71321-fy14v342.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#kf6" }, { "id": "KF7", "claim": "Cell-line-based computational drug-response estimates were associated with subtype and remain treatment hypotheses.", "context": "The reported pRRophetic/CTRP/PRISM drug-response estimates are computational. Their axes say estimated AUC while the text calls the endpoint IC50; the text names prednisone while the supplement names prednisolone. No exact IC50 or clinical drug recommendation is inferred.", "source_locator": "PDF p. 7 / print p. 20, Results: Potential drug development; PDF p. 11 / print p. 24, actual drug-response panels under label D, although the caption assigns drugs to D/E; official Supplementary Fig. S2E-F; PDF pp. 12-13 / print pp. 25-26, Discussion limitations.", "evidence": [ { "label": "Drug-prediction method reported", "value": "pRRophetic using CTRP and PRISM sensitivity data" }, { "label": "Main displayed drug axes", "value": "Estimated AUC of docetaxel; Estimated AUC of dexamethasone" }, { "label": "Supplementary displayed drug axes", "value": "Estimated AUC of paclitaxel; Estimated AUC of prednisolone" } ], "source": "data/deep_geo/doi-10-71321-fy14v342.json#/key_findings/6", "evidence_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#kf7" }, { "id": "KF8", "claim": "The article reports an exploratory comparison of 151 existing prognostic signatures within TCGA subtypes.", "context": "Risk scores were recalculated and candidate signatures compared within the same TCGA data. These best-candidate C-index values are exploratory within-cohort discrimination, not external performance or prospective utility. The Chen EG (2017) attribution remains unresolved because reference 41 does not clearly identify the claimed prognostic model.", "source_locator": "PDF p. 4 / print p. 17, Method: Personalized management for distinct subtypes; PDF p. 12 / print p. 25, Clinical delicacy management and Discussion; PDF p. 11 / print p. 24, actual C-index comparison under panel E (text/caption refer to F, but no F panel is displayed); PDF p. 15 / print p. 28, references 41-42.", "evidence": [ { "label": "Candidate prognostic signatures", "value": "151" }, { "label": "Article-reported C1 C-index", "value": "0.741" }, { "label": "Article-reported C2 C-index", "value": "0.698" }, { "label": "Article-reported C3 C-index", "value": "0.796" }, { "label": "Reported model labels", "value": "Chen EG (2017) for C1/C2; Ma B (2020) for C3, as attributed by this article" }, { "label": "Source-attribution boundary", "value": "The Discussion names 21-gene and 16-gene models, but their exact source-to-model mapping is not independently established here; reference 41 is a DGCR5/miR-1180 paper" } ], "source": "data/deep_geo/doi-10-71321-fy14v342.json#/key_findings/7", "evidence_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#kf8" } ], "field_entry": [ "Lung adenocarcinoma molecular research", "Cancer transcriptomic systems biology" ], "review_topics": [ "Circadian-related expression subtypes in LUAD", "Retrospective subtype associations and treatment-response hypotheses" ], "concepts": { "Molecular classification": [ "Circadian-related tumor expression", "LUAD heterogeneity", "NMF clusters", "Nearest template prediction" ], "Associated features": [ "Proliferation enrichment", "Lipid-metabolic pathways", "Somatic mutation", "Copy-number alteration", "Inferred immune infiltration" ], "Evidence boundaries": [ "Retrospective survival association", "TIS", "SubMap", "Predicted drug response", "Within-cohort C-index comparison" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Retrospective public bulk-transcriptomic classification, external NTP assignment and outcome/annotation analysis, with separate computational treatment-response hypotheses", "evidence_type": "Human tumor-expression associations and cross-cohort assessment; genomic/immune annotations and computational drug/response prediction", "population": "Public LUAD tumor-expression cohorts; separately reported immunotherapy reference records with unresolved composition. No prospective subtype-guided trial or new single-cell experiment.", "primary_endpoint": "Expression-defined C1/C2/C3 cluster structure and cross-cohort template assignment", "secondary_endpoint": "Retrospective survival, pathway, genomic and inferred immune differences; computational treatment hypotheses and within-TCGA signature comparisons", "data_modalities": [ "Bulk tumor transcriptomics", "Retrospective survival and clinical annotations", "Somatic mutation and GISTIC copy-number annotations", "GSVA/GSEA pathway scores", "Bulk-expression immune inference", "TIS and SubMap expression similarity", "Cell-line-based drug-response prediction" ], "external_validation": true, "scale_metrics": [ { "label": "TCGA-LUAD reported input", "value": "497 cohort records" }, { "label": "GSE72094 reported input", "value": "442 cohort records" }, { "label": "GSE68465 reported input", "value": "462 cohort records" }, { "label": "GSE50081 reported input", "value": "127 cohort records" }, { "label": "GSE42127 reported input", "value": "133 cohort records" }, { "label": "GSE41271 reported input", "value": "183 cohort records" }, { "label": "GSE31210 reported input", "value": "246 cohort records" }, { "label": "Reported LUAD input arithmetic", "value": "2090 across seven listed cohorts; not a deduplicated participant total" }, { "label": "Separate immunotherapy abstract count", "value": "79 records; split and overlap unresolved" }, { "label": "CRD-related gene list", "value": "2091 entries reported" }, { "label": "Expression clusters", "value": "Three: C1, C2 and C3" }, { "label": "External NTP assessment", "value": "Six named GEO cohorts; retrospective and confidence-filtered" } ], "counting_note": "The seven LUAD input counts sum arithmetically to 2090. Participant-level disjointness is not established; filtered classification/survival and genomic subsets have their own denominators. The 79 immunotherapy records are a separate abstract-reported reference count, not added to claim a unique total. External validation here means retrospective template assignment and outcome association, not prospective clinical utility or treatment-response validation." }, "study_profile_source": "data/deep_geo/doi-10-71321-fy14v342.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-71321-fy14v342.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-71321-fy14v342.json", "gold_content_sha256": "5f07bbef4e5c53e3873e3fea6933c88228aab055b64b739686d517e892e63961", "provenance": { "publisher_url": "https://www.lifeconflux.com/10.71321/fy14v342/", "publisher_ojs_url": "https://ojs.lifeconfluxpress.com/index.php/lifeconflux/article/view/fy14v342", "official_pdf_url": "https://ojs.lifeconfluxpress.com/index.php/lifeconflux/article/download/fy14v342/Download", "crossref_url": "https://api.crossref.org/works/10.71321/fy14v342", "supplement_url": "https://www.lifeconflux.com/static/Papers/2025_Volume1_Issue3/4/Supplementary%20Material.zip", "source_version": "Scientific synthesis adopts the official OJS-linked PDF marked vor in Crossref, byte-identical to the supplied 15-page PDF. SHA-256: 80b8e8c5e22ac793661e01123bdddcf42ae02f9503bb55acaaa26369b021c776. It prints 2025-06-30, Life Conflux 1(3):14-28; PDF pages and actual visual content govern evidence locators.", "review_basis": "The complete PDF and available official S1/S2 figures and Tables S1/S2 were previously reviewed. This release rechecked cohort/validation wording, the 151-signature Methods/Results and actual swapped Figure 2/3 images, reusing retained source hashes and audits.", "identity_status": "IDENTITY_REVIEW_REQUIRED. Scientific V2 is published independently of unresolved official bibliographic identity; current site master/citation authors, date fields, DOI, slug and canonical are preserved.", "author_version_conflict": "The adopted PDF has 16 authors: Ruhao Wu, Teng Li, Kaisaierjiang Kadier, Pengyuan Xu, Peiyu Yuan, Tinglan Fu, Yu Yang, Xufeng Huang, Zhou Shujing, Zhengrui Li, Pengpeng Zhang, Song-Bin Guo, Haonan Zhang, Shiqian Zhang, Chaoyang Yu, Ge Zhang. OJS/Crossref have 14 including Shuai Xu and omitting Tinglan Fu, Zhengrui Li and Pengpeng Zhang. The other publisher main byline has 16 but Teng Li fifteenth. This evidence layer does not select a definitive author order.", "date_pagination_conflict": "PDF/full-text history/Crossref online date: 2025-06-30. OJS display/citation date: 2025-10-20; DC issued: 2025-06-15. PDF pages: 14-28; OJS/Crossref: e137. These source-version observations do not replace retained site citation metadata.", "figure_locator_rule": "PDF p. 6 / print p. 19 is enrichment with a Figure 2 survival caption; PDF p. 8 / print p. 21 is proportions/survival with a Figure 3 enrichment caption. PDF p. 11 / print p. 24 has drug panels D and signature panels E; text/caption instead refer to signature F. Locators specify actual page/content.", "prediction_boundary": "TIS, SubMap and drug outputs are indirect/computational. The 151-signature C-index values are exploratory within-TCGA comparisons; exact Chen-model attribution remains unresolved. No result is promoted to demonstrated clinical treatment effectiveness.", "source_protection": "Full PDFs, page images, raw publisher snapshots and detailed audits remain outside the public repository. The evidence layer contains original paraphrases, source hashes, source-specific limits and locators." }, "scientific_role": "A public-cohort LUAD expression-classification study with external template assessment, biological associations and computational treatment hypotheses.", "evidence_position": "Retrospective expression and annotation evidence; not direct rhythm measurement, prospective subtype-guided treatment utility or externally validated best-model performance.", "related_concepts": [ "Molecular heterogeneity", "Cross-cohort template assignment", "Association versus clinical utility" ], "citation_contexts": [ "Reviews of circadian-related cancer expression heterogeneity and retrospective molecular-subtype associations.", "Methods discussions separating template transfer, outcome association, immune/drug prediction and within-cohort model comparison from clinical validation." ], "evidence_scope": { "supports": [ "Retrospective LUAD expression clustering and cross-cohort NTP assessment under the reported confidence filtering.", "Reported outcome, pathway, genomic and inferred immune associations for expression-defined clusters.", "Computational treatment hypotheses and article-reported within-TCGA signature comparisons, with source gaps retained." ], "does_not_establish": [ "A prospective subtype-guided clinical trial, treatment benefit or clinical decision rule.", "Direct measurement of patient circadian phase, sleep behavior or causal circadian mechanisms.", "Immunotherapy response rates, benefit probabilities or chemotherapy/corticosteroid recommendations for the subtypes.", "A deduplicated unique-patient total spanning LUAD and immunotherapy datasets.", "Externally validated best-signature performance, calibration, decision benefit or resolved Chen EG model attribution.", "Resolved author order, dates or pagination across the conflicting official bibliographic records." ] }, "limitations": [ "Retrospective and largely computational evidence; no prospective subtype-guided treatment trial or direct patient circadian-physiology experiment is reported.", "The seven LUAD input counts sum arithmetically to 2090. Participant-level disjointness is not established, and the separately reported 79 immunotherapy records are not added to claim a unique total.", "NTP confidence filtering and incomplete clinical information alter analysis denominators. The input cohort counts are not every downstream survival, genomic or prediction denominator.", "Validation Results say five external cohorts while naming six GEO accessions. Six named cohorts are described; accession differences alone do not prove patient disjointness.", "The adopted PDF swaps Figure 2/3 captions relative to visual content: PDF p. 6 / print p. 19 is enrichment; PDF p. 8 / print p. 21 is proportions/survival. Locators identify actual page and content.", "Template-feature heatmap labels conflict with referenced cohort names: one says GSE64865 and another says GSE42127 where its caption says GSE41271. Their identity is not repaired by guess.", "The 79 immunotherapy reference records lack a verified cohort split, adequately identified second source, tumor-histology breakdown and overlap crosswalk. Data availability cites references 60/61 absent from the supplied list ending at 52.", "TIS, checkpoint expression and SubMap are indirect predictions or similarity analyses, not actual response rates, benefit probabilities or a recommendation to give immunotherapy to C3 patients.", "Drug text/axis IC50 versus estimated-AUC and prednisone versus prednisolone discrepancies are retained. Predicted sensitivity does not establish clinical chemotherapy or corticosteroid benefit.", "The 151-signature comparison ranks recalculated candidates within TCGA. The reported best C-index values do not establish external validation, calibration, decision benefit or resolved Chen EG model attribution.", "Supplementary legends mention S3/S4 silhouette and survival analyses, but the supplied official ZIP contains only S1/S2 images. Their unavailable adjusted hazard ratios, confidence intervals and independent prognostic claims are not supplied.", "Table S1 contains 2091 listed entries including apparent spreadsheet date-conversion tokens. They are not corrected or used to assert an independently reproduced clean gene signature.", "IDENTITY_REVIEW_REQUIRED: scientific synthesis adopts the official-linked 16-author PDF, 2025-06-30 and print pages 14-28. Current 14-author site bibliographic metadata is preserved; authorship/order, publisher dates and e137 versus print pagination remain unresolved." ], "scope_source": "data/deep_geo/doi-10-71321-fy14v342.json#/evidence_scope" }, { "id": "doi-10-1016-j-cbi-2025-111421", "title": "Modeling Diabetic Cardiomyopathy Using Human Cardiac Organoids: Effects of High Glucose and Lipid Conditions", "doi": "10.1016/j.cbi.2025.111421", "year": 2025, "journal": "Chemico-Biological Interactions", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.md", "paper_geo_status": "v2", "authors": [ "Xiangyu Wang", "Xin Tan", "Ting Zhang", "Shuai Xu", "Yiyao Zeng", "Anchen Xu", "Xian Li", "Ge Zhang", "Yufeng Jiang", "Hezi Jiang", "Jili Fan", "Xiaohong Bo", "Huimin Fan", "Yafeng Zhou" ], "doi_url": "https://doi.org/10.1016/j.cbi.2025.111421", "publisher_url": null, "pmid": "39984109", "pmcid": null, "openalex_id": "https://openalex.org/W4407731417", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1016-j-cbi-2025-111421.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1016-j-cbi-2025-111421.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1016-j-cbi-2025-111421.csl.json", "evidence_status": "reviewed_v2", "question_count": 8, "key_findings": [ { "id": "KF1", "claim": "The investigators generated hiPSC-derived three-dimensional cardiac organoids and documented growth and cardiac-lineage marker staining.", "context": "This is characterization of an in vitro construct. Marker-positive images do not establish mature adult-heart physiology, precise cell proportions, perfused vasculature or fidelity across independent human donors.", "source_locator": "Journal Pre-proof PDF pp. 7, 12-16, Methods 2.3-2.4, Results 3.1-3.2 and Figs. 1A-D and 2A; Fig. 1 is on PDF p. 13 and Fig. 2A on PDF p. 15.", "evidence": [ { "label": "Reported geometry", "value": "Approximately 500 micrometers at day 2 and approximately 1500 micrometers at day 14, stated in Results 3.1; these are not independently re-estimated bar values." }, { "label": "Lineage readouts", "value": "MLC2A, MLC2V, cTnT, CD31 and WT1 immunofluorescence." }, { "label": "Cell source", "value": "Commercial human induced pluripotent stem cells; independent donor count and detailed line identity are not specified." }, { "label": "Timing boundary", "value": "Figure 1C-D and the results describe day 14, while the differentiation schematic ends at day 13; the schematic is not promoted as an exact reproducible timetable." } ], "source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#kf1" }, { "id": "KF2", "claim": "The CCK-8 screen showed lower viability-associated signal at higher sodium-palmitate concentrations and a non-monotonic response across the displayed glucose conditions.", "context": "CCK-8 is an assay of cellular metabolic activity used here as a viability readout. The figure does not provide an absolute surviving-cell count, a validated clinical glucose threshold or a drug dose for patients. The glucose-alone plot and combined glucose/palmitate experiments are separate comparisons.", "source_locator": "Journal Pre-proof PDF pp. 8, 15-16, Methods 2.5-2.6, Results 3.3 and Fig. 2B-C (figure on PDF p. 15; legend on PDF p. 16).", "evidence": [ { "label": "Exposure duration", "value": "48 hours; followed by 2 hours with CCK-8 reagent and an absorbance measurement at 450 nm." }, { "label": "Palmitate screen", "value": "0, 50, 100, 150, 200, 250 and 300 micromolar are displayed; the 200-300 micromolar groups are below the 0-palmitate comparator." }, { "label": "Glucose screen", "value": "5, 12.5, 25, 33.3 and 50 mM are displayed. The peak is at 25 mM, and the 50 mM bar is below the displayed 5 mM group; no glucose-free group is shown in Fig. 2C." }, { "label": "Reported sample label", "value": "Fig. 2 legend: n=6, mean +/- SD; the independent biological-replicate unit is not defined." }, { "label": "Quantitative boundary", "value": "No exact viability percentage, effect size or p value is reconstructed from bar heights or significance symbols; no minimum toxic threshold is selected." } ], "source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#kf2" }, { "id": "KF3", "claim": "Under the combined glucose/palmitate conditions, selected apoptosis-related readouts were elevated relative to the labeled control, with lower signals in intermediate-glucose groups than in the group labeled PA/0 mM glucose and the highest-glucose condition.", "context": "The evidence comprises BAX/APAF1 mRNA and TUNEL staining in organoids. These readouts support an experimental injury pattern, not a demonstrated clinical apoptotic pathway or proof that an intermediate glucose concentration protects human hearts.", "source_locator": "Journal Pre-proof PDF pp. 10, 17-20, Methods 2.7-2.8, Results 3.4, Fig. 3B-C and Fig. 4; Table 1 primers on PDF pp. 8-10.", "evidence": [ { "label": "Combined exposure labels", "value": "Palmitate fixed at 200 micromolar; glucose labels 0, 5, 12.5, 25, 33.3 and 50 mM, with a separate CON/control group." }, { "label": "Gene readouts", "value": "BAX and APAF1 relative mRNA expression measured by RT-qPCR; Table 1 provides primer sequences." }, { "label": "Imaging readout", "value": "TUNEL images and red-fluorescence intensity; this is not a reported percentage of apoptotic cells." }, { "label": "Reported sample labels", "value": "Fig. 3 and Fig. 4 legends: n=3, mean +/- SD. These are not verified independent donor counts." }, { "label": "Excluded marker directions", "value": "TNNT2 and MYH6 are excluded from this claim because their Fig. 3D/H directions do not agree with the blanket prose description in Results 3.4." } ], "source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#kf3" }, { "id": "KF4", "claim": "The combined-exposure experiment showed changes in inflammatory and fibrosis-associated readouts alongside altered Masson staining.", "context": "TNF, IL6 and IL1B transcription, profibrotic transcripts and staining are experimental correlates of injury in a cultured construct. They do not establish clinical myocardial fibrosis, collagen turnover in patients or a uniquely identified causal mechanism.", "source_locator": "Journal Pre-proof PDF pp. 8-10 and 20-22, Methods 2.7 and 2.9, Results 3.5 and Fig. 5A-I (figure on PDF p. 21; legend continues on PDF p. 22).", "evidence": [ { "label": "Experimental conditions", "value": "200 micromolar palmitate with displayed glucose labels from 0 to 50 mM and a separate control." }, { "label": "Inflammatory markers", "value": "TNFA, IL1B and IL6 panels A-C show higher expression in the labeled treatment conditions than CON, with differing responses across glucose groups." }, { "label": "Fibrosis-related markers", "value": "COL1A1, FBN1, TGFB1 and CCN2 panels D-G, with Masson quantification and images in H-I." }, { "label": "Reported sample label", "value": "Fig. 5 legend: n=3, mean +/- SD; no unique participant or donor total is assigned." }, { "label": "Reporting boundary", "value": "No fold-change, collagen percentage or exact p value is digitized from the figure. The Masson readout is reported as staining, not as independently confirmed fibrin deposition." } ], "source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#kf4" }, { "id": "KF5", "claim": "The paper includes a three-group metformin comparison in which CCK-8 signal and selected expression readouts shifted toward control values in the DCM+MET group.", "context": "This is a descriptive comparison of the groups labeled in the pre-proof. The metformin concentration is not stated in the inspected methods, results or legends, and no clinical efficacy or fully reproducible dosing claim is made.", "source_locator": "Journal Pre-proof PDF pp. 11-12 and 23-25, Methods 2.12-2.14, Results 3.7 and Figs. 7-8; Fig. 7 on PDF p. 24 and Fig. 8 on PDF p. 25.", "evidence": [ { "label": "Group labels", "value": "CON, DCM and DCM+MET." }, { "label": "Model exposure", "value": "Results 3.7 specifies 200 micromolar sodium palmitate plus 33.3 mM glucose; samples were collected 48 hours after intervention in Methods 2.12." }, { "label": "Selected observations", "value": "Fig. 8A shows a higher CCK-8 signal in DCM+MET than DCM; Fig. 7 BAX/APAF1 and Fig. 8 BAX/COL1A1 panels show lower signals in the labeled DCM+MET group than DCM." }, { "label": "Reported sample labels", "value": "Fig. 7 legend: n=3; Fig. 8A legend: n=6. Independent biological replication and the separate Western-blot sample count are not specified." }, { "label": "Missing dosing information", "value": "Metformin concentration, precise independent replicate definition and raw observations were not supplied in the acquired file. No dose, percentage rescue or effect size is inferred." } ], "source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#kf5" } ], "field_entry": [ "Cardiac disease modeling", "Human stem-cell-derived organoids" ], "review_topics": [ "Glucose and palmitate injury experiments", "Three-dimensional cellular assay systems" ], "concepts": { "Experimental system": [ "Human induced pluripotent stem cells", "Cardiac organoids", "Diabetic cardiomyopathy model" ], "Exposures": [ "Glucose", "Sodium palmitate", "Metformin" ], "Accepted assay contexts": [ "CCK-8", "BAX", "APAF1", "TUNEL", "Inflammatory transcripts", "Masson staining" ], "Interpretation boundaries": [ "In vitro evidence", "Biological versus technical replication", "Journal Pre-proof version", "Protocol reporting gaps" ] }, "profile_type": "preclinical_multimodal", "study_profile": { "profile_type": "preclinical_multimodal", "study_design": "In vitro hiPSC-derived cardiac organoid generation, glucose/palmitate exposure and descriptive drug-response testing", "evidence_type": "Cell-culture morphology, immunofluorescence, CCK-8, RT-qPCR, TUNEL, histological staining and Western blots from a publisher Journal Pre-proof", "population": "Commercial human induced pluripotent stem cells differentiated into organoids; donor count and line identifiers not reported. No recruited patients or in vivo animal cohort.", "primary_endpoint": "Main evidence-page readout: CCK-8 signal after glucose/palmitate exposure; the paper does not designate a prespecified primary endpoint.", "secondary_endpoint": "Organoid geometry and marker staining; selected apoptosis, inflammatory and fibrosis-associated readouts; descriptive metformin group comparison.", "external_validation": false, "data_modalities": [ "Bright-field morphology", "Cardiac-lineage immunofluorescence", "CCK-8 absorbance", "RT-qPCR", "TUNEL microscopy", "Masson staining", "Western blots" ], "counting_note": "The Methods state that experiments were conducted at least three times. Captions report n=6 for CCK-8 and n=3 for several transcript/staining panels, but do not define independent donor, differentiation-batch or technical-replicate counts. Assay points are not summed into a total human or organoid n.", "scale_metrics": [ { "label": "Source version", "value": "37-page Journal Pre-proof; definitive final full text not compared" }, { "label": "Exposure duration", "value": "48 hours" }, { "label": "Palmitate screen", "value": "50-300 micromolar plus a 0-palmitate comparator" }, { "label": "Glucose screen", "value": "5-50 mM as displayed in Fig. 2C" }, { "label": "CCK-8 caption sample label", "value": "n=6; biological independence unspecified" }, { "label": "Selected transcript/staining sample label", "value": "n=3; biological independence unspecified" }, { "label": "Metformin concentration", "value": "Not reported in the acquired file" } ] }, "study_profile_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1016-j-cbi-2025-111421.json", "gold_content_sha256": "e2279edf76ab5b9f4c626bc4c39e4822169b203e04b6fa615f5a029954e6282a", "provenance": { "publisher_url": "https://www.sciencedirect.com/science/article/pii/S0009279725000511", "doi_url": "https://doi.org/10.1016/j.cbi.2025.111421", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/39984109/", "crossref_url": "https://api.crossref.org/works/10.1016/j.cbi.2025.111421", "source_record_url": "https://www.researchgate.net/publication/389140383_Modeling_Diabetic_Cardiomyopathy_Using_Human_Cardiac_Organoids_Effects_of_High_Glucose_and_Lipid_Conditions", "review_date": "2026-10-27", "review_basis": "The acquired 37-page Journal Pre-proof was read in full; Figs. 1-8 and their captions were inspected as rendered pages. Identity was compared with the current Crossref record and preserved publisher/PubMed records. The definitive full text and cited supplementary files were unavailable for direct comparison.", "source_version": "Publisher-branded Journal Pre-proof; not the definitive version of record. ResearchGate is the authorized acquisition channel, not a version certification.", "local_full_text_sha256": "92e7fa7eecfc52074c83b59824c0d7f875047b6b71fcfcab6087fab4e720bb91", "copyright": "Copyright 2025 Elsevier B.V. The private full text is retained outside the public repository and is not redistributed.", "unresolved_source_scope": "Supplementary files 1 and 2, final-text comparison, metformin concentration and biological-replicate definitions remain unavailable.", "quantitative_rule": "Report only printed conditions, caption sample labels and source-supported directions; no graph digitization, invented effect sizes, synthetic donor totals or clinical extrapolation." }, "scientific_role": "An in vitro organoid experiment with viability, transcript and imaging observations; version and protocol limitations are retained.", "evidence_position": "Preclinical human-cell-derived model evidence from a Journal Pre-proof; no clinical validation or complete reproducibility claim.", "related_concepts": [ "Lipotoxicity-associated cellular injury", "Experimental replicate units", "Descriptive drug-response readouts" ], "citation_contexts": [ "Modeling methods: cite the source version and stated culture exposure conditions while retaining unresolved protocol details.", "Results: cite selected organoid observations; do not turn them into validated patient outcomes or a metformin regimen." ], "evidence_scope": { "supports": [ "The described generation and marker characterization of hiPSC-derived cardiac organoids.", "The reported viability-screen pattern and selected apoptosis, inflammatory and fibrosis-associated group observations in the acquired pre-proof.", "A descriptive metformin-labeled group comparison, with the absent dose and unresolved biological replicate count explicitly disclosed." ], "does_not_establish": [ "Clinical diagnostic accuracy, patient benefit, prevention of diabetic heart disease or a glucose target for patients.", "A validated metformin dose, treatment regimen, safety profile or clinical effect size.", "Independent biological replication across a known number of donors or a complete reproduction protocol.", "A reconciled TNNT2/MYH6 expression direction, verified JC-1 ratio orientation, calibrated contractile force or measured mitochondrial respiratory capacity.", "Equivalence of every detail in the pre-proof and definitive final full text, or independent verification of the two unavailable supplementary files." ] }, "limitations": [ "The reviewed source is a 37-page publisher-branded Journal Pre-proof obtained through the author-authorized ResearchGate private-file channel. It is not the definitive version of record. DOI, title and all 14 authors agree with the current Crossref record, publisher landing page and PubMed record, but full final-text equivalence has not been verified.", "The study is an in vitro experiment using human-derived cells, not a human clinical cohort or an animal experiment. hiPSC line identifiers, independent donor number and the biological versus technical replicate unit are not clearly reported; caption n=3/n=6 values must not be converted into a unique human n.", "Methods 2.14 describes experiments conducted at least three times, mean +/- SD and one-way ANOVA. A post-hoc procedure, multiplicity strategy, randomization, blinded outcome assessment and a prospective sample-size calculation are not specified in the acquired source.", "TNNT2 and MYH6 are not included as accepted directional findings: Results 3.4 and 3.7 describe marker increases too broadly, whereas Figs. 3D/H and 7 display lower TNNT2/MYH6 in relevant treatment groups than control. No text or figure direction is silently chosen as a correction.", "JC-1 findings are excluded from directional or quantitative conclusions: Methods 2.11 specifies a red/green ratio, while Fig. 6B labels green/red. Reported fluorescence-channel wavelengths also require clarification. No mitochondrial respiration or ATP measurement was reported; membrane-potential fluorescence cannot establish respiratory capacity.", "The metformin concentration is absent from the inspected methods, results and legends. The labeled-group observations are described without an inferred regimen, dose-response claim, percentage rescue or extrapolation to patient efficacy.", "The culture methods print 10 mM for Y-27632, CHIR99021 and IWR-1. These values are not silently changed to micromolar concentrations and are not offered as an independently verified reproduction protocol.", "The glucose-alone figure displays a 5 mM baseline but no glucose-free group; its control terminology differs from the text. No exact clinical or in vitro toxicity threshold is certified. No explicit osmotic-control experiment is reported.", "Figure 3A measures diameter excursion in micrometers, despite use of the word force in the text. It is not a calibrated mechanical-force measurement, and no claim of validated cardiac pumping performance is made.", "Supplementary files 1 and 2 are cited but were not present in the acquired PDF or retrieved from an accessible official channel. Their dynamic contraction and high-dose morphology material is not treated as viewed or independently verified.", "Quantitative plots are not digitized. Bar heights, exact p values, raw biological replicates and precision estimates are not reconstructed; data are stated to be available on request." ], "scope_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/evidence_scope" }, { "id": "b4galt2", "title": "Novel post-translational modification learning signature reveals B4GALT2 as an immune exclusion regulator in lung adenocarcinoma", "doi": "10.1136/jitc-2024-010787", "year": 2025, "journal": "Journal for ImmunoTherapy of Cancer", "type": "Article", "paper_url": "https://drgezhang.com/papers/b4galt2.html", "markdown_url": "https://drgezhang.com/papers/b4galt2.md", "paper_geo_status": "v2", "authors": [ "Pengpeng Zhang", "Dingli Wang", "Guangyao Zhou", "Shuai Jiang", "Ge Zhang", "Lianmin Zhang", "Zhenfa Zhang" ], "doi_url": "https://doi.org/10.1136/jitc-2024-010787", "publisher_url": null, "pmid": "40010763", "pmcid": "PMC11865799", "openalex_id": "https://openalex.org/W4407984543", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/b4galt2.bib", "citation_ris_url": "https://drgezhang.com/citations/b4galt2.ris", "citation_csl_json_url": "https://drgezhang.com/citations/b4galt2.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "A PTM-related expression score stratified retrospective LUAD prognosis across discovery and GEO cohorts.", "context": "TCGA discovery and six GEO retrospective reapplications; selecting models by validation-set C-index may yield optimistic model ranking.", "evidence": [ { "label": "Development", "value": "TCGA-LUAD" }, { "label": "GEO prognosis evaluation", "value": "6 cohorts" }, { "label": "Algorithm selection", "value": "Stepcox (both) + SuperPC; mean C-index across evaluated cohorts" }, { "label": "Feature discovery", "value": "31 survival-associated PTM-related genes" } ], "source_locator": "PMC11865799: Methods Multi-source data integration (s2-1), Identification and evaluation of a PTMLS (s2-2); Results PTMLS development (s3-2) and Clinical validation (s3-3); Figures 3–4. Figure 2 interpretation must use correction DOI 10.1136/jitc-2024-010787corr1.", "source": "data/deep_geo/b4galt2.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/b4galt2.html#kf1" }, { "id": "KF2", "claim": "Lower PTMLS scores were associated with immune-signature and retrospectively observed treatment-response patterns.", "context": "Computational immune deconvolution and heterogeneous treatment cohorts do not establish a treatment-selection assay or prospective response prediction.", "evidence": [ { "label": "LUAD immunotherapy series described", "value": "OAK, POPLAR and NG" }, { "label": "Immune-score trend", "value": "Lower PTMLS generally showed higher estimated lymphocyte and immune-score signatures" }, { "label": "Clinical boundary", "value": "Retrospective association across heterogeneous regimens and cancers" } ], "source_locator": "PMC11865799: Results PTMLS: a novel prognostic and immunotherapy response predictor (s3-2); PTMLS as a determinant of tumor immune landscape (s3-6); Figures 3I–T, 5A–F; supplemental Figure S1.", "source": "data/deep_geo/b4galt2.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/b4galt2.html#kf2" }, { "id": "KF3", "claim": "B4GALT2 expression correlated with the PTMLS and unfavorable retrospective prognostic patterns.", "context": "Correlation and reported Kaplan–Meier analyses are observational, not a multivariable causal effect or proof of direct immunosuppression.", "evidence": [ { "label": "B4GALT2–PTMLS correlation", "value": "Reported r=0.82" }, { "label": "Reported survival association", "value": "HR 1.62, 95% CI 1.36–1.92 in the article-reported analysis" }, { "label": "Immune marker association", "value": "Inverse associations with CD8A expression" } ], "source_locator": "PMC11865799: Results B4GALT2: a key determinant in LUAD progression and immune response (s3-7); Figure 6A–Q.", "source": "data/deep_geo/b4galt2.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/b4galt2.html#kf3" }, { "id": "KF4", "claim": "The institutional tissue cohort associated high B4GALT2 expression with an immune-desert CD8 distribution phenotype.", "context": "Archival observational immunohistochemistry measures spatial phenotype and survival association; 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CD44/CD69/GZMB" } ], "source_locator": "PMC11865799: Methods Cell Culture and Lentiviral Transfection (s2-7), Mouse model for immune response assessment (s2-11); Results B4GALT2 role in immune regulation (s3-9), B4GALT2 inhibition potentiates anti-PD-1 (s3-10); Figures 8C–J and 9A–B.", "source": "data/deep_geo/b4galt2.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/b4galt2.html#kf5" } ], "field_entry": [ "Lung adenocarcinoma immunology", "Molecular prognostic modeling" ], "review_topics": [ "B4GALT2 and immune exclusion", "Post-translational modification signatures" ], "concepts": { "disease_and_immunity": [ "Lung adenocarcinoma", "CD8 spatial exclusion", "Immune-desert phenotype" ], "molecular_and_models": [ "B4GALT2", "Post-translational modification signature", "Stepcox and SuperPC" ], "evidence_and_intervention": [ "Archival pathology cohort", "Mouse anti-PD-1 combination", "Published Figure 2 correction" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Retrospective multi-series expression modeling with computational immunotherapy associations, institutional LUAD tissue immune phenotyping and in-vitro/in-vivo B4GALT2 perturbation.", "evidence_type": "Human retrospective transcriptomic and pathological association plus mouse and cell-line intervention experiments.", "population": "TCGA LUAD discovery; six GEO LUAD prognosis series; additional mixed-cancer immunotherapy cohorts; 171 institutional LUAD archival tumor specimens; GSE207422 single-cell specimens.", "primary_endpoint": "Association between PTMLS expression score and retrospective LUAD survival across cohorts.", "secondary_endpoint": "Immune-cell distribution and B4GALT2 expression associations; treatment-response dataset analyses; proliferation and anti-PD-1 readouts in experimental systems.", "data_modalities": [ "Bulk LUAD expression and survival series", "Clinical immunotherapy cohorts across tumor types", "LUAD FFPE multiplex tissue imaging", "Single-cell transcriptomic data", "LUAD cell-line growth assays", "Immunocompetent mouse tumor studies and flow cytometry" ], "external_validation": true, "scale_metrics": [ { "label": "Discovery/validation", "value": "TCGA-LUAD plus six GEO LUAD series" }, { "label": "Independent institutional tissue series", "value": "171 archived LUAD patients in Figure 7 cohort" }, { "label": "Single-cell data", "value": "GSE207422 reported 15 specimens" }, { "label": "Signature feature context", "value": "31 prognostic PTM-related genes considered in model construction" }, { "label": "Intervention species", "value": "LLC-cell mouse tumor model with anti-PD-1 treatment" } ], "counting_note": "TCGA, GEO, treatment cohorts, single-cell specimens, 171 institutional patients and mice are distinct scales and not combined into a unique-patient total. Methods and Figure 8 caption report incompatible LLC inoculation cell numbers; neither is promoted as a verified dose." }, "study_profile_source": "data/deep_geo/b4galt2.json#/study_profile", "model_profile": { "model_name": "Post-translational modification learning signature (PTMLS)", "algorithm_selection": "Stepcox (both) + SuperPC, selected by the reported mean validation-set C-index", "development": "TCGA-LUAD retrospective expression and survival", "evaluation": "Six GEO LUAD survival datasets and separate mixed-cancer treatment series", "clinical_boundary": "No prospective score-guided immune checkpoint therapy trial or independently validated clinical deployment." }, "model_profile_source": "data/deep_geo/b4galt2.json#/model_profile", "narrative_genre": null, "gold_source": "data/deep_geo/b4galt2.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/b4galt2.json", "gold_content_sha256": "939db7daa990b5836cdfe4c1bb97684a4c618762aa6d3c8933df25f94ad78bee", "provenance": { "doi_url": "https://doi.org/10.1136/jitc-2024-010787", "publisher_url": "https://jitc.bmj.com/content/13/2/e010787", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11865799/", "pmcid": "PMC11865799", "correction_doi_url": "https://doi.org/10.1136/jitc-2024-010787corr1", "correction_pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12164647/", "license": "Main article CC BY-NC 4.0. Official correction notice has separate restrictive re-use terms; corrected figures are referenced rather than republished.", "license_url": "https://creativecommons.org/licenses/by-nc/4.0/", "source_of_truth": "Journal for ImmunoTherapy of Cancer 2025;13(2):e010787; main PMC11865799 VOR JATS and Figure 2 official correction DOI 10.1136/jitc-2024-010787corr1 (12 June 2025).", "source_record_notes": "Original/revised Figure 2 and official correction HTML supplied privately. The evidence page does not reproduce protected correction figure assets.", "identity_note": "Existing bibliography is preserved. The Ge Zhang coauthor is not to be conflated with the initials GZ used for another equal-contributing author; coauthor ORCID across two papers remains inconsistent.", "numerical_discrepancy": "Mouse LLC inoculum is 2×10^5 in Methods versus 1×10^6 in Figure 8H caption; not harmonized." }, "scientific_role": "Retrospective PTM-expression signature research with LUAD tissue immune phenotyping and mouse B4GALT2 perturbation.", "evidence_position": "Retrospective human association and preclinical intervention; no established human anti-PD-1 treatment benefit.", "related_concepts": [ "Immune-desert CD8 phenotype", "PTMLS", "Correction to Figure 2" ], "citation_contexts": [ "Reviews separating tissue immune-exclusion associations from preclinical gene-suppression and anti-PD-1 experiments.", "Methods reviews of PTM-related LUAD signatures with explicit attention to the published correction." ], "evidence_scope": { "supports": [ "Retrospective PTMLS/B4GALT2 associations with LUAD survival and tumor immune patterns.", "An association between B4GALT2 staining and CD8 spatial phenotypes in institutional tissue specimens.", "Preclinical effects of B4GALT2 knockdown and anti-PD-1 treatment in the described experimental mouse model." ], "does_not_establish": [ "Prospective clinical response prediction or better human patient outcomes from using PTMLS.", "Causal mediation of immune exclusion in human LUAD from observational staining patterns.", "Proven clinical efficacy or safety of inhibiting B4GALT2 alongside immune checkpoint blockade.", "A definitive LLC inoculum count because Methods and Figure 8 legend disagree.", "Original uncorrected Figure 2 heatmap as a current scientific source." ] }, "limitations": [ "A published correction replaced the original Figure 2 differential-gene heatmap. 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Results 3.1; Fig. 1", "source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#kf1" }, { "id": "KF2", "claim": "TCPSLevel was associated with clinical and outcome differences.", "context": "Expression-score construction and retrospective association.", "evidence": [ { "label": "Expression bins", "value": "100" }, { "label": "Background samplings", "value": "1,000" }, { "label": "Reported survival cutoff", "value": "0.4" } ], "source_locator": "Methods 2.4; Results 3.2; Fig. 2", "source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#kf2" }, { "id": "KF3", "claim": "The ensemble analysis yielded three molecular subtypes.", "context": "Consensus framework selection and external NTP evaluation.", "evidence": [ { "label": "Candidate combinations", "value": "20" }, { "label": "Selected combination", "value": "CV-PAM" }, { "label": "Reported external NTP datasets", "value": "6" } ], "source_locator": "Methods 2.6-2.7; 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Results 3.7; Fig. 5K-N", "source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#kf5" }, { "id": "KF6", "claim": "ASPH was evaluated in human tissues and through TPC-1 silencing.", "context": "Human tissue association and separate cultured-cell perturbation.", "evidence": [ { "label": "Tumor specimens", "value": "48" }, { "label": "Adjacent specimens", "value": "48" }, { "label": "TPC-1 silencing", "value": "Reduced proliferation and migration" } ], "source_locator": "Methods: tissue and cell experiments; Results 3.6 and 3.8; Fig. 6", "source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#kf6" }, { "id": "KF7", "claim": "IPS and CMap supplied candidate immune/drug-response hypotheses.", "context": "Computational treatment-related hypothesis generation.", "evidence": [ { "label": "Evidence", "value": "Computational scoring and signature matching" } ], "source_locator": "Methods 2.10 and 2.20; 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no reason for excluding the numerical difference is inferred. Methods reports 17,709 cells and Results 17,518, without a reconstructed QC-exclusion process. One reported donor is not a large participant cohort; 48 tumor and 48 adjacent specimens do not mean 96 independent patients. Cohorts, cells, paired specimens and cultured-cell experiments are not added into a unique-participant total. 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Unavailable supplementary or figure-only details are not reconstructed." }, "scientific_role": "Stage-associated network and molecular-subtype analysis with external classifier evaluation and separate ASPH tissue and cell follow-up.", "evidence_position": "Public transcriptomics, human tissue observations and cell experiments; not physiological circadian measurement, individual transition-time prediction or clinical drug efficacy.", "related_concepts": [ "Network-based cancer subtyping", "Classifier versus outcome evidence" ], "citation_contexts": [ "Methods: expression-network approaches to thyroid-cancer heterogeneity.", "Evidence synthesis: computational subtype characterization alongside candidate experimental follow-up, without treating a subtype classifier as a survival model." ], "evidence_scope": { "supports": [ "Stage II had the highest reported network instability signal.", "TCPSLevel was associated with clinical and outcome differences.", "The ensemble analysis yielded three molecular subtypes.", "miniPC classified the consensus subtype labels using a compact gene set.", "Single-cell analysis localized expression patterns across cellular compartments.", "ASPH was evaluated in human tissues and through TPC-1 silencing.", "IPS and CMap supplied candidate immune/drug-response hypotheses." ], "does_not_establish": [ "Longitudinal prediction of an individual patient's transition time.", "Clinical intervention benefit.", "miniPC as an established survival model rather than a subtype classifier.", "Cell counts as patient counts or paired-specimen counts as independent participants.", "Complete demonstration of direct ASCL2 regulation or binding.", "Clinical efficacy of CMap-nominated compounds.", "Classification of this study as a physiological circadian-rhythm experiment.", "Resolution of all Methods/Results counts or accession differences." ] }, "limitations": [ "TCGA counts of 544 in Methods and 484 in GRN analysis describe different reported analytical stages; no reason for excluding the numerical difference is inferred. Methods reports 17,709 cells and Results 17,518, without a reconstructed QC-exclusion process. One reported donor is not a large participant cohort; 48 tumor and 48 adjacent specimens do not mean 96 independent patients. Cohorts, cells, paired specimens and cultured-cell experiments are not added into a unique-participant total. External validation means retrospective expression-template/classifier evaluation, not prospective clinical utility.", "Cross-sectional stage comparisons do not establish longitudinal prediction of each patient's future deterioration time.", "The reported cutoff is not a cross-cohort locked clinical threshold. Grouping rules used in other analyses are not automatically equivalent.", "Methods 2.6 prints GSE333630 whereas other locations use GSE33630. These are not silently rewritten as a fully verified accession inventory.", "This is subtype classification, not prospective individual survival-benefit validation. 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IPS is not an observed outcome in patients receiving immunotherapy.", "Longitudinal prediction of an individual patient's transition time.", "Clinical intervention benefit.", "miniPC as an established survival model rather than a subtype classifier.", "Cell counts as patient counts or paired-specimen counts as independent participants.", "Complete demonstration of direct ASCL2 regulation or binding.", "Clinical efficacy of CMap-nominated compounds.", "Classification of this study as a physiological circadian-rhythm experiment.", "Resolution of all Methods/Results counts or accession differences." ], "scope_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/evidence_scope" }, { "id": "doi-10-1200-po-24-00875", "title": "Reply to: Addressing Bias in Feature Importance: A Hybrid Approach for Risk Prediction in Prognostic Survival Models", "doi": "10.1200/po-24-00875", "year": 2025, "journal": "JCO Precision Oncology", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00875.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00875.md", "paper_geo_status": "v2", "authors": [ "Ge Zhang", "Shiqian Zhang", "Haonan Zhang", "Ruhao Wu", "Haoze Zheng" ], "doi_url": "https://doi.org/10.1200/po-24-00875", "publisher_url": null, "pmid": "39787464", "pmcid": null, "openalex_id": "https://openalex.org/W4406202665", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1200-po-24-00875.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1200-po-24-00875.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1200-po-24-00875.csl.json", "evidence_status": "reviewed_v2", "question_count": 4, "key_findings": [ { "id": "KF1", "claim": "The reply describes the breadth of the authors' earlier hybrid modeling framework.", "context": "A retrospective account of previous work, not a new model-comparison experiment in this correspondence.", "evidence": [ { "label": "learners", "value": "12" }, { "label": "candidate modeling schemes", "value": "132" } ], "source_locator": "Reply PDF-text rendition p. 1, opening paragraph; reference 2 on p. 2 identifies the original proctectomy study.", "source": "data/deep_geo/doi-10-1200-po-24-00875.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00875.html#kf1" }, { "id": "KF2", "claim": "The authors explain a consensus selection strategy using average concordance across validation techniques.", "context": "Their stated rationale for scheme selection; no new C-index value or independent validation cohort is reported here.", "evidence": [ { "label": "selection criterion described", "value": "Average concordance index across validation techniques" } ], "source_locator": "Reply PDF-text rendition p. 1, paragraph on consensus evaluation following the ensemble-learning discussion.", "source": "data/deep_geo/doi-10-1200-po-24-00875.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00875.html#kf2" }, { "id": "KF3", "claim": "The reply discusses SHAP as its approach to interpreting feature contributions.", "context": "An explanation of the authors' interpretability choice; it does not establish causal effects or experimentally demonstrate freedom from bias.", "evidence": [ { "label": "interpretation method", "value": "Shapley Additive Explanation (SHAP)" } ], "source_locator": "Reply PDF-text rendition pp. 1-2, paragraph addressing feature-importance bias, continuing after the p. 1 corresponding-author footer.", "source": "data/deep_geo/doi-10-1200-po-24-00875.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00875.html#kf3" } ], "field_entry": [ "Survival prediction methodology", "Clinical machine learning interpretation" ], "review_topics": [ "Hybrid model-selection rationale", "Feature-importance criticism and replies" ], "concepts": { "fields": [ "clinical prediction methodology" ], "methods": [ "hybrid survival modeling", "consensus model selection", "SHAP" ], "concepts": [ "feature importance", "concordance index", "interpretability", "overfitting" ] }, "profile_type": "narrative_review", "study_profile": { "profile_type": "narrative_review", "narrative_genre": "correspondence", "study_design": "Methodological reply concerning prior prognostic modeling", "evidence_type": "Author explanation and defense of prior methods", "translation_scope": "Model-development and interpretability discussion; not new clinical validation", "evidence_domains": [ "hybrid survival modeling", "model selection", "feature-importance interpretation" ], "diseases_covered": [ "rectal cancer" ], "scale_metrics": [ { "label": "learners described from prior work", "value": "12" }, { "label": "candidate schemes described from prior work", "value": "132" }, { "label": "new cohort reported in the reply", "value": "None" } ], "counting_note": "Learners and schemes are methodological units from prior work, not independent cohorts or additional patients." }, "study_profile_source": "data/deep_geo/doi-10-1200-po-24-00875.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": "correspondence", "gold_source": "data/deep_geo/doi-10-1200-po-24-00875.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1200-po-24-00875.json", "gold_content_sha256": "49fff6289050d3d3a094abfc0cb1d717d69e53ef5c80d1911ad9ce434ec35bb4", "provenance": { "publisher_url": "https://ascopubs.org/doi/10.1200/PO-24-00875", "doi_url": "https://doi.org/10.1200/PO-24-00875", "identity_url": "https://pubmed.ncbi.nlm.nih.gov/39787464/", "full_text_url": "https://www.researchgate.net/publication/387871458_Reply_to_Addressing_Bias_in_Feature_Importance_A_Hybrid_Approach_for_Risk_Prediction_in_Prognostic_Survival_Models", "evidence_basis": "The complete two-page typeset reply, including five-author signature, DOI and January 9, 2025 publication footer, was read from Ge Zhang's public ResearchGate upload. Identity matches the PubMed record; the publisher-hosted full text was not available.", "version": "Typeset ASCO correspondence text uploaded by Ge Zhang on January 11, 2025; accessed October 26, 2026 through its HTML rendition. PDF binary not retrieved.", "figure_verification": "The two-page reply contains no figures, tables or new experimental results." }, "scientific_role": "Author response explaining methodological choices in earlier studies.", "evidence_position": "Methodological argument; separate from the primary retrospective validation evidence.", "related_concepts": [ "Ensemble learning", "Concordance-based selection", "SHAP attribution" ], "citation_contexts": [ "Discussion of the authors' rationale for comparing hybrid modeling schemes.", "Review of methodological debate about feature-importance interpretation in prognostic models." ], "evidence_scope": { "supports": [ "Attribution of the authors' model-selection rationale and interpretability arguments.", "Literature discussion of how this team responded to criticism of earlier survival models." ], "does_not_establish": [ "A new cohort, performance estimate or prospective clinical validation.", "Proof that SHAP eliminates feature-importance bias or yields causal explanations.", "Universal superiority of hybrid ensembles or improved patient survival from model use." ] }, "limitations": [ "The reply's claims about robustness and generalizability are author arguments; they are not new empirical validation.", "The original proctectomy article is the source for sample sizes, performance estimates and external-validation limits.", "The complete author-uploaded typeset text was accessible through ResearchGate; the PDF binary and publisher-hosted full text were not retrieved." ], "scope_source": "data/deep_geo/doi-10-1200-po-24-00875.json#/evidence_scope" }, { "id": "doi-10-3389-fonc-2025-1538574", "title": "Resolving tumor microenvironment heterogeneity to forecast immunotherapy response in triple-negative breast cancer through multi-scale analysis", "doi": "10.3389/fonc.2025.1538574", "year": 2025, "journal": "Frontiers in Oncology", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html", "markdown_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.md", "paper_geo_status": "v2", "authors": [ "Shihao Sun", "Shuang Chen", "Kaiyuan Li", "Ge Zhang", "Nan Wang", "Yijia Xu", "Xinxing Wang", "Jiangrui Chi", "Lin Li", "Yi Sun" ], "doi_url": "https://doi.org/10.3389/fonc.2025.1538574", "publisher_url": null, "pmid": "40904511", "pmcid": "PMC12401915", "openalex_id": "https://openalex.org/W4413303258", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-3389-fonc-2025-1538574.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-3389-fonc-2025-1538574.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-3389-fonc-2025-1538574.csl.json", "evidence_status": "reviewed_v2", "question_count": 7, "key_findings": [ { "id": "KF1", "claim": "The TNBC single-cell series revealed BRCA1-associated differences in annotated tumor immune and stromal states.", "context": "Observed four versus four specimens allow exploratory group comparison; 32,386 cells are nested within eight donors and are not independent patients.", "evidence": [ { "label": "TNBC samples", "value": "4 BRCA1-MT and 4 BRCA1-WT" }, { "label": "QC-retained cells", "value": "32,386; 18,182 mutant-group and 14,204 wild-type-group" }, { "label": "Broad annotated lineages", "value": "7 principal populations" } ], "source_locator": "PMC12401915: Methods Data acquisition and processing (s2_1); Results The single-cell atlas of BRCA1 MT and BRCA1 WT samples (s3_1); Figure 1A–D.", "source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#kf1" }, { "id": "KF2", "claim": "T-cell exhaustion and dendritic/macrophage-associated expression programs differed by BRCA1 group.", "context": "State labels and inferred scores are descriptive transcriptomic signatures; lineage transitions and immunotherapy effectiveness cannot be inferred directly.", "evidence": [ { "label": "Comparison", "value": "BRCA1-WT versus BRCA1-MT single-cell specimens" }, { "label": "CD4/CD8 states", "value": "Treg, Tex and other computationally annotated subsets" }, { "label": "Intercellular readouts", "value": "Pseudotime and inferred spatial signaling, not direct lineage tracing" } ], "source_locator": "PMC12401915: Results T cells in BRCA1-WT specimens (s3_2); Activated TAMs and tolerogenic DCs (s3_3); Figures 2–3 and supplemental Figures S3–S5.", "source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#kf2" }, { "id": "KF3", "claim": "Distinct CAF states and ISG15-associated molecular programs were prioritized using multi-modal data.", "context": "Relative enrichment, pseudotime, spatial co-localization and proteomic associations do not prove BRCA1 regulates CAF differentiation through a causal ISG15 pathway.", "evidence": [ { "label": "CAF state trend", "value": "myCAF associated with BRCA1-WT; iCAF associated with BRCA1-MT" }, { "label": "Spatial observation", "value": "4 BRCA1-WT spatial samples, not a direct genotype-matched spatial comparison" }, { "label": "Paired proteomics", "value": "9 tumor/adjacent-tissue pairs" }, { "label": "Marker", "value": "ISG15 associated with myCAF enriched signatures" } ], "source_locator": "PMC12401915: Results BRCA1-driven CAF reprogramming (s3_6), Multi-scale analysis pinpointed ISG15 (s3_8), ISG15-driven predictor (s3_9); Figures 5–8; Methods high-sensitivity label-free proteomics (s2_11) and supplied DataSheet1.doc Supplementary Methods.", "source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#kf3" }, { "id": "KF4", "claim": "The ICI response classifier showed modest retrospective discrimination in treatment cohorts from other cancers.", "context": "The held-out subsets come from a mixed-cancer model-selection pipeline; the study states it lacks an ICI-treated TNBC validation cohort.", "evidence": [ { "label": "Pooled cohort definition", "value": "Four cohorts combining to 661 records for 80:20 model development/evaluation" }, { "label": "Chosen approach", "value": "K-nearest neighbors, selected among the models by validation performance" }, { "label": "Validation ROC AUC", "value": "0.60 (95% CI 0.51–0.69)" }, { "label": "Testing ROC AUC", "value": "0.61 (95% CI 0.51–0.71)" } ], "source_locator": "PMC12401915: Methods Reconstruction of the ICI response predictor (s2_10); Results Construction of an ISG15-driven predictive system (s3_9); Figure 8D–G. Paper text inconsistency: Methods mentions 13 cohorts (n=829); Results mentions 12.", "source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#kf4" }, { "id": "KF5", "claim": "High predicted response group correlated with immune-signature and selected survival patterns but does not establish TNBC treatment benefit.", "context": "The correlation in METABRIC is not treated ICI response and the TCGA TNBC survival comparison did not reach nominal significance.", "evidence": [ { "label": "METABRIC overall survival", "value": "Reported nominal P<0.05 by predicted response group" }, { "label": "TCGA TNBC overall survival", "value": "P=0.182; not statistically significant" }, { "label": "TIDE interpretation", "value": "Computational exclusion and dysfunction estimates, not observed ICI response" } ], "source_locator": "PMC12401915: Results Construction of an ISG15-driven predictive system for ICI response (s3_9); Figure 8H–K; Discussion (s4), paragraph explicitly stating no ICI-treated TNBC validation.", "source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#kf5" } ], "field_entry": [ "Breast cancer single-cell genomics", "Immunotherapy response modeling" ], "review_topics": [ "BRCA1-associated TNBC microenvironment", "ISG15 and cancer-associated fibroblasts" ], "concepts": { "disease_and_cells": [ "Triple-negative breast cancer", "BRCA1 mutation status", "Cancer-associated fibroblasts" ], "omics_and_biomarkers": [ "Single-cell and spatial transcriptomics", "Paired tissue proteomics", "ISG15" ], "prediction_scope": [ "Cross-cancer KNN response model", "AUC approximately 0.61", "No treated TNBC validation" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Retrospective single-cell TNBC group comparison, spatial reference mapping, bulk expression/network prioritization, paired in-house tissue proteomics and secondary immunotherapy-response classifier development.", "evidence_type": "Human multi-modal observational molecular association with a mixed-cancer retrospective treatment-response model; no experimental causal gene perturbation.", "population": "Eight BRCA1-defined TNBC single-cell specimens; four BRCA1-WT TNBC spatial samples; independently collected 9 paired breast tumor/adjacent tissues; mixed-cancer ICI-response expression cohorts for model training/testing.", "primary_endpoint": "Differences in single-cell and spatially inferred tumor immune/stromal programs across BRCA1 status.", "secondary_endpoint": "ISG15/myCAF association and retrospective response-model discrimination in cross-cancer ICI cohorts.", "data_modalities": [ "TNBC single-cell RNA sequencing", "Spatial RNA expression reference mapping", "Bulk expression, coexpression and pathway analysis", "Paired tissue label-free proteomics", "Cross-cancer ICI transcriptomic response modeling" ], "external_validation": false, "scale_metrics": [ { "label": "TNBC single-cell donors", "value": "8 specimens: 4 BRCA1-mutant and 4 BRCA1 wild-type" }, { "label": "Cells after QC", "value": "32,386; 18,182 BRCA1-mutant and 14,204 BRCA1 wild-type" }, { "label": "Spatial specimens", "value": "4 BRCA1-WT TNBC spatial samples; no matched BRCA1-MT spatial series in this analysis" }, { "label": "Paired proteomics", "value": "9 tumor samples and 9 corresponding para-tumor specimens; nine pairs, not 18 independent patients" }, { "label": "ICI model pooled subset", "value": "Four external treatment cohorts pooled to 661 records and divided 80:20 internally" }, { "label": "KNN classifier discrimination", "value": "Reported validation AUC 0.60 (95% CI 0.51–0.69); testing AUC 0.61 (95% CI 0.51–0.71)" } ], "counting_note": "Cell profiles, donor tumor specimens, spatial samples, paired proteomic tissues and external cross-cancer treated cohorts are distinct counting units and may involve overlaps or subsets. The article inconsistently describes 13 ICI pre-treatment cohorts (829 records) in Methods versus 12 in Results; no unsupported sum or cohort count is promoted." }, "study_profile_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/study_profile", "model_profile": { "model_name": "ISG15-related ICI-response classifier", "model_family": "K-nearest neighbors selected among evaluated learners", "development": "Mixed-cancer external ICI response cohorts, principal pooled set n=661", "evaluation": "Within-pool 80:20 development split; reported AUC 0.60 validation and 0.61 testing", "clinical_boundary": "No independent treated TNBC response cohort; not suitable as a validated TNBC treatment-selection test." }, "model_profile_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/model_profile", "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-3389-fonc-2025-1538574.json", "gold_content_sha256": "f15ac4ea402e992c67a455fc72d22261b65479de41b585ff7aefa0bc01e2e9e0", "provenance": { "doi_url": "https://doi.org/10.3389/fonc.2025.1538574", "publisher_url": "https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2025.1538574/full", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC12401915/", "pmcid": "PMC12401915", "license": "Article-level CC BY 4.0 in PMC/Frontiers. 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The eleven-author order, title, DOI and Letter to the Editor designation match the publisher record. Publisher first publication is August 16, 2025; later issue pagination is 270-271.", "version": "Online-first Wiley typeset text (2025; 0:1-2), uploaded by Zhengrui Li August 17, 2025; accessed October 26, 2026 in HTML. PDF binary and later issue PDF not retrieved.", "figure_verification": "No figure, table or original experimental dataset appears in the reviewed two-page letter." }, "scientific_role": "Conceptual letter outlining three care strategies and implementation constraints.", "evidence_position": "Author proposals supported by cited background; no original astronaut or robotics experiment.", "related_concepts": [ "Tele-dentistry", "3D fabrication", "Microgravity robotics" ], "citation_contexts": [ "Attribution of the three-part space-dentistry proposal.", "Discussion of untested technology adaptations and communication constraints in long-duration missions." ], "evidence_scope": { "supports": [ "Attribution of the three proposed strategies and acknowledged operational constraints.", "Discussion of research needs for adapting terrestrial dental technologies to spaceflight." ], "does_not_establish": [ "Improved oral health or fewer mission interruptions in astronauts.", "Safe or effective autonomous dental treatment in microgravity.", "Validated performance of remote guidance, 3D fabrication or AI robotics during space missions." ] }, "limitations": [ "The letter offers proposals rather than comparative clinical or engineering validation.", "Health concerns and technology examples derive from cited sources, not original observations in this letter.", "The reviewed text uses 2025 online-first pagination 1-2; the later issue record is Oral Diseases 32(1), 270-271 (2026). This is recorded as a version-pagination relationship, without changing the site's publication identity.", "Full text was read through the ResearchGate HTML rendition of the author-uploaded typeset version; the PDF binary and the later issue PDF were not retrieved." ], "scope_source": "data/deep_geo/doi-10-1111-odi-70054.json#/evidence_scope" }, { "id": "doi-10-2147-ijn-s522157", "title": "Targeted Delivery of Exosome-Derived miRNA-185-5p Inhibitor via Liposomes Alleviates Apoptosis and Cuproptosis in Dilated Cardiomyopathy", "doi": "10.2147/ijn.s522157", "year": 2025, "journal": "International Journal of Nanomedicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-2147-ijn-s522157.html", "markdown_url": "https://drgezhang.com/papers/doi-10-2147-ijn-s522157.md", "paper_geo_status": "v2", "authors": [ "Shuai Xu", "Yiyao Zeng", "Xin Tan", "Ge Zhang", "Anchen Xu", "Huimin Fan", "Fengyi Yu", "Zhen Qin", "Yahui Song", "Yufeng Jiang", "Xiangyu Wang", "Duoduo Zhang", "Yuxin Nong", "Dede Lian", "Junnan Tang", "Yafeng Zhou" ], "doi_url": "https://doi.org/10.2147/ijn.s522157", "publisher_url": "https://www.dovepress.com/targeted-delivery-of-exosome-derived-mirna-185-5p-inhibitor-via-liposo-peer-reviewed-fulltext-article-IJN", "pmid": "40755464", "pmcid": "PMC12315914", "openalex_id": "https://openalex.org/W4412693526", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-2147-ijn-s522157.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-2147-ijn-s522157.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-2147-ijn-s522157.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "The study characterized miR-185-5p-inhibitor-loaded liposomes functionalized with the reported heart-targeting peptide.", "context": "The carrier is a liposomal formulation; the candidate miRNA relationship to previous exosomal profiling does not make this an exosome-transfusion experiment.", "source_locator": "Methods: Lipo@miR-185-5p Inhibitor Preparation; Result and Discussion: Physicochemical Characterization of the Lipo@miR-185-5p Inhibitor Complex; Fig. 1", "evidence": [ { "label": "Targeting peptide", "value": "APWHLSSQYSRT" }, { "label": "Loaded-particle DLS diameter", "value": "172.35 ± 0.8 nm" }, { "label": "Encapsulation efficiency", "value": "98.0 ± 1.2%" }, { "label": "Reported release", "value": "Approximately 80% at 48 hours" }, { "label": "Size-method distinction", "value": "TEM describes approximately 100 nm; DLS reports hydrodynamic size" } ], "source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-2147-ijn-s522157.html#kf1" }, { "id": "KF2", "claim": "Peptide-functionalized liposomes produced greater cardiac fluorescence than the non-targeted comparator in the tested mouse biodistribution experiment.", "context": "Fluorescence localization supports distribution of the labeled preparation, not exclusive cardiac delivery or a directly quantified intact-drug tissue dose.", "source_locator": "Methods: Biodistribution of Liposome@CY5.5-Encapsulated miR-185-5p Inhibitor by in vivo Imaging System; Fig. 2A", "evidence": [ { "label": "Comparators", "value": "Lipo-HT versus Lipo-V" }, { "label": "Imaging times", "value": "2, 8, 12 and 24 hours" }, { "label": "Reported pattern", "value": "Greater cardiac fluorescence with the targeting peptide, especially at 8 and 12 hours" } ], "source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-2147-ijn-s522157.html#kf2" }, { "id": "KF3", "claim": "The loaded formulation improved reported echocardiographic readouts in the DOX-associated mouse cardiac injury model.", "context": "Animal intervention evidence only. 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MCC950 with ICIs.", "Independent biological replication from each of the 68,058 scRNA cells.", "Definitive attribution of all effects to one canonical NLRP3 pathway." ] }, "limitations": [ "The intervention evidence comes from tested preclinical melanoma models, with no human interventional cohort.", "The paper notes that ICI dose/frequency may exceed typical clinical dosing and calls for additional tumor models and clinical evaluation.", "Pooled cardiac single-cell samples limit interpretation of cell counts as biological replication.", "GSE180045 provides supportive human association, not independent validation of MCC950 treatment efficacy.", "The findings do not definitively attribute all effects to one canonical NLRP3 pathway." ], "scope_source": "data/deep_geo/nlrp3-ici.json#/evidence_scope" }, { "id": "doi-10-1093-eurheartj-ehaf523", "title": "The macrophage-derived motor protein KIF13B enhances MERTK-mediated efferocytosis and prevents atherosclerosis in mice", "doi": "10.1093/eurheartj/ehaf523", "year": 2025, "journal": "European Heart Journal", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.md", "paper_geo_status": "v2", "authors": [ "Yitong Xu", "Jingxuan Chen", "Yiran Liu", "Ge Zhang", "Guolin Miao", "Jingdong Wu", "Kaikai Lu", "Yinqi Zhao", "Wenxi Zhang", "Liwen Zheng", "Lianxin Zhang", "Jinxuan Chen", "Zihao Zhou", "Yufei Han", "Pingping Lai", "Jiabao Guo", "Donghui Wu", "Si Mei", "Ling Zhang", "Yang Zhao", "Wei Huang", "Yuhui Wang", "Junnan Tang", "Dongyu Zhao", "Xunde Xian" ], "doi_url": "https://doi.org/10.1093/eurheartj/ehaf523", "publisher_url": "https://academic.oup.com/eurheartj/advance-article/doi/10.1093/eurheartj/ehaf523/8212255", "pmid": "40709729", "pmcid": null, "openalex_id": "https://openalex.org/W4412654976", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1093-eurheartj-ehaf523.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1093-eurheartj-ehaf523.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1093-eurheartj-ehaf523.csl.json", "evidence_status": "reviewed_v2", "question_count": 8, "key_findings": [ { "id": "KF1", "claim": "KIF13B expression is lower in advanced human arterial and carotid lesions and in progressing mouse plaques.", "context": "Human findings are associative, not evidence that manipulating KIF13B changes human atherosclerosis.", "evidence": [ { "label": "GSE40231", "value": "40 non-atherosclerotic and 40 atherosclerotic arterial-wall samples showed lower KIF13B in atherosclerotic tissue." }, { "label": "Human carotid tissue", "value": "Early n=6 and advanced n=6 lesions showed lower KIF13B protein in advanced plaques, with macrophage co-localization." }, { "label": "Mouse progression", "value": "Ldlr-deficient mice, n=6 per group, showed lower plaque KIF13B after 20 versus 12 weeks of Western diet." } ], "source_locator": "Results: The expression of KIF13B is negatively correlated with the progression of atherosclerosis in patients and mice; Figure 1 and Supplementary Figure S1.", "source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#kf1" }, { "id": "KF2", "claim": "Global Kif13b loss worsened experimental atherosclerosis in Ldlr-deficient mice, but circulating lipids also increased in that model.", "context": "The global Ldlr-deficient comparison does not isolate a lipid-independent mechanism; Apoe-background observations did not show the same lipid effect.", "evidence": [ { "label": "Ldlr model", "value": "After 12 weeks of Western diet, control versus global Kif13b-deficient Ldlr-deficient mice had n=6 mice per group; lesions and circulating total cholesterol and triglycerides increased with Kif13b loss." }, { "label": "Plaque phenotype", "value": "Necrotic-core area rose up to approximately twofold, CD68-positive macrophage infiltration more than threefold, and apoptotic-cell accumulation increased." }, { "label": "Apoe background", "value": "Worsened plaques were also reported in the Apoe-deficient background without the same circulating-lipid change." } ], "source_locator": "Results: Deletion of Kif13b in Ldlr−/− mice exacerbates atherosclerosis; Figure 2 and Supplementary Figure S2.", "source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#kf2" }, { "id": "KF3", "claim": "Single-cell and macrophage analyses implicated altered macrophage states with lower Kif13b during experimental atherosclerosis.", "context": "The study-generated aortic single-cell comparison pooled five mice into one library per genotype; Results and Figure 3E disagree on diet duration, so no single definitive duration is assigned.", "evidence": [ { "label": "GSE155513", "value": "Figure 3 uses one single-cell library at each 8-week and 26-week high-fat-diet time point; macrophage abundance rose and Kif13b reduction was prominent in macrophages." }, { "label": "Study-generated single-cell", "value": "Five aortas were pooled per genotype into one library, yielding 14 clusters and eight cell types; Cd80-positive, Il1b-positive, Spp1-positive and Cd206-positive macrophage states were emphasized, with Kif13b loss associated with fewer Cd206-positive and more Il1b-positive and Spp1-positive states." }, { "label": "Independent observations", "value": "GSE215103 Apoe-deficient macrophage reanalysis and ox-LDL-treated BMDM and THP-1 experiments also showed lower KIF13B." } ], "source_locator": "Results: Kif13b deficiency primarily affects macrophage dynamics in mouse atherosclerosis; Figure 3.", "source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#kf3" }, { "id": "KF4", "claim": "Myeloid conditional deletion and Kif13b-deficient bone-marrow transfer worsened plaque phenotypes without corresponding plasma-lipid changes in their mouse models.", "context": "These results support a lipid-independent myeloid or hematopoietic contribution in the tested models, not a macrophage-exclusive or proven human causal effect.", "evidence": [ { "label": "Lyz2-Cre model", "value": "Kif13b-floxed controls n=9 versus Lyz2-Cre;Kif13b-floxed mice n=6 after AAV8-PCSK9 and 12 weeks of Western diet; lesions, necrotic core, macrophages and apoptotic cells increased without material total-cholesterol, triglyceride or lipoprotein differences." }, { "label": "Bone-marrow transfer", "value": "Ldlr-deficient recipients of control versus Kif13b-deficient donor marrow, n=6 per group after 12 weeks of Western diet, showed worse plaque outcomes without plasma-lipid change." } ], "source_locator": "Results: Myeloid-specific deletion of Kif13b aggravates atherosclerosis in a lipid-independent manner; Figure 4 and Supplementary Figures S3–S4.", "source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#kf4" }, { "id": "KF5", "claim": "Kif13b-deficient macrophages had impaired efferocytosis and reduced MERTK protein; restoring MERTK in deficient BMDMs improved efferocytosis.", "context": "The genetic rescue was a macrophage cell experiment, not a demonstrated in vivo MERTK therapy or human rescue.", "evidence": [ { "label": "Transcriptomics", "value": "Wild-type and knockout BMDM RNA-seq n=3 per group and apoptotic-cell co-incubation RNA-seq n=3 per group nominated efferocytosis pathways." }, { "label": "Functional phenotype", "value": "BMDM efferocytosis assays n=5 per group and MERTK immunofluorescence n=10 per group implicated lower MERTK among evaluated efferocytosis proteins; in vivo conditional and marrow-transfer models also had impaired efferocytosis." }, { "label": "MERTK restoration", "value": "MERTK restoration in Kif13b-deficient BMDMs improved efferocytosis; western blot n=3 per group and efferocytosis rescue n=10 per group." } ], "source_locator": "Results: Loss of Kif13b inhibits MERTK-mediated macrophage efferocytosis; Figure 5.", "source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#kf5" }, { "id": "KF6", "claim": "The KIF13B–ITCH–CBL–MERTK data support post-translational MERTK regulation, while the exact proposed ITCH-mediated CBL degradation step remains incompletely demonstrated.", "context": "CBL is the endogenous gene/protein investigated; CBLB is distinct. Unchanged Mertk mRNA argues against a transcriptional explanation of lower MERTK protein in this experiment.", "evidence": [ { "label": "MERTK turnover", "value": "Mertk mRNA was unchanged in compared BMDMs n=3 per group; in THP-1 knockdown cells MERTK protein fell to about 40% at 16 hours of cycloheximide chase." }, { "label": "Protein mechanism", "value": "Proteasome inhibitor MG132 at 10 µM, but not chloroquine at 10 µM, blocked MERTK loss; MERTK ubiquitination and CBL protein increased with KIF13B loss." }, { "label": "ITCH interaction and rescue", "value": "KIF13B and ITCH co-immunoprecipitated, ITCH fell with KIF13B loss, and ITCH overexpression in deficient BMDMs reversed higher CBL and lower MERTK; direct proof of each proposed ITCH-to-CBL degradation step is incomplete." }, { "label": "Human association", "value": "Advanced human plaque tissues n=6 per group showed lower KIF13B, ITCH and MERTK and higher CBL; this is associative." } ], "source_locator": "Results: KIF13B decreases CBL-mediated ubiquitination of MERTK by interacting with itch in macrophages; Figure 6.", "source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#kf6" }, { "id": "KF7", "claim": "NX-1607 improved MERTK and efferocytosis phenotypes in macrophages and reduced atherosclerotic phenotypes in mice; its target identity does not unambiguously validate endogenous CBL.", "context": "The article calls NX-1607 a CBL inhibitor, while external authoritative drug-development sources identify it as a CBL-B/CBLB inhibitor; CBL and CBLB are distinct genes. These are preclinical rescue results, not human atherosclerosis treatment efficacy.", "evidence": [ { "label": "Macrophage assays", "value": "NX-1607 at 50 nM increased MERTK in BMDMs; MERTK/CBL western blot n=3 per group, efferocytosis at DMSO, 50 and 100 nM n=10 per group, and 50 nM co-immunoprecipitation in three independent experiments were reported." }, { "label": "Mouse schedule and outcome", "value": "Ldlr-deficient and Kif13b-deficient Ldlr-deficient mice received 20 weeks total Western diet, with NX-1607 5 mg/kg/day only in the final 16 weeks, n=6 per group; plaque burden, necrotic core, macrophage and apoptotic-cell accumulation declined, and MERTK/efferocytosis increased without reported lipid change." }, { "label": "Safety and clinical boundary", "value": "ALT and AST showed no reported liver-toxicity signal in these mouse measurements, but white blood cells and lymphocytes declined; NCT05107674 is a Phase I advanced-malignancy trial, not an atherosclerosis trial." } ], "source_locator": "Results: The CBL inhibitor NX-1607 effectively ameliorates atherosclerosis by enhancing macrophage efferocytosis; Figure 7 and Supplementary Figures S6–S7.", "source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/key_findings/6", "evidence_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#kf7" } ], "field_entry": [ "Atherosclerosis research", "Innate immune vascular biology" ], "review_topics": [ "Macrophage efferocytosis in plaque", "Post-translational control of apoptotic-cell clearance" ], "concepts": { "conditions": [ "Atherosclerosis", "Advanced atherosclerotic plaque", "Plaque necrotic core", "Atherosclerotic lesion progression" ], "genes_and_proteins": [ "KIF13B", "MERTK", "ITCH", "CBL", "CBLB (distinct from CBL)", "SPP1", "IL1B", "CD68", "LYZ2", "LDLR", "APOE", "PCSK9" ], "cells_and_processes": [ "Myeloid cells", "Macrophages", "Bone-marrow-derived macrophages", "THP-1 macrophages", "Spp1-positive macrophages", "Cd206-positive macrophages", "Il1b-positive macrophages", "Cd80-positive macrophages", "Efferocytosis", "Apoptotic-cell clearance", "Protein ubiquitination", "Proteasomal degradation", "MERTK protein stability" ], "models_and_datasets": [ "Ldlr-deficient mouse", "Kif13b-deficient Ldlr-deficient mouse", "Apoe-deficient mouse", "Lyz2-Cre conditional deletion", "AAV8-PCSK9", "Bone-marrow transplantation", "Western diet", "High-fat diet", "ox-LDL", "GSE40231", "GSE155513", "GSE215103" ], "intervention": [ "NX-1607 preclinical intervention" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Mechanistic translational preclinical study combining associative human arterial and plaque observations with mouse atherosclerosis genetics, public and study-generated transcriptomics, macrophage experiments, genetic rescue and pharmacologic intervention.", "evidence_type": "Human tissue association; causal mouse and macrophage experiments; public dataset reanalysis; preclinical pharmacologic rescue.", "population": "Human arterial-wall and carotid-plaque tissue samples; Ldlr-deficient and Apoe-deficient mouse models; mouse bone-marrow-derived macrophages and THP-1 cells. No treated human atherosclerosis cohort.", "primary_endpoint": "Experimental atherosclerotic lesion burden and macrophage efferocytosis across genetic and pharmacologic models.", "secondary_endpoint": "Plaque necrotic core, macrophage and apoptotic-cell accumulation, circulating lipids, MERTK protein regulation and reported safety observations.", "data_modalities": [ "Human tissue expression and immunostaining", "Mouse plaque histology and plasma lipids", "Public and pooled aortic single-cell RNA sequencing", "BMDM RNA sequencing", "Macrophage efferocytosis and protein assays", "Genetic rescue and preclinical pharmacology" ], "external_validation": true, "scale_metrics": [ { "label": "GSE40231 arterial-wall samples", "value": "STAGE/CABG human dataset: 40 non-atherosclerotic arterial-wall samples and 40 atherosclerotic arterial-wall samples; these are sample counts, not 80 unique participants." }, { "label": "Human carotid lesion tissues", "value": "Early lesions n=6 and advanced lesions n=6." }, { "label": "Mouse plaque progression", "value": "Ldlr-deficient mice after Western diet for 12 or 20 weeks; n=6 mice per group." }, { "label": "Global Kif13b loss", "value": "Ldlr-deficient control and Kif13b-deficient Ldlr-deficient mice after 12 weeks of Western diet; n=6 mice per group." }, { "label": "Public single-cell GSE155513", "value": "Figure 3 describes n=1 single-cell library at each 8-week and 26-week dietary time point; do not treat library counts as mouse counts." }, { "label": "Study-generated aortic single-cell experiment", "value": "Five mice pooled into one single-cell library per genotype; the Results state 20 weeks of Western diet while Figure 3E states 12 weeks of high-fat diet." }, { "label": "Public macrophage single-cell GSE215103", "value": "Reanalysis of Apoe-deficient mouse peritoneal macrophages; no unique mouse or library count inferred here." }, { "label": "Myeloid conditional model", "value": "Kif13b-floxed controls n=9 versus Lyz2-Cre;Kif13b-floxed mice n=6, AAV8-PCSK9 and 12 weeks of Western diet." }, { "label": "Bone-marrow transplantation", "value": "Ldlr-deficient recipients of control or Kif13b-deficient donor marrow; n=6 mice per group after 12 weeks of Western diet." }, { "label": "BMDM transcriptomics", "value": "Wild-type versus Kif13b-deficient BMDMs n=3 per group, including apoptotic-cell co-incubation transcriptomics n=3 per group." }, { "label": "NX-1607 mouse intervention", "value": "Ldlr-deficient and Kif13b-deficient Ldlr-deficient mice, n=6 per group; 20 weeks total Western diet with 5 mg/kg/day NX-1607 only during the final 16 weeks." } ], "counting_note": "Counts have different denominators: human tissue samples, mice, pooled single-cell libraries, independent cultures or experiments. They cannot be summed as unique participants or independent biological replicates. Five mice pooled to one library per genotype are not five independent libraries; the generated single-cell experiment has conflicting Results and Figure 3E diet durations." }, "study_profile_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1093-eurheartj-ehaf523.json", "gold_content_sha256": "49f8ef3ea47de7f99adec0a505990341953c2e94acf1e0fbf5bcf69186334fbc", "provenance": { "doi": "10.1093/eurheartj/ehaf523", "pmid": "40709729", "publisher": "Oxford Academic, European Heart Journal", "publisher_url": "https://doi.org/10.1093/eurheartj/ehaf523", "version_of_record": "European Heart Journal 46(45):4969–4984; first published 25 July 2025.", "source_material": "Publisher version of record, Supplementary Methods and Supplementary Figures S1–S7; public datasets GSE40231, GSE155513 and GSE215103.", "data_availability": "The data underlying this article will be shared on reasonable request to the corresponding author.", "counting_note": "Human samples, mice, cultures and pooled single-cell libraries are separate denominators; no overall unique n is inferred.", "scrna_duration_note": "Study-generated aortic single-cell Results state 20 weeks of Western diet, whereas Figure 3E states 12 weeks of high-fat diet; five mice were pooled into one library per genotype. The discrepancy is not resolved here.", "nx_target_identity_note": "The article describes NX-1607 as a CBL inhibitor; external authoritative drug-development sources identify it as a CBL-B/CBLB inhibitor. CBL and CBLB are distinct genes. NX-1607 rescue does not unambiguously validate the endogenous CBL mechanism.", "clinical_context_note": "NCT05107674 is a Phase I study in advanced malignancies, not an atherosclerosis clinical trial; no human atherosclerosis treatment efficacy is established." }, "scientific_role": "Macrophage KIF13B mechanism study connecting MERTK regulation, efferocytosis and experimental atherosclerosis.", "evidence_position": "Mouse and macrophage perturbation and rescue experiments with associative human plaque observations; preclinical plaque protection, not proven human treatment efficacy.", "related_concepts": [ "Myeloid plaque biology", "Efferocytosis-regulatory mechanisms" ], "citation_contexts": [ "Background: defective apoptotic-cell clearance in atherosclerosis.", "Mechanistic evidence: experimental regulation of macrophage efferocytosis, distinct from VSMC KIF13B state remodeling." ], "evidence_scope": { "supports": [ "Association between lower KIF13B and advanced human arterial or carotid-plaque tissue, and progression in mouse plaque observations.", "Causal worsening of mouse plaque phenotypes after global, myeloid or hematopoietic Kif13b perturbation within their respective experimental models.", "A myeloid or hematopoietic contribution without corresponding plasma-lipid differences in conditional and transplantation models, separate from the lipid increase in global Ldlr-deficient knockout mice.", "Reduced MERTK protein and efferocytosis after Kif13b loss and improvement of BMDM efferocytosis following MERTK restoration.", "Evidence consistent with post-translational ITCH/CBL/MERTK regulation and article-reported NX-1607 rescue in macrophages and mice." ], "does_not_establish": [ "Human KIF13B causality, prediction of clinical outcomes or human atherosclerosis treatment efficacy.", "That the global Ldlr-deficient knockout plaque phenotype is lipid independent.", "Macrophage-exclusive effects of Lyz2-Cre deletion or bone-marrow transplantation, or five independent single-cell libraries from five pooled mice.", "One definitive diet duration for the study-generated pooled aortic single-cell comparison, because Results and Figure 3E disagree.", "That MERTK restoration is an effective in vivo or human therapy, or that every proposed ITCH-to-CBL ubiquitination and degradation step has been directly resolved.", "That NX-1607 reverses 20 weeks of established disease, has proven human atherosclerosis benefit, or unequivocally validates endogenous CBL rather than the distinct CBLB target described by external sources." ] }, "limitations": [ "Human arterial-wall and carotid-plaque results are associative tissue observations with small carotid groups, not causal human intervention evidence.", "The global Kif13b-deficient Ldlr model had higher circulating cholesterol and triglycerides, limiting attribution of its plaque phenotype solely to local plaque biology.", "Lyz2-Cre targets myeloid lineages and donor-marrow transplantation changes hematopoietic compartments; neither isolates macrophages exclusively.", "Study-generated single-cell data pooled five mice to one library per genotype, limiting independent biological replication at the library level.", "The Results and Figure 3E give discordant 20-week Western-diet and 12-week high-fat-diet descriptions for the pooled aortic single-cell experiment.", "GSE155513 Figure 3 time points use one single-cell library each; sample and library counts must not be conflated.", "MERTK restoration rescue was demonstrated in Kif13b-deficient BMDMs, not as an in vivo MERTK treatment.", "The exact ITCH-mediated CBL ubiquitination/degradation step in the proposed network remains incompletely demonstrated; MERTK regulation is not fully assigned to one mechanism.", "The article's CBL-inhibitor description of NX-1607 conflicts with external CBL-B/CBLB target identification, preventing unambiguous pharmacologic validation of endogenous CBL.", "NX-1607 was tested preclinically during the final 16 of 20 Western-diet weeks, not as reversal after 20 weeks of established disease; no human atherosclerosis efficacy was assessed.", "Mouse NX-1607 measurements found no reported ALT/AST liver-toxicity signal but did report lower white blood cells and lymphocytes, so safety is not established." ], "scope_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/evidence_scope" }, { "id": "doi-10-1002-tox-24284", "title": "Advancing predictive markers in lung adenocarcinoma: A machine learning-based immunotherapy prognostic prediction signature", "doi": "10.1002/tox.24284", "year": 2024, "journal": "Environmental Toxicology", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.md", "paper_geo_status": "v2", "authors": [ "Zhongyan Li", "Shengbin Pei", "Yanjuan Wang", "Ge Zhang", "Haoran Lin", "Shiyang Dong" ], "doi_url": "https://doi.org/10.1002/tox.24284", "publisher_url": null, "pmid": "38591820", "pmcid": null, "openalex_id": "https://openalex.org/W4394621029", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1002-tox-24284.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1002-tox-24284.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1002-tox-24284.csl.json", "evidence_status": "reviewed_v2", "question_count": 5, "key_findings": [ { "id": "KF1", "claim": "The reported IPPS contains 13 genes and uses Lasso plus SuperPC selected from 101 candidate combinations.", "context": "Retrospective development in TCGA-LUAD. Candidate-gene survival screening included TCGA and five GEO cohorts; selection of the final algorithm used the mean C-index in those same five GEO cohorts.", "evidence": [ { "label": "signature genes", "value": "13" }, { "label": "candidate combinations", "value": "101" }, { "label": "selected model", "value": "Lasso + SuperPC" } ], "source_locator": "Methods 2.2, author-uploaded publisher-layout pp. 2-3; Results 3.1-3.2, pp. 3-5; Figure 1D-E; Figure 2A.", "source": "data/deep_geo/doi-10-1002-tox-24284.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.html#kf1" }, { "id": "KF2", "claim": "The article reports TCGA training-cohort AUCs of 0.80, 0.79 and 0.78 for 1-, 3- and 5-year survival.", "context": "These are apparent performance estimates in the TCGA development cohort, not independent external or prospective validation. The GSE31210 text-versus-figure discrepancy is excluded from performance claims.", "evidence": [ { "label": "1-year TCGA AUC", "value": "0.80" }, { "label": "3-year TCGA AUC", "value": "0.79" }, { "label": "5-year TCGA AUC", "value": "0.78" } ], "source_locator": "Results 3.2, author-uploaded publisher-layout p. 5; Figure 2H, p. 4. Text and displayed TCGA panel agree.", "source": "data/deep_geo/doi-10-1002-tox-24284.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.html#kf2" }, { "id": "KF3", "claim": "The initial OAK/POPLAR comparison used overall-survival extremes and does not by itself establish an objective immunotherapy-response classifier.", "context": "Figure 1D and Results 3.1 define groups by survival greater than 12 months or less than 6 months, while labelling them CR/PR and PD/SD. Those labels must not be treated as verified RECIST response classifications.", "evidence": [ { "label": "longer-survival definition", "value": "overall survival >12 months" }, { "label": "shorter-survival definition", "value": "overall survival <6 months" } ], "source_locator": "Results 3.1 and Figure 1D, author-uploaded publisher-layout p. 3; compare Methods 2.1, p. 2.", "source": "data/deep_geo/doi-10-1002-tox-24284.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.html#kf3" }, { "id": "KF4", "claim": "The drug-sensitivity analysis generates computational treatment hypotheses rather than observations of drug benefit in patients.", "context": "The Methods names oncoPredict and pRRophetic, and Results 3.7 uses CTRP and PRISM drug-sensitivity resources. No new drug-treatment experiment is established by this analysis.", "evidence": [ { "label": "inference tools", "value": "oncoPredict and pRRophetic" }, { "label": "drug-response resources", "value": "CTRP and PRISM" } ], "source_locator": "Methods 2.4, author-uploaded publisher-layout pp. 2-3; Results 3.7, p. 7; Discussion, pp. 10-12. No compound-specific effect estimate is reproduced.", "source": "data/deep_geo/doi-10-1002-tox-24284.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.html#kf4" } ], "field_entry": [ "Computational oncology", "LUAD prognostic modeling" ], "review_topics": [ "Immune-associated transcriptomic signatures", "Validation leakage in molecular survival models" ], "concepts": { "conditions": [ "lung adenocarcinoma" ], "methods": [ "survival modeling", "Lasso", "supervised principal components", "time-dependent ROC analysis" ], "models_tools": [ "IPPS", "oncoPredict", "pRRophetic" ], "datasets": [ "TCGA-LUAD", "GSE13213", "GSE26939", "GSE30219", "GSE31210", "GSE42127", "OAK", "POPLAR" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Retrospective public-cohort gene screening and survival-model selection with computational immune and drug analyses", "evidence_type": "Retrospective transcriptomic associations and model-development performance", "population": "LUAD records from TCGA, five GEO datasets and an OAK/POPLAR-derived discovery comparison", "primary_endpoint": "Overall survival association and time-dependent discrimination", "secondary_endpoint": "Inferred immune infiltration, genomic associations and computational drug sensitivity", "data_modalities": [ "bulk transcriptomics", "clinical survival data", "mutation and copy-number data", "computational immune and drug-response estimates" ], "external_validation": false, "scale_metrics": [ { "label": "final signature genes", "value": "13" }, { "label": "candidate model combinations", "value": "101" }, { "label": "GEO cohorts used in screening and model selection", "value": "5" } ], "counting_note": "Methods 2.1 reports 577 LUAD cases from OAK/POPLAR, whereas Results 3.1 and Figure 1D describe a selected group of 296. The retrieved article does not fully reconcile those denominators; no pooled participant count is inferred. TCGA and five GEO cohorts entered survival-based gene screening, and the five GEO cohorts also determined model selection. They are distinct datasets, not independent held-out validation after model selection." }, "study_profile_source": "data/deep_geo/doi-10-1002-tox-24284.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1002-tox-24284.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1002-tox-24284.json", "gold_content_sha256": "b97978052377f9de3a26df30ab8729cc54307e821daba3f7b145a3535271718b", "provenance": { "publisher_url": "https://onlinelibrary.wiley.com/doi/10.1002/tox.24284", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/38591820/", "author_uploaded_fulltext_url": "https://www.researchgate.net/publication/379695827_Advancing_predictive_markers_in_lung_adenocarcinoma_A_machine_learning-based_immunotherapy_prognostic_prediction_signature", "figure1_url": "https://www.researchgate.net/figure/Comparative-Study-of-Immunotherapy-Cohorts-and-Model-Gene-Selection-A-The-volcano-plot_fig1_379695827", "figure2_url": "https://www.researchgate.net/figure/Model-Construction-and-Evaluation-A-Comparison-of-C-index-values-for-101-predictive_fig2_379695827", "version": "Author-uploaded publisher-layout early-online version, 2024, pp. 1-13, DOI 10.1002/tox.24284; Wiley download stamp 12 April 2024. The current publisher record lists Environmental Toxicology 39(10), 4581-4593, first online 9 April 2024.", "evidence_basis": "The complete article transcription through its references and final p. 13 footer was read on ResearchGate; Figures 1 and 2 were visually inspected on 26 October 2026. The formal title, ordered six-author list and DOI match the publisher record. The current issue PDF was not obtained, so complete byte-for-byte or post-pagination textual equivalence is not claimed.", "uploader": "Ge Zhang; ResearchGate author-content statement dated 14 April 2024.", "accessed_on": "2026-10-26", "acquired_format": "ResearchGate HTML full-text transcription and public figure-page screenshots; no PDF binary acquired.", "fulltext_transcription_sha256": "3f27b079adb01e49b923a198959cd57d96201251458c3c47bb0005cd3a22daee", "license": "Copyright 2024 Wiley Periodicals LLC. No open licence is asserted. Full text and screenshots are retained only in the private audit directory and are not distributed with the website.", "reporting_discrepancies": "OAK/POPLAR 577 versus selected 296; OS-defined CR/PR and PD/SD labels; GSE31210 AUC disagreement between Results 3.2 and Fig. 2L. These are disclosed without choosing an unsupported correction." }, "scientific_role": "A retrospective 13-gene model-development study with outcome-based screening, multi-algorithm selection and computational drug hypotheses.", "evidence_position": "Development and retrospective association evidence; no untouched external or prospective immunotherapy-benefit validation.", "related_concepts": [ "IPPS", "Outcome-based selection", "Computational drug sensitivity" ], "citation_contexts": [ "Methods reviews describing the Lasso plus SuperPC model selected from 101 algorithm combinations.", "Critical appraisal of cohort reuse, outcome-based immunotherapy sample selection and the distinction between prognostic AUCs and treatment-response evidence." ], "evidence_scope": { "supports": [ "Description of the reported 13-gene Lasso-plus-SuperPC development procedure and 101 candidate combinations.", "The text-and-figure-consistent TCGA training AUCs, explicitly labelled as apparent development-cohort performance.", "A source-based distinction between survival-defined discovery groups, prognostic modeling and computational drug-response inference." ], "does_not_establish": [ "An independently validated predictor of RECIST response or differential benefit from immunotherapy.", "Prospective clinical utility or improved outcomes from IPPS-guided treatment.", "Unbiased external performance after gene and algorithm selection using the same GEO cohorts.", "A reconciled OAK/POPLAR denominator or a resolved GSE31210 AUC estimate.", "Experimental drug efficacy or causal functions of the model genes." ] }, "limitations": [ "The study is retrospective. Survival-based gene selection used all six TCGA/GEO cohorts, and five GEO cohorts were reused to choose the algorithm. Their results cannot be treated as untouched external validation.", "Methods 2.1 states 577 OAK/POPLAR LUAD cases, while Results 3.1 and Figure 1D state a selected 296. The retrieved version does not sufficiently specify the full filtering relationship; no reconciled or pooled denominator is asserted.", "Results 3.1 and Figure 1D use OS >12 months and OS <6 months but name the groups CR/PR and PD/SD. Survival strata do not establish objective response categories or differential immunotherapy benefit.", "GSE31210 AUCs differ between Results 3.2 (0.67, 0.76, 0.72 at 1, 3, 5 years) and Figure 2L (0.67, 0.73, 0.75). Neither series is adopted as a verified performance estimate.", "The TCGA AUCs quoted here are apparent training-cohort estimates. Individual participant data and code were not reanalysed, and no uncertainty interval is invented.", "Drug-response analyses are computational. The Discussion uses experimental language, but Methods 2.4 and Results 3.7 describe inference from drug-sensitivity databases.", "The author-uploaded publisher-layout text was readable publicly on ResearchGate, and Figures 1 and 2 were visually checked there. Direct PDF download was blocked in this environment; the archived source fingerprint identifies the acquired web transcription, not PDF bytes. 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External evaluation refers only to the five human bulk-expression classifier datasets, not prospective clinical validation or resolved single-cell provenance. 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No raw-data reanalysis or independent reconstruction of the score." }, "scientific_role": "Retrospective gene-expression classifier and separate interpretability-score analysis for ulcerative colitis.", "evidence_position": "Public bulk-expression analysis with external dataset evaluation; the single-cell source remains unresolved, and prospective diagnostic or clinical drug utility is not established.", "related_concepts": [ "Cross-dataset expression classification", "Classifier-versus-interpretability distinction" ], "citation_contexts": [ "Methods: computational expression-based characterization of inflammatory bowel disease.", "Evidence synthesis: retrospective ulcerative-colitis classification results, retaining unresolved single-cell provenance and non-causal gene interpretation." ], "evidence_scope": { "supports": [ "Retrospective human UC-versus-control expression classification.", "Article-reported external bulk-dataset discrimination.", "Computational interpretation and hypothesis generation, with the single-cell provenance issue kept unresolved." ], "does_not_establish": [ "Prospective diagnostic utility or prediction of individual future disease onset.", "Causal roles for all 12 selected genes.", "Clinical efficacy of nominated compounds.", "UC single-cell validation from an independently verified matching source." ] }, "limitations": [ "Participant independence across cohorts has not been established by raw-data deduplication.", "The final 12-gene panel and the Fig. 3E 14-variable minimum-error statement must remain distinct.", "External model evaluation cannot exclude every preprocessing or feature-selection bias.", "The score formula was not independently reconstructed in this review.", "The GSE182272 accession-provenance mismatch remains unresolved.", "The models were not rerun and the complete supplementary data were not audited in this batch." ], "scope_source": "data/deep_geo/doi-10-18632-aging-205564.json#/evidence_scope" }, { "id": "doi-10-1200-po-24-00089", "title": "Artificial Intelligence Hybrid Survival Assessment System for Robot-Assisted Proctectomy: A Retrospective Cohort Study", "doi": "10.1200/po.24.00089", "year": 2024, "journal": "JCO Precision Oncology", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.md", "paper_geo_status": "v2", "authors": [ "Shiqian Zhang", "Ge Zhang", "Ming Wang", "Song-Bin Guo", "Fuqi Wang", "Yun Li", "Kaisaierjiang Kadier", "Zhaokai Zhou", "Pengpeng Zhang", "Hao Chi", "Chuchu Zhang", "Quanbo Zhou", "Pin Lyu", "Shuaiya Zhao", "Shuaixi Yang", "Weitang Yuan" ], "doi_url": "https://doi.org/10.1200/po.24.00089", "publisher_url": "https://ascopubs.org/doi/10.1200/PO.24.00089", "pmid": "39432882", "pmcid": null, "openalex_id": "https://openalex.org/W4403588641", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1200-po-24-00089.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1200-po-24-00089.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1200-po-24-00089.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "The study constructed RAP-AIscore using a systematic comparison of 132 candidate survival-modeling schemes in a double-center retrospective cohort.", "context": "506 unique RAP patients; NSCVRCS Meta n=384 plus independent SYEMH n=122. Discovery and Replication are subsets of Meta and must not be counted twice.", "evidence": [ { "label": "total unique patients", "value": "506" }, { "label": "NSCVRCS Meta", "value": "384" }, { "label": "Discovery", "value": "268" }, { "label": "Replication", "value": "116" }, { "label": "SYEMH", "value": "122" }, { "label": "modeling schemes", "value": "132" } ], "source_locator": "Abstract: Methods; Methods: Data Sources and Study Population; Results: Outcome and Treatment of Missing Values", "source": "data/deep_geo/doi-10-1200-po-24-00089.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#kf1" }, { "id": "KF2", "claim": "The selected Surv.coxboost + Surv.aorsf hybrid scheme achieved the highest average C-index among the 132 evaluated schemes.", "context": "Systematic retrospective comparison of candidate survival-modeling schemes.", "evidence": [ { "label": "average C-index", "value": "0.833" } ], "source_locator": "Results: Comprehensive Development of AI-Hybrid Score System; Fig. 2B-D", "source": "data/deep_geo/doi-10-1200-po-24-00089.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#kf2" }, { "id": "KF3", "claim": "RAP-AIscore showed time-dependent postoperative overall-survival discrimination in the internal NSCVRCS cohorts.", "context": "Retrospective internal development and validation; Meta contains the Discovery and Replication subsets.", "evidence": [ { "label": "Replication 12/36/60/72-month AUCs", "value": "0.851 / 0.849 / 0.902 / 0.915" }, { "label": "Meta 12/36/60/72-month AUCs", "value": "0.911 / 0.924 / 0.931 / 0.948" }, { "label": "Discovery 12/36/60/72-month AUCs", "value": "0.927 / 0.960 / 0.949 / 0.962" } ], "source_locator": "Results: The Predictive Value of RAP-AIscore System; Fig. 2E-H; Data Supplement Fig. S6", "source": "data/deep_geo/doi-10-1200-po-24-00089.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#kf3" }, { "id": "KF4", "claim": "The final interpretable RAP-AIscore used 10 accessible predictors.", "context": "Predictive model variables; their inclusion does not establish causal effects on mortality.", "evidence": [ { "label": "predictor count", "value": "10" }, { "label": "predictors", "value": "pTNM, ROM, CEA, Ns, PostCEA, Ts, CA199, HLP, Postchem, Minutes" } ], "source_locator": "Fig. 3C-D; Data Supplement Table S5", "source": "data/deep_geo/doi-10-1200-po-24-00089.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#kf4" }, { "id": "KF5", "claim": "Conditional-inference analysis separated patients into three prognostic risk states.", "context": "The Results text reports Replication low/intermediate/high counts of 68/20/19, which sum to 107 and do not reconcile with the stated Replication cohort size of 116. These subgroup counts are retained as article-reported values; the denominator discrepancy is unresolved and must not be interpreted as documented exclusions or a complete partition of all 116 patients.", "evidence": [ { "label": "low", "value": "RAP-AIscore <= 2.394" }, { "label": "intermediate", "value": "> 2.394 to <= 5.55" }, { "label": "high", "value": "> 5.55" }, { "label": "Article-reported Replication low/intermediate/high counts (sum 107; cohort 116; unresolved denominator discrepancy)", "value": "68 / 20 / 19" }, { "label": "Meta low/intermediate/high counts", "value": "258 / 60 / 66" }, { "label": "three-state discrimination", "value": "P < 0.001 in Replication and Meta" } ], "source_locator": "Results: Interpretability and Clinical Stratification of RAP-AIscore; Fig. 4A-E", "source": "data/deep_geo/doi-10-1200-po-24-00089.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#kf5" }, { "id": "KF6", "claim": "RAP-AIscore retained prognostic discrimination in the independent SYEMH external cohort, although early external discrimination was modest.", "context": "Independent retrospective SYEMH evaluation, n=122; external 1-year AUC was 0.587.", "evidence": [ { "label": "1-year AUC", "value": "0.587" }, { "label": "2-year AUC", "value": "0.754" }, { "label": "3-year AUC", "value": "0.810" }, { "label": "high-vs-low survival", "value": "P < 0.0001" }, { "label": "three-state discrimination", "value": "P < 0.001" } ], "source_locator": "Results: Extension to External Cohort From the RAP-AIscore; Fig. 5A-J", "source": "data/deep_geo/doi-10-1200-po-24-00089.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#kf6" } ], "field_entry": [ "Artificial intelligence in oncology", "Rectal cancer prognosis" ], "review_topics": [ "Machine learning for postoperative survival", "Interpretable cancer risk stratification" ], "concepts": { "conditions": [ "rectal cancer" ], "procedures": [ "robot-assisted proctectomy" ], "methods": [ "survival machine learning", "hybrid model selection", "SHAP", "conditional inference tree" ], "outcomes": [ "overall survival", "postoperative risk stratification" ], "validation": [ "internal validation", "independent external validation" ] }, "profile_type": "clinical_cohort", "study_profile": { "profile_type": "clinical_cohort", "study_design": "Double-center retrospective cohort study with internal and independent external validation", "evidence_type": "Human postoperative prognostic survival-modeling study", "unique_total_n": 506, "population": "Patients with rectal cancer undergoing robot-assisted proctectomy", "primary_endpoint": "In-hospital and post-discharge overall survival", "secondary_endpoint": "Postoperative prognostic risk stratification and time-dependent survival discrimination", "data_modalities": [ "electronic health records", "clinical and laboratory variables", "operative and pathologic characteristics", "longitudinal survival outcomes" ], "external_validation": true, "cohorts": [ { "name": "NSCVRCS Discovery", "role": "model development", "n": 268, "subset_of": "NSCVRCS Meta" }, { "name": "NSCVRCS Replication", "role": "internal validation", "n": 116, "subset_of": "NSCVRCS Meta" }, { "name": "NSCVRCS Meta", "role": "complete in-house/modeling cohort", "n": 384, "contains": [ "NSCVRCS Discovery", "NSCVRCS Replication" ] }, { "name": "SYEMH", "role": "independent external validation", "n": 122 } ] }, "study_profile_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/study_profile", "model_profile": { "initial_variables": 53, "algorithm_count": 12, "modeling_schemes": 132, "selected_algorithms": [ "Surv.coxboost", "Surv.aorsf" ], "feature_selection": "Filter + sequential-forward-floating wrapper feature selection maximizing Harrell C-index", "final_predictor_count": 10, "final_predictors": [ "pTNM", "ROM", "CEA", "Ns", "PostCEA", "Ts", "CA199", "HLP", "Postchem", "Minutes" ], "validation_strategy": [ "10 repetitions of 10-fold cross-validation", "Monte Carlo cross-validation: 100 iterations, sampling rate 0.7", "bootstrap: 1,000 iterations, sampling rate 0.7" ], "interpretability": [ "SHAP", "nomogram", "conditional inference tree", "t-SNE risk-state visualization" ] }, "model_profile_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/model_profile", "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1200-po-24-00089.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1200-po-24-00089.json", "gold_content_sha256": "1bd3630ab381e29d9920df5a2844506c8fd93bea295947730458243a92144346", "provenance": { "doi_url": "https://doi.org/10.1200/po.24.00089", "publisher_url": "https://ascopubs.org/doi/10.1200/PO.24.00089", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/39432882/" }, "scientific_role": "Interpretable survival-modeling framework for rectal-cancer patients after robot-assisted proctectomy.", "evidence_position": "Two-center retrospective human prognostic modeling with external evaluation; not prospective clinical utility or a causal survival advantage of robotic surgery.", "related_concepts": [ "Postoperative prognostic modeling", "Externally evaluated survival models" ], "citation_contexts": [ "Methods: interpretable AI for postoperative oncology prognosis.", "Evidence synthesis: survival models in the robot-assisted rectal-cancer surgery population, retaining external-performance limitations." ], "evidence_scope": { "supports": [ "Retrospective development of an interpretable RAP-specific survival model.", "Systematic hybrid model selection.", "Internal time-dependent survival discrimination.", "Independent retrospective external evaluation, with modest 1-year AUC of 0.587.", "Three-state prognostic stratification." ], "does_not_establish": [ "Prospective clinical utility.", "Improved survival from RAP-AIscore-guided care or treatment efficacy.", "Causal effects of the 10 predictors.", "Universal generalizability to all RAP populations or settings.", "Replacement of clinician judgment or pathologic staging." ] }, "limitations": [ "The two-center study and independent external evaluation were retrospective.", "Prospective clinical utility and survival benefit from model-guided management were not established.", "External 1-year discrimination was modest, with AUC 0.587.", "Generalizability to all hospitals and RAP populations was not established.", "The Results text reports Replication low/intermediate/high counts of 68/20/19, which sum to 107 and do not reconcile with the stated Replication cohort size of 116. These subgroup counts are retained as article-reported values; the denominator discrepancy is unresolved and must not be interpreted as documented exclusions or a complete partition of all 116 patients." ], "scope_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/evidence_scope" }, { "id": "doi-10-1186-s10020-024-00963-z", "title": "Assessing personalized molecular portraits underlying endothelial-to-mesenchymal transition within pulmonary arterial hypertension", "doi": "10.1186/s10020-024-00963-z", "year": 2024, "journal": "Molecular Medicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.md", "paper_geo_status": "v2", "authors": [ "Ruhao Wu", "Ge Zhang", "Mingzhou Guo", "Yue Li", "Lu Qin", "Tianci Jiang", "Pengfei Li", "Yu Wang", "Ke Wang", "Yize Liu", "Zhiqiu He", "Zhe Cheng" ], "doi_url": "https://doi.org/10.1186/s10020-024-00963-z", "publisher_url": null, "pmid": "39462326", "pmcid": "PMC11513636", "openalex_id": "https://openalex.org/W4403785027", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1186-s10020-024-00963-z.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1186-s10020-024-00963-z.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1186-s10020-024-00963-z.csl.json", "evidence_status": "reviewed_v2", "question_count": 7, "key_findings": [ { "id": "KF1", "claim": "Single-cell profiling showed PAH-associated heterogeneity across nine annotated lung cell types.", "context": "The observations are at cell and donor-sample levels in a small retrospective human lung series; cell counts are not participant counts.", "evidence": [ { "label": "Donor samples", "value": "3 PAH and 6 control samples" }, { "label": "Cells initially analyzed", "value": "31,444" }, { "label": "Cells retained after QC", "value": "28,906" }, { "label": "Annotated cell types", "value": "9, arising from 21 computational clusters" } ], "source_locator": "PMC11513636: Materials and methods — scRNA-seq data collecting, processing and analysis; Results — scRNA-seq analysis revealed cell landscape and characteristics in PAH; Figure 2A; supplementary Figures S1–S2.", "source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#kf1" }, { "id": "KF2", "claim": "Endothelial trajectory analyses identified expression states consistent with an EndMT-related program, including an EC3 state.", "context": "Slingshot and Monocle2 infer ordering from cross-sectional gene-expression data. They do not directly observe an individual endothelial cell converting in vivo or prove causality.", "evidence": [ { "label": "Endothelial cells analyzed", "value": "3,165" }, { "label": "Endothelial states", "value": "EC1, EC2 and EC3" }, { "label": "Patterns along inferred trajectory", "value": "3 gene-expression clusters (C1–C3)" }, { "label": "Associated biological programs", "value": "Mesenchymal differentiation, extracellular matrix organization and oxidative phosphorylation" } ], "source_locator": "PMC11513636: Materials and methods — Pseudotime trajectory inference; Results — Trajectory analyses revealed EndMT in endothelial populations; Figure 4A–G; Figure 5A.", "source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#kf2" }, { "id": "KF3", "claim": "Network and expression-based selection nominated six EndMT pattern genes from the EC3-related analysis.", "context": "This is computational prioritization of disease-associated expression features. A secondary discrepancy in the EC3 marker count is disclosed rather than resolved by assumption.", "evidence": [ { "label": "Candidate genes", "value": "6: RARRES2, CBY1, MSRB3, TC2N, CKS1B and SMAGP" }, { "label": "Co-expression modules", "value": "13" }, { "label": "Reported greenyellow module genes", "value": "66" } ], "source_locator": "PMC11513636: Results — Identification of EndMT-related modules and genes; Figure 6B–F; main-text description of Table S6. Table S4 has 604 unique gene rows while the main text reports 602 EC3 markers; the discrepant marker count is not used as an accepted quantitative claim here.", "source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#kf3" }, { "id": "KF4", "claim": "A two-gene glmNet score showed PAH-versus-control discrimination in an internal held-out test set.", "context": "The testing subset came from the same GSE117261 dataset as discovery and was also used to compare the nine algorithms and select the preferred model. The reported performance may therefore be optimistic, rather than an untouched final validation estimate. The C-index is reported as such, not relabeled as ROC AUC, and the supplementary residual column is not relabeled as RMSR.", "evidence": [ { "label": "Candidate learners", "value": "9" }, { "label": "Discovery/testing split", "value": "7:3 within GSE117261" }, { "label": "Discovery resampling", "value": "10-fold cross-validation repeated 10 times" }, { "label": "PETS formula", "value": "2.6926723 × RARRES2 + 0.7410611 × TC2N" }, { "label": "glmNet internal test accuracy", "value": "0.833333333333333" }, { "label": "glmNet internal test C-index", "value": "0.890756302521008" }, { "label": "glmNet internal test F1-score", "value": "0.888888888888889" }, { "label": "glmNet internal test precision and recall", "value": "0.842105263157895 and 0.941176470588235" }, { "label": "Supplementary |Residuals| column", "value": "0.253593" } ], "source_locator": "PMC11513636: Materials and methods — PETS generated from integrative machine-learning program; Results — Machine learning-based integrative program generates PETS; Figure 7A–D; Additional file 13, Table S7, glmNet row (worksheet row 3, columns B–G).", "source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#kf4" }, { "id": "KF5", "claim": "Targeted experiments supported expression changes in selected candidate genes under hypoxic conditions.", "context": "Expression-level concordance does not establish that RARRES2 or TC2N causes EndMT or that inhibiting either gene improves PAH. No numerical fold changes or replicate counts are inferred from figures.", "evidence": [ { "label": "Human PAEC observations", "value": "Higher expression reported for RARRES2, TC2N, CKS1B and SMAGP under hypoxia" }, { "label": "Mouse PAEC observations", "value": "Higher Rarres2 and Tc2n mRNA under hypoxia" }, { "label": "Tissue observation", "value": "Reported chemerin signal in CD31-marked endothelial regions of hypoxic PAH mouse lung" }, { "label": "Human/mouse cell hypoxia condition", "value": "1% oxygen stated in cell-culture methods" } ], "source_locator": "PMC11513636: Materials and methods — Cell lines and cultures; RNA extraction and real-time quantitative PCR; Results — Identification of EndMT-related modules and genes, and Machine learning-based integrative program generates PETS; Figure 7E and supplementary Figure S6 caption. Experimental n and numerical fold changes are not supplied by these text/caption locators.", "source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#kf5" } ], "field_entry": [ "Pulmonary vascular biology", "Computational biomarker research" ], "review_topics": [ "Endothelial expression states in PAH", "EndMT-related candidate classification" ], "concepts": { "Disease and cell context": [ "Pulmonary arterial hypertension", "Pulmonary artery endothelial cells", "Endothelial-to-mesenchymal transition" ], "Candidate signatures": [ "PETS", "RARRES2/chemerin", "TC2N" ], "Methods": [ "Single-cell transcriptomics", "Pseudotime inference", "Co-expression feature selection", "Internal test-set validation" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Retrospective public single-cell and bulk transcriptome analysis with computational trajectories, co-expression feature selection and internal machine-learning evaluation; targeted hypoxic endothelial-cell and tissue expression experiments", "evidence_type": "Human tissue transcriptomic association and classifier development, supported by limited gene-expression experiments rather than causal gene perturbation or a prospective clinical trial", "population": "GSE169471 lung single-cell samples: three PAH and six controls; GSE117261 used for internal classifier development/testing. Cells, donor samples, expression records and experimental systems are distinct units.", "primary_endpoint": "PAH-associated endothelial expression states and EndMT-related gene prioritization in retrospective tissue datasets", "secondary_endpoint": "Internal discrimination of PAH versus controls by the candidate PETS expression score, with selected gene-expression observations under hypoxia", "data_modalities": [ "Human lung single-cell RNA sequencing", "Public bulk lung transcriptomes", "Pseudotime trajectory inference and co-expression networks", "Internal machine-learning classification", "RT-qPCR in human and mouse pulmonary artery endothelial cells", "Reported chemerin/CD31 tissue immunofluorescence" ], "external_validation": false, "scale_metrics": [ { "label": "Single-cell donor samples", "value": "3 PAH samples and 6 control samples in GSE169471" }, { "label": "Cells before and after quality control", "value": "31,444 initially analyzed; 28,906 retained" }, { "label": "Endothelial trajectory subset", "value": "3,165 cells; EC1, EC2 and EC3 computational states" }, { "label": "Candidate expression genes", "value": "6 EndMT pattern genes; the final PETS score uses RARRES2 and TC2N" }, { "label": "Model evaluation", "value": "9 algorithms; GSE117261 internal discovery/testing split 7:3; tenfold cross-validation repeated 10 times in discovery" } ], "counting_note": "No unique participant total is manufactured across cell-level data, donor samples, bulk expression datasets and experiments. The 3,165 endothelial cells are a subset of the retained single-cell population, not additional donors. The 7:3 GSE117261 split is internal evaluation, not an independent external cohort; exact analytical split sizes and experimental replicate counts are not inferred from percentages or plots." }, "study_profile_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/study_profile", "model_profile": { "model_name": "PAH Endothelial-to-mesenchymal Transition Signature (PETS)", "model_family": "glmNet candidate classifier", "features": "RARRES2 and TC2N expression", "evaluation": "Internal 7:3 discovery/testing split of GSE117261; tenfold cross-validation with ten repetitions within discovery. The testing subset also compared algorithms and selected the preferred model, so performance may be optimistic.", "clinical_boundary": "Retrospective tissue-expression classification, not demonstrated early clinical diagnosis, serum-test validity, treatment response or clinical benefit" }, "model_profile_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/model_profile", "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1186-s10020-024-00963-z.json", "gold_content_sha256": "5d71ab5958288b69870144b0eaaf18351ff2f76dc958eb4dcd72a322d9083f53", "provenance": { "source_of_truth": "Version of record, Molecular Medicine 30:189, published 26 October 2024; PMID 39462326; PMC11513636. Complete PMC XML and retrieved original supplementary Tables S4 and S7 retained privately with SHA-256 hashes on 2026-10-14.", "original_article_url": "https://doi.org/10.1186/s10020-024-00963-z", "full_text_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11513636/", "publisher_url": "https://link.springer.com/article/10.1186/s10020-024-00963-z", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/39462326/", "license": "Article-specific CC BY 4.0 notice in publisher Rights and permissions and PMC permissions. This is an original summary, not a reproduction of the full article or figures.", "license_url": "https://creativecommons.org/licenses/by/4.0/", "identity_verification": "Ge Zhang is listed with the Department of Cardiology, First Affiliated Hospital of Zhengzhou University, Henan cardiovascular research-center and cardiac injury/repair laboratory affiliations. The version of record identifies Ruhao Wu, Ge Zhang and Mingzhou Guo as equal contributors. The article does not supply a Ge Zhang-specific ORCID identifier; name/affiliation and the existing ORCID-derived master record are concordant.", "version_relationship": "Published journal research article; no linked preprint relation was established from checked article metadata.", "numeric_verification": "Cell/donor counts, endothelial subset and PETS formula checked against main text and figure captions; internal test metrics checked directly against the downloaded original Table S7 glmNet row. No total patient n, experimental replicate count, serum concentration or treatment effect was inferred.", "reporting_discrepancies": "Ancillary count: main text 602 EC3 markers versus 604 distinct rows in original Table S4. Communication-role wording and MSRB1/MSRB3 inconsistency also retained in limitations. These passages are not used to establish directional cell communication, a specific MSRB expression result or a confirmed marker total." }, "scientific_role": "Exploratory integration of single-cell and bulk tissue expression to nominate endothelial states and an internally tested two-gene classifier.", "evidence_position": "Retrospective omics association with limited expression experiments; no direct lineage tracing, causal perturbation or independently validated clinical assay.", "related_concepts": [ "Pseudotime interpretation", "Tissue-to-blood translation boundary", "Internal versus external validation" ], "citation_contexts": [ "Background: endothelial heterogeneity and EndMT-associated transcriptional programs in PAH.", "Methods: candidate-gene selection and internal classifier evaluation, with clear limits on causal and clinical interpretation." ], "evidence_scope": { "supports": [ "PAH-associated endothelial transcriptional heterogeneity and computationally inferred EndMT-related expression programs.", "A candidate two-gene PETS classifier with internal test-set performance under the reported dataset and analysis procedure.", "Selected expression changes in hypoxic endothelial experimental systems." ], "does_not_establish": [ "Direct lineage-tracing proof that the inferred trajectory is an in vivo cell-fate conversion.", "A causal molecular mechanism from RARRES2 or TC2N to PAH or EndMT.", "An independently externally validated or prospective diagnostic test, or demonstrated detection of early disease.", "A validated serum PETS assay: the score was derived from transcriptomic expression, so discussion of serum translation remains a hypothesis.", "Clinical efficacy or safety of chemerin/CMKLR1-targeted therapy, or any PETS-guided treatment benefit." ] }, "limitations": [ "Human datasets are retrospective and the single-cell analysis has few donor samples; thousands of cells do not imply thousands of independent patients.", "Trajectory inference, pathway scoring, ligand-receptor inference and co-expression are computational associations, not direct causal mechanisms.", "The machine-learning testing subset is an internal split of GSE117261 and was also used to compare the nine algorithms and select the preferred model. Reported performance may therefore be optimistic. No untouched final test set, independent external clinical validation or prospective validation was established.", "PETS is based on transcript expression. Discussion of serum-marker applications should not be read as a validated blood test.", "Main text reports 602 EC3 marker genes, but the retrieved original Table S4 contains 604 distinct gene rows. This unresolved ancillary count difference is not silently harmonized.", "A Results sentence describes lower incoming and higher outgoing communications but labels the role change in the opposite direction; no sender/receiver direction claim is carried into this evidence page.", "A main-text sentence refers to MSRB1 while the candidate list and primer list use MSRB3. The page avoids drawing a gene-specific conclusion from that inconsistent sentence.", "Targeted expression experiments do not demonstrate a beneficial intervention. Experimental sample sizes and fold-change values are not invented from plots." ], "scope_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/evidence_scope" }, { "id": "doi-10-1002-clc-70019", "title": "Associations Between Cardiovascular Health (Life's Essential 8) and Mental Disorders", "doi": "10.1002/clc.70019", "year": 2024, "journal": "Clinical Cardiology", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1002-clc-70019.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1002-clc-70019.md", "paper_geo_status": "v2", "authors": [ "Yudi Xu", "Wenjing Ning", "Yuyuan Zhang", "Yuhao Ba", "Huimin Liu", "Long Liu", "Libo Wang", "Chunguang Guo", "Hui Xu", "Siyuan Weng", "Zhaokai Zhou", "Zongao Cai", "Hongxuan Ma", "Ge Zhang", "Yanjie Jia", "Xinwei Han" ], "doi_url": "https://doi.org/10.1002/clc.70019", "publisher_url": null, "pmid": "39314085", "pmcid": "PMC11420513", "openalex_id": "https://openalex.org/W4402780523", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1002-clc-70019.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1002-clc-70019.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1002-clc-70019.csl.json", "evidence_status": "reviewed_v2", "question_count": 5, "key_findings": [ { "id": "KF1", "claim": "The depression evidence is based on a defined complete-data adult survey sample and a symptom threshold.", "context": "The reported depression count agrees between Abstract Results and Results §3.1. PHQ-9 ascertainment is a symptom measure, not prospective incident depression.", "evidence": [ { "label": "analytic participants", "value": "13,028" }, { "label": "participants with PHQ-9 ≥10", "value": "1,206" }, { "label": "survey period", "value": "2007–2012" } ], "source_locator": "Methods §2.1 Study Population (clc70019-sec-0080), §2.3 Outcomes (clc70019-sec-0100); Results §3.1 (clc70019-sec-0140); Abstract Results", "source": "data/deep_geo/doi-10-1002-clc-70019.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-clc-70019.html#kf1" }, { "id": "KF2", "claim": "Higher total LE8 score was associated with lower adjusted odds of prevalent depressive symptoms.", "context": "Weighted logistic regression adjusted for age, sex, race, marital status, poverty and education; association per 10-point LE8 increment.", "evidence": [ { "label": "OR per 10-point LE8 increase", "value": "0.61" }, { "label": "95% confidence interval", "value": "0.58–0.65" }, { "label": "P value", "value": "<0.001" } ], "source_locator": "Methods §2.5 Statistical Analysis (clc70019-sec-0120); Results §3.2 (clc70019-sec-0150); Table 2 (clc70019-tbl-0002), Depression column, total-score continuous row and footnotes a–b", "source": "data/deep_geo/doi-10-1002-clc-70019.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-clc-70019.html#kf2" }, { "id": "KF3", "claim": "Moderate and high LE8 groups had lower depression odds relative to the low-score group.", "context": "The score categories are low 0–49, moderate 50–79 and high 80–100. 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This is not an exhaustive absence-of-correction claim.", "evidence_basis": "Formal Methods §§2.1–2.5, Results §§3.1–3.2 and text-encoded Table 2 depression columns. Anxiety counts and effects are excluded because Abstract versus Results/Table 2 conflict.", "source_verification_scope": "Formal Methods, Results and text-encoded tables were checked directly. No original statistical reanalysis and no source figures reproduced.", "license": "CC BY 4.0, as stated in article-level permissions.", "source_sha256": "0bdc92cabe8ddd3dea781e53aadec051e4d6142bbce9091a93a6ec1cb2041f5b" }, "scientific_role": "Population-survey analysis of LE8 and depressive symptoms, with the conflicting anxiety evidence explicitly excluded.", "evidence_position": "Adjusted prevalence association without intervention or prospective diagnostic validation.", "related_concepts": [ "Life’s Essential 8", "PHQ-9", "Survey-weighted analysis" ], "citation_contexts": [ "Evidence review of cardiovascular-health profiles and prevalent depressive symptoms.", "Methodological discussion of interpreting questionnaire outcomes and observational odds ratios." ], "evidence_scope": { "supports": [ "Survey-weighted associations of LE8 and its subscores with PHQ-9-defined depressive symptoms in the selected 2007–2012 sample.", "The depression-specific counts and estimates that agree across the abstract, Results and Table 2." ], "does_not_establish": [ "That interventions improving LE8 prevent or treat depression or anxiety.", "A causal direction between cardiovascular health and depressive symptoms.", "Resolved anxiety event counts or effect estimates; these remain excluded.", "Prospective depression prediction or psychiatric diagnosis by LE8." ] }, "limitations": [ "Unresolved anxiety conflict: Abstract Results reports 2,947 anxiety participants and OR 0.78 (95% CI 0.75–0.81), whereas Results §3.1 reports 3,326 and Results §3.3/Table 2 give OR 0.80 (0.77–0.82). This page does not choose between these values; all anxiety estimates and anxiety-based conclusions are excluded. The discrepancy has not been declared corrected.", "Cross-sectional associations do not determine temporal order, causality or efficacy of a cardiovascular-health intervention.", "PHQ-9 ≥10 identifies depressive symptoms for this analysis and is not equivalent to an independently adjudicated psychiatric diagnosis.", "Complete-data selection, self-reported behaviors and residual confounding can affect associations.", "Supplementary subgroup/sensitivity results and spline plots are outside the independently verified quantitative claim set." ], "scope_source": "data/deep_geo/doi-10-1002-clc-70019.json#/evidence_scope" }, { "id": "doi-10-1016-j-jtemb-2024-127543", "title": "Associations between magnesium depletion score and depression among individuals aged 20 to 60 years", "doi": "10.1016/j.jtemb.2024.127543", "year": 2024, "journal": "Journal of Trace Elements in Medicine and Biology", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.md", "paper_geo_status": "v2", "authors": [ "Zongao Cai", "Jiachen She", "Xiaozhu Liu", "Ruihui Li", "Shuang Guo", "Zeyang Han", "Jiyang Zhou", "Hairong Zhang", "Yudi Xu", "Ge Zhang", "Zhaokai Zhou", "Xueli Guo", "Shiyong Wu" ], "doi_url": "https://doi.org/10.1016/j.jtemb.2024.127543", "publisher_url": null, "pmid": "39406123", "pmcid": null, "openalex_id": "https://openalex.org/W4403267871", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1016-j-jtemb-2024-127543.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1016-j-jtemb-2024-127543.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1016-j-jtemb-2024-127543.csl.json", "evidence_status": "reviewed_v2", "question_count": 8, "key_findings": [ { "id": "KF1", "claim": "The pooled NHANES 2005–2018 cross-sectional analysis included 18,247 adults aged 20–60 years; 1,753 met the study's PHQ-9 threshold of at least 10.", "context": "These are unweighted participant counts after the stated exclusions. PHQ-9 reflects self-reported symptoms in the preceding two weeks; the threshold classification is not an independently confirmed clinical diagnosis or incident depression outcome.", "evidence": [ { "label": "analytic participants", "value": "18,247" }, { "label": "PHQ-9 at least 10", "value": "1,753" }, { "label": "PHQ-9 below 10", "value": "16,494" }, { "label": "survey years", "value": "2005–2018" } ], "source_locator": "Publisher PDF p. 2, Methods 2.1–2.2 and Fig. 1; pp. 3–4, Table 1.", "source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#kf1" }, { "id": "KF2", "claim": "MDS was a 0–5 score assembled from diuretic use, proton pump inhibitor use, reduced estimated glomerular filtration rate and heavy drinking.", "context": "The score is an operational proxy assembled from medication, renal-function and alcohol variables. This study did not measure or validate whole-body magnesium deficiency against serum magnesium. A higher score must not be described as a directly measured magnesium concentration.", "evidence": [ { "label": "score range", "value": "0–5" }, { "label": "diuretic use", "value": "1 point" }, { "label": "proton pump inhibitor use", "value": "1 point" }, { "label": "renal component", "value": "1 point for eGFR between 60 and 90; 2 points below 60 mL/min/1.73 m²" }, { "label": "heavy drinking component", "value": "1 point; more than 1 drink/day for women or 2 drinks/day for men" } ], "source_locator": "Publisher PDF p. 2, Methods 2.3; p. 5, Discussion limitations.", "source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#kf2" }, { "id": "KF3", "claim": "In survey-weighted Model 3, each one-point higher MDS was associated with higher odds of PHQ-9-defined depression: OR 1.15, 95% CI 1.04–1.26, P=0.0100.", "context": "Model 3 adjusted for age, sex, race/ethnicity, education, marital status, BMI, smoking, diabetes and dietary energy, calcium and magnesium intake. This adjusted prevalence-odds association is neither a prospective risk estimate nor an effect of changing magnesium status.", "evidence": [ { "label": "model", "value": "Survey-weighted Model 3" }, { "label": "comparison", "value": "Per 1 MDS point" }, { "label": "OR", "value": "1.15" }, { "label": "95% CI", "value": "1.04–1.26" }, { "label": "P", "value": "0.0100" } ], "source_locator": "Publisher PDF p. 3, Methods 2.5; p. 4, Results 3.2 and Table 2, continuous MDS row and footnote a.", "source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#kf3" }, { "id": "KF4", "claim": "Relative to MDS 0, Model 3 ORs were 1.03 (95% CI 0.87–1.21) for MDS 1, 1.41 (1.12–1.78) for MDS 2, and 1.58 (1.06–2.35) for MDS at least 3.", "context": "MDS 1 did not show a statistically significant association. The highest category contained only 368 participants, including 71 with PHQ-9 at least 10; sparse high scores limit precision and do not define a clinical screening or treatment threshold.", "evidence": [ { "label": "MDS 1 versus 0", "value": "OR 1.03; 95% CI 0.87–1.21; P=0.7600" }, { "label": "MDS 2 versus 0", "value": "OR 1.41; 95% CI 1.12–1.78; P=0.0040" }, { "label": "MDS at least 3 versus 0", "value": "OR 1.58; 95% CI 1.06–2.35; P=0.0300" }, { "label": "highest-category participants", "value": "368" }, { "label": "highest-category PHQ-9 at least 10", "value": "71" } ], "source_locator": "Publisher PDF p. 4, Table 1 continuation, MDS rows; Table 2, Model 3 categorical MDS rows and footnote b.", "source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#kf4" }, { "id": "KF5", "claim": "The component analysis reported an association for proton pump inhibitor use in Model 3: OR 2.24, 95% CI 1.78–2.80, P<0.0001.", "context": "Diuretic use, heavy drinking and the renal-function categories had confidence intervals crossing 1 in the same model. These component estimates do not establish medication-induced depression, magnesium mediation, or benefit from stopping a prescribed medication.", "evidence": [ { "label": "PPI-use OR", "value": "2.24" }, { "label": "95% CI", "value": "1.78–2.80" }, { "label": "P", "value": "<0.0001" }, { "label": "analysis", "value": "Survey-weighted component associations, Model 3" } ], "source_locator": "Publisher PDF p. 5, Table 3, Model 3 component rows and footnote a; p. 4, Results 3.2.", "source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#kf5" }, { "id": "KF6", "claim": "The restricted cubic spline analysis reported P=0.084 for nonlinearity.", "context": "The test did not detect nonlinearity at the paper's 0.05 significance level; this is not proof that the relationship is linear. Figure 2's wording about a beneficial threshold is not adopted as a clinical claim, and no numerical threshold is extracted from the curve.", "evidence": [ { "label": "nonlinearity P", "value": "0.084" }, { "label": "test", "value": "Restricted cubic spline; likelihood-ratio assessment" }, { "label": "reference shown in figure", "value": "MDS 0" } ], "source_locator": "Publisher PDF p. 3, Methods 2.5; p. 4, Results 3.2; p. 5, Fig. 2 and its caption.", "source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#kf6" }, { "id": "KF7", "claim": "All reported subgroup interaction P values in Table 4 exceeded 0.05.", "context": "Failure to detect interaction does not show that every subgroup estimate is statistically significant, identical or clinically useful. Several subgroup confidence intervals cross 1, and some are wide; these stratified analyses are not independent external validation.", "evidence": [ { "label": "age interaction P", "value": "0.140" }, { "label": "sex interaction P", "value": "0.180" }, { "label": "race/ethnicity interaction P", "value": "0.134" }, { "label": "reported interaction tests", "value": "All P>0.05" } ], "source_locator": "Publisher PDF p. 3, Methods 2.5; p. 4, Results 3.3; p. 6, Table 4, interaction column and footnote a.", "source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/key_findings/6", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#kf7" } ], "field_entry": [ "Nutritional epidemiology", "Population mental-health research" ], "review_topics": [ "Magnesium depletion proxies and depressive symptoms", "Medication and renal-function components in cross-sectional nutritional scores" ], "concepts": { "population": [ "NHANES 2005–2018", "adults aged 20–60 years" ], "exposure": [ "magnesium depletion score", "proton pump inhibitor use", "renal function", "heavy drinking" ], "outcome": [ "PHQ-9", "depressive symptoms", "cross-sectional prevalence" ], "methods": [ "survey-weighted logistic regression", "restricted cubic splines", "interaction analysis" ] }, "profile_type": "clinical_cohort", "study_profile": { "profile_type": "clinical_cohort", "study_design": "Secondary pooled cross-sectional analysis of NHANES 2005–2018", "evidence_type": "Survey-weighted human prevalence-odds association", "population": "Adults aged 20–60 years after exclusions for missing PHQ-9, MDS and specified covariates and for pregnancy", "primary_endpoint": "PHQ-9 score at least 10 at the survey assessment", "secondary_endpoint": "The same PHQ-9 outcome in score-category, component, spline and subgroup analyses; no separate prospective endpoint", "data_modalities": [ "PHQ-9 symptom questionnaire", "medication-use and alcohol variables", "estimated glomerular filtration rate", "demographic and health covariates", "two 24-hour dietary recalls" ], "unique_total_n": 18247, "cohorts": [ { "name": "Pooled NHANES 2005–2018 analytic sample", "role": "Single cross-sectional analytic sample; 1,753 participants met PHQ-9 at least 10 and 16,494 did not", "n": 18247 } ], "external_validation": false }, "study_profile_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json", "gold_content_sha256": "c7e2608ac267bdf46ae4c11e0835ea464d3d4d8e3ea7bf10dbd82e6fc3067c6d", "provenance": { "publication_url": "https://doi.org/10.1016/j.jtemb.2024.127543", "publisher_url": "https://www.sciencedirect.com/science/article/pii/S0946672X24001639", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/39406123/", "data_url": "https://www.cdc.gov/nchs/nhanes/index.htm", "source_version": "Seven-page publisher-formatted published article, Journal of Trace Elements in Medicine and Biology 86 (2024), article 127543; online 9 October 2024. Title, 13-author order, DOI and publication identity match the DOI deposit, PubMed and existing site record.", "review_basis": "Full main PDF read and Tables 1–4 plus Figures 1–2 visually checked on 27 October 2026. Main-article denominators, definitions and Model 3 estimates were checked across text and tables. No participant-level reanalysis was performed.", "fulltext_access": "The author supplied access through the normal ResearchGate author-account full-text download. The copyrighted source PDF is retained in the private audit directory and is not redistributed by this website.", "source_sha256": "7f62346a80463eea31c7f5a70af9529ef8f0f8a80446da00812f58093d5c5be8", "supplementary_scope": "Supplementary Tables 1–2 are referenced in the main article but were not obtained in this audit. Their detailed dietary thresholds and alternative-category estimates are excluded; the displayed findings are supported by the audited main article.", "reporting_caveats": "Figure 2 caption terminology and overbroad interpretations of nonlinearity or subgroup consistency are not adopted. Crossref's retrieved record contained no correction relation; absence of a relation is not proof that no later notice exists." }, "scientific_role": "A survey-weighted secondary analysis relating a four-domain proxy score to concurrent PHQ-9 classification in US adults aged 20–60.", "evidence_position": "Observational prevalence-odds evidence, with questionnaire-defined symptoms and no biochemical magnesium validation or intervention.", "related_concepts": [ "Proxy exposure measurement", "PHQ-9 outcome definition", "Cross-sectional confounding" ], "citation_contexts": [ "Evidence synthesis on MDS and depressive symptoms, specifying the PHQ-9 threshold, sample exclusions and adjusted odds rather than incident disease risk.", "Methods discussion of composite exposure scores and survey weighting; not evidence for a validated depression screening tool." ], "evidence_scope": { "supports": [ "Reported survey-weighted MDS–PHQ-9 prevalence-odds associations in the included adults aged 20–60 years.", "Definition of the proxy score, questionnaire outcome, analytic denominator and covariate-adjustment set in the main article.", "Descriptive assessment of score categories, components, spline nonlinearity and subgroup interactions within the same survey sample." ], "does_not_establish": [ "That magnesium depletion causes depression, or that lowering MDS or magnesium supplementation prevents or treats depression.", "A validated clinical diagnosis, depression screening rule, individual prognosis or treatment threshold derived from MDS.", "Direct measurement of serum or whole-body magnesium, or proof that magnesium mediates the observed medication associations.", "Proof of linearity from P=0.084, identical effects across subgroups, or statistical significance in every subgroup.", "Numerical results from Supplementary Tables 1–2, which were referenced by the paper but not obtained for this audit." ] }, "limitations": [ "The cross-sectional design cannot establish temporal direction; reverse causation and residual confounding remain possible (Discussion, p. 5).", "MDS combines medication use, kidney function and drinking behavior; it is not a biochemical magnesium measurement, and serum-magnesium comparison was unavailable (Methods 2.3; Discussion, p. 5).", "PHQ-9 at least 10 is the study's questionnaire-based outcome, not an independently adjudicated clinical diagnosis (Methods 2.2).", "Participants with specified missing data were excluded. The main text reports use of recommended NHANES weights but does not identify the exact weight variable, pooled-weight construction or a missing-data imputation procedure; no participant-level reanalysis is claimed (Fig. 1; Methods 2.1 and 2.5).", "High MDS values were uncommon: scores 3, 4 and 5 contained 325, 41 and 2 participants and were pooled. High-score and subgroup estimates are correspondingly imprecise (Methods 2.3; Tables 2 and 4).", "Supplementary Tables 1–2 were not available for this audit. Dietary-threshold specifications and alternative-category sensitivity estimates from those files are not presented as verified results.", "Figure 2's caption uses beneficial-threshold language, but the design and results do not establish a beneficial or clinical intervention threshold. The nonlinearity P value does not prove linearity.", "Generalization beyond the included US adult survey population requires independent evidence." ], "scope_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/evidence_scope" }, { "id": "doi-10-15212-cvia-2024-0023", "title": "Causal Associations Between the Gut Microbiome and Aortic Aneurysm: A Mendelian Randomization Study", "doi": "10.15212/cvia.2024.0023", "year": 2024, "journal": "Cardiovascular Innovations and Applications", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-15212-cvia-2024-0023.html", "markdown_url": "https://drgezhang.com/papers/doi-10-15212-cvia-2024-0023.md", "paper_geo_status": "v2", "authors": [ "Yan Lv", "Dexin Shen", "Ge Zhang", "Bo Wang", "Haiyu Wang", "Jinying Zhang", "Junnan Tang" ], "doi_url": "https://doi.org/10.15212/cvia.2024.0023", "publisher_url": null, "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W4394787832", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-15212-cvia-2024-0023.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-15212-cvia-2024-0023.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-15212-cvia-2024-0023.csl.json", "evidence_status": "reviewed_v2", "question_count": 5, "key_findings": [ { "id": "KF1", "claim": "The study paired microbial genetic instruments with separate AA and AAA outcome summary statistics.", "context": "Methods report SNP selection at P<1×10−5, exclusion of F<10 instruments, and LD clumping at r²=0.001 across 10,000 kb. These are reported criteria; instrument rows and exposure–outcome sample overlap were not independently verified.", "evidence": [ { "label": "Exposure source", "value": "MiBioGen: 18,473 participants, 24 multi-ethnic cohorts" }, { "label": "AA cases / controls", "value": "7,395 / 349,539" }, { "label": "AAA cases", "value": "3,548" }, { "label": "Reported SNP entries", "value": "2,031" } ], "source_locator": "Methods: Data Source for Gut Microbiota; Data Source for Outcomes; Selection of Instrumental Variables. Results: Selection of Instrumental Variables for Gut Microbiomes. https://www.scienceopen.com/hosted-document?doi=10.15212/CVIA.2024.0023", "source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-15212-cvia-2024-0023.html#kf1" }, { "id": "KF2", "claim": "Main Table 1 reports opposite-direction AA estimates for Family XIII UCG001 and Bifidobacteriaceae.", "context": "IVW estimates on the original microbial GWAS genetic-proxy scale; no bacterial dose or treatment contrast is established. These are rows in the authors’ Bonferroni-selected table, not an independently reproduced full-screen significance claim.", "evidence": [ { "label": "Genus Family XIII UCG001", "value": "8 SNPs; IVW OR 1.33, 95% CI 1.14–1.55; P=0.000203273" }, { "label": "Family Bifidobacteriaceae", "value": "11 SNPs; IVW OR 0.79, 95% CI 0.70–0.89; P=0.0000800528" }, { "label": "MR-Egger uncertainty", "value": "P=0.765969749 and P=0.787451213, respectively; no independent statistical confirmation by that estimator" } ], "source_locator": "Results: Bonferroni-Corrected Test; Table 1, AA / Family XIII UCG001 and Bifidobacteriaceae IVW and MR-Egger rows. https://www.scienceopen.com/hosted-document?doi=10.15212/CVIA.2024.0023#tb001", "source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-15212-cvia-2024-0023.html#kf2" }, { "id": "KF3", "claim": "Bilophila had a positive IVW association with AAA, while alternative estimator intervals included the null.", "context": "Genus-level genetic proxy and AAA outcome. Method-specific uncertainty prevents a claim of unanimous robustness or established causality.", "evidence": [ { "label": "Instruments", "value": "13 SNPs" }, { "label": "IVW", "value": "OR 1.36, 95% CI 1.17–1.57; P=0.0000452" }, { "label": "MR-Egger", "value": "OR 1.55, 95% CI 0.48–5.03; P=0.483243703" }, { "label": "Weighted median", "value": "OR 1.34, 95% CI 0.98–1.85; P=0.068775942" }, { "label": "Weighted mode", "value": "OR 1.29, 95% CI 0.80–2.08; P=0.309338759" } ], "source_locator": "Results: Bonferroni-Corrected Test; Table 1, AAA / Genus Bilophila, all four methods. https://www.scienceopen.com/hosted-document?doi=10.15212/CVIA.2024.0023#tb001", "source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-15212-cvia-2024-0023.html#kf3" } ], "field_entry": [ "Cardiovascular genetics", "Microbiome epidemiology" ], "review_topics": [ "Gut microbial traits and aneurysm", "Two-sample Mendelian randomization" ], "concepts": { "Diseases": [ "Aortic aneurysm", "Abdominal aortic aneurysm" ], "Methods": [ "Two-sample Mendelian randomization", "GWAS summary statistics", "Inverse-variance weighting", "Horizontal pleiotropy", "Multiple testing" ], "Microbial traits": [ "Family XIII UCG001", "Bifidobacteriaceae", "Bilophila" ] }, "profile_type": "multicohort_observational", "study_profile": { "profile_type": "multicohort_observational", "study_design": "Two-sample Mendelian randomization of public microbial-trait and aneurysm GWAS summary statistics.", "evidence_type": "Genetic-instrument association estimates under MR assumptions, with alternative estimator comparisons.", "population": "MiBioGen multi-ethnic microbiome GWAS across 24 cohorts and FinnGen version 9 outcomes from a Finnish biobank population.", "primary_endpoint": "Aortic aneurysm (AA) case-control GWAS outcome.", "secondary_endpoint": "Abdominal aortic aneurysm (AAA); TAA was analyzed in the paper but is excluded here because of source endpoint ambiguity.", "data_modalities": [ "16S microbiome-trait GWAS summary associations", "SNP instruments", "FinnGen case-control GWAS summary statistics" ], "external_validation": false, "scale_metrics": [ { "label": "Exposure GWAS", "value": "18,473 participants from 24 MiBioGen cohorts" }, { "label": "AA GWAS", "value": "7,395 cases and 349,539 controls as reported" }, { "label": "AAA GWAS", "value": "3,548 cases; Methods report the same 349,539-control source" }, { "label": "Selected SNP entries", "value": "2,031 across taxonomic levels; not unique participants" } ], "counting_note": "Exposure and outcome sources are not combined into a patient total. AA and subtype outcomes overlap. Methods state 196 retained taxa, while Results counts (9 phyla, 16 classes, 20 orders, 31 families, 119 genera) sum to 195; this remains unresolved." }, "study_profile_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-15212-cvia-2024-0023.json", "gold_content_sha256": "80aee0ebae1c3219cd03eabd295a230f1555c1728c71c417025fc89f6af724db", "provenance": { "publisher_url": "https://www.scienceopen.com/hosted-document?doi=10.15212/CVIA.2024.0023", "doi_url": "https://doi.org/10.15212/CVIA.2024.0023", "version_of_record": "Official ScienceOpen-hosted Cardiovascular Innovations and Applications article; publisher ID cvia.2024.0023; copyright 2024 The Authors.", "license": "Creative Commons Attribution 4.0 International, explicitly stated in Article / License.", "license_url": "https://creativecommons.org/licenses/by/4.0/", "evidence_basis": "Current official hosted full-text Methods, Results and Table 1, retrieved 2026-10-26; only AA and AAA main-table findings included.", "supporting_material_url": "https://cvia-journal.org/wp-content/uploads/2024/03/Supplementary_tables_1_5.xlsx", "supporting_material_note": "Official spreadsheet download returned HTTP 406; equation and figure asset requests returned HTTP 403. No access control bypass and no independent supplement-based sensitivity verification.", "source_conflict_note": "TAA definition and 196-versus-195 taxon counts remain unresolved. Results also use imprecise lower-level wording for some OR<1 taxa; this page quotes Table 1 estimates on their genetic-proxy scale without asserting an intervention direction.", "source_sha256": "1b912092865c5c1951364009a4890ba8b5559d1008db299ad3712e0dbec1ff13" }, "scientific_role": "Genetic-instrument analysis with bounded AA and AAA main-table findings.", "evidence_position": "Assumption-dependent summary genetic associations, not intervention or clinical validation.", "related_concepts": [ "MiBioGen", "FinnGen", "Bilophila" ], "citation_contexts": [ "Reviews comparing microbial-trait MR associations with aneurysm outcomes.", "Discussions separating IVW findings from sensitivity uncertainty and treatment evidence." ], "evidence_scope": { "supports": [ "The stated MiBioGen and FinnGen data-source design and AA/AAA estimates printed in main Table 1.", "Different uncertainty across MR estimators for the same microbial trait and outcome." ], "does_not_establish": [ "Benefits from changing the microbiome, probiotics, antibiotics or aneurysm-prevention treatment.", "A validated screening biomarker, patient-level risk score or clinical threshold.", "Proof of absent pleiotropy, valid instruments, or independently reproduced supplementary sensitivity and full multiple-testing results.", "A resolved TAA endpoint definition or reconciled screen-wide microbial-taxon count." ] }, "limitations": [ "The TAA Methods definition uses thoracoabdominal rather than thoracic outcomes; TAA-specific findings are excluded pending clarification.", "The retained-taxon total is stated as 196, while Results category counts sum to 195; neither is presented as a reconciled screen-wide count.", "Bonferroni correction is described by taxonomic level, but equation images and supplements were unavailable. Main-table estimates are reported as author-selected associations, not an independently reproduced screen-wide significance claim.", "Alternative estimator intervals do not uniformly exclude the null; MR estimates remain assumption-dependent.", "The exposure GWAS is multi-ethnic and the outcome source is Finnish. Portability, population structure and sample overlap require consideration; overlap was not quantified here.", "Supplementary MR-PRESSO, Steiger, leave-one-out and instrument tables were not independently inspected. Non-significant diagnostic tests would not prove the absence of pleiotropy.", "No intervention, prospective diagnostic validation or clinical treatment benefit was tested." ], "scope_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/evidence_scope" }, { "id": "doi-10-1111-jcmm-18408", "title": "Deciphering lung adenocarcinoma evolution: Integrative single-cell genomics identifies the prognostic lung progression associated signature", "doi": "10.1111/jcmm.18408", "year": 2024, "journal": "Journal of Cellular and Molecular Medicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.md", "paper_geo_status": "v2", "authors": [ "Pengpeng Zhang", "Zijun Yang", "Zuo Liu", "Ge Zhang", "Lianmin Zhang", "Zhenfa Zhang", "Jun Fan" ], "doi_url": "https://doi.org/10.1111/jcmm.18408", "publisher_url": null, "pmid": "38837585", "pmcid": "PMC11149493", "openalex_id": "https://openalex.org/W4399330698", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-18408.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-18408.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-18408.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "Two single-cell series identified heterogeneous epithelial states across early LUAD pathological categories.", "context": "Single-cell cross-sectional profiles; inferCNV and trajectory scores estimate rather than observe clonal evolution.", "evidence": [ { "label": "Pathological specimens", "value": "4 AIS, 8 MIA and 9 IAC in GSE189357/GSE150938" }, { "label": "Computational annotation", "value": "12 broad cell types; 8 re-clustered inferred tumor epithelial groups" } ], "source_locator": "PMC11149493: Methods §2.1 Data set source (jcmm18408-sec-0003); Results §3.1 (jcmm18408-sec-0024); Figure 2A–H.", "source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#kf1" }, { "id": "KF2", "claim": "Cluster 6-associated transcriptomic features were enriched during the reported AIS-to-IAC comparison.", "context": "Proportional and pseudotime associations do not establish observed within-patient malignant transformation.", "evidence": [ { "label": "State of interest", "value": "Epithelial Cluster 6" }, { "label": "Associated programs", "value": "E2F targets and G2M checkpoint signatures" }, { "label": "Inference methods", "value": "inferCNV, pseudotime and SCENIC" } ], "source_locator": "PMC11149493: Results §3.2 Biological characteristic analysis of tumour clusters (jcmm18408-sec-0025); Figure 3A–H.", "source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#kf2" }, { "id": "KF3", "claim": "LPAS was constructed from nine genes and associated with overall survival in TCGA and five GEO cohorts.", "context": "Retrospective survival discrimination and cohort reapplication, not independent prospective treatment guidance.", "evidence": [ { "label": "Selection", "value": "41 univariately associated module genes, followed by 9-gene LPAS" }, { "label": "TCGA time-dependent ROC AUC", "value": "1-year 0.713; 5-year 0.675" }, { "label": "Independent series", "value": "GSE13213, GSE29016, GSE30219, GSE31210, GSE68465" }, { "label": "Model composition", "value": "PSMB1, ENY2, NPTN, RPS16, HYAL3, KLK8, CAMTA1, MAGEH1, AKR1A1" } ], "source_locator": "PMC11149493: Methods §2.8 (jcmm18408-sec-0010); Results §§3.3–3.4 (jcmm18408-sec-0026, jcmm18408-sec-0027); Figures 4B–G and 5A–F.", "source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#kf3" }, { "id": "KF4", "claim": "LPAS scores were associated with computationally inferred immune infiltration and treatment-related expression patterns.", "context": "Immune deconvolution, TIDE and SubMap are analytical scores or expression matching; they are not verified patient-level benefit from immunotherapy.", "evidence": [ { "label": "Low-score association", "value": "Higher inferred immune/stromal signatures in TCGA" }, { "label": "Drug results", "value": "CTRP/PRISM compound-screen associations are exploratory" }, { "label": "Therapy-response analyses", "value": "SubMap/TIDE-based association; mixed external malignancy cohorts" } ], "source_locator": "PMC11149493: Results §§3.5, 3.7, 3.9 (jcmm18408-sec-0028, jcmm18408-sec-0030, jcmm18408-sec-0032); Figures 6A–C, 8D–G, 10A–L.", "source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#kf4" }, { "id": "KF5", "claim": "PSMB1 knockdown changed LUAD cell-line growth and motility endpoints.", "context": "Culture experiments provide selected cell-functional evidence but not an in-vivo antitumor effect or human therapeutic validation.", "evidence": [ { "label": "Experimental systems", "value": "A549 and H1299 human LUAD cell lines" }, { "label": "Intervention", "value": "PSMB1-targeting siRNA" }, { "label": "Reported assays", "value": "CCK-8, colony formation, wound healing and Transwell" } ], "source_locator": "PMC11149493: Methods §§2.15–2.19 (jcmm18408-sec-0017 through jcmm18408-sec-0021); Results §3.10 (jcmm18408-sec-0033); Figure 11A–D.", "source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#kf5" } ], "field_entry": [ "Lung cancer molecular pathology", "Computational oncology" ], "review_topics": [ "Cell states in early lung adenocarcinoma", "Transcriptomic survival risk signatures" ], "concepts": { "disease_and_stage": [ "Lung adenocarcinoma", "Adenocarcinoma in situ", "Minimally invasive adenocarcinoma" ], "data_and_methods": [ "Single-cell transcriptomics", "inferCNV and pseudotime", "Retrospective survival modeling" ], "molecular_and_translation": [ "Cluster 6", "LPAS", "PSMB1 knockdown" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Secondary integration of human LUAD single-cell and bulk expression cohorts with retrospective survival modeling, computational immune/drug-response inference and in-vitro PSMB1 perturbation.", "evidence_type": "Human transcriptomic association, retrospective model evaluation and LUAD cell-line functional assays.", "population": "Early pathological LUAD tissue samples across AIS, MIA and IAC; independent retrospective GEO/TCGA LUAD survival cohorts and additional tumor-treatment series from heterogeneous cancers.", "primary_endpoint": "Association of the LPAS expression score with overall survival in retrospective LUAD series.", "secondary_endpoint": "Single-cell state contrasts across pathological stages; immune/stromal signature associations; computational immunotherapy/drug-response hypotheses; PSMB1 knockdown cell phenotypes.", "data_modalities": [ "Two publicly available LUAD scRNA-seq series", "TCGA and GEO transcriptomic and clinical survival data", "Exploratory external treatment-response expression datasets", "Local LUAD RNA sequencing", "A549 and H1299 siRNA perturbation assays" ], "external_validation": true, "scale_metrics": [ { "label": "Single-cell specimen scale", "value": "GSE189357 and GSE150938: 4 AIS, 8 MIA and 9 IAC specimens (21 reported across pathology groups)" }, { "label": "Independent survival-series list", "value": "GSE13213 (119), GSE29016 (39), GSE30219 (86), GSE31210 (227) and GSE68465 (443) as reported analyzed series" }, { "label": "Model discovery", "value": "TCGA-LUAD; cohort n not inferred from unspecified filtering" }, { "label": "Local stage-associated RNA sequencing", "value": "14 LUAD surgical specimens (reported)" }, { "label": "LPAS signature", "value": "9 genes" } ], "counting_note": "The 21 scRNA-seq specimens, 14 local RNA-seq specimens, TCGA cases, five survival cohorts and mixed-cancer immunotherapy datasets represent distinct analytic layers; neither cross-dataset independence nor a synthetic unique-patient total is inferred." }, "study_profile_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/study_profile", "model_profile": { "model_name": "Lung progression-associated signature (LPAS)", "model_family": "Nine-gene expression-based survival model", "development": "TCGA-LUAD retrospective transcriptomic and survival data", "external_evaluation": "Five GEO LUAD retrospective survival cohorts; horizon-specific AUCs vary.", "clinical_boundary": "No prospective LPAS-guided clinical decision validation." }, "model_profile_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/model_profile", "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1111-jcmm-18408.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1111-jcmm-18408.json", "gold_content_sha256": "02c01069af3d81cb447fb2316f5d80cb6d8efc6c973d6f7263cf36c31e4cd829", "provenance": { "doi_url": "https://doi.org/10.1111/jcmm.18408", "publisher_url": "https://onlinelibrary.wiley.com/doi/10.1111/jcmm.18408", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11149493/", "pmcid": "PMC11149493", "license": "CC BY 4.0, as shown in article-specific PMC JATS permissions. This evidence page is original factual synthesis.", "license_url": "https://creativecommons.org/licenses/by/4.0/", "source_of_truth": "Version-of-record article, J Cell Mol Med 2024, published online 4 June 2024; PMC11149493 JATS and Figure 2–11 legends in the supplied source pack.", "supporting_material": "Article Table S1 was obtained; no synthetic patient aggregation is used.", "identity_note": "Publisher/PMC author order is retained by existing publication master; JATS ORCID attribution for one coauthor conflicts with another related paper and is not used to revise structured identities.", "scientific_boundary": "No inference of lineage tracing, prospective clinical decision value or immunotherapy benefit from computational association." }, "scientific_role": "Retrospective LUAD multi-dataset signature discovery with an ancillary PSMB1 cell-line perturbation study.", "evidence_position": "Observational transcriptomic/prognostic associations and in-vitro functional readouts; no prospective LPAS-guided therapy evidence.", "related_concepts": [ "AIS–MIA–IAC comparison", "LPAS nine-gene signature", "PSMB1 siRNA" ], "citation_contexts": [ "Reviews evaluating cross-sectional single-cell LUAD states and prognostic transcriptomic signatures.", "Discussions distinguishing cell-line perturbation from clinical proof of a molecular therapeutic target." ], "evidence_scope": { "supports": [ "Cluster 6 and LPAS show reproducible associations in the reported transcriptomic cohorts.", "Higher LPAS corresponds to less favorable retrospective LUAD survival in the evaluated cohorts.", "PSMB1 silencing reduces selected proliferation and movement phenotypes in A549/H1299 assays." ], "does_not_establish": [ "A directly traced longitudinal path from an AIS cell to an IAC cell or a causal origin of Cluster 6.", "Independent prospective diagnostic, treatment selection, or outcome improvement from LPAS.", "Clinical benefit from PSMB1 inhibition, LPAS-guided immunotherapy or computationally prioritized compounds.", "Unique participant counts aggregated across partially overlapping or heterogeneous public datasets." ] }, "limitations": [ "Early stages and bulk outcome datasets are distinct study populations; pseudotime is not lineage tracing.", "Source dataset descriptions include heterogeneous immunotherapy studies, and the article uses different counting contexts rather than a single combined n.", "Single-cell immune estimates and simulated drug sensitivity are not direct measurements of clinical response.", "PSMB1 siRNA provides selected in-vitro evidence, not an in-vivo drug efficacy or clinical trial." ], "scope_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/evidence_scope" }, { "id": "doi-10-1007-s10238-024-01439-4", "title": "Deciphering the prognostic role of endoplasmic reticulum stress in lung adenocarcinoma: integrating prognostic prediction and immunotherapy strategies", "doi": "10.1007/s10238-024-01439-4", "year": 2024, "journal": "Clinical and Experimental Medicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1007-s10238-024-01439-4.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1007-s10238-024-01439-4.md", "paper_geo_status": "v2", "authors": [ "Bing Wen", "Pengpeng Zhang", "Jiping Xie", "Zhaokai Zhou", "Ge Zhang", "Lianmin Zhang", "Zhenfa Zhang" ], "doi_url": "https://doi.org/10.1007/s10238-024-01439-4", "publisher_url": null, "pmid": "39052154", "pmcid": "PMC11272744", "openalex_id": "https://openalex.org/W4400980865", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1007-s10238-024-01439-4.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1007-s10238-024-01439-4.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1007-s10238-024-01439-4.csl.json", "evidence_status": "reviewed_v2", "question_count": 4, "key_findings": [ { "id": "KF1", "claim": "A 10-gene ERAS signature was selected from 22 survival-associated genes.", "context": "Univariate Cox screening followed by LASSO in the TCGA development dataset; 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Fig. 6F-H", "source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s10238-024-01439-4.html#kf2" }, { "id": "KF3", "claim": "SERPINH1 and GPR37 expression was higher in LUAD tumor than paired adjacent tissue in the reported qPCR experiment.", "context": "Expression validation only; it does not test survival prediction or treatment effect.", "evidence": [ { "label": "clinical tissue pairs", "value": "10" }, { "label": "genes tested in this qPCR comparison", "value": "2: SERPINH1 and GPR37" } ], "source_locator": "Methods: Clinical specimen collection, Par12; Results: Experimental validation, Par23; Supplementary Fig. 3A-B (MOESM3)", "source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1007-s10238-024-01439-4.html#kf3" } ], "field_entry": [ "Lung cancer genomics", "Computational oncology" ], "review_topics": [ "Stress-associated prognostic signatures", "Retrospective molecular risk models" ], "concepts": { "conditions": [ "lung adenocarcinoma" ], "methods": [ "LASSO Cox regression", "survival analysis", "single-cell transcriptomics" ], "models_tools": [ "ERAS" ], "genes": [ "SERPINH1", "GPR37" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Retrospective public-dataset prognostic modeling with tissue expression experiments", "evidence_type": "Human transcriptomic associations and limited expression validation", "population": "LUAD bulk transcriptomic cohorts, nine treatment-naive patients represented in a single-cell dataset, and paired clinical tissue specimens", "primary_endpoint": "Overall survival association and prognostic discrimination", "secondary_endpoint": "Inferred immune states, computational drug sensitivity and tissue gene expression", "data_modalities": [ "bulk transcriptomics", "single-cell transcriptomics", "clinical survival data", "qPCR" ], "external_validation": true, "scale_metrics": [ { "label": "bulk survival datasets", "value": "TCGA plus seven named GEO datasets" }, { "label": "single-cell input patients", "value": "9" }, { "label": "paired tissue specimens", "value": "10 tumor-adjacent pairs" }, { "label": "final signature genes", "value": "10" } ], "counting_note": "Datasets and specimen pairs are distinct units. No unique pooled participant total is derived. The Results text calls the external survival datasets six but enumerates seven; Methods and Figure 4C identify TCGA plus seven GEO datasets. 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The study should not be cited as significant prognostic validation in every external dataset.", "Immune-infiltration and TMB group differences described in Results include nonsignificant comparisons; computational immune and drug-sensitivity estimates are not observed treatment-response validation.", "The qPCR experiment assesses two genes in 10 paired tissue specimens; it does not validate the complete survival model or establish that these genes cause tumor progression.", "The selected figures were checked for labels, reported values and direction, without reanalysis of participant-level or raw qPCR data." ], "scope_source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/evidence_scope" }, { "id": "time-cart", "title": "Deciphering the tumor immune microenvironment from a multidimensional omics perspective: insight into next-generation CAR-T cell immunotherapy and beyond", "doi": "10.1186/s12943-024-02047-2", "year": 2024, "journal": "Molecular Cancer", "type": "Article", "paper_url": "https://drgezhang.com/papers/time-cart.html", "markdown_url": "https://drgezhang.com/papers/time-cart.md", "paper_geo_status": "v2", "authors": [ "Zhaokai Zhou", "Jiahui Wang", "Jiaojiao Wang", "Shuai Yang", "Ruizhi Wang", "Ge Zhang", "Zhengrui Li", "Run Shi", "Zhan Wang", "Qiong Lu" ], "doi_url": "https://doi.org/10.1186/s12943-024-02047-2", "publisher_url": null, "pmid": "38918817", "pmcid": "PMC11201788", "openalex_id": "https://openalex.org/W4400057543", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/time-cart.bib", "citation_ris_url": "https://drgezhang.com/citations/time-cart.ris", "citation_csl_json_url": "https://drgezhang.com/citations/time-cart.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "Spatial localization of lymphocytes provides information not captured by simple immune-cell abundance.", "context": "The review discusses immune-excluded and inflamed TIME patterns and spatial proximity from published studies, without constructing or validating a new spatial test.", "evidence": [ { "label": "Immune patterns", "value": "Immune-excluded, immune-inflamed and TLS-containing contexts" }, { "label": "Spatial dimensions", "value": "Stroma, tumor core and invasive margin" }, { "label": "Evidence format", "value": "Narrative examples from cited observational research" } ], "source_locator": "PMC11201788: Classification of the TIME (Sec3), Spatial architecture of the TIME (Sec4), Distribution of immune cells and immune checkpoints (Sec5), Distance between immune cells and tumor/immune cells (Sec6); 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The contradictory IHC heading and MR sensitivity-table labeling are explicitly disclosed.", "license": "CC BY 4.0, as stated in formal article permissions.", "license_url": "https://creativecommons.org/licenses/by/4.0/" }, "scientific_role": "Candidate-gene study connecting nominal genetic evidence with tissue IHC and A549 perturbation.", "evidence_position": "Preclinical and hypothesis-generating evidence; not a clinical diagnostic or therapeutic validation study.", "related_concepts": [ "Gene-expression instruments", "Apoptosis and migration" ], "citation_contexts": [ "Candidate prioritization: the specified nominal TGFBR2 IVW result with MR assumptions and source-table limitations.", "Experimental biology: lower tissue staining and A549 knockdown responses with small-sample and cell-model boundaries." ], "evidence_scope": { "supports": [ "A reported nominal inverse TGFBR2 MR association in the specified analysis.", "Lower TGFBR2-positive staining in the eight-specimen IHC comparison.", "The specified A549 knockdown-associated assay responses." ], "does_not_establish": [ "Unconditional causality or universal protection against LUAD from a nominal selected-gene MR association.", "Reliable diagnostic, prognostic or treatment-selection performance in clinical practice.", "Drug efficacy or safety from docking predictions.", "That all MR sensitivity results are free of unresolved direction or source-table labeling issues." ] }, "limitations": [ "Results 3.7 is headed increased TGFBR2 expression, while its paragraph, the abstract and Figure 8 show decreased expression. This page explicitly attributes the lower staining direction to the latter sources; no formal correction was found in the current publisher page or JATS links.", "The forward MR result is nominal and comes from a multi-stage selection pipeline. It is not an unconditional causal conclusion or clinical biomarker validation.", "The main text cites Supplementary Table S2 for forward heterogeneity and pleiotropy values, but the downloaded S2 contains LUAD-to-TGFBR2 exposure/outcome labels and different Q-test P values. This page does not claim that those sensitivity results validate absence of heterogeneity or pleiotropy.", "The tissue comparison is small: five LUAD and three control specimens. It does not establish generalizable diagnostic performance.", "Functional testing used A549 only. Triplicate wells in the CCK8 setup are not independent donors; the number of independent biological replicates is not stated uniformly across the reported cell assays.", "The paper reports computational drug predictions. No clinical drug efficacy or safety is established." ], "scope_source": "data/deep_geo/doi-10-3389-fonc-2024-1425895.json#/evidence_scope" }, { "id": "doi-10-1093-hmg-ddae189", "title": "Integrated multi-omics analysis revealed the molecular networks and potential targets of cellular senescence in Alzheimer’s disease", "doi": "10.1093/hmg/ddae189", "year": 2024, "journal": "Human Molecular Genetics", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1093-hmg-ddae189.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1093-hmg-ddae189.md", "paper_geo_status": "none", "authors": [ "Yudi Xu", "Shutong Liu", "Zhaokai Zhou", "Hongzhuo Qin", "Yuyuan Zhang", "Ge Zhang", "Hongxuan Ma", "Xinwei Han", "Huimin Liu", "Zaoqu Liu" ], "doi_url": "https://doi.org/10.1093/hmg/ddae189", "publisher_url": null, "pmid": "39690817", "pmcid": null, "openalex_id": "https://openalex.org/W4405558741", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1093-hmg-ddae189.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1093-hmg-ddae189.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1093-hmg-ddae189.csl.json", "evidence_status": "limited", "question_count": 0, "key_findings": [], "field_entry": [], "review_topics": [], "concepts": {}, "evidence_url": "https://drgezhang.com/papers/doi-10-1093-hmg-ddae189.html#limited-evidence", "source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/limited_evidence.json", "provenance": [ { "url": "https://academic.oup.com/hmg/article/34/5/381/7926367", "label": "Official publisher article and publication history", "format": "Publisher HTML and complete 11-page publisher-typeset advance-article PDF obtained through the authorized author account", "locator": "DOI 10.1093/hmg/ddae189; advance publication 18 December 2024; final issue 34(5), 381–391 (2025). Main Figures 1–4, Table 1 and Methods were reviewed." }, { "url": "https://academic.oup.com/hmg/article/34/5/381/7926367#supplementary-data", "label": "Official publisher supplementary data", "format": "Three unique files: two DOCX files and one XLSX workbook, acquired 27 October 2026", "locator": "supplementary_figure_ddae189.docx: Figures 1–6; supplementary_table_ddae189.xlsx: Tables 1–11; supplementary_materials_ddae189.docx: STROBE-MR checklist, especially item 4d. These materials have been obtained and inspected." }, { "url": "https://r9.risteys.finngen.fi/endpoints/G6_ALZHEIMER", "label": "FinnGen R9 official Alzheimer endpoint", "format": "Official Risteys endpoint HTML, retrieved 27 October 2026", "locator": "G6_ALZHEIMER: Case counts → Remove individuals based on genotype QC, 9,301 cases. Control definition is all non-cases; this page does not independently supply the paper’s exact control total or identify its actual analysis input." } ], "scope": "The complete 11-page publisher advance article and three official supplementary files have been reviewed. A conflict over the actual GWAS analysis input prevents full V2 certification; the verified source context and bounded expression observations are recorded below.", "evidence_notice": "The complete 11-page publisher advance article and three official supplementary files have been reviewed. A conflict over the actual GWAS analysis input prevents full V2 certification; the verified source context and bounded expression observations are recorded below.", "evidence_scope": null, "limitations": [ "Full V2 remains on hold until an exact archived GWAS input filename/release and checksum, linked to the analysis code or run record, or a formal author clarification resolves which dataset generated the MR estimates. Agreement between the main Methods and the official R9 case count does not establish the analysis input used.", "The source contains unresolved mediation annotations: Figure 1 labels an EXOSC9 probe differently from Table 1/Figure 3C, and Figure 3 coefficients differ from the MR tables, including a SLFN12 sign discrepancy. This note neither corrects the labels nor certifies the proposed mediation chains.", "The qPCR supplement lists four values per group per target and the immunoblot supplement lists three entries per group; biological independence is not specified. The qPCR plot/table scale discrepancy remains unresolved, so no exact fold change, effective biological sample size or plotted P value is certified.", "MR depends on instrument relevance, independence and exclusion restriction. The reported sensitivity checks do not prove all assumptions, and the supplement reports significant SLFN12 heterogeneity. Gene-target causality is not established by this limited note.", "The PC12 experiments measure expression after an amyloid-peptide challenge. They do not test gene knockdown or rescue, animal disease modification, patient outcomes, or the safety and efficacy of a treatment. 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Results 3.4: Protein-Protein Interaction Network Analysis of DEPs in DCM-HF; Fig. 3A-E; Fig. S2", "source": "data/deep_geo/olink-dcm.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/olink-dcm.html#kf6" } ], "field_entry": [ "Cardiovascular biomarker research", "Dilated cardiomyopathy and heart failure" ], "review_topics": [ "Blood protein biomarkers in cardiomyopathy", "Targeted proteomics for biomarker discovery" ], "concepts": { "conditions": [ "dilated cardiomyopathy", "DCM-HF", "heart failure", "chronic heart failure", "ventricular systolic dysfunction" ], "biomarkers_proteins": [ "SPP1", "osteopontin", "IGFBP7", "F11R", "JAM-A", "CHI3L1", "YKL-40", "PLAUR", "uPAR", "NT-proBNP", "BLM hydrolase", "CSTB", "LGALS4", "Galectin-4", "CCL15", "CDH5", "CXCL16", "SR-PSOX", "CCL2" ], "clinical_phenotypes": [ "LVEF", "NT-proBNP", "CRP", "eGFR", "LDL-C", "albumin", "heart rate" ], "biological_processes": [ "inflammation", "extracellular-matrix remodeling", "fibrosis", "cell adhesion", "fibrinolysis", "tissue repair", "cell migration", "cell proliferation", "platelet aggregation", "apoptosis-related programs" ], "data_types": [ "plasma targeted proteomics", "plasma ELISA", "human cardiac transcriptomics", "clinical phenotypes" ], "assays_platforms": [ "Olink Cardiovascular III", "proximity extension assay", "Normalized Protein eXpression", "NPX", "ELISA" ], "methods": [ "OlinkAnalyze", "false-discovery-rate correction", "Pearson correlation", "Gene Ontology", "KEGG", "STRING", "Cytoscape", "CytoHubba", "NetworkAnalyst", "binary logistic regression", "ROC analysis" ], "external_datasets": [ "GSE116250", "GSE141910", "GSE165303" ], "evidence_concepts": [ "biomarker discovery", "independent assay replication", "diagnostic discrimination", "cross-modality external evaluation", "hypothesis-generating biological interpretation" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Cross-sectional targeted plasma-proteomics biomarker discovery and validation study with external human cardiac transcriptomic evaluation", "evidence_type": "Targeted plasma proteomics, independent plasma ELISA replication, cardiac transcriptomics, ROC analysis, clinical correlation analysis, functional enrichment, and protein-protein interaction analysis", "population": "Locally recruited adults with dilated cardiomyopathy and heart failure (DCM-HF) and healthy controls, together with external human DCM and non-failing/control cardiac transcriptomic datasets", "primary_endpoint": "Identification and independent plasma-assay replication of DCM-HF-associated protein biomarkers", "secondary_endpoint": "Evaluation of diagnostic discrimination of the corresponding gene-expression panel across external cardiac transcriptomic datasets and biological/clinical contextualization of the differential-protein set", "data_modalities": [ "targeted plasma proteomics", "plasma ELISA", "human cardiac transcriptomics", "clinical phenotypes", "functional enrichment and protein-interaction analysis" ], "external_validation": true, "scale_metrics": [ { "label": "local participants", "value": "103: 50 DCM-HF and 53 healthy controls" }, { "label": "Olink discovery cohort", "value": "38 participants: 20 DCM-HF and 18 healthy controls" }, { "label": "Olink panel", "value": "92 cardiovascular-related proteins" }, { "label": "proteins differing at p<0.05", "value": "33" }, { "label": "focused differentially abundant proteins", "value": "13; all higher in DCM-HF, P<0.001 in Results and significant after FDR correction" }, { "label": "prioritized candidate markers", "value": "5: SPP1, IGFBP7, F11R, CHI3L1 and PLAUR" }, { "label": "independent ELISA cohort", "value": "65 participants: 30 DCM-HF and 35 healthy controls" }, { "label": "external cardiac transcriptomic datasets", "value": "3: GSE116250, GSE141910 and GSE165303" }, { "label": "combined five-gene AUCs", "value": "0.959, 0.773 and 0.803, respectively" }, { "label": "external-evaluation modality", "value": "human cardiac gene expression; not independent plasma proteomics" } ], "counting_note": "The article reports 103 local participants across two separate cohorts: 38 participants in the Olink discovery cohort and 65 participants in the ELISA validation cohort. These local counts can be combined because the article explicitly reports 50 DCM-HF patients and 53 healthy controls overall. The three external GEO datasets are different evidence units: article-reported analyzed sample counts differ from native or independently documented dataset composition for several accessions. External dataset counts are therefore preserved as reported in provenance and are not aggregated into a derived external total n." }, "study_profile_source": "data/deep_geo/olink-dcm.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/olink-dcm.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/olink-dcm.json", "gold_content_sha256": "7feffbf278a710ece359a04f7a9bb84b37dfb96392bc86b3991d5479da260930", "provenance": { "publisher_url": "https://pubs.acs.org/doi/10.1021/acs.jproteome.4c00522", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/39129220/", "pmcid": "PMC11385702", "doi_url": "https://doi.org/10.1021/acs.jproteome.4c00522", "version_of_record": "Journal of Proteome Research, Volume 23, Issue 9, pages 4139-4150; published online 12 August 2024 and in issue 6 September 2024", "license": "Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0)", "local_ethics": "The article reports Institutional Review Board approval from the Fourth Affiliated Hospital of Soochow University, approval 2022-KT-105.", "article_reported_registration": "The article reports ChiCTR2100051469; this identifier is retained as article-reported provenance only because public registry indexing appears inconsistent with the DCM-HF proteomics study.", "external_datasets": "GSE116250; GSE141910; GSE165303", "supporting_material": "Table S1: all 92 Olink Cardiovascular III proteins; Tables S2-S4: correlation analyses; Table S5: raw ELISA validation data; Figure S1: study flowchart; Figure S2: NetworkAnalyst/PPI analysis; Figure S3: DEP-clinical-indicator correlation visualization", "code_repository": "No dedicated article-specific code repository was identified in the reviewed version-of-record resources.", "source_note_external_counts": "The article reports GSE116250 as 15 controls and 38 DCM, GSE141910 as 162 controls and 162 DCM, and GSE165303 as 48 controls and 74 DCM. Native or independently documented dataset composition differs: GSE116250 contains 14 non-failing, 37 DCM and 13 ischemic-cardiomyopathy samples; GSE141910 is documented as a 366-sample left-ventricular resource including 166 non-failing and 166 DCM samples plus HCM and PPCM; GSE165303 is a multi-assay heart-tissue series whose RNA-seq subset is independently documented as 51 non-failing and 50 DCM hearts. The exact filtering logic used to obtain the article-reported analyzed counts is not fully specified, so this evidence page preserves the discrepancy and does not aggregate an external total n.", "source_note_registration": "The article reports ChiCTR2100051469. Publicly indexed information for that identifier describes a magnetocardiography/myocardial-ischemia diagnostic study rather than this DCM-HF proteomics study, so the registration linkage is treated as unresolved and should not be represented as a verified ClinicalTrial entity or trial sameAs link.", "source_note_mouse_models": "The Introduction refers to exploring mechanisms in human plasma and mouse models, but the Methods and Results do not describe an original animal experiment in this publication. Mouse evidence discussed in the article derives from cited prior studies and is not treated as evidence generated by this study.", "evidence_basis": "ACS version of record and Supporting Information, PubMed/PMC records, NCBI GEO records, and independently documented dataset composition used to audit provenance discrepancies" }, "scientific_role": "Targeted plasma-protein discovery with local ELISA replication and separate cardiac gene-expression evaluation in DCM-HF.", "evidence_position": "Human cross-sectional candidate-biomarker study; tissue-transcriptomic evaluation is not plasma-proteomic replication, and prospective clinical utility is not established.", "related_concepts": [ "Circulating protein candidates", "Cross-assay biomarker evaluation" ], "citation_contexts": [ "Background: circulating molecular biomarkers in dilated cardiomyopathy with heart failure.", "Methods: targeted protein panels and orthogonal assay evaluation, with plasma and cardiac-tissue evidence kept separate." ], "evidence_scope": { "supports": [ "A predefined 92-protein cardiovascular Olink panel detected differential plasma protein abundance between the studied DCM-HF and healthy-control groups.", "Thirteen proteins showed marked higher abundance in the Olink discovery analysis and remained significant after FDR correction.", "SPP1, IGFBP7, F11R, CHI3L1 and PLAUR showed directionally consistent higher plasma levels in an independent local ELISA cohort.", "The corresponding five-gene expression panel showed diagnostic discrimination across three external human cardiac transcriptomic datasets.", "Several DCM-HF-associated plasma proteins were correlated with clinical indicators including NT-proBNP, LVEF, CRP and eGFR in the studied cohort.", "Functional-enrichment and protein-interaction analyses provide biological hypotheses involving inflammatory, remodeling and related processes.", "The five prioritized markers constitute candidates for larger biomarker-validation studies." ], "does_not_establish": [ "That the Olink analysis provides an unbiased whole-proteome survey; it used a predefined targeted cardiovascular panel.", "That the 13 differentially abundant proteins cause DCM-HF or directly determine disease severity.", "That SPP1, IGFBP7, F11R, CHI3L1 or PLAUR are clinically validated diagnostic tests for DCM-HF.", "That external cardiac transcriptomic evaluation constitutes independent plasma-proteomic replication.", "That ROC discrimination in existing case-control/transcriptomic datasets predicts who will develop DCM-HF prospectively.", "That the five-marker panel has demonstrated incremental clinical utility over echocardiography, cardiac MRI, NT-proBNP, troponin, or standard diagnostic assessment.", "That correlation, GO/KEGG enrichment or PPI-network analysis establishes a causal molecular mechanism.", "That any of the identified proteins is a validated therapeutic target or that biomarker-guided treatment improves clinical outcomes.", "That this publication generated original mouse-model evidence; the Methods and Results do not describe an animal experiment." ] }, "limitations": [ "The Olink discovery cohort was small, with 20 DCM-HF patients and 18 healthy controls.", "The Olink assay was a predefined 92-protein cardiovascular panel rather than an unbiased whole-proteome measurement.", "The local discovery and ELISA analyses were cross-sectional and do not establish prospective incident-disease prediction or longitudinal prognostic performance.", "The external GEO evaluation used cardiac transcriptomic data rather than independent plasma-proteomic cohorts, so it supports corresponding gene-expression discrimination rather than direct protein-level replication.", "Article-reported sample counts for the external GEO datasets differ from native or independently documented dataset composition, and the exact filtering logic is not fully specified.", "Clinical correlations were exploratory and were not independently replicated for each protein-clinical-variable relationship.", "GO/KEGG, STRING, Cytoscape and related analyses are computational and do not establish causal mechanisms or therapeutic efficacy.", "The article reports ChiCTR2100051469, but publicly indexed registry information for that identifier appears to correspond to a different study; 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They do not map new integration sites or demonstrate malignant transformation in an original experiment.", "evidence": [ { "label": "Mechanistic focus", "value": "Insertional mutagenesis and dysregulated cell-growth programs" }, { "label": "Visual support", "value": "Figure 1A, within the article's only conceptual figure" }, { "label": "Related but distinct topic", "value": "HHV-6 reactivation is discussed; a causal HHV-6 pathway to post-CAR-T lymphoma is not established" } ], "source_locator": "Cancer Letters 597 (2024) 217083, PDF p. 2, Section 3.1 (Insertional mutagenesis), references 14-23; p. 3, Figure 1A (conceptual schematic, not an experiment).", "source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#kf2" }, { "id": "KF3", "claim": "Persistent CAR signaling and an inflammatory cytokine environment are proposed as additional contexts in which malignant clones might emerge or expand.", "context": "The discussion draws on external work on activation, exhaustion, inflammation and tumor biology. 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The competing-hypothesis layout is not evidence that CAR-T therapy has no causal role.", "evidence": [ { "label": "Conceptual structure", "value": "Two hypothesis groups, illustrated in Figure 1 panels A and B" }, { "label": "Clinical context", "value": "Prior treatment history, susceptibility and peri-infusion therapy" }, { "label": "Excluded inference", "value": "Figure 1B supplies no statistical test of a null association" } ], "source_locator": "Cancer Letters 597 (2024) 217083, PDF pp. 2 and 4, Section 3.3 (Potential susceptibility and bridging therapy considerations), references 34-52; p. 3, Figure 1B (hypothesis, not a statistical comparison).", "source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#kf4" }, { "id": "KF5", "claim": "Case reports, transgene assays and product-specific observations require separate interpretation before drawing a general safety conclusion.", "context": "The review discusses both CAR-positive and CAR-negative tumors and calls for continued investigation. This evidence page retains that research question while excluding inconsistent denominators and the article's broad reassurance about risk.", "evidence": [ { "label": "Evidence distinction", "value": "Detection of a CAR transgene concerns tumor origin; it is not by itself a complete causal mechanism" }, { "label": "Numerical audit", "value": "Reference 36 confuses patients, events and biopsies; reference 37 mixes early and later follow-up populations" }, { "label": "Supported output", "value": "A critical review framework, not a pooled incidence or proof of universal safety" } ], "source_locator": "Cancer Letters 597 (2024) 217083, PDF pp. 2 and 4, Section 3.3, references 36, 37, 40 and 46; p. 4, Sections 4-5. Numerical cross-check: reference 36, DOI 10.1182/blood.2022015728, Abstract, Results and Table 4 (PMC9346960); reference 37, DOI 10.1182/blood-2023-182817, Background versus Results.", "source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#kf5" } ], "field_entry": [ "Cellular immunotherapy safety", "Hematologic oncology" ], "review_topics": [ "Secondary T-cell malignancy after CAR-T therapy", "Mechanistic and treatment-history explanations" ], "concepts": { "therapy_and_safety": [ "CAR-T cell therapy", "Secondary T-cell malignancy", "Long-term safety surveillance" ], "mechanisms": [ "Insertional mutagenesis", "Persistent cellular activation", "Inflammatory microenvironment" ], "interpretation": [ "Tumor transgene testing", "Host susceptibility", "Treatment-history confounding" ] }, "profile_type": "narrative_review", "study_profile": { "profile_type": "narrative_review", "study_design": "Narrative mechanistic review of secondary T-cell malignancy in the context of CAR-T therapy.", "evidence_type": "Qualitative discussion of regulatory reports, external clinical observations and mechanistic publications; no original intervention, cohort or pooled analysis.", "translation_scope": "Safety-research interpretation for hematologic cancer immunotherapy; no patient-selection rule, risk calculator or treatment recommendation validated here.", "evidence_domains": [ "Vector integration and cellular growth regulation", "Persistent activation, exhaustion and inflammation", "Host susceptibility and previous or peri-infusion treatments", "Tumor transgene testing and long-term safety interpretation" ], "diseases_covered": [ "T-cell malignancies arising after CAR-T therapy", "B-cell and plasma-cell malignancies treated with CAR-T products in cited studies" ], "scale_metrics": [ { "label": "Article format", "value": "5-page narrative review; PubMed PMID 38925363 includes publication type Review" }, { "label": "Conceptual figure", "value": "1 figure with 2 panels; no original data table" }, { "label": "Reference list", "value": "53 numbered entries; entries 13 and 53 repeat the same publication" }, { "label": "New clinical sample", "value": "No original patient cohort or pooled sample size" } ], "counting_note": "Figure and reference counts describe the review, not an experimental denominator. External patients, tumor events and biopsies are different units and cannot be summed as participants recruited by this paper." }, "study_profile_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1016-j-canlet-2024-217083.json", "gold_content_sha256": "9eb6b14f05bfbbe74406a9a5e7ab9a6c7ce08382064d3145d13568da5c937d65", "provenance": { "doi_url": "https://doi.org/10.1016/j.canlet.2024.217083", "publisher_url": "https://www.sciencedirect.com/science/article/pii/S0304383524004786", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/38925363/", "source_url": "https://www.researchgate.net/publication/381691837_The_underlying_mechanism_of_chimeric_antigen_receptor_CAR-T_cell_therapy_triggering_secondary_T-cell_cancers_mystery_of_the_Sphinx", "regulatory_context_url": "https://www.fda.gov/vaccines-blood-biologics/safety-availability-biologics/fda-investigating-serious-risk-t-cell-malignancy-following-bcma-directed-or-cd19-directed-autologous", "count_audit_primary_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9346960/", "followup_abstract_url": "https://ashpublications.org/blood/article/142/Supplement%201/1025/501613/C-CAR039-a-Novel-Anti-CD20-CD19-Bi-Specific-CAR-T", "version_of_record": "Publisher-typeset Cancer Letters 597 (2024) 217083, 5 pages. Available online 24 June 2024; issue dated 10 August 2024. DOI, title and all eight authors match the publisher record, Crossref and PubMed; the existing bibliographic identity is preserved.", "source_artifacts": "Complete publisher-typeset PDF accessed through the authorized ResearchGate author account on 27 October 2026; source file and rendered audit pages retained privately outside the site repository. No supplementary dataset is declared in the supplied article.", "source_sha256": "51b6845804c227cc587784d301ecaa45d1031112e66b90d2ad80435d0298586c", "license": "The PDF states copyright 2024 Elsevier B.V., all rights reserved. ResearchGate is the lawful access channel in the authorized account, not an open redistribution license. Neither the PDF nor its figure is republished.", "identity_note": "Eight-author order confirmed, with Ge Zhang second and affiliated with cardiology at the First Affiliated Hospital of Zhengzhou University. PubMed classifies the work as Review; the site's protected Article metadata is unchanged.", "review_note": "Full text and the single figure inspected. Citation-count discrepancies are disclosed and excluded. Crossref returned no update-to or related-correction entry on 27 October 2026; this does not certify every cited statement.", "scope_note": "Complete V2 representation of a bounded narrative-review core, not blanket validation of all claims or numbers in the source article." }, "scientific_role": "Narrative review organizing candidate mechanisms and competing explanations for T-cell malignancy after CAR-T treatment.", "evidence_position": "Review-level synthesis with disclosed citation-count inconsistencies; no new cohort, pooled incidence or causal safety determination.", "related_concepts": [ "Insertional mutagenesis", "Tumor transgene assays", "Long-term safety surveillance" ], "citation_contexts": [ "Literature background on possible mechanisms and alternative explanations for secondary T-cell malignancy after CAR-T treatment.", "Critical discussion of why case reports, transgene testing and conceptual diagrams cannot supply a general clinical risk estimate." ], "evidence_scope": { "supports": [ "Attribution of the mechanistic and competing-explanation framework to this 2024 narrative review.", "Discussion of insertional mutagenesis, activation, inflammation and prior treatment as research questions, with the cited primary sources consulted for specific claims.", "Recognition that a conceptual diagram, case description and transgene assay answer different questions from a comparative incidence study." ], "does_not_establish": [ "A new clinical cohort, prospective experiment, systematic review or meta-analysis.", "A general incidence of secondary T-cell malignancy, a product ranking or a current patient-specific risk estimate.", "That absence of a CAR transgene excludes every indirect treatment contribution, or that its presence identifies a unique oncogenic driver.", "That HHV-6 reactivation causes post-CAR-T lymphoma, that mature T cells cannot transform, or that Figure 1B proves no association.", "A universal benefit-risk conclusion or advice to ignore a new malignancy after treatment." ] }, "limitations": [ "This is a selective narrative review without a reproducible systematic search, risk-of-bias assessment or pooled analysis. Its 2024 discussion is not a current clinical guideline.", "Section 3.3 describes transgene-negative biopsies from 16 patients when citing reference 36. The cited study's Abstract, Results and Table 4 instead distinguish 13 affected patients, 16 tumor events and 11 available biopsies (DOI 10.1182/blood.2022015728; PMC9346960). No estimate using the review's conflated count is accepted here.", "Section 3.3 uses 28 patients for reference 37. The cited ASH abstract describes 28 as the earlier population in its Background and 48 recipients in its long-term Results (DOI 10.1182/blood-2023-182817). Its event counts cannot be attached to the earlier denominator.", "Figure 1B and the text's suggestion of no significant association are hypotheses, not an original statistical result. Lack of insertion in a recognized oncogene does not demonstrate absence of treatment-related malignant transformation.", "The historical report counts and infusion total in Section 4 are not a matched numerator and denominator; no frequency is calculated. Product-specific reports cannot establish class-wide safety.", "Statements about HHV-6, mature T-cell resistance and inflammatory carcinogenesis must not be promoted from discussion or extrapolation into demonstrated mechanisms of secondary malignancy in humans.", "The article has 53 reference numbers, with the same Ghilardi publication repeated as references 13 and 53. These are not 53 independent studies." ], "scope_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/evidence_scope" }, { "id": "doi-10-2139-ssrn-4857099", "title": "Transition from Sleeve Lobectomy to Lobectomy after Effective Chemoimmunotherapy in Central-Type NSCLC: A Multicenter Retrospective Study", "doi": "10.2139/ssrn.4857099", "year": 2024, "journal": "Preprint", "type": "Preprint", "paper_url": "https://drgezhang.com/papers/doi-10-2139-ssrn-4857099.html", "markdown_url": "https://drgezhang.com/papers/doi-10-2139-ssrn-4857099.md", "paper_geo_status": "none", "authors": [ "Pengpeng Zhang", "Xiao Zhang", "Xiaofei Wang", "Jiaheng Xie", "Ge Zhang", "Zhaokai Zhou", "Yu Zhuang", "Lianmin Zhang", "Zhenfa Zhang" ], "doi_url": "https://doi.org/10.2139/ssrn.4857099", "publisher_url": null, "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W4399480127", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-2139-ssrn-4857099.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-2139-ssrn-4857099.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-2139-ssrn-4857099.csl.json", "evidence_status": "limited", "question_count": 0, "key_findings": [], "field_entry": [], "review_topics": [], "concepts": {}, "evidence_url": "https://drgezhang.com/papers/doi-10-2139-ssrn-4857099.html#limited-evidence", "source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/limited_evidence.json", "provenance": [ { "url": "https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4857099", "label": "SSRN preprint record", "format": "Indexed official landing-page text, not an acquired manuscript", "locator": "Title; author list; 21 Pages Posted: 10 Jun 2024; Preprints with The Lancet notice" } ], "scope": "Preprint-specific identity and research context; the original manuscript and any later-version relationship remain unverified.", "evidence_notice": "Preprint-specific identity and research context; the original manuscript and any later-version relationship remain unverified.", "evidence_scope": null, "limitations": [ "The dated original manuscript, methods, figures and supplements are needed for complete scientific review. No formal version relationship has been established." ], "scope_source": "data/limited_evidence.json#/papers/10.2139~1ssrn.4857099/scope" }, { "id": "doi-10-2147-cia-s462542", "title": "TYG Index as a Novel Predictor of Clinical Outcomes in Advanced Chronic Heart Failure with Renal Dysfunction Patients", "doi": "10.2147/cia.s462542", "year": 2024, "journal": "Clinical Interventions in Aging", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html", "markdown_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.md", "paper_geo_status": "v2", "authors": [ "Chang Su", "Zeyu Wang", "Zhen Qin", "Yan Lv", "Yachen Hou", "Ge Zhang", "Mengdie Cheng", "Xinyue Cui", "Zhiyu Liu", "Pengchong Du", "Tianding Liu", "Peiyu Yuan", "Junnan Tang", "Jinying Zhang" ], "doi_url": "https://doi.org/10.2147/cia.s462542", "publisher_url": null, "pmid": "38706634", "pmcid": "PMC11068055", "openalex_id": "https://openalex.org/W4396222788", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-2147-cia-s462542.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-2147-cia-s462542.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-2147-cia-s462542.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "The analysis comprised 717 patients after follow-up losses, with outcome follow-up of about two years.", "context": "This is an observational advanced-heart-failure population selected for renal dysfunction and repeated HF hospitalization; the initial included population is not the analyzed sample size.", "evidence": [ { "label": "Initially included", "value": "815 patients" }, { "label": "Lost to follow-up", "value": "98 patients (12.0%)" }, { "label": "Analyzed", "value": "717 patients" }, { "label": "Median follow-up (IQR)", "value": "21.58 (17.98–25.39) months" }, { "label": "Renal dysfunction definition", "value": "eGFR <90 mL/min/1.73 m²" } ], "source_locator": "PMC11068055: Method — Study and Population, Inclusion Criteria, Exclusion Criteria, and Follow-Up; Figure 1; Results — Baseline Characteristics.", "source": "data/deep_geo/doi-10-2147-cia-s462542.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#kf1" }, { "id": "KF2", "claim": "A TyG cutoff of 8.48 separated groups with different composite-event risks, with moderate discrimination in the source cohort.", "context": "The endpoint-specific cutoff and ROC performance were derived and evaluated in the same cohort; no independent external validation was reported.", "evidence": [ { "label": "MACEs cutoff", "value": "8.48" }, { "label": "ROC AUC", "value": "0.759" }, { "label": "Sensitivity", "value": "0.836" }, { "label": "Specificity", "value": "0.588" }, { "label": "Low TyG group", "value": "318 patients, TyG <8.48" }, { "label": "High TyG group", "value": "399 patients, TyG ≥8.48" } ], "source_locator": "PMC11068055: Results — Baseline Characteristics; Figure 2; Table 1 (Clinical and Laboratory Characteristics According to the TyG (MACEs), anchor t0001).", "source": "data/deep_geo/doi-10-2147-cia-s462542.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#kf2" }, { "id": "KF3", "claim": "Higher TyG was associated with a higher adjusted hazard of the reported composite adverse-event endpoint.", "context": "The comparison is the high-TyG group versus the low-TyG group in an observational multivariable Cox model. The hazard ratio is not an absolute event probability or a treatment effect.", "evidence": [ { "label": "Adjusted MACEs hazard ratio", "value": "5.402" }, { "label": "95% confidence interval", "value": "3.771–7.739" }, { "label": "Reported significance", "value": "P <0.001 in Results; table rounds P to 0" } ], "source_locator": "PMC11068055: Table 5 — Multivariate Cox Regression Analysis Results for MACEs, TyG row (anchor t0005); Results — Relationship Between TyG and MACEs. The narrative cross-reference points to Table 4, but the verified result is in Table 5.", "source": "data/deep_geo/doi-10-2147-cia-s462542.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#kf3" }, { "id": "KF4", "claim": "The mortality-specific TyG threshold was 8.50, and high TyG remained associated with all-cause mortality after adjustment.", "context": "The mortality cutoff reclassifies the same patients, rather than creating a second independent cohort. Its performance does not establish general clinical transportability.", "evidence": [ { "label": "ACM cutoff", "value": "8.50" }, { "label": "Mortality ROC AUC", "value": "0.700" }, { "label": "Low and high groups", "value": "330 and 387 patients, respectively" }, { "label": "Adjusted mortality hazard ratio", "value": "5.062" }, { "label": "95% confidence interval", "value": "3.268–7.839" }, { "label": "Reported significance", "value": "P <0.001 in Results; table rounds P to 0" } ], "source_locator": "PMC11068055: Results — Baseline Characteristics and Relationship Between TyG and ACM; Figure 3; Table 2 (anchor t0002); Table 6 — Multivariate Cox Regression Analysis Results for ACM, TyG row (anchor t0006).", "source": "data/deep_geo/doi-10-2147-cia-s462542.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#kf4" } ], "field_entry": [ "Cardiorenal medicine", "Clinical prognosis" ], "review_topics": [ "Metabolic biomarkers in advanced heart failure", "Risk assessment with impaired kidney function" ], "concepts": { "Clinical setting": [ "Advanced chronic heart failure", "Renal dysfunction", "Cardiorenal risk" ], "Biomarkers": [ "Triglyceride-glucose index", "Insulin-resistance surrogate" ], "Methods": [ "Retrospective cohort", "Cox proportional-hazards regression", "ROC threshold selection", "Prognostic association" ] }, "profile_type": "clinical_cohort", "study_profile": { "profile_type": "clinical_cohort", "study_design": "Retrospective single-center observational cohort; admissions from September 2019 through December 2020, with follow-up completed in March 2022", "evidence_type": "Admission laboratory biomarker association with longitudinal outcomes, using outcome-derived ROC thresholds, Cox regression and Kaplan-Meier analyses", "population": "Adults with advanced chronic heart failure, eGFR below 90 mL/min/1.73 m², and at least two heart-failure hospitalizations at the First Affiliated Hospital of Zhengzhou University; 717 analyzed after 98 losses among 815 initially included", "primary_endpoint": "Reported MACEs composite: cardiovascular or non-cardiovascular death, worsening-HF rehospitalization, heart transplantation, mechanical circulatory support, malignant arrhythmia, myocardial infarction, or unstable-angina rehospitalization; this is broader than a conventional three-point MACE endpoint", "secondary_endpoint": "All-cause mortality during follow-up; reported median follow-up 21.58 months (interquartile range 17.98–25.39)", "data_modalities": [ "Retrospective inpatient and outpatient records", "Admission fasting triglyceride and glucose measurements", "Telephone and clinic follow-up", "Clinical laboratory values and medication history" ], "external_validation": false, "unique_total_n": 717, "cohorts": [ { "name": "Analyzed single-center cohort", "n": 717, "role": "Same cohort used for threshold selection, association estimation and outcome assessment" } ] }, "study_profile_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-2147-cia-s462542.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-2147-cia-s462542.json", "gold_content_sha256": "9432ef9271d6440c557140ea7c359175feb47967e4294557cfc3d9eb0fd68f66", "provenance": { "source_of_truth": "Version-of-record article in Clinical Interventions in Aging, 2024;19:639–654; PubMed PMID 38706634; PMC11068055. The complete PMC XML and its hash were retained privately on 2026-10-14.", "original_article_url": "https://doi.org/10.2147/CIA.S462542", "full_text_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC11068055/", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/38706634/", "license": "Article-specific CC BY-NC 3.0 notice in the PMC permissions section. This evidence narrative is an original summary; no publisher figures or full article text are republished here.", "license_url": "https://creativecommons.org/licenses/by-nc/3.0/", "identity_verification": "Ge Zhang is formally listed with the Department of Cardiology, First Affiliated Hospital of Zhengzhou University and the cardiovascular research-center/key-laboratory affiliations, consistent with the existing ORCID-derived master record. The article does not supply a Ge Zhang-specific ORCID identifier.", "version_relationship": "Published journal article; no linked preprint relation was established from the checked article metadata.", "numeric_verification": "Cohort flow, ROC thresholds and group sizes were checked against Methods, Results, Figures 1–3 and Tables 1–2. Adjusted estimates were checked directly against the TyG rows of Tables 5–6; rounded table P values are not interpreted as exact zero." }, "scientific_role": "Single-center observational assessment of admission TyG and subsequent adverse outcomes in advanced HF with renal dysfunction.", "evidence_position": "Retrospective biomarker association with outcome-derived cutoffs in one cohort; neither external validation nor a TyG-targeted treatment study.", "related_concepts": [ "Triglyceride-glucose index interpretation", "Prognostic threshold transportability" ], "citation_contexts": [ "Background: metabolic risk markers in advanced HF complicated by renal dysfunction.", "Methods: why same-cohort ROC cutoffs and adjusted hazards require external validation before clinical use." ], "evidence_scope": { "supports": [ "A prognostic association between admission TyG and subsequent outcomes in this selected retrospective cohort.", "Outcome-specific discrimination and hazard-ratio estimates under the study definitions and modeling choices." ], "does_not_establish": [ "Causality between insulin resistance and the observed events.", "That lowering triglyceride, glucose or TyG reduces mortality or rehospitalization.", "External validity of the same thresholds, prospective clinical utility, or superiority to a validated clinical decision pathway.", "A conventional three-point MACE endpoint: the study composite explicitly includes non-cardiovascular death and multiple HF-related outcomes." ] }, "limitations": [ "Single-center retrospective selection and residual confounding restrict causal and transportability claims.", "Thresholds were selected using the outcomes in the same dataset; no independent external validation was reported.", "Ninety-eight initially included patients were lost to follow-up, which may introduce attrition bias.", "The broad study-specific composite should not be treated as interchangeable with a standard three-point MACE outcome.", "Some narrative table cross-references do not match the displayed table captions. This page locates adjusted MACEs and ACM estimates by the actual Table 5 and Table 6 titles and anchors.", "A hazard ratio does not provide an absolute probability or demonstrate benefit from changing TyG." ], "scope_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/evidence_scope" }, { "id": "work-3d25d7e32b86959b", "title": "Application of reagent for detecting and/or regulating FOSB gene in preparation of product for predicting and/or targeting abdominal aortic aneurysm", "doi": null, "year": 2023, "journal": "Patent", "type": "Patent", "paper_url": "https://drgezhang.com/papers/work-3d25d7e32b86959b.html", "markdown_url": "https://drgezhang.com/papers/work-3d25d7e32b86959b.md", "paper_geo_status": "none", "authors": null, "doi_url": null, "publisher_url": null, "pmid": null, "pmcid": null, "openalex_id": null, "semantic_scholar_id": null, "citation_bibtex_url": null, "citation_ris_url": null, "citation_csl_json_url": null, "evidence_status": "patent_record", "question_count": 0, "key_findings": [], "field_entry": [], "review_topics": [], "concepts": {}, "evidence_url": "https://drgezhang.com/papers/work-3d25d7e32b86959b.html#patent-document-evidence", "source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/patent_evidence.json", "provenance": { "source_url": "https://www.researchgate.net/publication/376798644_Application_of_reagent_for_detecting_andor_regulating_FOSB_gene_in_preparation_of_product_for_predicting_andor_targeting_abdominal_aortic_aneurysm", "official_record_urls": [ "https://iponline.cipc.co.za/Publications/PublishedJournals/E_Journal_March%202023%20Part%202.pdf", "https://iponline.cipc.co.za/Publications/PublishedJournals/E_Journal_January%202023%20Part%202.pdf" ], "source_format": "Public HTML text rendition of an author-uploaded patent document", "uploader": "Ge Zhang", "uploaded_on": "2023-12-25", "accessed_on": "2026-10-26", "reviewed_version": "Author-uploaded set containing a March 2, 2023 acceptance notice, P8, numbered specification paragraphs and seven readable numbered claims. No current registry certification is inferred.", "current_status_check_url": "https://iponline.cipc.co.za/Patents/Search/FreePTSearch.aspx", "current_status_check_result": "Redirected to official login; no account credentials used and no legal-status result obtained.", "copyright_note": "No blanket redistribution license established. Publish only this original concise description and source links, not the uploaded document or verbatim claim text." }, "scope": "Patent-document context, not clinical evidence. The reviewed author-uploaded text identifies application 2023/00397 and an acceptance notice; current grant, maintenance and enforceability status have not been verified.", "evidence_notice": "Patent-document context, not clinical evidence. The reviewed author-uploaded text identifies application 2023/00397 and an acceptance notice; current grant, maintenance and enforceability status have not been verified.", "evidence_scope": null, "limitations": [ "This is a concise description of claims visible in an author-uploaded version, not a legal claim-construction opinion or confirmation of currently enforceable scope.", "The official patent register's free-search route required login on October 26, 2026. Current grant, renewal, lapse, amendment and enforceability status are unknown.", "The PDF binary was not obtained. Some opening text has unreadable font encoding; drawing images and sequence-listing content were not independently inspected.", "The historical title wording and inventor-order differences remain unresolved as bibliographic issues. Existing website identity is preserved.", "Patent acceptance and claimed applications do not demonstrate clinical accuracy, safety, efficacy or regulatory approval." ], "scope_source": "data/patent_evidence.json#/evidence_notice" }, { "id": "doi-10-2139-ssrn-4391582", "title": "Artificial Intelligence-Powered Comprehensive Framework Develops a Survival Assessment System by Multicenter Integration for Advanced Heart Failure with Renal Dysfunction", "doi": "10.2139/ssrn.4391582", "year": 2023, "journal": "Preprint", "type": "Preprint", "paper_url": "https://drgezhang.com/papers/doi-10-2139-ssrn-4391582.html", "markdown_url": "https://drgezhang.com/papers/doi-10-2139-ssrn-4391582.md", "paper_geo_status": "none", "authors": [ "Ge Zhang", "Zeyu Wang", "Zhuang Tong", "Zhen Qin", "Chang Su", "Demin Li", "Youyang Zheng", "Teng Li", "Jinying Zhang", "Junnan Tang" ], "doi_url": "https://doi.org/10.2139/ssrn.4391582", "publisher_url": null, "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W4328007711", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-2139-ssrn-4391582.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-2139-ssrn-4391582.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-2139-ssrn-4391582.csl.json", "evidence_status": "limited", "question_count": 0, "key_findings": [], "field_entry": [], "review_topics": [], "concepts": {}, "evidence_url": "https://drgezhang.com/papers/doi-10-2139-ssrn-4391582.html#limited-evidence", "source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/limited_evidence.json", "provenance": [ { "url": "https://api.crossref.org/works/10.2139/ssrn.4391582", "label": "DOI deposit", "format": "Official Crossref metadata, not a manuscript", "locator": "message.title; message.type; message.subtype; message.author[0:10]; message.published" } ], "scope": "Preprint-specific identity and research context; the original manuscript and any later-version relationship remain unverified.", "evidence_notice": "Preprint-specific identity and research context; the original manuscript and any later-version relationship remain unverified.", "evidence_scope": null, "limitations": [ "The dated original manuscript, methods, figures and supplements are needed for complete scientific review. No formal version relationship has been established." ], "scope_source": "data/limited_evidence.json#/papers/10.2139~1ssrn.4391582/scope" }, { "id": "apvs", "title": "Atherosclerotic plaque vulnerability quantification system for clinical and biological interpretability", "doi": "10.1016/j.isci.2023.107587", "year": 2023, "journal": "iScience", "type": "Article", "paper_url": "https://drgezhang.com/papers/apvs.html", "markdown_url": "https://drgezhang.com/papers/apvs.md", "paper_geo_status": "v2", "authors": [ "Ge Zhang", "Xiaolin Cui", "Zhen Qin", "Zeyu Wang", "Yongzheng Lu", "Yanyan Xu", "Shuai Xu", "Laiyi Tang", "Li Zhang", "Gangqiong Liu", "Xiaofang Wang", "Jinying Zhang", "Junnan Tang" ], "doi_url": "https://doi.org/10.1016/j.isci.2023.107587", "publisher_url": "https://linkinghub.elsevier.com/retrieve/pii/S2589004223016644", "pmid": "37664595", "pmcid": "PMC10470306", "openalex_id": "https://openalex.org/W4385707803", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/apvs.bib", "citation_ris_url": "https://drgezhang.com/citations/apvs.ris", "citation_csl_json_url": "https://drgezhang.com/citations/apvs.csl.json", "evidence_status": "reviewed_v2", "question_count": 8, "key_findings": [ { "id": "KF1", "claim": "The integrative machine-learning program reduced 96 dysregulated co-expression pattern genes to a 14-gene APVS signature.", "context": "APVS generation and model selection across nine classical machine-learning learners", "evidence": [ { "label": "candidate DCPGs", "value": "96" }, { "label": "machine-learning learners", "value": "9" }, { "label": "selected APVS genes", "value": "14" }, { "label": "optimal learners", "value": "random forest and backpropagation neural network" }, { "label": "learner evaluation", "value": "10-fold cross-validation with 100 repetitions" }, { "label": "feature selection", "value": "RF-RFE with 10-fold, 10-repeated cross-validation" } ], "source_locator": "Results: Machine learning-based integrative program generates APVS; Fig. 2A-E; Methods: APVS generated from an integrative program", "source": "data/deep_geo/apvs.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/apvs.html#kf1" }, { "id": "KF2", "claim": "The APVS classifier showed strong discrimination across independent datasets spanning clinical and pathological atherosclerotic states.", "context": "Independent external validation of STEMI/CCS, plaque-stage, plaque-rupture, and STEMI/healthy comparisons", "evidence": [ { "label": "GSE59867 STEMI vs CCS AUC", "value": "0.985" }, { "label": "GSE62646 STEMI vs CCS AUC", "value": "0.997" }, { "label": "GSE28829 advanced vs early plaque AUC", "value": "0.952" }, { "label": "GSE41571 ruptured vs stable plaque AUC", "value": "0.972" }, { "label": "GSE48060 STEMI vs healthy AUC", "value": "0.871" }, { "label": "GSE60993 STEMI vs healthy AUC", "value": "0.916" }, { "label": "GSE141512 STEMI vs healthy AUC", "value": "1.000" } ], "source_locator": "Results: Robust performance of APVS-based classifier; Fig. S2B and Fig. 3A-B", "source": "data/deep_geo/apvs.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/apvs.html#kf2" }, { "id": "KF3", "claim": "Higher APVSLevel was associated with worse cardiovascular prognosis and greater coronary atherosclerotic severity.", "context": "Clinical interpretability analyses across MACE and coronary stenosis datasets", "evidence": [ { "label": "MACE association", "value": "HR 3.819; p<0.01" }, { "label": "high vs low APVSLevel MACE incidence", "value": "log-rank p<0.01" }, { "label": "APVSLevel vs coronary stenosis degree", "value": "p<0.001" }, { "label": "APVSLevel vs Duke CAD Index", "value": "p<0.01" } ], "source_locator": "Results: The clinical interpretability underlying APVSLevel; Fig. 4A-D and Fig. 4J", "source": "data/deep_geo/apvs.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/apvs.html#kf3" }, { "id": "KF4", "claim": "APVSLevel reproduced plaque-vulnerability differences at single-cell resolution.", "context": "Two single-cell RNA-sequencing cohorts comparing atherosclerotic core with adjacent normal tissue and vulnerable STEMI plaques with stable CCS plaques", "evidence": [ { "label": "GSE159677 cells", "value": "43,964" }, { "label": "atherosclerotic core vs adjacent normal APVSLevel", "value": "higher in atherosclerotic core; p<0.0001" }, { "label": "GSE184073 cells", "value": "2,237" }, { "label": "vulnerable STEMI vs stable CCS plaque APVSLevel", "value": "higher in vulnerable STEMI plaques; p<0.0001" } ], "source_locator": "Results: Single-cell resolution interpretation of the biological significance of APVSLevel; Fig. 7A-B and Fig. S13A", "source": "data/deep_geo/apvs.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/apvs.html#kf4" }, { "id": "KF5", "claim": "High plaque vulnerability was linked to inflammatory macrophage states and loss of plaque-stabilizing fibrotic macrophage phenotypes.", "context": "Single-cell macrophage-state analysis in vulnerable STEMI versus stable CCS plaques", "evidence": [ { "label": "CXCL3+/IL1B+ inflammatory macrophages", "value": "higher APVSLevel in STEMI plaques" }, { "label": "C1Q+ fibrotic macrophages", "value": "lower APVSLevel in STEMI plaques" }, { "label": "APVSLevel-high atherosclerotic core", "value": "more monocyte/macrophage and endothelial cells; fewer myofibroblast and SMC populations" } ], "source_locator": "Results: Single-cell resolution interpretation; Fig. 7C-E and Fig. S14", "source": "data/deep_geo/apvs.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/apvs.html#kf5" }, { "id": "KF6", "claim": "APVSLevel-high plaques showed a more inflammatory, procoagulant, and matrix-destabilizing molecular state, whereas APVSLevel-low plaques were relatively stromal-rich and fibrotic.", "context": "Bulk and single-cell pathway-level biological interpretation", "evidence": [ { "label": "APVSLevel-high pathways", "value": "coagulation cascade, collagen degradation, Notch signaling, TLR signaling" }, { "label": "APVSLevel-high cell programs", "value": "inflammatory response, granulocyte activation, macrophage M1 polarization" }, { "label": "APVSLevel-low phenotype", "value": "stromal-rich, fibroblast migration, fibrous content, relative immune suppression" }, { "label": "single-cell high-vulnerability programs", "value": "coagulation, hypoxia, TNF signaling, heme metabolism, oxidative stress, senescence, DNA damage" } ], "source_locator": "Results: The biological implications underlying APVSLevel; Fig. 5, Fig. S6-S8, Fig. 7E, and Fig. S14D-E", "source": "data/deep_geo/apvs.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/apvs.html#kf6" }, { "id": "KF7", "claim": "Plaque vulnerability was accompanied by remodeling of macrophage-myofibroblast communication networks.", "context": "CellChat and NicheNet analyses of APVSLevel-high versus APVSLevel-low atherosclerotic core states", "evidence": [ { "label": "pro-inflammatory signaling", "value": "MIF and VCAM strengthened in APVSLevel-high states" }, { "label": "profibrogenic signaling", "value": "SPP1 and FN1 reduced in APVSLevel-high states" }, { "label": "Mono/Mac-directed ligand-target axes", "value": "IL34/CTSK; IL6/SOCS3; AGT/SPP1; APOE/SPP1" }, { "label": "myofibroblast-directed ligand-target axes", "value": "CXCL2/CDKN1A; ADM/CCL2; NRG1/FOS; ITGB2/CCL2" } ], "source_locator": "Results: Intercellular crosstalk within the atherosclerotic core was remodeled by APVS; Fig. 7F-K and Fig. S15-S16", "source": "data/deep_geo/apvs.json#/key_findings/6", "evidence_url": "https://drgezhang.com/papers/apvs.html#kf7" } ], "field_entry": [ "Atherosclerosis research", "Computational cardiovascular medicine" ], "review_topics": [ "Molecular assessment of plaque vulnerability", "Transcriptomic characterization of coronary disease" ], "concepts": { "conditions": [ "atherosclerosis", "coronary artery disease", "acute myocardial infarction", "ST-elevation myocardial infarction", "chronic coronary syndrome", "acute coronary syndrome" ], "plaque_phenotypes": [ "atherosclerotic plaque vulnerability", "stable plaque", "ruptured plaque", "early-stage plaque", "advanced plaque", "atherosclerotic core", "fibrous plaque" ], "outcomes": [ "major adverse cardiovascular events", "coronary stenosis", "plaque rupture", "restenosis after PCI" ], "methods": [ "machine learning", "random forest", "backpropagation neural network", "recursive feature elimination", "weighted gene co-expression network analysis", "principal coordinates analysis", "single-cell RNA sequencing", "gene set enrichment analysis", "gene set variation analysis", "DIRAC", "VissE", "xCell", "CellChat", "NicheNet", "Subclass Mapping" ], "models_tools": [ "APVS", "APVS classifier", "APVSLevel" ], "cell_types": [ "monocyte/macrophage", "vascular smooth muscle cell", "myofibroblast", "endothelial cell", "B cell", "plasma cell", "mast cell", "neutrophil", "foam cell" ], "pathways_processes": [ "inflammation", "coagulation", "extracellular matrix degradation", "fibrosis", "oxidative stress", "cellular senescence", "DNA damage", "Notch signaling", "TLR signaling", "TNF signaling", "heme metabolism", "cholesterol homeostasis" ], "mechanistic_entities": [ "CXCL3", "IL1B", "C1Q", "IL34", "CTSK", "IL6", "SOCS3", "AGT", "SPP1", "APOE", "CXCL2", "CDKN1A", "ADM", "CCL2", "NRG1", "FOS", "ITGB2", "FN1", "MIF", "VCAM" ], "datasets_cohorts": [ "GSE59867", "GSE62646", "GSE28829", "GSE41571", "GSE48060", "GSE60993", "GSE141512", "GSE21545", "GSE159677", "GSE184073" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Retrospective multicohort computational systems biology study", "evidence_type": "Bulk transcriptomics, single-cell RNA sequencing, machine learning, and clinical association analyses", "population": "Atherosclerotic and coronary artery disease samples spanning stable and unstable clinical and pathological states", "primary_endpoint": "Discrimination of atherosclerotic and coronary pathological states using the APVS classifier", "secondary_endpoint": "Clinical and biological quantification of plaque vulnerability using APVSLevel", "data_modalities": [ "bulk transcriptomics", "single-cell RNA sequencing", "clinical outcomes", "coronary stenosis phenotypes" ], "external_validation": true, "scale_metrics": [ { "label": "bulk transcriptomic cohorts", "value": "22" }, { "label": "bulk samples reported in Summary", "value": "2,235" }, { "label": "single-cell cohorts", "value": "2" }, { "label": "single-cell samples reported in Summary", "value": "14" }, { "label": "GSE159677 single-cell scale", "value": "43,964 cells from 3 atherosclerotic cores and 3 adjacent normal tissues" }, { "label": "GSE184073 single-cell scale", "value": "2,237 cells from plaques of 3 STEMI and 4 CCS patients" } ], "counting_note": "The publication reports 2,235 samples from 22 bulk cohorts and 14 samples from two single-cell cohorts in the Summary, while detailed single-cell analyses describe 3 atherosclerotic cores plus 3 adjacent normal tissues and plaques from 3 STEMI plus 4 CCS patients. These modality-specific counts are preserved as reported and are not combined into a derived unique-participant total." }, "study_profile_source": "data/deep_geo/apvs.json#/study_profile", "model_profile": { "candidate_dcpgs": 96, "algorithm_count": 9, "learner_evaluation": "10-fold cross-validation with 100 repetitions", "optimal_learners": [ "random forest", "backpropagation neural network" ], "feature_selection": "Random-forest recursive feature elimination with Gini-based importance and 10-fold, 10-repeated cross-validation", "signature_size": 14, "classifier": "Backpropagation neural network", "quantification_system": "APVSLevel", "quantification_basis": "APVS expression profile combined with principal-coordinate information" }, "model_profile_source": "data/deep_geo/apvs.json#/model_profile", "narrative_genre": null, "gold_source": "data/deep_geo/apvs.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/apvs.json", "gold_content_sha256": "fa4caf51318364345bc52b8404eecd5cf17f36426c0b7d2d7a3b4c455baad281", "provenance": { "publisher_url": "https://www.cell.com/iscience/fulltext/S2589-0042(23)01664-4", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/37664595/", "pmcid": "PMC10470306", "code_url": "https://github.com/DrZoggg/APVS", "evidence_basis": "Version of record and PMC full text" }, "scientific_role": "Transcriptomic machine-learning framework connecting plaque-vulnerability signatures with bulk and single-cell biological interpretation.", "evidence_position": "Retrospective multicohort human expression analysis; a research framework, not an approved diagnostic test or demonstrated treatment benefit.", "related_concepts": [ "Molecular plaque stratification", "Bulk-to-single-cell interpretation" ], "citation_contexts": [ "Methods: computational approaches to molecular plaque assessment.", "Evidence synthesis: plaque-vulnerability expression signatures and their cellular context, without replacing coronary imaging or clinical assessment." ], "evidence_scope": { "supports": [ "APVS discriminates several studied coronary and plaque pathological states in retrospective transcriptomic datasets.", "APVSLevel is associated with plaque vulnerability, coronary stenosis severity, and MACE risk in the studied cohorts.", "APVSLevel-high states exhibit stronger inflammatory, immune, procoagulant, and plaque-destabilizing molecular programs.", "Single-cell datasets support APVSLevel as a molecular descriptor of vulnerable plaque biology and cellular-state remodeling.", "APVS/APVSLevel can serve as a research framework for molecular stratification and mechanistic exploration of atherosclerotic plaque vulnerability." ], "does_not_establish": [ "That APVS is a clinically approved diagnostic test for plaque vulnerability.", "That the 14 APVS genes are causal drivers of plaque rupture.", "That APVSLevel-guided treatment reduces myocardial infarction, mortality, or other clinical events.", "That transcriptomic APVS/APVSLevel can replace coronary imaging, cardiac biomarkers, or standard clinical assessment.", "That retrospective public-dataset validation is equivalent to prospective multicenter clinical validation.", "That drug-response or signature-reversal analyses constitute therapeutic recommendations." ] }, "limitations": [ "The study was based predominantly on retrospective public high-throughput datasets.", "Prospective multicenter studies are required to confirm the biological and clinical interpretability of APVSLevel.", "The APVS classifier requires further direct comparison with established clinical biomarkers.", "The functions of many APVS-related molecules remain incompletely established and require additional in vivo and in vitro validation.", "Incomplete clinical and molecular traits in source datasets may obscure associations between APVS and some relevant factors." ], "scope_source": "data/deep_geo/apvs.json#/evidence_scope" }, { "id": "doi-10-1016-j-jma-2023-05-007", "title": "Biodegradable Mg alloy modified with bioactive exosomes for cardiovascular stent application", "doi": "10.1016/j.jma.2023.05.007", "year": 2023, "journal": "Journal of Magnesium and Alloys", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.md", "paper_geo_status": "v2", "authors": [ "Ya-chen Hou", "Jing-an Li", "Chang Cao", "Chang Su", "Zhen Qin", "Ge Zhang", "Jia-cheng Guo", "Jun-nan Tang", "Jin-ying Zhang", "Shao-kang Guan" ], "doi_url": "https://doi.org/10.1016/j.jma.2023.05.007", "publisher_url": null, "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W4382243369", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1016-j-jma-2023-05-007.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1016-j-jma-2023-05-007.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1016-j-jma-2023-05-007.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "Exosome-associated coating and particle characteristics were documented using material-level tests.", "context": "Exosome identity-related Western blot complete images were cited as missing Figure S1; no conclusion requires interpretation of that unavailable supplement.", "evidence": [ { "label": "Alloy", "value": "Mg-Zn-Y-Nd modified with MgF2 and PDA/exosome" }, { "label": "Particle size from NTA", "value": "Reported 50–150 nm distribution" }, { "label": "Source completeness", "value": "Full Western-blot Figure S1 supplement unavailable; excluded from validated findings" } ], "source_locator": "Publisher VOR PDF: Abstract and Results §3.1 Exosome characterization, PDF pp.1,6 (printed pp.4988,4993); main Figure 2. The full Western blot is referred to as Figure S1 and was not available in the source pack.", "source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#kf1" }, { "id": "KF2", "claim": "The modified surface showed different corrosion characteristics from bare magnesium alloy in laboratory immersion/electrochemical tests.", "context": "Corrosion outcomes reflect specified HBSS and bench-test conditions, not confirmed long-term human implant degradation or clinical durability.", "evidence": [ { "label": "Test domain", "value": "Electrochemical behavior, pH, hydrogen evolution and weight loss" }, { "label": "Material comparison", "value": "Bare Mg alloy, MgF2, MgF2–PDA and MgF2–PDA/exosome" }, { "label": "Result direction", "value": "Article reports improved resistance with modified coating" } ], "source_locator": "Publisher VOR PDF: Methods §2.4 Corrosion resistance, Results §3.3 Corrosion resistance; Figures 3–5; PDF pp.3–9 (printed 4990–4996).", "source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#kf2" }, { "id": "KF3", "claim": "MgF2–PDA/exosome surfaces were associated with improved cultured endothelial readouts.", "context": "Bench-cell observations are surrogate readouts relevant to endothelialization, not a measurement of human-stent clinical restenosis or healing.", "evidence": [ { "label": "Endothelial assays", "value": "Adhesion, CCK-8 growth proxy, CD31 staining, NO release and migration" }, { "label": "Reported 3-day surface cell density", "value": "Approximately 1.8×10^5 cells/cm² on coated surface versus 2×10^4 on bare alloy (article-described comparison)" }, { "label": "Figure-level replicates", "value": "Figure 8B/C: n=6; Figure 8D: n=3" } ], "source_locator": "Publisher VOR PDF: Methods §§2.8–2.10, Results §3.7 vascular endothelial cell responses; Figure 8A–H; PDF pp.4–5 and 10–12 (printed 4991–4992 and 4997–4999).", "source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#kf3" }, { "id": "KF4", "claim": "Inflammatory and smooth-muscle cell readouts differed under the coated-material conditions.", "context": "Macrophage TNF-α/CD206 or smooth-muscle α-SMA/OPN expression is not a directly tested causal anti-restenosis mechanism in human vessels.", "evidence": [ { "label": "Macrophage assessment", "value": "TNF-α, CD206 and reactive oxygen species in extract-solution culture" }, { "label": "Smooth-muscle assessment", "value": "α-SMA, osteopontin and cell competition assays" }, { "label": "Model domain", "value": "In-vitro phenotype and compatibility metrics" } ], "source_locator": "Publisher VOR PDF: Results §§3.6–3.8, Figures 7, 9 and 10; PDF pp.9–14 (printed 4996–5001).", "source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#kf4" }, { "id": "KF5", "claim": "Exosome-associated signals were observed in cultured endothelial uptake and release assays.", "context": "Fluorescence overlap with cellular organelles indicates reported localization, not a proven cargo-mediated causal pathway or controlled therapeutic dose.", "evidence": [ { "label": "Release window", "value": "Approximately 5–7 days in the tested coating system" }, { "label": "Cellular colocalization", "value": "Reported overlap with lysosomal and mitochondrial fluorescent markers" }, { "label": "Interpretation", "value": "Exploratory uptake/localization observations" } ], "source_locator": "Publisher VOR PDF: Methods §§2.10–2.11, Results §3.8 Release and uptake of exosomes, Figure 11; PDF pp.5–6 and 14–15 (printed 4992–4993 and 5001–5002).", "source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#kf5" }, { "id": "KF6", "claim": "A short rat aortic wire-implant experiment showed descriptive vessel-wall histological differences.", "context": "The animal intervention used wires rather than clinical coronary stents; the presented H&E sections do not independently establish quantitative lumen patency, thrombosis prevention or long-term safety.", "evidence": [ { "label": "Rodent design", "value": "15 SD rats; bare-Mg, MgF2 and MgF2–PDA/exosome wire groups, n=5 each" }, { "label": "Site and time", "value": "Rat abdominal aorta; 21-day histology" }, { "label": "Endpoint limitation", "value": "Qualitative H&E representative sections only in Figure 12" } ], "source_locator": "Publisher VOR PDF: Methods §2.12 The SD rat experiment, PDF p.6 (printed 4993); Results and Figure 12, PDF pp.15–16 (printed 5002–5003).", "source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#kf6" } ], "field_entry": [ "Cardiovascular biomaterials", "Biodegradable stent research" ], "review_topics": [ "Exosome-functionalized magnesium alloys", "Preclinical endothelial compatibility" ], "concepts": { "device_materials": [ "Biodegradable magnesium alloy", "MgF2–PDA/exosome coating", "Vascular scaffold surfaces" ], "preclinical_biology": [ "Endothelialization surrogates", "Macrophage phenotype", "Smooth muscle cell markers" ], "evidence_levels": [ "Corrosion bench tests", "Rat aortic wire histology", "Supplement Figure S1 absent" ] }, "profile_type": "preclinical_multimodal", "study_profile": { "profile_type": "preclinical_multimodal", "study_design": "Surface-modified biodegradable magnesium alloy development with physicochemical testing, in-vitro platelet/macrophage/endothelial/smooth-muscle assays and small rodent abdominal-aorta wire implantation.", "evidence_type": "Preclinical material characterization and cell behavior with qualitative vascular histology; 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Descriptive histology does not provide an independently quantified clinical patency outcome." }, "study_profile_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1016-j-jma-2023-05-007.json", "gold_content_sha256": "decdf46ba1a2d69beaa90f6c8c1fab328bb3d42fa6e76899881511eb7d567a17", "provenance": { "doi_url": "https://doi.org/10.1016/j.jma.2023.05.007", "publisher_url": "https://www.sciopen.com/article/10.1016/j.jma.2023.05.007", "license": "CC BY-NC-ND 4.0 in publisher version-of-record PDF; original evidence summary only, without adapting/reproducing article text, figures or tables.", "license_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/", "version_of_record": "Journal of Magnesium and Alloys 12(12) (2024): 4988–5004; article online 27 June 2023; DOI 10.1016/j.jma.2023.05.007. Existing repository year 2023 is preserved.", "source_artifacts": "Official SciOpen VOR 17-page PDF and Figures 1–12; supplementary Figure S1 still unavailable.", "source_limitation": "Cannot verify the full Western blot panel referenced as Figure S1; all accepted KFs derive from accessible VOR material without use of that image.", "clinical_boundary": "Bench and animal observations only; no human clinical safety, restenosis or stent-outcome evidence." }, "scientific_role": "Coating-material development with endothelial/immune cell tests and small rat abdominal-aorta wire implantation.", "evidence_position": "Preclinical physicochemical and cell readouts plus short animal histology; no human-stent outcome validation.", "related_concepts": [ "MgF2–polydopamine coating", "Exosome surface release", "Rat aortic wire implantation" ], "citation_contexts": [ "Reviews comparing biologically functionalized metallic cardiovascular implant surfaces.", "Preclinical biomaterial reports distinguishing cell-level endothelial surrogates from clinical restenosis outcomes." ], "evidence_scope": { "supports": [ "Modified material surfaces change measured corrosion and vascular-cell readouts under the stated in-vitro conditions.", "The article reports a small rat aortic wire implantation study with histological observations after 21 days.", "The design offers preclinical hypotheses about biomaterial surface engineering and compatibility." ], "does_not_establish": [ "Clinical efficacy, safety, coronary stent patency, thrombosis reduction or restenosis benefit in humans.", "A rigorously measured long-term implantation outcome, given representative rat tissue images only.", "A confirmed exosomal molecular cargo mechanism of endothelial repair.", "Any result relying on the missing full Western-blot Figure S1.", "Evidence that surface endothelial cell density in vitro is equivalent to in-vivo reendothelialization of human stents." ] }, "limitations": [ "Missing formal supplementary Figure S1 prevents independent checking of the complete immunoblot panel; no result is attributed to that file.", "The preclinical implant was wire placement in rat abdominal aorta, not an implanted human coronary stent.", "Figure 12 shows qualitative histology at 21 days; no clinical or long-term luminal patency study is demonstrated.", "Corrosion, cell proliferation, platelet adhesion and release data depend on specific in-vitro testing protocols.", "The official volume/issue is Journal of Magnesium and Alloys 12(12) (2024), pages 4988–5004; article first online in 2023. Existing bibliographic site year remains protected." ], "scope_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/evidence_scope" }, { "id": "doi-10-1111-jcmm-17789", "title": "Differential expression profiles of plasma exosomal microRNAs in dilated cardiomyopathy with chronic heart failure", "doi": "10.1111/jcmm.17789", "year": 2023, "journal": "Journal of Cellular and Molecular Medicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.md", "paper_geo_status": "v2", "authors": [ "Li Zhang", "Ge Zhang", "Yongzheng Lu", "Jiamin Gao", "Zhen Qin", "Shuai Xu", "Zeyu Wang", "Yanyan Xu", "Yu Yang", "Jinying Zhang", "Junnan Tang" ], "doi_url": "https://doi.org/10.1111/jcmm.17789", "publisher_url": "https://onlinelibrary.wiley.com/doi/10.1111/jcmm.17789", "pmid": "37243441", "pmcid": "PMC10339102", "openalex_id": "https://openalex.org/W4378516912", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-17789.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-17789.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1111-jcmm-17789.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "id": "KF1", "claim": "The study combined human DCM-HF plasma miRNA discovery with a separate external expression-assay comparison.", "context": "Human disease-versus-healthy comparison; no prospective clinical intervention.", "source_locator": "Methods 2.1, 2.8 and 2.9; Results 3.10; Fig. 6", "evidence": [ { "label": "Disease phenotype", "value": "DCM with chronic heart failure" }, { "label": "Discovery assay", "value": "Small-RNA library sequencing on Illumina HiSeq2500" }, { "label": "External qRT-PCR sample", "value": "10 DCM patients; 6 healthy controls" } ], "source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html#kf1" }, { "id": "KF2", "claim": "The isolated plasma preparations showed vesicle morphology, size and marker findings consistent with the reported exosomal preparation.", "context": "The authors use the term exosomes; these measurements alone do not establish cardiac cell of origin or exclusive endosomal origin.", "source_locator": "Methods 2.3-2.6; Results 3.1; Fig. 1B-D", "evidence": [ { "label": "Isolation", "value": "ExoQuick precipitation" }, { "label": "Median particle diameter", "value": "Approximately 81 nm in the reported groups" }, { "label": "Marker findings", "value": "CD63 and CD81 detected; Calnexin not detected" } ], "source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html#kf2" }, { "id": "KF3", "claim": "The Results identify 92 differential miRNA features after the stated fold-change and P-value screen.", "context": "The Results threshold is reported here; the Fig. 3A caption instead prints 0.05 for the absolute-logFC threshold, an unresolved reporting difference.", "source_locator": "Results 3.2; Table 1; Figs. 2 and 3A", "evidence": [ { "label": "Detected miRNA features", "value": "3,687" }, { "label": "Final threshold as stated in Results", "value": "Absolute logFC >0.5 and P<0.05" }, { "label": "Final differential features", "value": "92" }, { "label": "Upregulated / downregulated", "value": "48 / 44" } ], "source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html#kf3" }, { "id": "KF4", "claim": "Target prediction and network analysis connected differential miRNA features to candidate regulatory and pathway contexts.", "context": "Computational relationships do not demonstrate direct miRNA binding, altered target-protein abundance or pathway causality.", "source_locator": "Methods 2.10-2.12; 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Results 3.9-3.10; Methods 2.9", "evidence": [ { "label": "Table 1 hsa-miR-185-5p logFC", "value": "1.04" }, { "label": "Table 1 hsa-miR-185-5p P value", "value": "0.0322" }, { "label": "External 10-miRNA panel membership", "value": "Not included in the listed qRT-PCR panel" } ], "source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html#kf6" } ], "field_entry": [ "Extracellular-vesicle biomarker research", "Dilated cardiomyopathy and heart failure" ], "review_topics": [ "Circulating RNA biomarkers in cardiomyopathy", "Human plasma exosomal microRNA profiling" ], "concepts": { "disease": [ "dilated cardiomyopathy", "chronic heart failure" ], "specimen": [ "plasma extracellular vesicles", "exosomal miRNAs" ], "methods": [ "small-RNA sequencing", "qRT-PCR", "miRNA target prediction", "PCoA" ], "entities": [ "miR-185-5p", "CD63", "CD81" ], "evidence": [ "case-control molecular profiling", "external assay evaluation" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Human case-control plasma exosomal miRNA discovery with external qRT-PCR follow-up", "evidence_type": "Human molecular association and small external assay evaluation", "population": "Patients with DCM and chronic heart failure compared with healthy individuals; recruitment criteria included LVEF <=45%, NYHA II-IV and heart-failure history longer than 6 months", "primary_endpoint": "Between-group plasma exosomal miRNA expression differences", "secondary_endpoint": "Predicted target/pathway relationships and external hub-miRNA expression-profile evaluation", "counting_note": "Discovery and external assay phases are distinct. The discovery participant count is not reliably established from the reviewed text, so no complete unique-participant total is inferred. Sequencing features, predicted genes, network nodes and qRT-PCR technical triplicates are not additional participants. External validation here means a small external expression-assay comparison, not validation of a clinical diagnostic or prognostic tool.", "external_validation": true, "data_modalities": [ "plasma vesicle preparation and characterization", "small-RNA sequencing", "external qRT-PCR", "target prediction and pathway enrichment", "network analysis and PCoA" ], "scale_metrics": [ { "label": "Sequencing feature landscape", "value": "3,687 article-reported miRNA features" }, { "label": "Final differential feature set", "value": "92 features: 48 upregulated and 44 downregulated" }, { "label": "External qRT-PCR participants", "value": "10 DCM patients and 6 healthy controls" }, { "label": "External assay panel", "value": "10 selected hub miRNAs" } ] }, "study_profile_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1111-jcmm-17789.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1111-jcmm-17789.json", "gold_content_sha256": "46c4fd8718ab8ffa7533bade604d581d78124180a2bffabec82d0856a7d7f538", "provenance": { "doi_url": "https://doi.org/10.1111/jcmm.17789", "publisher_url": "https://onlinelibrary.wiley.com/doi/full/10.1111/jcmm.17789", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/37243441/", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10339102/", "review_basis": "Published main text, tables and figure legends at the cited primary sources. No independent reanalysis of participant-level data; unresolved reporting differences are identified in the evidence scope.", "data_availability": "Methods 2.8 states that raw sequencing data were uploaded to GEO, but no specific accession was verified from the reviewed text. The data-availability section also offers data on request. No accession or direct dataset link is inferred." }, "scientific_role": "Exploratory human DCM-HF plasma exosomal microRNA profiling with small external expression-assay follow-up.", "evidence_position": "Human case-control biomarker evidence; not prospective diagnosis, therapeutic RNA delivery or external miR-185-5p validation in this article.", "related_concepts": [ "Vesicle-associated RNA candidates", "Discovery versus assay follow-up" ], "citation_contexts": [ "Background: extracellular vesicles as sources of candidate heart-failure biomarkers.", "Evidence synthesis: human circulating microRNA expression studies in DCM-HF, separate from preclinical miRNA interventions." ], "evidence_scope": { "supports": [ "DCM-HF-associated plasma exosomal miRNA expression differences in the studied samples.", "An article-reported 92-feature screen and computational miRNA-target/pathway prioritization.", "Small external qRT-PCR evaluation of a selected 10-miRNA panel.", "Discovery-stage inclusion of hsa-miR-185-5p with the Table 1 values reported above." ], "does_not_establish": [ "A prospectively validated early diagnostic test or prognostic model for DCM.", "Causation of human DCM by the differential miRNAs or their predicted targets.", "External qRT-PCR validation of miR-185-5p in this article.", "Direct biochemical binding for every predicted miRNA-mRNA interaction.", "Cardiac-cell origin or exclusive exosomal origin of every measured circulating RNA.", "An effective miRNA-directed treatment in humans." ] }, "limitations": [ "The discovery participant count is not reliably established from the reviewed text; no synthetic total is supplied.", "The final Results screen uses absolute logFC >0.5, while Fig. 3A prints >0.05. P-value and FDR statements are not assumed to establish the same feature-wise threshold.", "Methods 2.9 includes an abdominal-aortic-wall/mRNA extraction passage inconsistent with the surrounding plasma-exosomal-miRNA assay description; this is retained as a reporting limitation, not reinterpreted as a myocardial tissue experiment.", "External evaluation is small (10 cases and 6 controls), and multivariate separation is not prospective diagnostic validation.", "Some feature labels retain homolog/isomiR-style naming in the source; the complete feature set is not relabeled as uniquely verified canonical human mature miRNAs." ], "scope_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/evidence_scope" }, { "id": "idebenone-ferroptosis", "title": "Idebenone attenuates ferroptosis by inhibiting excessive autophagy via the ROS-AMPK-mTOR pathway to preserve cardiac function after myocardial infarction", "doi": "10.1016/j.ejphar.2023.175569", "year": 2023, "journal": "European Journal of Pharmacology", "type": "Article", "paper_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html", "markdown_url": "https://drgezhang.com/papers/idebenone-ferroptosis.md", "paper_geo_status": "v2", "authors": [ "Demin Li", "Ge Zhang", "Zeyu Wang", "Jiacheng Guo", "Yu Liu", "Yongzheng Lu", "Zhen Qin", "Yanyan Xu", "Chang Cao", "Bo Wang", "Qianqian Guo", "Yunzhe Wang", "Guozhen Liu", "Xiaolin Cui", "Jinying Zhang", "Junnan Tang" ], "doi_url": "https://doi.org/10.1016/j.ejphar.2023.175569", "publisher_url": "https://linkinghub.elsevier.com/retrieve/pii/S0014299923000808", "pmid": "36740037", "pmcid": null, "openalex_id": "https://openalex.org/W4319160269", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/idebenone-ferroptosis.bib", "citation_ris_url": "https://drgezhang.com/citations/idebenone-ferroptosis.ris", "citation_csl_json_url": "https://drgezhang.com/citations/idebenone-ferroptosis.csl.json", "evidence_status": "reviewed_v2", "question_count": 6, "key_findings": [ { "claim": "Idebenone pretreatment reduced reported H2O2-associated injury in H9c2 cells, assessed using cell viability, ROS and lipid-peroxidation readouts.", "context": "H2O2-associated cell death is not exclusively ferroptosis, and these observations do not exclude other protective actions.", "source_locator": "Author-deposited full text: Results 3.1-3.2; Figs. 1-2", "evidence": [ { "label": "experimental system", "value": "H9c2 H2O2-associated injury" }, { "label": "intervention timing", "value": "Idebenone pretreatment" }, { "label": "readouts", "value": "Cell viability; ROS; lipid peroxidation" } ], "id": "KF1", "source": "data/deep_geo/idebenone-ferroptosis.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#kf1" }, { "claim": "RSL3 experiments, ferroptosis-related interventions and GPX4/FTH1/FPN1 readouts supported ferroptosis involvement; DFO/ferrostatin-1-related controls were described in the text.", "context": "This is experimental mechanistic support. Marker changes do not by themselves establish a complete, specific causal chain.", "source_locator": "Author-deposited full text: Results 3.2 and 3.5; Figs. 2 and 7", "evidence": [ { "label": "experimental probe", "value": "RSL3" }, { "label": "protein readouts", "value": "GPX4; FTH1; FPN1" }, { "label": "related controls", "value": "DFO; ferrostatin-1" } ], "id": "KF2", "source": "data/deep_geo/idebenone-ferroptosis.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#kf2" }, { "claim": "Metformin/rapamycin experiments and AMPK-mTOR-related readouts supported the proposed pathway, alongside LC3/p62 and autophagy-associated observations.", "context": "Pharmacologic perturbations are not complete gene-specific validation. These results do not imply that all ferroptosis depends on autophagy.", "source_locator": "Author-deposited full text: Results 3.3-3.5; Figs. 3-7", "evidence": [ { "label": "pharmacologic probes", "value": "Metformin; rapamycin" }, { "label": "pathway readouts", "value": "p-AMPK/AMPK; p-mTOR/mTOR" }, { "label": "autophagy associated readouts", "value": "LC3; p62" } ], "id": "KF3", "source": "data/deep_geo/idebenone-ferroptosis.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#kf3" }, { "claim": "The LAD-ligation model used three main groups—sham+vehicle, MI+vehicle and MI+idebenone—with dosing 24 h and 2 h before surgery followed by continued dosing and short- and longer-term observations.", "context": "This is a pretreatment-containing perioperative regimen, not a validated rescue regimen initiated exclusively after myocardial infarction. No dose recommendation or cross-species conversion is supplied.", "source_locator": "Author-deposited full text: Methods 2.11-2.12; Results 3.6; Fig. 8A", "evidence": [ { "label": "model", "value": "LAD ligation" }, { "label": "main groups", "value": "sham+vehicle; MI+vehicle; MI+idebenone" }, { "label": "preoperative dosing", "value": "24 h and 2 h before surgery" }, { "label": "subsequent dosing", "value": "Continued after surgery" }, { "label": "observation windows", "value": "Short-term and longer-term" } ], "id": "KF4", "source": "data/deep_geo/idebenone-ferroptosis.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#kf4" }, { "claim": "At four weeks, Results reported EF of 21.82% in MI and 33.76% in MI+idebenone, with Fig. 8 reporting n=5; histological/fibrosis readouts also improved qualitatively.", "context": "The percentages are EF values themselves, not relative percentage improvements. Mouse cardiac-function and histological observations do not establish human survival benefit or clinical utility.", "source_locator": "Author-deposited full text: Results 3.6; Fig. 8B-F", "evidence": [ { "label": "timepoint", "value": "4 weeks" }, { "label": "MI EF", "value": "21.82%" }, { "label": "MI plus idebenone EF", "value": "33.76%" }, { "label": "Fig 8 reported n", "value": "5" }, { "label": "histology fibrosis", "value": "Qualitatively improved readouts" } ], "id": "KF5", "source": "data/deep_geo/idebenone-ferroptosis.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#kf5" }, { "claim": "Myocardial oxidative, iron-handling and autophagy-associated readouts changed with intervention, including ROS/MDA/Fe2+, GPX4/FTH1/FPN1, LC3/p62 and tissue observations.", "context": "Readouts from different timepoints and materials cannot be treated as one continuous causal chain in a patient. Ambiguous fold-change wording is not recalculated into new effect sizes, and these tissue findings are not human clinical efficacy evidence.", "source_locator": "Author-deposited full text: Results 3.7-3.8; Figs. 9-10", "evidence": [ { "label": "oxidative iron readouts", "value": "ROS; MDA; Fe2+" }, { "label": "protein readouts", "value": "GPX4; FTH1; FPN1" }, { "label": "autophagy tissue readouts", "value": "LC3; p62; tissue observations" } ], "id": "KF6", "source": "data/deep_geo/idebenone-ferroptosis.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#kf6" } ], "field_entry": [ "Myocardial injury research", "Regulated cell death in cardiovascular disease" ], "review_topics": [ "Ferroptosis and autophagy in myocardial infarction", "Preclinical cardioprotection and intervention timing" ], "concepts": { "disease_model": [ "experimental myocardial infarction" ], "intervention": [ "idebenone" ], "processes": [ "ferroptosis", "autophagy", "oxidative injury" ], "entities": [ "AMPK", "mTOR", "GPX4" ], "evidence": [ "pretreatment-containing animal intervention", "cellular pharmacology" ] }, "profile_type": "preclinical_multimodal", "study_profile": { "profile_type": "preclinical_multimodal", "external_validation": false, "study_design": "Cellular and mouse intervention study with pharmacologic pathway probes", "evidence_type": "Preclinical functional and mechanism-supporting evidence", "population": "H9c2 cellular models and experimental myocardial-infarction mice", "primary_endpoint": "Experimental cell injury and mouse cardiac function", "secondary_endpoint": "Ferroptosis/autophagy-associated and histological readouts", "data_modalities": [ "cell viability", "oxidative/iron/lipid-peroxidation assays", "protein and autophagy readouts", "mouse echocardiography", "histology" ], "scale_metrics": [ { "label": "Cellular systems", "value": "H9c2 H2O2/RSL3 experimental systems" }, { "label": "Three main mouse groups", "value": "sham+vehicle; MI+vehicle; MI+idebenone" }, { "label": "Fig. 8 echocardiography/histology", "value": "Reported n=5" }, { "label": "Cell/protein experiments", "value": "Reported n varies by assay; not summed into a total animal count" } ], "counting_note": "Figure-level n is the reported unit for the corresponding experiment, not a study-wide deduplicated total. Cells, technical readouts and animals cannot be added together. This synthesis focuses on the reviewed core cellular and animal experiments; public-omics background analyses are not human drug-validation cohorts." }, "study_profile_source": "data/deep_geo/idebenone-ferroptosis.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/idebenone-ferroptosis.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/idebenone-ferroptosis.json", "gold_content_sha256": "8f6c18fa08ba54a2c73aa473cce8d1cbb72dca051c8a474c741d1155fe5cf258", "provenance": { "publication_url": "https://www.sciencedirect.com/science/article/pii/S0014299923000808", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/36740037/", "doi_url": "https://doi.org/10.1016/j.ejphar.2023.175569", "author_deposited_url": "https://www.researchgate.net/publication/368265058_Idebenone_attenuates_ferroptosis_by_inhibiting_excessive_autophagy_via_the_ROS-AMPK-mTOR_pathway_to_preserve_cardiac_function_after_myocardial_infarction", "review_basis": "Identity checked against PubMed and the publisher record in the supplied source review. Experimental details are attributed to Results and figure legends in the DOI-bearing author-deposited full text; not all PDF images or supplementary data were independently reviewed.", "data_availability": "Data available on request according to the publisher record." }, "scientific_role": "Cellular and mouse intervention study of idebenone-associated myocardial injury reduction and pathway-related evidence.", "evidence_position": "Preclinical experiments with pretreatment-containing regimens; not evidence of post-infarction-only clinical rescue, human safety or human survival benefit.", "related_concepts": [ "Redox-related cardiac injury", "Pretreatment-to-clinical translation" ], "citation_contexts": [ "Background: regulated cell-death processes in myocardial injury.", "Experimental evidence: ferroptosis- and autophagy-related cardioprotection, with dosing timing and alternative mechanisms retained." ], "evidence_scope": { "supports": [ "Protective observations under the specified cellular conditions.", "Experimental support for mechanism involvement.", "Mouse cardiac-function and tissue readouts under a regimen that includes preoperative dosing." ], "does_not_establish": [ "Human MI efficacy, safety or an approved MI indication.", "Clinical rescue efficacy when treatment begins only after myocardial infarction.", "That all autophagy should be inhibited or all cell death is ferroptosis.", "Complete exclusion of other protective mechanisms or direct drug binding to AMPK or mTOR.", "Human survival benefit inferred from mouse EF changes." ] }, "limitations": [ "Evidence is cellular and animal, not proof of human MI efficacy, safety or an approved MI indication; background use in other diseases is not an MI indication.", "Preoperative dosing limits extrapolation to treatment begun only after infarction.", "Pharmacologic and marker-based support does not show that all autophagy should be suppressed, that all cell death is ferroptosis or that other mechanisms are excluded.", "The experiments do not establish direct idebenone binding to AMPK or mTOR.", "EF percentages are measured functional values, not relative survival gains or clinical utility estimates.", "Detailed findings are attributed to the DOI-bearing author-deposited full text; not every PDF image or supplementary dataset was independently reviewed.", "An open-license label on ResearchGate alone is not treated as publisher-abstract reuse authorization; no Official Abstract is copied in this batch." ], "scope_source": "data/deep_geo/idebenone-ferroptosis.json#/evidence_scope" }, { "id": "doi-10-18063-ijb-740", "title": "Three-dimensional bioprinting of artificial blood vessel: Process, bioinks, and challenges", "doi": "10.18063/ijb.740", "year": 2023, "journal": "International Journal of Bioprinting", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html", "markdown_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.md", "paper_geo_status": "v2", "authors": [ "Ya-Chen Hou", "Xiaolin Cui", "Zhen Qin", "Chang Su", "Ge Zhang", "Jun-Nan Tang", "Jing-An Li", "Jin-Ying Zhang" ], "doi_url": "https://doi.org/10.18063/ijb.740", "publisher_url": null, "pmid": "37323481", "pmcid": "PMC10261152", "openalex_id": "https://openalex.org/W4380872576", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-18063-ijb-740.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-18063-ijb-740.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-18063-ijb-740.csl.json", "evidence_status": "reviewed_v2", "question_count": 7, "key_findings": [ { "id": "KF1", "claim": "Vascular construct design requires coordinated cellular and extracellular-matrix functions rather than a hollow tube alone.", "context": "Conceptual synthesis of native-vessel organization and graft design requirements", "evidence": [ { "label": "cellular components highlighted", "value": "3: endothelial cells, vascular smooth muscle cells and fibroblasts" }, { "label": "supporting environment", "value": "extracellular matrix supports cellular organization and tissue function" }, { "label": "design scope", "value": "endothelial compatibility, patency, mechanical performance and nutrient transport must be considered together; no clinical efficacy estimate is supplied" } ], "source_locator": "Section 1: Introduction (sec1-1), paragraph describing endothelial cells, smooth muscle cells, fibroblasts and ECM; Sections 2.1-2.3; Table 1", "source": "data/deep_geo/doi-10-18063-ijb-740.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#kf1" }, { "id": "KF2", "claim": "Bioinks have different structural roles, and supportive and sacrificial functions should be distinguished.", "context": "Material selection for constructing vessel walls and creating removable lumen templates", "evidence": [ { "label": "functional roles", "value": "2: support materials and sacrificial materials" }, { "label": "supportive examples discussed", "value": "modified PEG, hyaluronic-acid systems, collagen/gelatin systems and decellularized extracellular matrix" }, { "label": "sacrificial examples discussed", "value": "Pluronic F-127 and alginate-based strategies; material roles depend on formulation and process" }, { "label": "scope", "value": "a material name alone does not determine graft suitability or whether it acts as support or template" } ], "source_locator": "Section 3: Bioinks for 3D bioprinting (sec1-3); Section 3.1: Support hydrogel; Sections 3.2.1-3.2.3, including Pluronic F-127 (sec3-6), Alginate (sec3-7) and Discussion on the existing hydrogel (sec3-8); Table 2", "source": "data/deep_geo/doi-10-18063-ijb-740.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#kf2" }, { "id": "KF3", "claim": "Printability and cell compatibility depend on interacting rheological and crosslinking choices.", "context": "Narrative synthesis of hydrogel processing requirements; not a universal validated manufacturing specification", "evidence": [ { "label": "hydrogel properties explicitly considered", "value": "4: shear thinning, yield stress, viscosity and molding ability" }, { "label": "broad crosslinking classes", "value": "2: chemical/covalent crosslinking and physical interactions such as hydrogen bonding or electrostatic attraction" }, { "label": "trade-off", "value": "viscosity and rapid stabilization can preserve geometry while extrusion stress, light exposure and other processing conditions can harm cells" }, { "label": "scope", "value": "performance depends on formulation, cell loading and process conditions; no single optimal recipe is established" } ], "source_locator": "Section 1: Introduction (sec1-1), crosslinking paragraph; Section 2.2: Hydrogel requirements (sec2-2); Section 2.3: Forming requirements (sec2-3); Section 4.1: Material extrusion (sec2-6)", "source": "data/deep_geo/doi-10-18063-ijb-740.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#kf3" }, { "id": "KF4", "claim": "The review compares conventional printing families and an embedded-support strategy with different constraints.", "context": "Methodological comparison of fabrication approaches rather than a controlled head-to-head effectiveness experiment", "evidence": [ { "label": "conventional families", "value": "3: material extrusion, material jetting and vat polymerization" }, { "label": "embedded strategy", "value": "FRESH is discussed separately as printing within a removable support bath" }, { "label": "method-specific limitations", "value": "extrusion involves shear and resolution trade-offs; jetting restricts ink viscosity; vat polymerization requires suitable photosensitive materials; FRESH requires rapid and compatible ink gelation" }, { "label": "scope", "value": "advantages depend on the intended construct and ink; the review does not establish one method as clinically superior" } ], "source_locator": "Section 4: 3D bioprinting techniques (sec1-5); Sections 4.1-4.4 (sec2-6 through sec2-9); Table 3", "source": "data/deep_geo/doi-10-18063-ijb-740.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#kf4" }, { "id": "KF5", "claim": "A cited FRESH experiment illustrates how a removable support bath can preserve soft hydrogel geometry.", "context": "Illustrative primary technical experiment by Hinton et al. 2015, summarized in the review; parameters are not a universal vascular-graft standard", "evidence": [ { "label": "support-bath condition", "value": "approximately 22 degrees C during printing" }, { "label": "release condition", "value": "37 degrees C to melt the gelatin support bath" }, { "label": "representative alginate filament", "value": "199 +/- 41 micrometres diameter" }, { "label": "measurement boundary", "value": "filament diameter is not vessel-lumen diameter, clinical graft patency, burst pressure or a patient outcome" } ], "source_locator": "Section 4.4: Freeform reversible embedding of suspended hydrogel (FRESH) (sec2-9), reference 196; Hinton et al., Science Advances 2015, DOI 10.1126/sciadv.1500758, Results paragraphs on support-bath rheology and alginate-filament printing, Figure 2A-B and Materials and Methods: FRESH 3D printing", "source": "data/deep_geo/doi-10-18063-ijb-740.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#kf5" }, { "id": "KF6", "claim": "The review identifies unresolved steps between printed constructs and clinical vascular grafts.", "context": "Translational appraisal as of the 2023 review, informed by cited in vitro and animal examples rather than new clinical outcome data", "evidence": [ { "label": "evidence level", "value": "review of engineering and preclinical demonstrations; no new patient cohort or clinical trial" }, { "label": "historical statement", "value": "the authors reported no clinical vessel-bioprinting cases in their review context at publication in 2023" }, { "label": "barriers discussed", "value": "mechanical durability, endothelial function, maturation, reproducible manufacturing, sterilization and safety" }, { "label": "time boundary", "value": "the historical statement is not an independently updated 2026 claim about every product, trial or regulatory authorization" } ], "source_locator": "Section 1: Introduction (sec1-1), clinical-translation paragraph; Section 3.2.3: Discussion on the existing hydrogel (sec3-8); Section 5: Conclusion and future perspectives (sec1-6)", "source": "data/deep_geo/doi-10-18063-ijb-740.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#kf6" } ], "field_entry": [ "Cardiovascular tissue engineering", "Vascular biomaterials" ], "review_topics": [ "Bioink design for vascular constructs", "Printing processes and translation barriers" ], "concepts": { "application": [ "tissue-engineered vascular grafts", "vascular bioprinting", "coronary bypass graft context" ], "materials": [ "hyaluronic acid", "collagen", "gelatin methacryloyl", "decellularized extracellular matrix", "alginate", "Pluronic F-127", "modified polyethylene glycol" ], "processes": [ "material extrusion", "material jetting", "vat polymerization", "FRESH", "sacrificial templating", "crosslinking" ], "design_constraints": [ "shear thinning", "yield stress", "cell compatibility", "endothelial function", "mechanical durability", "nutrient transport" ] }, "profile_type": "narrative_review", "study_profile": { "profile_type": "narrative_review", "study_design": "Narrative methodological review of vascular bioprinting materials, process choices and translational challenges; no new clinical recruitment or pooled meta-analysis", "evidence_type": "Literature synthesis of biomaterial properties, printing methods, in vitro constructs and selected preclinical vascular-graft examples", "translation_scope": "Engineering and preclinical design framework for tissue-engineered vascular constructs; cited technical demonstrations are not evidence of clinical graft efficacy or routine availability", "evidence_domains": [ "vascular structure and graft requirements", "bioink rheology and cell compatibility", "supportive and sacrificial hydrogels", "crosslinking and printing methods", "preclinical translation and manufacturing barriers" ], "diseases_covered": [ "coronary artery disease and ischemic-heart-disease bypass context", "vascular disease requiring graft replacement" ], "scale_metrics": [ { "label": "material functions distinguished", "value": "2: support materials and sacrificial materials" }, { "label": "broad crosslinking categories discussed", "value": "2: chemical/covalent and physical interactions" }, { "label": "conventional printing families summarized", "value": "3: extrusion, material jetting and vat polymerization" }, { "label": "additional embedded-printing strategy", "value": "FRESH, discussed separately in Section 4.4" }, { "label": "illustrative cited FRESH process", "value": "approximately 22 degrees C support bath; release at 37 degrees C; representative alginate filament diameter 199 +/- 41 micrometres" } ], "counting_note": "These numbers describe the review organization and one cited technical example. They are not a count of trials, included studies, recruited participants, pooled specimens or a clinical cohort. The FRESH filament measurement comes from Hinton et al. 2015, not a new experiment by the review authors. No overall participant n is assigned." }, "study_profile_source": "data/deep_geo/doi-10-18063-ijb-740.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-18063-ijb-740.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-18063-ijb-740.json", "gold_content_sha256": "6395048de62359f122fd7103d3a7271ed8bd9b571408dfd99cc6be3754855f36", "provenance": { "publisher_url": "https://doi.org/10.18063/ijb.740", "doi_url": "https://doi.org/10.18063/ijb.740", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/37323481/", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10261152/", "pmcid": "PMC10261152", "version_of_record": "International Journal of Bioprinting 2023;9(4):740, published 28 April 2023; DOI 10.18063/ijb.740; PubMed publication type Review", "license": "Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0), article-level license in PMC. This evidence summary uses original factual synthesis; no figures or tables are reproduced.", "license_url": "https://creativecommons.org/licenses/by-nc/4.0/", "author_identity": "Ge Zhang is author 5, affiliated with Cardiology at the First Affiliated Hospital of Zhengzhou University and the associated Henan cardiovascular research centers. The same DOI is listed in public ORCID 0000-0002-3116-3246, including work put-code 136257902. The article itself does not supply an ORCID for this author.", "orcid_url": "https://orcid.org/0000-0002-3116-3246", "primary_technical_example_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC4646826/", "primary_technical_example": "Hinton et al., Three-dimensional printing of complex biological structures by freeform reversible embedding of suspended hydrogels, Science Advances 2015;1:e1500758, DOI 10.1126/sciadv.1500758, review reference 196. The support-bath temperature, release temperature and illustrative filament diameter were independently cross-checked in the primary text.", "supporting_material": "No article-level supplementary experimental dataset is required for the claims on this review page; the source is a literature synthesis, with technical examples traced to its references.", "preprint_relation": "No linked preprint was identified in the inspected publisher/PMC/Crossref metadata; no new exhaustive literature search was performed.", "evidence_basis": "Version-of-record full-text XML, PubMed/Europe PMC author-affiliation and publication-type metadata, Crossref DOI metadata, public ORCID works and the cited primary FRESH paper, checked 15 October 2026." }, "scientific_role": "Narrative synthesis connecting hydrogel functions, cell compatibility, fabrication methods and clinical-translation constraints.", "evidence_position": "Secondary engineering and preclinical synthesis; no new clinical cohort, pooled clinical effect or demonstrated graft efficacy.", "related_concepts": [ "Support and sacrificial materials", "Embedded hydrogel printing", "Endothelialization and durability" ], "citation_contexts": [ "Background: material and process trade-offs in tissue-engineered vascular graft research.", "Methods rationale: choosing supportive bioinks, removable templates and embedded printing, while tracing quantitative examples to original experiments." ], "evidence_scope": { "supports": [ "A qualitative design framework for comparing vascular-bioprinting materials and processes.", "The need to balance geometry, cell compatibility, mechanical behavior, nutrient transport and manufacturing constraints.", "The distinction between supportive materials, sacrificial templates and removable support baths.", "A source-located FRESH technical example whose specific parameters were cross-checked against the cited primary paper.", "A historical account of translational challenges discussed in the 2023 publication." ], "does_not_establish": [ "A pooled clinical effect, a patient sample size, a randomized comparison or a meta-analytic estimate.", "A systematic search with reproducible eligibility criteria, formal risk-of-bias assessment or comprehensive evidence coverage.", "That any described printed construct is a routinely available, clinically effective or regulator-approved vascular graft.", "That an illustrative filament dimension or cell-viability result is a clinical graft outcome or universal manufacturing standard.", "A universally optimal bioink, crosslinking method or printing technology.", "Current legal or regulatory requirements from the review discussion, or an updated 2026 inventory of trials or products." ] }, "limitations": [ "This is a narrative review and does not report a systematic search, formal study-selection flow or pooled effect analysis.", "The examples span different materials, cell systems, constructs and animal contexts, so quantitative values are not directly interchangeable.", "Illustrative experimental numbers come from cited primary studies and are not original measurements generated by the review.", "No patient cohort, graft-level clinical efficacy comparison or long-term human safety validation was conducted in this publication.", "The review reflects literature available at its 2023 publication; it is not a continually updated registry of products, clinical cases or approvals.", "Engineering specifications and regulatory discussion require their own current authoritative sources before operational use; this page does not present them as validated current requirements." ], "scope_source": "data/deep_geo/doi-10-18063-ijb-740.json#/evidence_scope" }, { "id": "smc-fate", "title": "Smooth muscle cell fate decisions decipher a high-resolution heterogeneity within atherosclerosis molecular subtypes", "doi": "10.1186/s12967-022-03795-9", "year": 2022, "journal": "Journal of Translational Medicine", "type": "Article", "paper_url": "https://drgezhang.com/papers/smc-fate.html", "markdown_url": "https://drgezhang.com/papers/smc-fate.md", "paper_geo_status": "v2", "authors": [ "Ge Zhang", "Zaoqu Liu", "Jinhai Deng", "Long Liu", "Yu Li", "Siyuan Weng", "Chunguang Guo", "Zhaokai Zhou", "Li Zhang", "Xiaofang Wang", "Gangqiong Liu", "Jiacheng Guo", "Jing Bai", "Yunzhe Wang", "Youyou Du", "Tao-Sheng Li", "Junnan Tang", "Jinying Zhang" ], "doi_url": "https://doi.org/10.1186/s12967-022-03795-9", "publisher_url": "https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-022-03795-9", "pmid": "36474294", "pmcid": "PMC9724432", "openalex_id": "https://openalex.org/W4311633514", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/smc-fate.bib", "citation_ris_url": "https://drgezhang.com/citations/smc-fate.ris", "citation_csl_json_url": "https://drgezhang.com/citations/smc-fate.csl.json", "evidence_status": "reviewed_v2", "question_count": 8, "key_findings": [ { "id": "KF1", "claim": "Human atherosclerotic plaques showed substantial vascular smooth muscle cell transcriptional heterogeneity.", "context": "Single-cell profiling of diseased right-coronary-artery segments from four human donors", "evidence": [ { "label": "single-cell donors", "value": "4" }, { "label": "post-QC plaque cells", "value": "11,756" }, { "label": "major plaque cell populations", "value": "8" }, { "label": "SMCs analyzed", "value": "5,419" }, { "label": "SMC clusters", "value": "9" } ], "source_locator": "Results: The landscapes of human atherosclerotic plaques revealed by scRNA-seq analysis, Fig. 2A; Results: SMC lineages' phenotypic and functional heterogeneity, Fig. 3A-E", "source": "data/deep_geo/smc-fate.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/smc-fate.html#kf1" }, { "id": "KF2", "claim": "Pseudotime analysis organized plaque SMCs into a structured differentiation trajectory with distinct early, intermediate, and terminal state distributions.", "context": "Monocle2 reconstruction of SMC state relationships", "evidence": [ { "label": "pseudotime states", "value": "5" }, { "label": "trajectory structure", "value": "five cellular states separated at two key time points" }, { "label": "early-state enrichment", "value": "SMC4 and SMC6" }, { "label": "intermediate high-plasticity enrichment", "value": "SMC2, SMC5 and SMC7" }, { "label": "terminal-state enrichment", "value": "SMC1, SMC8 and SMC9" }, { "label": "phenotypic trend", "value": "contractile-like features declined; fibroblast-like markers increased through the middle-to-late trajectory before decreasing at the terminal end" } ], "source_locator": "Results: Trajectory reconstruction revealed SMC cell fate decisions, Fig. 4A-C", "source": "data/deep_geo/smc-fate.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/smc-fate.html#kf2" }, { "id": "KF3", "claim": "SMC state-associated genes were distilled into the SMC cell fate decision signature (SCFDS).", "context": "Integration of trajectory-ordering genes, state-associated genes, variable SMC genes, and temporal expression modules", "evidence": [ { "label": "SMC cell-fate leader genes", "value": "1,072" }, { "label": "Mfuzz temporal modules", "value": "8" }, { "label": "SCFDS modules", "value": "Cluster 2 and Cluster 6, representing progressively upregulated and downregulated programs" }, { "label": "upregulated SCFDS programs", "value": "extracellular matrix, inflammatory response and TGF-beta-related processes" }, { "label": "downregulated SCFDS programs", "value": "vasculature development and AGE-RAGE-related processes" } ], "source_locator": "Results: Trajectory reconstruction revealed SMC cell fate decisions, Fig. 4D-H; Additional file 3: Table S1; Additional file 4: Table S2", "source": "data/deep_geo/smc-fate.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/smc-fate.html#kf3" }, { "id": "KF4", "claim": "SCFDS-based analysis separated atherosclerosis into three molecular subtypes with distinct biology and different coronary stenosis patterns.", "context": "Consensus molecular subtyping in the discovery bulk transcriptomic cohort", "evidence": [ { "label": "optimal subtype number", "value": "3" }, { "label": "C1", "value": "DNA-damage repair type" }, { "label": "C2", "value": "immune-activated type" }, { "label": "C3", "value": "stromal-rich type" }, { "label": "coronary stenosis association", "value": "C2 showed greater stenosis severity and C3 lower severity; p<0.05 in the discovery analysis" } ], "source_locator": "Results: The molecular subtyping of atherosclerosis based on cell fate decision signature, Fig. 5A-I; coronary stenosis comparison in Fig. 5E", "source": "data/deep_geo/smc-fate.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/smc-fate.html#kf4" }, { "id": "KF5", "claim": "The three-subtype expression taxonomy was reproduced across five independent retrospective external transcriptomic cohorts using nearest-template prediction.", "context": "Cross-cohort evaluation of subtype-specific expression templates", "evidence": [ { "label": "template construction", "value": "top 300 subtype-specific upregulated genes per subtype" }, { "label": "external cohorts", "value": "5" }, { "label": "datasets shown in Fig. 6", "value": "GSE20681, GSE21545, GSE59867, GSE62646 and GSE90074" }, { "label": "validation type", "value": "retrospective expression-template reproducibility across distinct platforms" } ], "source_locator": "Results: Performance of SCFDS subtypes verified by nearest template prediction, Fig. 6B-C", "source": "data/deep_geo/smc-fate.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/smc-fate.html#kf5" }, { "id": "KF6", "claim": "The three SCFDS subtypes were associated with distinct molecular and plaque-microenvironment programs.", "context": "Pathway enrichment and inferred cell-landscape analyses", "evidence": [ { "label": "C1 programs", "value": "base-excision repair, DNA replication, nucleotide-excision repair and oxidative phosphorylation" }, { "label": "C2 programs", "value": "stronger immune and inflammatory activation with a more complex inflammatory lesion environment" }, { "label": "C3 programs", "value": "stromal/ECM metabolism, greater fibrous content and a relatively immune-suppressed microenvironment" } ], "source_locator": "Results: The molecular subtyping of atherosclerosis based on cell fate decision signature, Fig. 5G-I; Results: Assessment of multi-dimensional potential biological implications, Fig. 7A-G", "source": "data/deep_geo/smc-fate.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/smc-fate.html#kf6" } ], "field_entry": [ "Vascular biology", "Single-cell atherosclerosis research" ], "review_topics": [ "Smooth muscle cell heterogeneity in human plaque", "Cell-state programs and molecular disease subtypes" ], "concepts": { "conditions": [ "atherosclerosis", "coronary artery disease", "coronary stenosis", "stable coronary artery disease", "acute myocardial infarction" ], "biological_processes": [ "vascular smooth muscle cell phenotypic switching", "SMC differentiation", "SMC cell fate", "plaque remodeling", "atherosclerotic plaque microenvironment", "extracellular matrix remodeling", "inflammation" ], "cell_types": [ "vascular smooth muscle cells", "monocytes/macrophages", "endothelial cells", "T cells", "B cells", "mast cells", "plasma cells" ], "smc_phenotypes": [ "contractile-like SMC state", "inflammatory SMC state", "synthetic/ECM-associated SMC state", "fibroblast-like SMC state" ], "data_types": [ "single-cell RNA sequencing", "bulk transcriptomics", "coronary stenosis phenotype" ], "methods": [ "Seurat", "UMAP", "CellChat", "Monocle2", "pseudotime analysis", "Mfuzz", "MOVICS", "nearest template prediction", "over-representation analysis", "gene set enrichment analysis", "GSVA", "xCell" ], "signature_taxonomy": [ "SMC cell fate decision signature", "SCFDS", "C1 DNA-damage repair type", "C2 immune-activated type", "C3 stromal-rich type" ], "representative_markers": [ "ACTA2", "MYH11", "CNN1", "TAGLN", "ENG", "NT5E" ], "pathways": [ "extracellular matrix", "collagen signaling", "CXCL signaling", "TGF-beta signaling", "inflammatory response", "base-excision repair", "DNA replication", "nucleotide-excision repair", "oxidative phosphorylation", "AGE-RAGE signaling" ], "datasets": [ "SRP199578", "GSE20680", "GSE20681", "GSE21545", "GSE59867", "GSE62646", "GSE90074" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Retrospective integrative multicohort transcriptomic and single-cell computational study", "evidence_type": "Human coronary-plaque single-cell RNA sequencing, bulk transcriptomics, pseudotime analysis, molecular subtyping, pathway analysis, inferred cellular microenvironment analysis, and retrospective clinical association", "population": "Human atherosclerosis and coronary artery disease samples spanning different degrees of coronary stenosis, stable coronary artery disease, and acute myocardial infarction, together with human coronary atherosclerotic plaque single-cell data", "primary_endpoint": "Identification of SMC cell-fate-associated transcriptional programs and SCFDS-based molecular subtypes of atherosclerosis", "secondary_endpoint": "Characterization of subtype biological programs, coronary stenosis associations, and cross-cohort expression-template reproducibility", "data_modalities": [ "single-cell RNA sequencing", "bulk transcriptomics", "coronary stenosis phenotypes", "clinical coronary disease states", "pathway and cellular-microenvironment inference" ], "external_validation": true, "scale_metrics": [ { "label": "single-cell donors", "value": "4 cardiac transplant recipients with diseased right-coronary-artery segments" }, { "label": "single cells after quality control", "value": "11,756" }, { "label": "major plaque cell populations", "value": "8" }, { "label": "SMCs analyzed in depth", "value": "5,419" }, { "label": "SMC transcriptional clusters", "value": "9" }, { "label": "SMC pseudotime states", "value": "5" }, { "label": "SMC cell-fate leader genes", "value": "1,072" }, { "label": "Mfuzz temporal gene modules", "value": "8" }, { "label": "bulk transcriptomic scale reported in Abstract", "value": "1,070 samples across six bulk cohorts" }, { "label": "discovery cohort", "value": "GSE20680; 195 blood-expression samples stratified by coronary stenosis severity" }, { "label": "SCFDS molecular subtypes", "value": "3" }, { "label": "external NTP cohorts", "value": "5" } ], "counting_note": "The article reports 1,070 bulk transcriptomic samples across six bulk cohorts in the Abstract, while the Methods states that 1,074 samples from seven independent public cohorts were enrolled and separately describes the four-donor single-cell dataset. Participants, longitudinal samples, bulk transcriptomic samples and single cells represent different counting units and are therefore preserved by modality rather than combined into a derived unique-participant total. The article also contains minor inconsistencies in cohort enumeration, so dataset-level provenance is reported explicitly." }, "study_profile_source": "data/deep_geo/smc-fate.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/smc-fate.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/smc-fate.json", "gold_content_sha256": "fc0a8d71d3e7a75a1edc37e576aae499903ae6bcb8d2336ac582dc1fc060cc09", "provenance": { "publisher_url": "https://link.springer.com/article/10.1186/s12967-022-03795-9", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/36474294/", "pmcid": "PMC9724432", "doi_url": "https://doi.org/10.1186/s12967-022-03795-9", "version_of_record": "Journal of Translational Medicine, Volume 20, Article 568, published 6 December 2022", "license": "Creative Commons Attribution 4.0 International License", "single_cell_source": "SRP199578; diseased right-coronary-artery segments from four cardiac transplant recipients", "bulk_discovery": "GSE20680; 195 samples stratified by coronary stenosis. The article Methods describes these as PBMC samples, whereas the GEO accession describes whole-blood cell expression profiling.", "external_cohorts": "GSE20681; GSE21545; GSE59867; GSE62646; GSE90074", "supplementary_material": "Additional file 1: Figure S1, single-cell RNA-seq quality control; Additional file 2: Figure S2, plaque cell-type mapping; Additional file 3: Table S1, SMC cell-fate leader genes; Additional file 4: Table S2, Mfuzz gene modules", "ethics": "Ethics Committee of the First Affiliated Hospital of Zhengzhou University, approval 2021-KY-0720; analyzed source data were mainly obtained from public databases", "source_note_counting": "The Abstract reports 1,070 bulk samples across six bulk cohorts, whereas the Methods states 1,074 samples across seven independent public cohorts while separately describing the four-donor single-cell dataset. Counts are preserved by modality and are not collapsed into a derived unique-participant total.", "source_note_sample_type": "For GSE20680, the article Methods uses the term PBMC samples, whereas the NCBI GEO record describes whole-blood cell gene-expression profiling. This evidence page preserves the discrepancy rather than silently harmonizing the sample type.", "source_note_accession": "The Results narrative contains GSE26081 once, whereas Fig. 6 identifies GSE20681. NCBI GEO confirms GSE20681 as the PREDICT coronary artery disease dataset; GSE26081 is an unrelated breast-cancer ER-alpha dataset. This evidence page therefore uses GSE20681 while retaining the discrepancy in provenance.", "evidence_basis": "Version of record, PMC full text, PubMed record, supplementary information, and NCBI GEO records" }, "scientific_role": "Human plaque single-cell state reconstruction linked to multicohort transcriptomic subtyping of atherosclerosis.", "evidence_position": "Retrospective human transcriptomics and computational pseudotime; inferred state relationships, not direct longitudinal lineage tracing or subtype-guided treatment evidence.", "related_concepts": [ "Smooth muscle cell plasticity research", "Cell-state-to-subtype integration" ], "citation_contexts": [ "Background: cellular heterogeneity and smooth muscle cell remodeling in atherosclerosis.", "Methods: integration of human plaque single-cell programs with bulk-expression subtypes, retaining the pseudotime limitation." ], "evidence_scope": { "supports": [ "Human coronary atherosclerotic plaques contain substantial transcriptional heterogeneity among vascular smooth muscle cells.", "The analyzed SMC transcriptomes can be computationally organized into a pseudotime trajectory with five states and distinct cluster distributions.", "A 1,072-gene fate-leader set and temporal expression modules summarize SMC state-associated transcriptional programs in these data.", "SCFDS-based analysis identified three retrospective molecular subtypes with distinct DNA-repair, inflammatory/immune and stromal/ECM-associated profiles.", "C2 was associated with greater coronary stenosis severity and C3 with lower severity in the discovery analysis.", "The three-subtype expression-template structure was reproducible across five independent retrospective transcriptomic cohorts.", "SCFDS can serve as a research framework for studying SMC-related molecular heterogeneity in atherosclerosis." ], "does_not_establish": [ "That the nine SMC clusters are fixed biological lineages or clinically defined cell types.", "That pseudotime directly observes individual human SMCs transforming longitudinally within the same lesion.", "That all 1,072 fate-leader genes causally regulate SMC fate.", "That C1, C2 and C3 are prospectively validated clinical diagnostic or prognostic classes.", "That C2 causes coronary stenosis progression or that C3 causally protects against plaque progression or clinical events.", "That pathway enrichment or inferred cell-composition differences prove the underlying mechanisms.", "That retrospective NTP reproducibility is equivalent to prospective multicenter clinical validation.", "That SCFDS-guided treatment improves myocardial infarction, mortality or other clinical outcomes.", "That the therapeutic hypotheses discussed by the authors constitute validated treatment recommendations." ] }, "limitations": [ "The study was primarily computational and cannot fully recapitulate the diversity of developmental states or directly demonstrate longitudinal SMC lineage transitions in human plaques.", "The plaque single-cell analysis was based on four human donors, limiting direct generalization of cell-state frequencies.", "All samples used for subtype analyses were retrospective; prospective multicenter clinical validation was not performed.", "NTP validation demonstrates retrospective expression-template reproducibility rather than prospective diagnostic, prognostic or treatment-predictive performance.", "Pathway enrichment, xCell and related computational inference generate biological hypotheses but do not establish causal mechanisms.", "The article contains inconsistencies in sample/cohort enumeration and one external-cohort accession identifier; counts and dataset provenance should therefore be preserved explicitly rather than silently reconciled." ], "scope_source": "data/deep_geo/smc-fate.json#/evidence_scope" }, { "id": "doi-10-1002-ehf2-14003", "title": "Uncovering the Genetic Links of SARS-CoV-2 Infections on Heart Failure Co-Morbidity by a Systems Biology Approach", "doi": "10.1002/ehf2.14003", "year": 2022, "journal": "ESC Heart Failure", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html", "markdown_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.md", "paper_geo_status": "v2", "authors": [ "Ge Zhang", "Xiaolin Cui", "Li Zhang", "Gangqiong Liu", "Xiaodan Zhu", "Jiahong Shangguan", "Wenjing Zhang", "Yingying Zheng", "Hui Zhang", "Junnan Tang", "Jinying Zhang" ], "doi_url": "https://doi.org/10.1002/ehf2.14003", "publisher_url": "https://academic.oup.com/eschf/article/9/5/2937/8323023", "pmid": "35727093", "pmcid": "PMC9349450", "openalex_id": "https://openalex.org/W4283273503", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1002-ehf2-14003.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1002-ehf2-14003.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1002-ehf2-14003.csl.json", "evidence_status": "reviewed_v2", "question_count": 8, "key_findings": [ { "id": "KF1", "claim": "Independent COVID-19 and HF expression analyses yielded a 12-gene shared transcriptomic signature.", "context": "Overlap was calculated across separately profiled disease datasets, not in a cohort of people with both COVID-19 and HF.", "evidence": [ { "label": "DEG threshold", "value": "|log2FC| > 1 and adjusted P < 0.05" }, { "label": "COVID-19 DEGs", "value": "102" }, { "label": "HF DEGs", "value": "253" }, { "label": "shared genes", "value": "12: S100A8, ABCB1, S100A11, PTGS2 (COX2), LY96, XCL1, RORA, CCL11, CCL4, S100A12, BCL2 and AQP9" } ], "source_locator": "Results: Identification of shared transcriptomic signature between HF and COVID-19; Figure 1B-D", "source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#kf1" }, { "id": "KF2", "claim": "Functional enrichment highlighted inflammatory and innate-immune pathways associated with the shared expression signals.", "context": "Enrichment points to pathway associations; it does not demonstrate that these pathways causally mediate COVID-19–HF comorbidity.", "evidence": [ { "label": "cellular processes", "value": "neutrophil chemotaxis and migration, monocyte chemotaxis, and inflammatory response" }, { "label": "molecular functions", "value": "chemokine activity, CCR chemokine receptor binding, RAGE receptor binding and Toll-like receptor binding" }, { "label": "signaling pathways", "value": "NF-κB-related and IL-17-related signaling, plus cytokine-cytokine receptor interaction" } ], "source_locator": "Results: Analysis of functional characteristics relevant to common pathogenesis; Figures 2-3; Supplementary Tables S1-S2", "source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#kf2" }, { "id": "KF3", "claim": "PPI topology prioritized ten inflammatory hub genes and a four-gene core of TLR4, TLR2, IL10 and STAT3.", "context": "Hub status reflects network centrality and algorithmic prioritization, not proof that these genes cause either disease.", "evidence": [ { "label": "initial PPI network", "value": "62 nodes and 655 edges" }, { "label": "ten hub genes", "value": "TLR4, TLR2, CXCL8, IL10, STAT3, IL1B, TLR1, TP53, CCL20 and CXCL10" }, { "label": "hub interaction network", "value": "59 nodes and 649 edges" }, { "label": "seven-algorithm core", "value": "TLR4, TLR2, IL10 and STAT3" }, { "label": "MCODE module 1", "value": "29 nodes, 381 edges, score 27.214; includes XCL1, CCL4 and CCL11" }, { "label": "MCODE module 2", "value": "23 nodes, 65 edges, score 11.818" } ], "source_locator": "Results: Protein-protein interaction analysis; Figures 4-5; Supplementary Tables S3-S4", "source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#kf3" }, { "id": "KF4", "claim": "External public PBMC expression datasets supported prioritization of TLR4, TLR2, STAT3, IL1B and CXCL8, with tissue-context nuance for IL1B.", "context": "The PCA percentages describe variance explained by the first two components, not AUC, accuracy, sensitivity, specificity, or prospective diagnostic validation. IL1B was not uniformly upregulated across tissues.", "evidence": [ { "label": "COVID-19 expression dataset", "value": "GSE164805: 10 COVID-19 and 5 healthy PBMC samples" }, { "label": "HF expression dataset", "value": "GSE9128/GDS3115: 8 HF pooled and 3 control pooled PBMC microarray samples" }, { "label": "final prioritized genes", "value": "TLR4, TLR2, STAT3, IL1B and CXCL8" }, { "label": "five-gene PCA first-two-component explained variance", "value": "COVID-19 96.0%; HF 93.2%; merged 89.9%" }, { "label": "earlier ten-hub-gene PCA explained variance", "value": "COVID-19 88.5%; HF 90.0%" }, { "label": "IL1B lung-tissue context", "value": "GSE147507 re-analysis showed increased IL1B in COVID-19 lung tissue (P=0.006), despite non-uniform PBMC patterns" } ], "source_locator": "Results: Validation of hub genes performance in two independent cohorts; Figures 6-7", "source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#kf4" }, { "id": "KF5", "claim": "Database-derived networks nominated TF and miRNA candidates for subsequent experimental testing.", "context": "These network edges are computational predictions, not experimentally confirmed upstream regulatory mechanisms.", "evidence": [ { "label": "TF network", "value": "47 predicted TF targets, 59 nodes and 98 edges" }, { "label": "TF-miRNA network", "value": "98 TFs, 137 miRNAs, 246 nodes and 310 edges" }, { "label": "highlighted predicted TFs", "value": "FOXC1, STAT3 and NFKB1 (NF-κB1)" }, { "label": "highlighted predicted miRNAs", "value": "miR-181, miR-520 and miR-143" } ], "source_locator": "Results: Determination of regulatory signature and network; Figure 8A-B; Supplementary Figure S1", "source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/key_findings/4", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#kf5" }, { "id": "KF6", "claim": "Drug-signature enrichment nominated muramyl dipeptide and glutathione as hypothesis-generating compounds.", "context": "DSigDB prioritization is an in-silico signal; no therapeutic efficacy was demonstrated for COVID-19, HF, or their co-occurrence.", "evidence": [ { "label": "input genes", "value": "CXCL8, STAT3, IL1B, TLR4 and TLR2" }, { "label": "analysis resource", "value": "DSigDB drug-signature enrichment" }, { "label": "candidate compounds", "value": "muramyl dipeptide (MDP) and glutathione (GSH)" }, { "label": "evidence level", "value": "in-silico hypothesis generation, not treatment-efficacy evidence" } ], "source_locator": "Results: Identification of candidate pharmacologic agents; Figure 8C; Discussion: Promising therapeutics", "source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/key_findings/5", "evidence_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#kf6" } ], "field_entry": [ "Inflammation in cardiovascular disease", "Cross-disease systems biology" ], "review_topics": [ "COVID-19 and heart failure inflammatory biology", "Shared disease-associated expression programs" ], "concepts": { "conditions": [ "COVID-19", "SARS-CoV-2 infection", "heart failure", "ischemic cardiomyopathy", "non-ischemic cardiomyopathy" ], "datasets": [ "GSE147507", "GSE26887", "GSE164805", "GSE9128", "GDS3115" ], "methods": [ "differential expression", "GO enrichment", "KEGG enrichment", "Reactome", "WikiPathways", "BioCarta", "Metascape", "PPI network analysis", "cytoHubba", "MCODE", "GeneMANIA", "ClueGO", "JASPAR", "RegNetwork", "DSigDB", "hierarchical clustering", "Spearman correlation", "principal component analysis" ], "modalities": [ "lung-biopsy transcriptomics", "cardiac-tissue transcriptomics", "pooled PBMC microarrays" ], "molecular_entities": [ "S100A8", "ABCB1", "S100A11", "PTGS2 (COX2)", "LY96", "XCL1", "RORA", "CCL11", "CCL4", "S100A12", "BCL2", "AQP9", "TLR4", "TLR2", "CXCL8", "IL10", "STAT3", "IL1B", "TLR1", "TP53", "CCL20", "CXCL10", "FOXC1", "NFKB1", "miR-181", "miR-520", "miR-143", "glutathione", "muramyl dipeptide" ], "biological_processes": [ "Toll-like receptor signaling", "NF-κB signaling", "chemokine signaling", "cytokine signaling", "IL-17 signaling", "neutrophil chemotaxis", "monocyte chemotaxis", "inflammatory response", "response to lipopolysaccharide" ], "hypothesis_level_concepts": [ "gut-heart axis", "gut microbiome dysbiosis", "microbial-product translocation", "lipopolysaccharide" ] }, "profile_type": "multicohort_omics", "study_profile": { "profile_type": "multicohort_omics", "study_design": "Cross-disease analysis of independent public COVID-19 and HF transcriptomic datasets, followed by enrichment, protein-interaction and regulatory-network analyses, and external expression-dataset evaluation", "evidence_type": "Public gene-expression differential-expression analysis, pathway enrichment, PPI topology, external PBMC expression evaluation, and computational TF/miRNA and drug-signature prioritization", "population": "Separate human COVID-19 lung-tissue and PBMC datasets and HF cardiac-tissue and pooled PBMC datasets; no dedicated cohort of patients simultaneously affected by COVID-19 and HF", "primary_endpoint": "Shared disease-associated expression signatures between independently profiled COVID-19 and HF datasets", "secondary_endpoint": "Inflammatory pathway and network-hub prioritization, external expression-pattern evaluation, and hypothesis-generating regulatory and compound candidates", "data_modalities": [ "lung-biopsy transcriptomics", "left-ventricular cardiac-tissue transcriptomics", "PBMC gene-expression microarrays, including pooled samples", "functional and pathway enrichment", "protein-protein-interaction network analysis", "TF/miRNA network prediction", "drug-signature enrichment" ], "external_validation": true, "scale_metrics": [ { "label": "GSE147507 human lung-biopsy component", "value": "2 independent uninfected donors and technical replicates from 1 deceased COVID-19 donor; the full GEO Series contains additional experimental systems" }, { "label": "GSE26887 formal LV tissue Series", "value": "7 T2DM HF, 12 non-T2DM HF and 5 controls: 19 HF and 5 control cardiac-tissue samples (24 total); the exact article HF DEG contrast grouping is not explicit" }, { "label": "GSE164805 external COVID-19 PBMC samples", "value": "10 COVID-19 (5 mild and 5 severe) and 5 healthy samples" }, { "label": "GSE9128/GDS3115 external HF PBMC arrays", "value": "8 HF pooled microarray samples and 3 pooled control microarray samples; not 11 independent participants" }, { "label": "GSE9128 original participant population", "value": "12 ischemic cardiomyopathy HF and 12 non-ischemic cardiomyopathy HF individuals (24 HF), plus 12 control individuals, pooled into 11 PBMC microarray samples" }, { "label": "differential-expression results", "value": "102 COVID-19 DEGs, 253 HF DEGs and 12 shared genes at absolute log2FC > 1 and adjusted P < 0.05" } ], "counting_note": "Dataset-level counts represent different biological and analytical units and are not summed into a synthetic participant total. GSE147507 contains multiple experimental systems; its human lung-biopsy component consists of two independent uninfected donors and technical replicates from one deceased COVID-19 donor. GSE26887 formally contains 19 HF and five control cardiac-tissue samples, but the precise grouping used for the article-reported 253 HF DEGs is not sufficiently specified in the accessible main text, so 24 is not asserted as the primary analytical contrast n. GSE164805 contains 10 COVID-19 and five healthy PBMC samples. GSE9128/GDS3115 contains 11 pooled PBMC microarray samples—eight HF pools and three control pools—derived from an original study population of 24 HF and 12 control individuals. Participants, pooled samples, technical replicates, and tissue samples are not interchangeable." }, "study_profile_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-1002-ehf2-14003.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-1002-ehf2-14003.json", "gold_content_sha256": "f45b951a025629f8d7e8a20dd3ffee8aeb0af61f1ba6bc270081e964936f2b59", "provenance": { "publisher_url": "https://doi.org/10.1002/ehf2.14003", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/35727093/", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC9349450/", "pmid": "35727093", "pmcid": "PMC9349450", "version_of_record": "ESC Heart Failure (2022), peer-reviewed publication with DOI 10.1002/ehf2.14003; PMID 35727093 and PMCID PMC9349450.", "datasets_cohorts": "Primary cross-disease analyses: GSE147507 COVID-19 lung component and GSE26887 HF left-ventricular tissue. External expression evaluation: GSE164805 COVID-19 PBMCs and GSE9128/GDS3115 pooled HF and control PBMC arrays.", "supporting_material": "Supplementary Tables S1-S4 and Supplementary Figure S1.", "evidence_basis": "The peer-reviewed article's Results, Methods, figures, supplementary-material references, and the stated formal GEO dataset identities provide the source locators; the analyses compare separate COVID-19 and HF datasets.", "accession_note": "The Figure 1 caption contains an apparent GSE26687 accession typo; Methods and Results and the formal GEO identity establish GSE26887 as the HF dataset. GSE26687 is not treated as a second scientific dataset.", "counting_note": "GSE147507 donor and technical-replicate counts, GSE26887 cardiac-tissue samples, GSE164805 PBMC samples, and GSE9128/GDS3115 pooled PBMC arrays have distinct units and are not added into a synthetic participant total." }, "scientific_role": "Comparison of independently sampled COVID-19 and heart-failure transcriptomes for shared inflammatory and regulatory hypotheses.", "evidence_position": "Public expression datasets analyzed separately across diseases; not a dedicated comorbid cohort, germline genetic evidence or demonstrated infection-to-heart-failure causality.", "related_concepts": [ "Cross-disease inflammatory signatures", "Transcriptomic hypothesis generation" ], "citation_contexts": [ "Background: molecular overlap between infection-related and heart-failure inflammation.", "Methods: cross-disease expression and network analysis, without inferring genetic causality or treatment efficacy." ], "evidence_scope": { "supports": [ "Shared transcriptional signals across independently profiled COVID-19 and HF datasets.", "Inflammatory and innate-immune pathway enrichment and network prioritization of TLR-associated genes.", "External public expression-dataset support for selected hub genes, with tissue-dependent IL1B interpretation.", "Computational TF/miRNA and candidate-compound hypothesis generation.", "Hypothesis generation around gut-heart and LPS biology, without direct measurement of microbiome or LPS." ], "does_not_establish": [ "Germline genetic correlation, inherited susceptibility, GWAS evidence, Mendelian randomization, or genetic causality.", "A causal SARS-CoV-2-to-HF mechanism or findings from a dedicated cohort simultaneously affected by COVID-19 and HF.", "Prospective clinical validation, diagnostic accuracy, or prognostic utility of a five-gene panel.", "Experimentally demonstrated TF/miRNA regulation or direct measurement of gut microbiome dysbiosis, intestinal permeability, or circulating LPS.", "Proteomic evidence or therapeutic efficacy of glutathione, muramyl dipeptide, or another intervention." ] }, "limitations": [ "Human evidence was assembled retrospectively from heterogeneous public expression datasets; no dedicated simultaneous COVID-19 and HF cohort or prospective clinical validation was reported.", "Lung tissue, cardiac tissue, and PBMC samples and their experimental platforms are not directly interchangeable.", "The GSE147507 human COVID-19 lung component had one deceased COVID-19 biological donor with technical replicates and two independent uninfected donors; total GEO Series entries are not a participant count.", "GSE9128/GDS3115 evaluated 11 pooled PBMC microarray samples rather than 11 independent participants, although the original population comprised 24 HF and 12 control individuals.", "The exact GSE26887 grouping that generated the article-reported 253 HF DEGs is not sufficiently explicit in the accessible main article; the formal Series contains 19 HF and five control cardiac-tissue samples.", "PPI, TF/miRNA and drug-signature findings are computational or database-derived and lack direct causal perturbation validation.", "Gut-microbiome composition, intestinal permeability and circulating LPS were not directly measured; gut-heart interpretation remains a hypothesis.", "No proteomics, candidate-compound treatment experiment, or demonstrated therapeutic efficacy for glutathione or muramyl dipeptide was reported." ], "scope_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/evidence_scope" }, { "id": "doi-10-3389-fonc-2021-659217", "title": "Efficacy and Safety of Apatinib Treatment for Advanced Cholangiocarcinoma After Failed Gemcitabine-Based Chemotherapy: An Open-Label Phase II Prospective Study", "doi": "10.3389/fonc.2021.659217", "year": 2021, "journal": "Frontiers in Oncology", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2021-659217.html", "markdown_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2021-659217.md", "paper_geo_status": "v2", "authors": [ "Ge Zhang", "Shuai Gong", "Lina Pang", "Lixia Hou", "Wei He" ], "doi_url": "https://doi.org/10.3389/fonc.2021.659217", "publisher_url": "https://www.frontiersin.org/articles/10.3389/fonc.2021.659217/full", "pmid": "34012920", "pmcid": "PMC8126718", "openalex_id": "https://openalex.org/W3158276903", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-3389-fonc-2021-659217.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-3389-fonc-2021-659217.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-3389-fonc-2021-659217.csl.json", "evidence_status": "reviewed_v2", "question_count": 4, "key_findings": [ { "claim": "Thirty-two patients enrolled; six withdrew before treatment, leaving 26 in the FAS/safety population and 24 in the efficacy analysis.", "context": "The unique total of 32 is enrollment only, not the response-rate denominator. Enrollment, treated and efficacy populations overlap and must not be added together.", "evidence": [ { "label": "enrolled", "value": "32" }, { "label": "withdrew before treatment", "value": "6" }, { "label": "FAS safety population", "value": "26" }, { "label": "efficacy population", "value": "24" } ], "source_locator": "Results: Patients' Characteristics; Efficacy of Apatinib Treatment", "id": "KF1", "source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2021-659217.html#kf1" }, { "claim": "Among 24 efficacy-evaluable patients, responses were CR 1, PR 4, SD 10 and PD 9; ORR was 20.8% and DCR was 62.5%.", "context": "These are observations without a concurrent control. ORR uses the reported percentage interval; DCR uses the Results-reported percentage interval, not the survival-day interval printed in the abstract.", "evidence": [ { "label": "efficacy denominator", "value": "24" }, { "label": "CR", "value": "1" }, { "label": "PR", "value": "4" }, { "label": "SD", "value": "10" }, { "label": "PD", "value": "9" }, { "label": "ORR", "value": "20.8%" }, { "label": "ORR reported 95 percent CI", "value": "9.24–40.47%" }, { "label": "DCR", "value": "62.5%" }, { "label": "DCR Results reported 95 percent CI", "value": "42.71–78.84%" } ], "source_locator": "Results: Efficacy of Apatinib Treatment", "id": "KF2", "source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/key_findings/1", "evidence_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2021-659217.html#kf2" }, { "claim": "Median PFS was 95 days (reported 95% CI 79.70–154.34 days), and median OS was 250 days (reported 95% CI 112.86–387.14 days).", "context": "Without a concurrent comparison, these observed survival times do not establish a survival gain or comparative benefit.", "evidence": [ { "label": "median PFS", "value": "95 days" }, { "label": "PFS reported 95 percent CI", "value": "79.70–154.34 days" }, { "label": "median OS", "value": "250 days" }, { "label": "OS reported 95 percent CI", "value": "112.86–387.14 days" } ], "source_locator": "Results: Efficacy of Apatinib Treatment; Fig. 1", "id": "KF3", "source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/key_findings/2", "evidence_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2021-659217.html#kf3" }, { "claim": "In the safety population of 26, myelosuppression, hypertension and proteinuria were reported in 69.2%, 57.7% and 46.2%; Grade 3 hypertension and leukopenia each occurred in three patients.", "context": "No Grade 4 events or drug-related deaths were reported. Adverse-event categories overlap and cannot be summed as independent patients; absence of observed events in a small sample does not establish absence of risk.", "evidence": [ { "label": "safety denominator", "value": "26" }, { "label": "myelosuppression", "value": "69.2%" }, { "label": "hypertension", "value": "57.7%" }, { "label": "proteinuria", "value": "46.2%" }, { "label": "Grade 3 hypertension", "value": "3 patients" }, { "label": "Grade 3 leukopenia", "value": "3 patients" }, { "label": "Grade 4 or drug related deaths", "value": "Not reported" } ], "source_locator": "Results: Safety; Table 3", "id": "KF4", "source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/key_findings/3", "evidence_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2021-659217.html#kf4" } ], "field_entry": [ "Biliary tract oncology", "Early-phase cancer treatment evidence" ], "review_topics": [ "Cholangiocarcinoma after chemotherapy failure", "Single-arm phase II activity and toxicity reporting" ], "concepts": { "disease": [ "advanced cholangiocarcinoma" ], "intervention": [ "apatinib" ], "design": [ "single-arm phase II", "open-label study" ], "outcomes": [ "objective response", "disease control", "PFS", "OS", "adverse events" ] }, "profile_type": "clinical_cohort", "study_profile": { "study_design": "Prospective, open-label, single-center, single-arm phase II study", "evidence_type": "Human interventional activity and descriptive safety evidence without a concurrent control", "population": "Advanced cholangiocarcinoma after gemcitabine-based treatment failure", "primary_endpoint": "Objective response rate", "secondary_endpoint": "Disease control, progression-free survival, overall survival and adverse events", "data_modalities": [ "clinical treatment records", "RECIST 1.1 tumor assessment", "survival follow-up", "CTCAE 4.0 toxicity assessment" ], "unique_total_n": 32, "cohorts": [ { "name": "Enrolled cohort — not the efficacy denominator", "role": "Enrollment total; treated/FAS and efficacy denominators are specified in KF1.", "n": 32 } ], "profile_type": "clinical_cohort", "external_validation": false }, "study_profile_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/study_profile", "model_profile": null, "model_profile_source": null, "narrative_genre": null, "gold_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json", "gold_source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/deep_geo/doi-10-3389-fonc-2021-659217.json", "gold_content_sha256": "53c1128befa7c7f4de7650706971f5ccf2e5669bfc135f197bb3393154483f65", "provenance": { "publication_url": "https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2021.659217/full", "pubmed_url": "https://pubmed.ncbi.nlm.nih.gov/34012920/", "pmc_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC8126718/", "review_basis": "Selected findings checked against published main text, readable tables and publication records. No participant-level reanalysis or comprehensive supplementary-data audit was performed.", "trial_registration": "NCT03521219 as reported in the article; registry concordance was not independently adjudicated in this content review." }, "scientific_role": "Prospective single-arm description of apatinib activity and toxicity after gemcitabine-based treatment failure in advanced cholangiocarcinoma.", "evidence_position": "Human single-center phase II observations without a randomized concurrent control; not comparative superiority, causal survival benefit or a current treatment recommendation.", "related_concepts": [ "Non-comparative oncology evidence", "Response-denominator interpretation" ], "citation_contexts": [ "Evidence synthesis: early-phase treatment studies in previously treated advanced cholangiocarcinoma.", "Methods: denominator-explicit interpretation of response and safety in single-arm oncology trials." ], "evidence_scope": { "supports": [ "Descriptive tumor-response, survival and safety observations in this small prospective single-arm study.", "Separate enrollment, safety and efficacy denominators with explicit attribution of the Results DCR interval." ], "does_not_establish": [ "Superiority or a causal comparative survival benefit without a randomized concurrent control.", "A general clinical treatment recommendation, corrected dosing or current guideline status.", "An anatomic-subgroup superiority claim or a newly corrected set of published estimates." ] }, "limitations": [ "The study is small, single-center and single-arm, with no randomized concurrent control.", "Enrollment, FAS/safety and efficacy use different, overlapping analysis denominators.", "Reporting note: the abstract DCR interval uses a survival-day interval. This page uses the Results-reported percentage interval with explicit attribution; it does not recompute or replace published confidence intervals.", "Reporting note: the abstract describes an intrahepatic-only population, whereas the body includes extrahepatic patients; the evidence page therefore uses advanced cholangiocarcinoma.", "Additional reporting differences concern anatomic-subgroup counts/significance and some adverse-event percentages. No subgroup-superiority claim or newly corrected numbers are generated from those differences.", "No clinical drug recommendation, corrected dose or current guideline status is supplied.", "Official Abstract addition is deferred in this batch because of the identified population and DCR-interval reporting issues, not a determination that copyright prohibits it." ], "scope_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/evidence_scope" }, { "id": "doi-10-3980-j-issn-1672-5123-2020-12-13", "title": "Culture methods of inducing embryonic stem cells to differentiate into retinal pigment epithelial cells", "doi": "10.3980/j.issn.1672-5123.2020.12.13", "year": 2020, "journal": "International Eye Science", "type": "Article", "paper_url": "https://drgezhang.com/papers/doi-10-3980-j-issn-1672-5123-2020-12-13.html", "markdown_url": "https://drgezhang.com/papers/doi-10-3980-j-issn-1672-5123-2020-12-13.md", "paper_geo_status": "none", "authors": [ "Ge Zhang", "Han Zhu", "Jing-Wen Zhang", "Yu-Di Xu", "Ming-Xuan Duan", "Ge Zhang" ], "doi_url": "https://doi.org/10.3980/j.issn.1672-5123.2020.12.13", "publisher_url": null, "pmid": null, "pmcid": null, "openalex_id": "https://openalex.org/W4399062302", "semantic_scholar_id": null, "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-3980-j-issn-1672-5123-2020-12-13.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-3980-j-issn-1672-5123-2020-12-13.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-3980-j-issn-1672-5123-2020-12-13.csl.json", "evidence_status": "limited", "question_count": 0, "key_findings": [], "field_entry": [], "review_topics": [], "concepts": {}, "evidence_url": "https://drgezhang.com/papers/doi-10-3980-j-issn-1672-5123-2020-12-13.html#limited-evidence", "source_url": "https://github.com/DrZoggg/Ge-Zhang.github.io/blob/main/data/limited_evidence.json", "provenance": [ { "url": "https://gjyk.ijournals.cn/gjykcn/article/pdf/202012013", "label": "Official review PDF", "format": "Complete publisher PDF reviewed locally", "locator": "PDF p. 1 / journal p. 2079: 文献综述, 摘要, Abstract and Introduction" } ], "scope": "Methods-review context from the complete official PDF; publisher-verified author and journal metadata are supplied with the citation.", "evidence_notice": "Methods-review context from the complete official PDF; publisher-verified author and journal metadata are supplied with the citation.", "evidence_scope": null, "limitations": [ "The publisher PDF identifies a narrative review in International Eye Science. The site's broad Article metadata category does not imply an original experiment or clinical study." ], "scope_source": "data/limited_evidence.json#/papers/10.3980~1j.issn.1672-5123.2020.12.13/scope" } ], "all_questions": [ { "id": "doi-10-1007-s10238-026-02130-6--qa-1", "work_id": "doi-10-1007-s10238-026-02130-6", "qa_index": 1, "question": "What data underpin the DCM network subtypes?", "answer": "Four public myocardial expression datasets were analyzed. Table 1 reports 245 DCM and 174 control samples in total. These are sample counts; the evidence page does not present them as a verified unique-patient total.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#qa-1", "question_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/0/answer", "answer_sha256": "ec67d0e57f12fa8784b8377f4eaaea942ad7d2cbbe84f12a1a3959af0f915181", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s10238-026-02130-6--qa-2", "work_id": "doi-10-1007-s10238-026-02130-6", "qa_index": 2, "question": "How were network perturbations constructed?", "answer": "The analysis ranked genes within each sample, calculated rank differences for interacting genes and compared those differences with a control-derived reference. Selected perturbation edges were then used for clustering.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#qa-2", "question_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/1/answer", "answer_sha256": "d38ea3b3a66e3d8e6b81dfe85c658f896d5bc8340bf8da960e906c229018cc4f", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s10238-026-02130-6--qa-3", "work_id": "doi-10-1007-s10238-026-02130-6", "qa_index": 3, "question": "How many molecular subtypes were identified?", "answer": "The selected solution comprised EPS1, EPS2 and EPS3. Their reported frequencies ranged from 43.2-52.5%, 40.0-44.2% and 7.5-13.5%, respectively, across the analyzed datasets.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#qa-3", "question_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/2/answer", "answer_sha256": "b815c3f9860ed99e2f6b05fe545eff215e5181ee546672a1bd9e64920afd8182", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s10238-026-02130-6--qa-4", "work_id": "doi-10-1007-s10238-026-02130-6", "qa_index": 4, "question": "Were the immune differences measured directly in individual cells?", "answer": "No. Immune-related scores were inferred from bulk gene-expression profiles using ssGSEA. Those associations are useful for generating hypotheses but are not direct cell counts or proof of immune causation.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#qa-4", "question_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/3/answer", "answer_sha256": "02d66fc28984f9d9173ae8632b9e658bc51efa6a1b9464fabdec434ad2158973", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s10238-026-02130-6--qa-5", "work_id": "doi-10-1007-s10238-026-02130-6", "qa_index": 5, "question": "Does EPS1 prove that immunoadsorption will work for a patient?", "answer": "No. EPS1 expression matched the responder profile in a retrospective Submap analysis. A trial of subtype-guided treatment, with prospectively specified outcomes, would be needed to establish clinical benefit.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#qa-5", "question_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/4/answer", "answer_sha256": "11902aded6d6dee94067436f18e254eede09ddcad2dc41675d76bf0db892045a", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s10238-026-02130-6--qa-6", "work_id": "doi-10-1007-s10238-026-02130-6", "qa_index": 6, "question": "What did the AC16-cell experiment validate?", "answer": "It checked the direction of eight genes selected from overlapping EPS1-versus-control and DCM-versus-control contrasts. Three increased and five decreased after angiotensin-II treatment. It does not validate all three subtypes or their treatment responses.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#qa-6", "question_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/5/answer", "answer_sha256": "3363b2300f6c2e6e5279ec3df4a65a602f6018dbd801ea279d10c1d445b48d4d", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s10238-026-02130-6--qa-7", "work_id": "doi-10-1007-s10238-026-02130-6", "qa_index": 7, "question": "Can the subtype frequencies be used as population prevalence estimates?", "answer": "No. They describe selected public myocardial datasets and the reported analysis procedure. They are not estimates from a population-based DCM sampling frame.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-026-02130-6.html#qa-7", "question_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-026-02130-6.json#/qa/6/answer", "answer_sha256": "c92d6467cfc20cedbdf3679bb3304ec99e9723b48054b78a751870c8de2dbf67", "evidence_refs": [ "KF1", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s11426-026-3629-x--qa-1", "work_id": "doi-10-1007-s11426-026-3629-x", "qa_index": 1, "question": "What experimental systems were actually studied?", "answer": "Controlled chemical solutions and mice were studied. The main atherosclerosis model uses male ApoE-/- mice after 16 weeks of high-fat feeding; the study does not report a cell-culture validation experiment or a human cohort.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#qa-1", "question_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/0/answer", "answer_sha256": "8dbca62b2d003c88b773d625abc3e9b1abf60fb20e3b82282418763bf7ade045", "evidence_refs": [ "KF3", "KF5", "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s11426-026-3629-x--qa-2", "work_id": "doi-10-1007-s11426-026-3629-x", "qa_index": 2, "question": "How does ReP respond to superoxide and glutathione?", "answer": "The authors assign the optical switching to catechol-based oxidation by superoxide and reduction by GSH. Superoxide increases the 740 nm PA response and GSH attenuates it; three alternating cycles are shown in solution.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#qa-2", "question_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/1/answer", "answer_sha256": "38782d5e3d6afd77562bfb4066068ceebb677a92e3fd42ec09e0d8265cdb6896", "evidence_refs": [ "KF1", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s11426-026-3629-x--qa-3", "work_id": "doi-10-1007-s11426-026-3629-x", "qa_index": 3, "question": "What quantitative PA calibration was reported?", "answer": "The displayed superoxide PA calibration spans 0 to 80 micromolar and has R-squared 0.977. The GSH panel spans 0 to 300 micromolar and has R-squared 0.982. The separate superoxide absorption titration extends to 125 micromolar; the ranges must not be conflated.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#qa-3", "question_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/2/answer", "answer_sha256": "8727d51428cc6994b95623f15df55100c1ee5772ebc445cc69b41ab09e24f53f", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s11426-026-3629-x--qa-4", "work_id": "doi-10-1007-s11426-026-3629-x", "qa_index": 4, "question": "Was an absolute or ratiometric plaque redox measurement validated?", "answer": "The displayed animal metric is relative PA intensity in an aortic-region ROI at 740 nm. Although introductory text uses ratiometric language, the figures do not define a validated two-wavelength ratio or convert animal signal into an absolute plaque superoxide concentration.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#qa-4", "question_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/3/answer", "answer_sha256": "2fc6e7be7a8f560295b1e9a565ccc6cfb67cb37c8780ea6aece75fc6a6efcffa", "evidence_refs": [ "KF3", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s11426-026-3629-x--qa-5", "work_id": "doi-10-1007-s11426-026-3629-x", "qa_index": 5, "question": "Which inflammatory and treatment conditions were tested in mice?", "answer": "The main groups are AS plus PBS, AS plus LPS, and AS plus LPS followed by dexamethasone, with n=3 per group. LPS is 50 micrograms in 50 microliters PBS intranasally on days 0 and 1. Dexamethasone is 2 mg/kg/day intraperitoneally from day 2 to day 8; ReP is 300 microliters at 200 micromolar via tail vein.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#qa-5", "question_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/4/answer", "answer_sha256": "f4dec72d6d3e6ea320e9ae4458adf94571d1194d2de3f2b79bdfc24f27d8fa06", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s11426-026-3629-x--qa-6", "work_id": "doi-10-1007-s11426-026-3629-x", "qa_index": 6, "question": "What did histology add to the imaging comparison?", "answer": "Lung wet/dry measurements and H&E support the pulmonary-inflammatory model. Plaque CD68, caspase-3 and Masson staining show group differences; the Fig. 6 percentages are descriptive annotations without supplied per-animal uncertainty or inferential tests.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#qa-6", "question_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/5/answer", "answer_sha256": "7173dc7deaa08f82129c216d95c1a961fc50ca51c7270820a5cabf33c6a4a98a", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s11426-026-3629-x--qa-7", "work_id": "doi-10-1007-s11426-026-3629-x", "qa_index": 7, "question": "Does the study show fewer ruptures or clinical treatment benefit?", "answer": "No rupture-prevention or human cardiovascular-event trial is reported. PA signal and tissue staining in these mouse groups do not establish dexamethasone benefit in patients, clinical diagnostic performance or event prediction.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#qa-7", "question_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/6/answer", "answer_sha256": "97b5c54a473c79a32fa50fd3b2d95fdb8aeb60e861896316bd6e2750aaaabaa1", "evidence_refs": [ "KF5", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s11426-026-3629-x--qa-8", "work_id": "doi-10-1007-s11426-026-3629-x", "qa_index": 8, "question": "What safety conclusion can be supported?", "answer": "The authors report seven-day body-weight observations and major-organ histology in mice. The independent tolerability n is not supplied; these descriptive results do not establish chronic, repeated-dose or human safety.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s11426-026-3629-x.html#qa-8", "question_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/7/question", "answer_source": "data/deep_geo/doi-10-1007-s11426-026-3629-x.json#/qa/7/answer", "answer_sha256": "158d8a162126bd0eb35a259cc73b2f1747273dc172d7876e121f0517022704a8", "evidence_refs": [ "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fcvm-2025-1724572--qa-1", "work_id": "doi-10-3389-fcvm-2025-1724572", "qa_index": 1, "question": "Which population and incident outcomes were analyzed?", "answer": "The analytic cohort comprised 205,504 participants and 18,542 incident CVD events during an article-reported 13-year follow-up period. The analytic sample is not the entire UK Biobank recruitment population. The reported 13-year period is not described here as a mean or median follow-up.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fcvm-2025-1724572.html#qa-1", "question_source": "data/deep_geo/doi-10-3389-fcvm-2025-1724572.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-3389-fcvm-2025-1724572.json#/qa/0/answer", "answer_sha256": "63c90591856e3acf0baf17db462a2c53f2bde3a50725a6c91a54ff4cfb0b2b4e", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fcvm-2025-1724572--qa-2", "work_id": "doi-10-3389-fcvm-2025-1724572", "qa_index": 2, "question": "What does the allostatic-load score represent?", "answer": "Allostatic load was operationalized using 12 baseline biomarkers with quartile-based risk scoring and a score range of 0–12. HDL and IGF-1 used the low-value risk direction. This biomarker score is not a direct measurement of psychological stress, a neuroendocrine response or an inflammatory intervention.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fcvm-2025-1724572.html#qa-2", "question_source": "data/deep_geo/doi-10-3389-fcvm-2025-1724572.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-3389-fcvm-2025-1724572.json#/qa/1/answer", "answer_sha256": "f9f2a23f43d9f42e7223780a49881b8d4151861033690fdec6f4a3343c7603b8", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fcvm-2025-1724572--qa-3", "work_id": "doi-10-3389-fcvm-2025-1724572", "qa_index": 3, "question": "What was the adjusted high-versus-zero AL association?", "answer": "In adjusted Model 3, AL ≥6 versus AL = 0 was associated with incident CVD at HR 2.15 (95% CI 1.99–2.33). AL = 0 is the reference group. This relative hazard association is not a 115% absolute-risk increase or a treatment effect.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fcvm-2025-1724572.html#qa-3", "question_source": "data/deep_geo/doi-10-3389-fcvm-2025-1724572.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-3389-fcvm-2025-1724572.json#/qa/2/answer", "answer_sha256": "2367cb615c4eb7e0e163dfc3b1b13e3b57a4a1410bb1e1c75d2fee587fc2c4ed", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fcvm-2025-1724572--qa-4", "work_id": "doi-10-3389-fcvm-2025-1724572", "qa_index": 4, "question": "What do the nonlinear and sensitivity analyses add?", "answer": "The AL–CVD association was nonlinear, and the main text reported directionally similar results after excluding events in the first three years after baseline. No additional precise hazard ratios from supplementary tables are supplied here, and this sensitivity analysis does not fully exclude reverse causation.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fcvm-2025-1724572.html#qa-4", "question_source": "data/deep_geo/doi-10-3389-fcvm-2025-1724572.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-3389-fcvm-2025-1724572.json#/qa/3/answer", "answer_sha256": "9dc93ed40699919cdec6699b376dce5a78aede5d232dcd63de11f02637b3d3e9", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fcvm-2025-1724572--qa-5", "work_id": "doi-10-3389-fcvm-2025-1724572", "qa_index": 5, "question": "Does the mediation estimate establish prevention by lowering neutrophils?", "answer": "Eight candidate mediators entered the correlation analysis; the neutrophil-count mediation estimate was 4.73%. This is model-based decomposition using baseline indicators, not a proven causal pathway or evidence that lowering neutrophils or an inflammatory marker prevents CVD.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fcvm-2025-1724572.html#qa-5", "question_source": "data/deep_geo/doi-10-3389-fcvm-2025-1724572.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-3389-fcvm-2025-1724572.json#/qa/4/answer", "answer_sha256": "0130f5e0fd45099377815703e100a659742dad0ed7a11d5a9cf91d8d49c49000", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1056-nejmc2518964--qa-1", "work_id": "doi-10-1056-nejmc2518964", "qa_index": 1, "question": "Which correspondence under this shared DOI is covered?", "answer": "Only the letter signed by Mengyao Li, Ge Zhang and Xiaozhu Liu, indexed as PMID 41780015, is covered. Other letters and the trialists' reply are excluded.", "answer_url": "https://drgezhang.com/papers/doi-10-1056-nejmc2518964.html#qa-1", "question_source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/qa/0/answer", "answer_sha256": "67e96950c70db0841648424aebfc2a2e5210e7dbbb70982bff287045c043ed27", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1056-nejmc2518964--qa-2", "work_id": "doi-10-1056-nejmc2518964", "qa_index": 2, "question": "What does the 83% figure mean?", "answer": "Among monotherapy patients who had stent thrombosis, the letter reports that 83% experienced it within 30 days. This is not the probability of thrombosis for every monotherapy patient.", "answer_url": "https://drgezhang.com/papers/doi-10-1056-nejmc2518964.html#qa-2", "question_source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/qa/1/answer", "answer_sha256": "ab275d6fd1375fb8805117a0474c1beca1d8f6ca3fa7e3f91d9c4743e34db9c1", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1056-nejmc2518964--qa-3", "work_id": "doi-10-1056-nejmc2518964", "qa_index": 3, "question": "What further investigation do the authors propose?", "answer": "They propose studying time-adaptive de-escalation, including platelet-function testing to inform transitions as ischemic and bleeding risks evolve.", "answer_url": "https://drgezhang.com/papers/doi-10-1056-nejmc2518964.html#qa-3", "question_source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/qa/2/answer", "answer_sha256": "e5b3caa2d54277b4b5b15422adbaa8cffa575634f4dc48f416f92b3cf420619c", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1056-nejmc2518964--qa-4", "work_id": "doi-10-1056-nejmc2518964", "qa_index": 4, "question": "Can this letter establish a safe aspirin-withdrawal schedule?", "answer": "No. It supplies interpretation and a research proposal, without a new randomized comparison or validated individualized stopping rule.", "answer_url": "https://drgezhang.com/papers/doi-10-1056-nejmc2518964.html#qa-4", "question_source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1056-nejmc2518964.json#/qa/3/answer", "answer_sha256": "dc09cb2793691abd6adc1d0d65f9f2267e6244a7fc9ec0e2f412db575c2b4344", "evidence_refs": [ "KF1", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-1", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 1, "question": "What type of article is this?", "answer": "It is a narrative Review Article synthesizing prior evidence. It reports no new experimental or clinical dataset, systematic study-selection workflow or pooled meta-analysis.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-1", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/0/answer", "answer_sha256": "452a1e89d5af7d487d8c2394fb240fdb5a7c96c6d63df28d298e3431fd598bc2", "evidence_refs": [ "KF1", "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-2", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 2, "question": "Which circadian clock components are central to cardiovascular immune regulation?", "answer": "The review centers on CLOCK-BMAL1, PER/CRY and REV-ERB/ROR feedback networks, including redox and epigenetic regulation; these are synthesized from prior work rather than tested as one new experiment.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-2", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/1/answer", "answer_sha256": "749d6203af26faba80e9bd9b94e4cc91e3b9279be2e19ba51bf6d5c704409805", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-3", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 3, "question": "How does circadian disruption interact with NF-kB and NLRP3?", "answer": "The review links clock and redox regulation with pattern-recognition receptor, NF-kB and NLRP3 inflammatory signaling, cytokines and chemokines. The underlying models are heterogeneous and do not establish one complete causal pathway in humans.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-3", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/2/answer", "answer_sha256": "1b3db77c4512719af4a479d7ebd78fd659f5e6001d4579a4d9d6d0dcd76bc764", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-4", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 4, "question": "Which immune cells show circadian trafficking or functional rhythms?", "answer": "Prior evidence discussed for neutrophils, monocytes/macrophages, lymphocytes and dendritic cells indicates rhythmic numbers, trafficking or function, with phase and mechanism varying across species and tissues.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-4", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/3/answer", "answer_sha256": "c111b654fb64e5026a5212cd858b0499140700b9c74f450efbbd5e737f40a626", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-5", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 5, "question": "Which cardiovascular diseases are discussed?", "answer": "The review discusses atherosclerosis, stroke, ischemic heart disease and myocardial infarction, and heart failure, with hypertension considered in blood-pressure chronotherapy. Evidence strength differs across disease contexts.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-5", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/4/answer", "answer_sha256": "2dda76c3f7f83c1caea44403230bb9bd5a34b23ba083156343386a9ac5e48546", "evidence_refs": [ "KF4", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-6", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 6, "question": "Does the review prove that REV-ERB agonists treat cardiovascular disease in humans?", "answer": "No. REV-ERB agonist chronotherapy is discussed as mechanistic and preclinical rationale, not demonstrated human cardiovascular treatment efficacy.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-6", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/5/answer", "answer_sha256": "507dc749bda415f26b2ce8ce5c435c7ae99868564e24cd497ce4cc2ef7fc615f", "evidence_refs": [ "KF5", "KF8" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-7", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 7, "question": "Should all antihypertensive medications be taken at bedtime?", "answer": "No. Clinical evidence conflicts: Hygia and related studies reported bedtime-dosing benefits, while BedMed did not reproduce a cardiovascular-event benefit. The review does not support a universal bedtime recommendation.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-7", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/6/answer", "answer_sha256": "febd84e8eab5d3fcf80cf365f7e09782869dd39b88eb1aba098e98d1a201d97d", "evidence_refs": [ "KF6", "KF8" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-8", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 8, "question": "Does bedtime aspirin have proven myocardial infarction or stroke outcome benefit?", "answer": "No large randomized trial cited by this review directly establishes reduced overall myocardial infarction or stroke incidence from bedtime aspirin dosing; physiological timing effects do not prove event reduction.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-8", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/7/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/7/answer", "answer_sha256": "419e2a161af6fe790d745c5ce0e92049b3d0a8d7e45e794b847ca2de05e4fbcd", "evidence_refs": [ "KF6", "KF8" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-9", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 9, "question": "Are SGLT2-inhibitor, colchicine, MRA or ARNI dosing times clinically established?", "answer": "No. The review discusses these drug classes, but does not establish clinically validated optimal timing or universal cardiovascular outcome benefits for them.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-9", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/8/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/8/answer", "answer_sha256": "b20b80ced34236e3d20a20d484eab1e98bd3bc23bb7b9d2063d729ce9554ffe6", "evidence_refs": [ "KF6", "KF8" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-10", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 10, "question": "Is this a systematic review or meta-analysis?", "answer": "No. The article reports no explicit systematic-search strategy, PRISMA study-selection workflow or quantitative meta-analysis; its 392 references are bibliography entries, not a systematic count of independent studies.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-10", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/9/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/9/answer", "answer_sha256": "578d3944e95942dc2c103bfdbcf91c48566369eefaa90bbc0f4f8d0059cf9ede", "evidence_refs": [ "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70052--qa-11", "work_id": "doi-10-1002-mdr2-70052", "qa_index": 11, "question": "What gaps remain before cardiovascular chronotherapy can become precision medicine?", "answer": "Constitutive-versus-inducible model differences, immune-subpopulation and spatiotemporal heterogeneity, individualized rhythm variation and high-quality circadian-aware clinical trials remain important gaps.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70052.html#qa-11", "question_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/10/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70052.json#/qa/10/answer", "answer_sha256": "68bb2fca283ede5f42fbc98f22bad4eb85ee95283fc5c68956965274aa4c1c56", "evidence_refs": [ "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-bioi-2026-0017--qa-1", "work_id": "doi-10-15212-bioi-2026-0017", "qa_index": 1, "question": "How many participants contributed to the analyses?", "answer": "The UK Biobank analytic cohort contained 261,865 participants. The external hospital cohort initially contained 1,798 participants, but the fully adjusted external analysis used 328 complete cases, including 88 MACE outcomes. These populations and subsets should not be added into a synthetic study total.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#qa-1", "question_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/0/answer", "answer_sha256": "cbc792015ac07c314b6aace1b450df3cc69326ccbd3972dce3157ab3600eb9b5", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-bioi-2026-0017--qa-2", "work_id": "doi-10-15212-bioi-2026-0017", "qa_index": 2, "question": "What does the TyG:eGFRcr-cys ratio combine?", "answer": "It divides the triglyceride–glucose index by estimated GFR derived using both creatinine and cystatin C. It is intended to summarize metabolic and renal risk-marker information, rather than directly measure a causal process.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#qa-2", "question_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/1/answer", "answer_sha256": "af3c43453755a50d6de6dc5ad73d807919b3c5f5487d70a8c599888c727e554c", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-bioi-2026-0017--qa-3", "work_id": "doi-10-15212-bioi-2026-0017", "qa_index": 3, "question": "What was the main prospective CVD association?", "answer": "In fully adjusted Model 3, the highest ratio quartile had a CVD HR of 1.24 compared with the lowest quartile, with a 95% CI of 1.18–1.30. This is an observational hazard ratio.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#qa-3", "question_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/2/answer", "answer_sha256": "b1671c6853f6f86093513687f1502ae9af05bebcfc42c2d13011d835f321a1ab", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-bioi-2026-0017--qa-4", "work_id": "doi-10-15212-bioi-2026-0017", "qa_index": 4, "question": "Were all cardiovascular outcomes significantly associated in the quartile comparison?", "answer": "No. The highest-versus-lowest-quartile CHD HR was 1.30, while the stroke HR was 1.05 with a 95% CI of 0.96–1.16 and P=0.29. Outcome and exposure-contrast details must be preserved.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#qa-4", "question_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/3/answer", "answer_sha256": "11e086179b75ad7c91de1997fa3b07a112360f828eb6a9b245521ada881aa119", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-bioi-2026-0017--qa-5", "work_id": "doi-10-15212-bioi-2026-0017", "qa_index": 5, "question": "What does external validation mean here?", "answer": "It means that the ratio–MACE association was examined in an independent hospital cohort. The fully adjusted complete-case analysis was small and the confidence interval was wide; this does not establish a calibrated prediction model or improved clinical decision-making.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#qa-5", "question_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/4/answer", "answer_sha256": "b01424b257c6b895473d6b023b7ab97d2da1ed3b265556a68fa29a5168884a3a", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-bioi-2026-0017--qa-6", "work_id": "doi-10-15212-bioi-2026-0017", "qa_index": 6, "question": "Does the network analysis establish a pre-disease transition?", "answer": "No. The analysis compared exposure-defined groups and was exploratory. It does not show that an individual crosses a validated early-warning threshold over time.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#qa-6", "question_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/5/answer", "answer_sha256": "0600950be884965e6cef7e6fabc556a2ff9248957e6f977dd472ac1de0eb1655", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-bioi-2026-0017--qa-7", "work_id": "doi-10-15212-bioi-2026-0017", "qa_index": 7, "question": "Can the ratio replace established cardiovascular risk scores?", "answer": "The article states that incremental discrimination and reclassification beyond established risk factors or scores were not evaluated. The ratio remains a candidate complementary marker requiring additional evaluation.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-bioi-2026-0017.html#qa-7", "question_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-15212-bioi-2026-0017.json#/qa/6/answer", "answer_sha256": "7f1d963cf24f776577c558b0258c3d38621b23fca3118cec209afb37b0f47875", "evidence_refs": [ "KF2", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ggn2-202500053--qa-1", "work_id": "doi-10-1002-ggn2-202500053", "qa_index": 1, "question": "What design rationale supports combining complementary learners in a clinical AI ensemble?", "answer": "Choose complementary learners in relation to the clinical context rather than pursuing a single algorithm as universally optimal. The authors frame learner combination as a methodological design choice for clinical AI.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ggn2-202500053.html#qa-1", "question_source": "data/deep_geo/doi-10-1002-ggn2-202500053.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1002-ggn2-202500053.json#/qa/0/answer", "answer_sha256": "1c7719f5287c7314f3af7cb7a3002c97a0398b189f9359806163f5cf355a0b73", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ggn2-202500053--qa-2", "work_id": "doi-10-1002-ggn2-202500053", "qa_index": 2, "question": "How does the AI ensemble Perspective propose evaluating and selecting models across independent cohorts?", "answer": "Evaluate and select models using aggregate evidence across independent cohorts. The Perspective recommends an evaluation strategy; it does not report executing these independent-cohort validations.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ggn2-202500053.html#qa-2", "question_source": "data/deep_geo/doi-10-1002-ggn2-202500053.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1002-ggn2-202500053.json#/qa/1/answer", "answer_sha256": "f4ce136e6e3a65361fd9714bb02410acf0380dbb6dd350f4f8bac1b666139077", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ggn2-202500053--qa-3", "work_id": "doi-10-1002-ggn2-202500053", "qa_index": 3, "question": "Why should clinical AI feature attribution be considered alongside sensitivity analysis and calibration?", "answer": "Interpret SHAP attributions as distribution-dependent and examine them alongside sensitivity analysis and calibration. The authors discuss robustness and interpretation constraints of feature attribution rather than identifying stable causal properties.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ggn2-202500053.html#qa-3", "question_source": "data/deep_geo/doi-10-1002-ggn2-202500053.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1002-ggn2-202500053.json#/qa/2/answer", "answer_sha256": "25c0cd636a1ec5e7e66898655db1716df3f1cf69798549d2e2e0c6116ecc2939", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ggn2-202500053--qa-4", "work_id": "doi-10-1002-ggn2-202500053", "qa_index": 4, "question": "Which deployment constraints does the AI ensemble Perspective identify for clinical translation?", "answer": "Account for distribution shift, computational resources, standardization and clinical workflows when planning translation. These constraints define a future translation agenda rather than demonstrated clinical benefits.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ggn2-202500053.html#qa-4", "question_source": "data/deep_geo/doi-10-1002-ggn2-202500053.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1002-ggn2-202500053.json#/qa/3/answer", "answer_sha256": "91df303e3b8d8916f4bcc4aa66ab0048c6c08d45c8e983a0bc9f16398d98839b", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-medd-2026-100004--qa-1", "work_id": "doi-10-1016-j-medd-2026-100004", "qa_index": 1, "question": "What problem does this correspondence address?", "answer": "It addresses when multimodal cardiovascular AI has enough current and clinically relevant evidence to predict, and when it should defer.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-medd-2026-100004.html#qa-1", "question_source": "data/deep_geo/doi-10-1016-j-medd-2026-100004.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1016-j-medd-2026-100004.json#/qa/0/answer", "answer_sha256": "8b6fafc98a9e5c6e35bce0b7d08b2d88e854d0469e95b8ba9e228e6ac248744e", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-medd-2026-100004--qa-2", "work_id": "doi-10-1016-j-medd-2026-100004", "qa_index": 2, "question": "How does it define the role of deferral?", "answer": "Deferral follows prespecified evidence-adequacy criteria and should trigger an alternative care pathway; it is not synonymous with calibration or high model confidence.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-medd-2026-100004.html#qa-2", "question_source": "data/deep_geo/doi-10-1016-j-medd-2026-100004.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1016-j-medd-2026-100004.json#/qa/1/answer", "answer_sha256": "69064b87cebe3e08b44ab99605001b8bb26a473c8baac41fe77666006de1b081", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-medd-2026-100004--qa-3", "work_id": "doi-10-1016-j-medd-2026-100004", "qa_index": 3, "question": "Which evaluation conditions does it propose?", "answer": "Five candidate conditions are complete inputs, a critical modality missing, natural co-missingness, temporal staleness and geographically or temporally external data.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-medd-2026-100004.html#qa-3", "question_source": "data/deep_geo/doi-10-1016-j-medd-2026-100004.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1016-j-medd-2026-100004.json#/qa/2/answer", "answer_sha256": "e16bbfb78b0463fda4b72064b152c70dfb1598a6062ef4f7c626d1e02149b2c9", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-medd-2026-100004--qa-4", "work_id": "doi-10-1016-j-medd-2026-100004", "qa_index": 4, "question": "Does it report new model accuracy or a clinical trial?", "answer": "No. It is a correspondence presenting conceptual proposals, with no new dataset or validated performance result.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-medd-2026-100004.html#qa-4", "question_source": "data/deep_geo/doi-10-1016-j-medd-2026-100004.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1016-j-medd-2026-100004.json#/qa/3/answer", "answer_sha256": "7eeccf4fe03cdba66e4acfe84db525df6210159f2b063e16d95ef675cbebfbcf", "evidence_refs": [ "KF1", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1155-humu-5591097--qa-1", "work_id": "doi-10-1155-humu-5591097", "qa_index": 1, "question": "What happened to mutant PAPPA2 in the expression experiment?", "answer": "At 48 hours after plasmid transfection, the three independent experiments showed lower mutant PAPPA2 protein in 293T cell lysates and culture supernatant, while the mRNA comparison was not statistically significant. This is an abundance result, not a direct protein half-life measurement.", "answer_url": "https://drgezhang.com/papers/doi-10-1155-humu-5591097.html#qa-1", "question_source": "data/deep_geo/doi-10-1155-humu-5591097.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1155-humu-5591097.json#/qa/0/answer", "answer_sha256": "38f45ef6c2923d5791d4d78bd0bb974c1ebca1741aaade99933c2856b2506199", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1155-humu-5591097--qa-2", "work_id": "doi-10-1155-humu-5591097", "qa_index": 2, "question": "Which primary-cell treatment conditions support the fibrosis-associated finding?", "answer": "Two donor-derived primary trabecular-meshwork lines were exposed for 48 hours to IGFBP5 at 100 ng/mL, PAPPA2 at 10 ng/mL, or their combination. PAPPA2 cotreatment attenuated the IGFBP5-associated protein and fluorescence responses. The reported 20 imaged cells per group per experiment are subsamples, not independent human donors.", "answer_url": "https://drgezhang.com/papers/doi-10-1155-humu-5591097.html#qa-2", "question_source": "data/deep_geo/doi-10-1155-humu-5591097.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1155-humu-5591097.json#/qa/1/answer", "answer_sha256": "e42780650ded33182e3eebdcb78a0df20e00af814fef7c6ab3a2713adff5f334", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1155-humu-5591097--qa-3", "work_id": "doi-10-1155-humu-5591097", "qa_index": 3, "question": "What did the mouse experiment measure, and did it reproduce the human variant?", "answer": "At eight weeks, five mice per genotype were assessed. Pappa2 heterozygous and knockout mice had higher intraocular pressure and more trabecular Masson-positive staining than wild type. These are deficiency models, not mice carrying an engineered human p.Gly131Ala allele.", "answer_url": "https://drgezhang.com/papers/doi-10-1155-humu-5591097.html#qa-3", "question_source": "data/deep_geo/doi-10-1155-humu-5591097.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1155-humu-5591097.json#/qa/2/answer", "answer_sha256": "e075124e9b04bc08bbbae7089c2e5affd0ea6da390266a4cd2b89f30e4d53fb9", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1155-humu-5591097--qa-4", "work_id": "doi-10-1155-humu-5591097", "qa_index": 4, "question": "Do these experiments validate a human glaucoma mutation or establish a treatment?", "answer": "No. The cell and mouse findings provide experimental support for PAPPA2-IGFBP5 biology but do not establish population pathogenicity or human therapeutic benefit. Family-wide segregation and the reported pedigree denominator are not independently reconciled here, and no human therapeutic intervention was tested.", "answer_url": "https://drgezhang.com/papers/doi-10-1155-humu-5591097.html#qa-4", "question_source": "data/deep_geo/doi-10-1155-humu-5591097.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1155-humu-5591097.json#/qa/3/answer", "answer_sha256": "0c6f11e625ba35d1708535fb70c9b047889c5f6486e7cfea62ebc168ff395ddb", "evidence_refs": [ "KF1", "KF2", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1126-science-aek9583--qa-1", "work_id": "doi-10-1126-science-aek9583", "qa_index": 1, "question": "What public-record problem does this Science Letter address?", "answer": "The authors describe a gap between a previously reported human outcome and the registry or preclinical publication, and argue that directly related human protocols and major outcomes should remain visible in current public records. The case is contextual evidence from other sources, not a new study in this Letter.", "answer_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#qa-1", "question_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/0/answer", "answer_sha256": "0f30a5add0e3542d95a150ff113e7b62af7466d8ae536647684ddb65cf6f40bf", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1126-science-aek9583--qa-2", "work_id": "doi-10-1126-science-aek9583", "qa_index": 2, "question": "Why can an outdated registry matter in single-patient research?", "answer": "An individual outcome may be the available human evidence. The Letter argues that families, clinicians, ethics committees and other researchers can rely on the public entry when judging continued testing and emerging risks.", "answer_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#qa-2", "question_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/1/answer", "answer_sha256": "747ca04dfb8e2601c476fb140c53aa1d97ac9a0e452c6009eef9d9f6f8df139d", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1126-science-aek9583--qa-3", "work_id": "doi-10-1126-science-aek9583", "qa_index": 3, "question": "Does reporting to regulators ensure that the public record is updated?", "answer": "The Letter distinguishes safety reports, trial registries and journal articles because their purposes and update schedules differ. Clinical information reaching an oversight body can still be absent from the public account of translation.", "answer_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#qa-3", "question_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/2/answer", "answer_sha256": "9ed39786c4b7c026b6637370efc9dc71a0910d26165d33bb942c55841117322b", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1126-science-aek9583--qa-4", "work_id": "doi-10-1126-science-aek9583", "qa_index": 4, "question": "Which changes do the authors propose for registries and preclinical papers?", "answer": "They propose disclosure and updating of directly related human protocols before preclinical manuscript acceptance, reporting of treatment-emergent deaths and life-threatening events separately from causal assessment, links between preclinical papers and trial records, and dated notices for major later human outcomes.", "answer_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#qa-4", "question_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/3/answer", "answer_sha256": "98806629c78b9eaa4954afb7a70ef3d98f78d8447c33b0d1cb5395de1d43edfc", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1126-science-aek9583--qa-5", "work_id": "doi-10-1126-science-aek9583", "qa_index": 5, "question": "Does this Letter establish treatment causality or assign responsibility?", "answer": "No. Its conclusion explicitly separates documenting subsequent human experience from assigning blame or settling causality. Its proposals concern reporting and governance, with no new clinical experiment or quantified treatment effect.", "answer_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#qa-5", "question_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/4/answer", "answer_sha256": "55cdea4045ae26a3f582d2e9a926114646ac0365b467d89422a6b39d8f49424b", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1038-s41698-026-01699-1--qa-1", "work_id": "doi-10-1038-s41698-026-01699-1", "qa_index": 1, "question": "What is ClockProCRC and how was it constructed?", "answer": "ClockProCRC is a transcriptomic circadian-misalignment scoring framework. The study began with a 906-gene colon circadian reference and separately used CRC single-cell co-expression analysis to derive nine modules and a 559-gene four-module CTD signature. The ClockProCRC scoring Methods then applied expression-matched random-background correction to circadian rhythm disorder genes using 100 expression bins and 1,000 random samplings. The reviewed manuscript text does not establish that the 559 CTD genes are identical to the final scoring gene set.", "answer_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#qa-1", "question_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/0/answer", "answer_sha256": "b4f33f8cb93114c573fe3ec31e4c6bb94227c50c838c752d92704c137c7c09b0", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1038-s41698-026-01699-1--qa-2", "work_id": "doi-10-1038-s41698-026-01699-1", "qa_index": 2, "question": "How large was the ClockProCRC study?", "answer": "The Methods reports 3,758 samples across 35 public GEO datasets. The primary GSE166555 single-cell cohort comprised 25 tissue samples (13 CRC and 12 normal mucosa) and retained 94,683 cells after quality control. These are heterogeneous sample, tissue and cell counts and should not be interpreted as 3,758 unique human participants.", "answer_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#qa-2", "question_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/1/answer", "answer_sha256": "25bf40efc1dee7e5f43e4c27d09c87bdb43830a66082a1fe3917c5581b4c58cf", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1038-s41698-026-01699-1--qa-3", "work_id": "doi-10-1038-s41698-026-01699-1", "qa_index": 3, "question": "Was ClockProCRC associated with colorectal-cancer progression and survival?", "answer": "Yes, within the analyzed retrospective/public datasets. ClockProCRC increased across progression-related states from normal mucosa through adenoma/dysplasia and CRC to colorectal liver metastasis, and higher scores were associated with worse overall survival in GSE17537 (n=55; log-rank P<0.01). This is association evidence rather than prospective clinical validation.", "answer_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#qa-3", "question_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/2/answer", "answer_sha256": "8e94e0c6667bc7ec64c7ff82b3c5d3c328a71f6f232a2c46e8ea5eda8cabd9e5", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1038-s41698-026-01699-1--qa-4", "work_id": "doi-10-1038-s41698-026-01699-1", "qa_index": 4, "question": "What did the single-cell analysis show about circadian misalignment and the CRC tumor microenvironment?", "answer": "In GSE200997 and GSE196964, ClockProCRC-defined higher-disruption states were associated with enrichment of epithelial and plasma-cell populations, relative depletion of fibroblast/endothelial populations, and altered intercellular communication including stronger pro-inflammatory signaling patterns. These analyses identify state associations and do not by themselves prove causality.", "answer_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#qa-4", "question_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/3/answer", "answer_sha256": "6c96ce690c35002cd86b16bed69e6420879dd57e8d7b816a657615c18488b3de", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1038-s41698-026-01699-1--qa-5", "work_id": "doi-10-1038-s41698-026-01699-1", "qa_index": 5, "question": "Why was SYNE1 prioritized in this study?", "answer": "SYNE1 emerged from the CTD gene-regulatory-network analysis. Across 100 genetic-algorithm iterations, 61 recurrent regulatory axes were identified, and the NFATC2→SYNE1 relationship showed higher modeled regulatory strength in CRC (0.607; 95% CI 0.412-0.802) than in normal mucosa (-0.102; 95% CI -0.058-0.262). SYNE1 also showed circadian perturbation-associated expression/rhythmicity changes in independent datasets.", "answer_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#qa-5", "question_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/4/answer", "answer_sha256": "7a89e54e0d1cf4008002e602e02685285f772490d92ea20c94d8d7e42e08a03c", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1038-s41698-026-01699-1--qa-6", "work_id": "doi-10-1038-s41698-026-01699-1", "qa_index": 6, "question": "What happened when SYNE1 was knocked down in colorectal-cancer cells?", "answer": "In HCT116 and SW480 cells, siRNA-mediated SYNE1 knockdown reduced Transwell migration/invasion, reduced wound-healing migration and colony formation, increased E-cadherin and ZO-1, and decreased N-cadherin. These findings support an in-vitro functional role but do not establish in-vivo therapeutic efficacy.", "answer_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#qa-6", "question_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/5/answer", "answer_sha256": "a2f9870d17f85f1fd343b148e6c85f2cc079996593bf4594de99968674b011c0", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1038-s41698-026-01699-1--qa-7", "work_id": "doi-10-1038-s41698-026-01699-1", "qa_index": 7, "question": "How did CLOCK knockdown, melatonin and the reported SYNE1 AUC relate to the circadian perturbation experiment?", "answer": "CLOCK knockdown increased ClockProCRC and disrupted SYNE1 rhythmicity; melatonin partially restored the ClockProCRC-defined state and SYNE1 rhythmicity in CRC-cell experiments. The reported SYNE1 AUC of 0.915 refers specifically to discrimination of CLOCK-knockdown experimental conditions, not to CRC diagnosis or patient-level prediction.", "answer_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#qa-7", "question_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/6/answer", "answer_sha256": "f0d2eb51eb087afd1a8ca23dc47387d1ac905babf469588f8bb6bf642722316c", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1038-s41698-026-01699-1--qa-8", "work_id": "doi-10-1038-s41698-026-01699-1", "qa_index": 8, "question": "Are ClockProCRC or SYNE1 clinically validated for diagnosis, prognosis or treatment selection?", "answer": "No. ClockProCRC has multicohort analytical and retrospective association evidence but lacks large prospective multicenter clinical validation and a universal clinical cutoff. SYNE1 has computational and in-vitro functional evidence but no SYNE1-directed animal efficacy or patient-treatment validation.", "answer_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#qa-8", "question_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/7/question", "answer_source": "data/deep_geo/doi-10-1038-s41698-026-01699-1.json#/qa/7/answer", "answer_sha256": "1d6e30123061a95721319d47064c40c488b96bd0de95c5bcf7d8bf26fb9c5a98", "evidence_refs": [ "KF2", "KF3", "KF5", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jdi-70462--qa-1", "work_id": "doi-10-1111-jdi-70462", "qa_index": 1, "question": "Who was included in the analysis?", "answer": "The final analytic cohort comprised 6,534 CHARLS participants aged at least 45 years without baseline CLMM. Baseline measurements were from 2011 and outcome ascertainment from 2015.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#qa-1", "question_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/0/answer", "answer_sha256": "07374c722a04b22ceaecb6c84f496cf441d17883481770b9aedfa321d761da2d", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jdi-70462--qa-2", "work_id": "doi-10-1111-jdi-70462", "qa_index": 2, "question": "What counted as cardiovascular–liver–metabolic multimorbidity?", "answer": "Participants had to meet at least two criteria for CVD, type 2 diabetes, and LAP-based suspected MASLD at follow-up. The liver component was a surrogate phenotype, not universal imaging or histological confirmation.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#qa-2", "question_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/1/answer", "answer_sha256": "1305ab95c892b1f110e4e0209bd2a46dab851166fe29e5e73cdeed295036908d", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jdi-70462--qa-3", "work_id": "doi-10-1111-jdi-70462", "qa_index": 3, "question": "How strong was the association with CHG?", "answer": "In the fully adjusted logistic model, the highest versus lowest CHG quartile had an OR of 1.64 with a 95% CI of 1.22–2.22. This is an observational odds ratio for the follow-up outcome.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#qa-3", "question_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/2/answer", "answer_sha256": "4f7f8b1193e9362eb3108bc5e2f8196362d3b9a1ad8237938316ed76ca054163", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jdi-70462--qa-4", "work_id": "doi-10-1111-jdi-70462", "qa_index": 4, "question": "Did CHG-BMI perform better than CHG alone?", "answer": "CHG-BMI had a stronger highest-versus-lowest-quartile association and the largest observed AUC among the compared indices. Its AUC of 0.643 was still modest and was evaluated in the analysis sample.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#qa-4", "question_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/3/answer", "answer_sha256": "d373a783b6431b95675be83f1e86ab3bcf9db5b0ffff5a3eb25a2f22796e3ee8", "evidence_refs": [ "KF3", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jdi-70462--qa-5", "work_id": "doi-10-1111-jdi-70462", "qa_index": 5, "question": "Was this an externally validated clinical prediction model?", "answer": "No. The article explicitly describes apparent, in-sample ROC evaluation without internal or external validation. Independent population validation and assessment beyond BMI and conventional risk factors are still needed.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#qa-5", "question_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/4/answer", "answer_sha256": "1ececb7a6a0c51abbad23497c62100b9cc783e7d567215e1f9f12ba3808feef9", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jdi-70462--qa-6", "work_id": "doi-10-1111-jdi-70462", "qa_index": 6, "question": "Did high CHG and high BMI interact statistically?", "answer": "The jointly high group had greater follow-up CLMM odds than the low–low group, but the multiplicative interaction was not statistically significant. Joint association therefore does not establish synergy.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#qa-6", "question_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/5/answer", "answer_sha256": "b226df8c27d023b7a48b59caa36fbc1a738309764badeeb02a1ee0478c57c0e8", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jdi-70462--qa-7", "work_id": "doi-10-1111-jdi-70462", "qa_index": 7, "question": "Can these findings guide a treatment intended to prevent CLMM?", "answer": "The study did not test an intervention. Observational associations and apparent discrimination do not establish that changing an index prevents disease or improves clinical decisions.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#qa-7", "question_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/6/answer", "answer_sha256": "cd7077f8cd628e3fef3ada378c5951e2036f2d5ccf9ab9498592170770daace2", "evidence_refs": [ "KF2", "KF3", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1172-jci194175--qa-1", "work_id": "doi-10-1172-jci194175", "qa_index": 1, "question": "What is the human evidence linking KIF13B to atherosclerotic plaque severity?", "answer": "Paired carotid endarterectomy tissue and independent human transcriptomic and proteomic datasets showed lower KIF13B in more advanced or unstable plaque states, with prominent VSMC differences and lower collagen in advanced local plaque regions. These are associative human observations and do not establish that manipulating KIF13B changes plaque outcomes in patients.", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-1", "question_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/0/answer", "answer_sha256": "709b9e752c975391248d06140556aca5376d9c76392d9174aa6cf4597e58c415", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1172-jci194175--qa-2", "work_id": "doi-10-1172-jci194175", "qa_index": 2, "question": "Did VSMC-specific Kif13b deletion cause worse atherosclerosis in mice?", "answer": "In the tested male AAV8-PCSK9 model, VSMC-specific Kif13b deletion increased lesion burden, necrotic core, macrophage accumulation and apoptotic-cell signal and reduced collagen/plaque-stability features. No genotype difference in measured plasma total cholesterol or triglycerides was detected in the primary comparison.", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-2", "question_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/1/answer", "answer_sha256": "c8b8ae3b4a48bc8fd8f8cfd19696ea7557b14448cfc02822ab592b3203271e59", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1172-jci194175--qa-3", "work_id": "doi-10-1172-jci194175", "qa_index": 3, "question": "What did the single-cell experiment show, and were there five independent replicates per genotype?", "answer": "The pooled aortic single-cell comparison associated KIF13B loss with reduced matrix/collagen programs and increased inflammatory VSMC-derived programs. Five mice were pooled into one single-cell library per genotype, so the design does not provide five independent scRNA-seq libraries per group.", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-3", "question_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/2/answer", "answer_sha256": "651e50e2c8caee5441906168a59817b0784100e3ef239f4f7849bfb1487f4557", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1172-jci194175--qa-4", "work_id": "doi-10-1172-jci194175", "qa_index": 4, "question": "Why does this page not assign one definitive diet duration to all single-cell analyses?", "answer": "The Results and Figure 5 describe the generated aortic single-cell experiment after 20 weeks of Western diet, whereas Figure 6 SCENIC and Figure 7 integrative captions reference 12 weeks. The evidence page preserves this source discrepancy instead of silently harmonizing it.", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-4", "question_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/3/answer", "answer_sha256": "f3775ec04a62d0bba0029d2701b072fcf3c3980a6e1c7fa42ce4017f9bca4047", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1172-jci194175--qa-5", "work_id": "doi-10-1172-jci194175", "qa_index": 5, "question": "How does KIF13B affect primary human vascular smooth muscle cells?", "answer": "Under oxLDL, KIF13B knockdown reduced contractile/matrix features, collagen secretion and collagen-gel contraction and increased inflammatory features, while KIF13B overexpression produced reciprocal effects. These are in vitro primary-HASMC perturbation data, not human treatment outcomes.", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-5", "question_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/4/answer", "answer_sha256": "69f761c11594d04780ff6c243126c1f1ce61de1f1c7f88d62bc7503149e28a33", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1172-jci194175--qa-6", "work_id": "doi-10-1172-jci194175", "qa_index": 6, "question": "Is KLF4 functionally downstream of KIF13B?", "answer": "In primary HASMC experiments, KIF13B loss increased KLF4, and concomitant KLF4 knockdown rescued the collagen-suppressive and inflammatory phenotype caused by KIF13B knockdown. This supports a downstream functional relationship in the tested cell system.", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-6", "question_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/5/answer", "answer_sha256": "530682dc4377aa3a9cc5e1d0313a0402d5ac68553ca8b7a4209d075d2c9714cc", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1172-jci194175--qa-7", "work_id": "doi-10-1172-jci194175", "qa_index": 7, "question": "What evidence supports the KIF13B-KCTD10-KLF4 mechanism?", "answer": "KIF13B knockdown stabilized KLF4 in CHX/proteasome experiments and reduced KLF4 ubiquitination. Integrated analyses nominated KCTD10, co-IP supported KCTD10-KLF4 association, KCTD10 increased KLF4 ubiquitination, and KCTD10 overexpression rescued KIF13B-loss phenotypes. The study does not resolve how KIF13B itself controls KCTD10 abundance.", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-7", "question_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/6/answer", "answer_sha256": "04edc91ebcaa223a67790da7e328b9382d7c9cd8c3a73437007c56ce84e53c74", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1172-jci194175--qa-8", "work_id": "doi-10-1172-jci194175", "qa_index": 8, "question": "Does Kenpaullone prove that KLF4 is a clinically validated treatment target for atherosclerosis?", "answer": "No. Kenpaullone reduced KLF4 promoter activity/expression and rescued cellular and mouse phenotypes in this study, but the experiments were preclinical. Kenpaullone is also a pharmacologically nonselective kinase inhibitor rather than an established KLF4-selective clinical drug, and no human atherosclerosis treatment efficacy or safety was tested.", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-8", "question_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/7/question", "answer_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/7/answer", "answer_sha256": "08dd62dedd039c567aac63e8445f0b0d2fc0d554f4b450550d8156ec839771ec", "evidence_refs": [ "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1172-jci194175--qa-9", "work_id": "doi-10-1172-jci194175", "qa_index": 9, "question": "How does this JCI study differ from the European Heart Journal KIF13B study?", "answer": "The JCI study focuses on vascular smooth muscle cells and a KIF13B-KCTD10-KLF4 mechanism controlling matrix/inflammatory VSMC states. The European Heart Journal study focuses on macrophage KIF13B, MERTK-dependent efferocytosis and an ITCH/CBL regulatory network. Together they describe distinct cell-type-specific KIF13B mechanisms in experimental atherosclerosis.", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-9", "question_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/8/question", "answer_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/8/answer", "answer_sha256": "eb873a708b926229460ad84db98de7c5e1a5cb5147fe866859d4e9b8a7dd0b1b", "evidence_refs": [ "KF1", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1172-jci194175--qa-10", "work_id": "doi-10-1172-jci194175", "qa_index": 10, "question": "Which public datasets and repositories support this evidence page?", "answer": "Key resources include study-generated mouse single-cell data GSE314838, human stable/unstable carotid plaque RNA-seq GSE120521, human plaque proteomics PXD062283, public spatial-transcriptomic evidence associated with GSE274572, the article's public methylation datasets, the JCI Supplemental Data, and the Supporting Data Values file.", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-10", "question_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/9/question", "answer_source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/9/answer", "answer_sha256": "965610682486066c22420078392f800272805e1d092cc17addd5c1f7ae95daf1", "evidence_refs": [ "KF1", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-curpro-2025-100054--qa-1", "work_id": "doi-10-1016-j-curpro-2025-100054", "qa_index": 1, "question": "Which research directions does the cardiovascular AI Correspondence propose for multimodal models?", "answer": "Develop multimodal AI along two directions: mechanism-oriented research and individualized digital twins. The authors propose complementary research directions rather than introduce a clinically validated digital twin product.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html#qa-1", "question_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/qa/0/answer", "answer_sha256": "1a4a1ff9637fcd9a2a1ae9829b1ea88a59b99b99b3aeea7c5bbc2580b42f69e1", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-curpro-2025-100054--qa-2", "work_id": "doi-10-1016-j-curpro-2025-100054", "qa_index": 2, "question": "How can imaging and molecular information support cardiovascular network and disease-subtyping hypotheses?", "answer": "Integrate imaging and molecular information to formulate network and disease-subtyping hypotheses. Data integration and cited empirical examples are discussed as a basis for interpretation, not as new causal experiments in this Correspondence.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html#qa-2", "question_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/qa/1/answer", "answer_sha256": "ab4aca82ee7961a04f36f6ab78e51ce98d54394704b62202812a79300159579e", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-curpro-2025-100054--qa-3", "work_id": "doi-10-1016-j-curpro-2025-100054", "qa_index": 3, "question": "What modeling approaches does the cardiovascular AI Correspondence discuss for patient-specific simulation?", "answer": "Explore updateable physiological models, image-to-mesh workflows and treatment-scenario simulation. The simulation discussion concerns model design and possible scenarios, not observed human treatment effects.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html#qa-3", "question_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/qa/2/answer", "answer_sha256": "4633aa4a22402e437e0ecd48221c19cd4ba63632a5ab38a724da2134ca086ba4", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-curpro-2025-100054--qa-4", "work_id": "doi-10-1016-j-curpro-2025-100054", "qa_index": 4, "question": "What requirements does the cardiovascular AI Correspondence identify for translating patient-specific models?", "answer": "Address longitudinal data, computational resources, prospective evaluation, privacy and governance before clinical translation. These are stated development and evaluation requirements, not completed prospective clinical validation.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html#qa-4", "question_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1016-j-curpro-2025-100054.json#/qa/3/answer", "answer_sha256": "63ae4ddd4077fbbe9e77fa12fae68a97aee8c59353db5aed897cd5558bbbc9a1", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-isci-2025-114320--qa-1", "work_id": "doi-10-1016-j-isci-2025-114320", "qa_index": 1, "question": "How did the nine-gene ALS model perform externally?", "answer": "The random forest signature reported AUC 1.00 in training, 0.91 internally, and 0.75 in independent GSE112680, reflecting lower transport performance; no prospective clinical impact test was performed.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#qa-1", "question_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/0/answer", "answer_sha256": "8109d4b9001ec546a1f86aa0c088f6c84e3c65d091b6970ccb9947c48cbf98b0", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-isci-2025-114320--qa-2", "work_id": "doi-10-1016-j-isci-2025-114320", "qa_index": 2, "question": "Does MR prove ABCA1 upregulation treats ALS?", "answer": "No. IVW MR estimated an inverse association with ALS susceptibility (OR 0.93; 95% CI 0.87–0.99) under genetic instrument assumptions; that is not a drug intervention or demonstrated treatment benefit.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#qa-2", "question_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/1/answer", "answer_sha256": "a5de31836c80b48d7da8ee31a8d6c1b81d7b67cb25f2af694180fb4cc24f3729", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-isci-2025-114320--qa-3", "work_id": "doi-10-1016-j-isci-2025-114320", "qa_index": 3, "question": "How many people were in the serum cohort?", "answer": "Fifteen ALS cases and fifteen controls (30 participants). The reported group comparison had P=0.006 but is too small to establish clinical diagnostic validity.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#qa-3", "question_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/2/answer", "answer_sha256": "ce656c587651f03bcdd8c901054a9b736619922afa1773cc3bc89a6a60fb45be", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-isci-2025-114320--qa-4", "work_id": "doi-10-1016-j-isci-2025-114320", "qa_index": 4, "question": "Was serum ABCA1 associated with functional disability?", "answer": "The reported ALSFRS-R total correlation r=-0.190, P=0.497 was not statistically significant; the evidence summary does not claim functional prediction.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#qa-4", "question_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/3/answer", "answer_sha256": "225558ab0374bd0d47af76136e106f3ddf43afbc11408d5bf2319e3553b0eb08", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-isci-2025-114320--qa-5", "work_id": "doi-10-1016-j-isci-2025-114320", "qa_index": 5, "question": "Is ABCA1 significantly upregulated in mouse spinal cord from day 70?", "answer": "No. The supplied original Supplementary Table 14 reports mouse day-70 P=0.414 (adjusted P approximately 1). Stronger reported evidence appears on days 100 and 120; the published day-70 significant-onward phrase is inconsistent with its numbers.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#qa-5", "question_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/4/answer", "answer_sha256": "424866f9073a4afa6b780d7ca64dd816e3e0f4dcb883e31a062938d17be6cf90", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-isci-2025-114320--qa-6", "work_id": "doi-10-1016-j-isci-2025-114320", "qa_index": 6, "question": "Are neutrophil and NK findings direct cell counts?", "answer": "No. The reported associations come from ssGSEA immune-cell transcriptomic signatures and should not be interpreted as flow-cytometric cell-number measurements.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-isci-2025-114320.html#qa-6", "question_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1016-j-isci-2025-114320.json#/qa/5/answer", "answer_sha256": "c962ecd0d249c76733a98f95efbd797433e2cef07ed67c6be1d9fb6b33e364fc", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fnut-2025-1658286--qa-1", "work_id": "doi-10-3389-fnut-2025-1658286", "qa_index": 1, "question": "How many participants and which outcomes were analyzed?", "answer": "One analytic sample of 29,340 adults was used for both outcomes; Tables 2 and 3 list 5,433 hyperuricemia and 1,346 self-reported gout cases. These case counts must not be substituted for survey-weighted prevalence.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fnut-2025-1658286.html#qa-1", "question_source": "data/deep_geo/doi-10-3389-fnut-2025-1658286.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-3389-fnut-2025-1658286.json#/qa/0/answer", "answer_sha256": "fe68cb7c891d7dbb822371faaeb14be08d551a8c27b459044bcad5d2914edbff", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fnut-2025-1658286--qa-2", "work_id": "doi-10-3389-fnut-2025-1658286", "qa_index": 2, "question": "Was every higher eGDR category significantly associated with less gout?", "answer": "No. Table 3 Model 3 gives OR 0.81, 95% CI 0.63–1.04 and P=0.093 for 4–6 versus <4 mg/kg/min. Results §3.3 states this loss of significance. The abstract's broader all-category statement is not adopted.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fnut-2025-1658286.html#qa-2", "question_source": "data/deep_geo/doi-10-3389-fnut-2025-1658286.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-3389-fnut-2025-1658286.json#/qa/1/answer", "answer_sha256": "061d74b801078a2fc2e68f2770de06d66a65010fdab91e3e307493664b189c9a", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fnut-2025-1658286--qa-3", "work_id": "doi-10-3389-fnut-2025-1658286", "qa_index": 3, "question": "What did the continuous adjusted analyses report?", "answer": "Per 1 mg/kg/min higher eGDR, Model 3 reports OR 0.83 (95% CI 0.81–0.85) for hyperuricemia and OR 0.83 (0.79–0.87) for gout. These are prevalence-odds associations.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fnut-2025-1658286.html#qa-3", "question_source": "data/deep_geo/doi-10-3389-fnut-2025-1658286.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-3389-fnut-2025-1658286.json#/qa/2/answer", "answer_sha256": "fc07796a86140986949668a197cee7b6cc5c393a84820922516b05d424887822", "evidence_refs": [ "KF2", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fnut-2025-1658286--qa-4", "work_id": "doi-10-3389-fnut-2025-1658286", "qa_index": 4, "question": "Does this demonstrate that raising eGDR will prevent disease?", "answer": "No. The cross-sectional design cannot establish temporal order or a preventive intervention effect. Gout is self-reported and eGDR is a calculated proxy.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fnut-2025-1658286.html#qa-4", "question_source": "data/deep_geo/doi-10-3389-fnut-2025-1658286.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-3389-fnut-2025-1658286.json#/qa/3/answer", "answer_sha256": "576c697aa6cf1fcdf2fc1916e9540023cf868a24b6fdede1fdc819cfd27c0a0d", "evidence_refs": [ "KF1", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fpubh-2025-1521372--qa-1", "work_id": "doi-10-3389-fpubh-2025-1521372", "qa_index": 1, "question": "What design, sample and mortality follow-up were used?", "answer": "The NHANES 2007–2018 analytic sample included 5,837 participants and 906 deaths, with a mean follow-up of 6.5 years and survey-weighted Cox analysis. Raw participant counts and survey-weighted percentages are different quantities and must not be directly substituted for one another.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fpubh-2025-1521372.html#qa-1", "question_source": "data/deep_geo/doi-10-3389-fpubh-2025-1521372.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-3389-fpubh-2025-1521372.json#/qa/0/answer", "answer_sha256": "ce7b4488f9e5b0606f3a4a76321376b2206e0d2d4423fa77c956a4c605a0910a", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fpubh-2025-1521372--qa-2", "work_id": "doi-10-3389-fpubh-2025-1521372", "qa_index": 2, "question": "How was short sleep associated with mortality?", "answer": "In fully adjusted Model 3, short sleep (<7 h versus 7–9 h) was associated with all-cause mortality at HR 1.25 (95% CI 1.04–1.51). This is an observational association, not a randomized intervention that shortens or extends sleep.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fpubh-2025-1521372.html#qa-2", "question_source": "data/deep_geo/doi-10-3389-fpubh-2025-1521372.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-3389-fpubh-2025-1521372.json#/qa/1/answer", "answer_sha256": "9371a2f7a00781630e80b6e94b40649809b2c7239166002af9efb63132796ac1", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fpubh-2025-1521372--qa-3", "work_id": "doi-10-3389-fpubh-2025-1521372", "qa_index": 3, "question": "How was long sleep associated with mortality?", "answer": "In Model 3, long sleep (>9 h versus 7–9 h) was associated with all-cause mortality at HR 1.50 (95% CI 1.10–2.04). The relative hazard is not an absolute-risk estimate or an individual prognosis.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fpubh-2025-1521372.html#qa-3", "question_source": "data/deep_geo/doi-10-3389-fpubh-2025-1521372.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-3389-fpubh-2025-1521372.json#/qa/2/answer", "answer_sha256": "bdc7d0b3c1be7e55ea723e81d2864d60ee63a41040d51b06721f9b7b44adda0b", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fpubh-2025-1521372--qa-4", "work_id": "doi-10-3389-fpubh-2025-1521372", "qa_index": 4, "question": "What did the sleep-trouble analysis show?", "answer": "Self-reported sleep trouble did not show a statistically significant association with mortality in Model 3: HR 1.04 (95% CI 0.87–1.25), P=0.651. This result for one self-reported indicator does not prove that all sleep disorders have no effect on mortality.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fpubh-2025-1521372.html#qa-4", "question_source": "data/deep_geo/doi-10-3389-fpubh-2025-1521372.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-3389-fpubh-2025-1521372.json#/qa/3/answer", "answer_sha256": "de40f0a86e2c0c4e4c41d536ba218b37483e45ca9945e198c736a843077de9cf", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fpubh-2025-1521372--qa-5", "work_id": "doi-10-3389-fpubh-2025-1521372", "qa_index": 5, "question": "Should 7.23 hours be interpreted as a prescribed individual target?", "answer": "Restricted cubic splines showed nonlinearity (P<0.001), with an estimated sleep-duration turning point of 7.23 h. The turning point is a model estimate from this dataset, not an intervention-validated sleep prescription or a precise target for every individual.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fpubh-2025-1521372.html#qa-5", "question_source": "data/deep_geo/doi-10-3389-fpubh-2025-1521372.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-3389-fpubh-2025-1521372.json#/qa/4/answer", "answer_sha256": "1d8dceed617cecf887a6b6c7699f49b3a795682a740755934809f1da28d9ae12", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-32604-or-2025-059290--qa-1", "work_id": "doi-10-32604-or-2025-059290", "qa_index": 1, "question": "What literature did this bibliometric study analyze?", "answer": "It analyzed 17,293 English-language documents after deduplication from a title-based Web of Science Core Collection search covering publications from 1 March 2014 to 1 March 2024. The reported database access date was 25 December 2024; this differs from the publication eligibility cutoff.", "answer_url": "https://drgezhang.com/papers/doi-10-32604-or-2025-059290.html#qa-1", "question_source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/qa/0/answer", "answer_sha256": "2371a0ffa1df0239b9ba092e484c3ece840ffc61f017a4fafe69306c2a8d246e", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-32604-or-2025-059290--qa-2", "work_id": "doi-10-32604-or-2025-059290", "qa_index": 2, "question": "How were the retrieved documents distributed across cancer-management topics?", "answer": "The article reports 1,655 prevention, 2,300 screening, 2,874 diagnosis, 10,298 treatment and 166 rehabilitation documents. These are literature counts in the retrieved corpus, not patients or clinical outcomes.", "answer_url": "https://drgezhang.com/papers/doi-10-32604-or-2025-059290.html#qa-2", "question_source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/qa/1/answer", "answer_sha256": "4366875d95f6f17b0344e8f22c69650f5260d459dfa2dd7f2fff034d5b969f7e", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-32604-or-2025-059290--qa-3", "work_id": "doi-10-32604-or-2025-059290", "qa_index": 3, "question": "Which treatment-related keyword frequencies are directly reported?", "answer": "Table 9 reports targeted therapy 1,069, tumor microenvironment 927, immunotherapy 900 and artificial intelligence 797. These frequencies describe bibliographic attention and should not be interpreted as measures of clinical effectiveness.", "answer_url": "https://drgezhang.com/papers/doi-10-32604-or-2025-059290.html#qa-3", "question_source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/qa/2/answer", "answer_sha256": "aebabda7c25cff1383d3da2d4be6a5a3e6f5c642031893e0104a2bfb6adeadce", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-32604-or-2025-059290--qa-4", "work_id": "doi-10-32604-or-2025-059290", "qa_index": 4, "question": "Can this study establish which cancer treatment works best?", "answer": "No. Its original evidence consists of document counts and bibliometric patterns. It does not compare patient interventions or estimate treatment effects; clinical claims discussed from other publications require those primary studies.", "answer_url": "https://drgezhang.com/papers/doi-10-32604-or-2025-059290.html#qa-4", "question_source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-32604-or-2025-059290.json#/qa/3/answer", "answer_sha256": "5c6e17b2b05eeb90595c6198636a36512b6d46ded9b2bc7986e83237aa4df4fc", "evidence_refs": [ "KF1", "KF2", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70725--qa-1", "work_id": "doi-10-1111-jcmm-70725", "qa_index": 1, "question": "How many participants were studied?", "answer": "The article reports 18 AAA patients and 9 controls: 10/5 in-house and 8/4 external. These numbers describe the two reported cohorts, not additional participants per assay.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#qa-1", "question_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/0/answer", "answer_sha256": "13fd44cfc17aaacb843904ddabf6bd866359c1b6dea3661288a8be30f883878a", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70725--qa-2", "work_id": "doi-10-1111-jcmm-70725", "qa_index": 2, "question": "Was this unbiased plasma proteomics?", "answer": "No. The study examined an isolated circulating vesicle-associated fraction with a targeted 92-protein Olink panel. Specimen wording also differs between source sections.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#qa-2", "question_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/1/answer", "answer_sha256": "d4cdc8a40c4599fa5ad92d58d45ddac7c0c43e2600b035fa3c00bc2256443410", "evidence_refs": [ "KF2", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70725--qa-3", "work_id": "doi-10-1111-jcmm-70725", "qa_index": 3, "question": "Which proteins were prioritized?", "answer": "IL-4, IL-6, MCP-1, Neurturin and Oncostatin-M. They are candidate biomarkers in the analyzed samples, not approved diagnostic markers.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#qa-3", "question_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/2/answer", "answer_sha256": "a2dbc496348e002f772e0acb46694a810ae0813e3c9e9cb060d0921f018cb3b5", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70725--qa-4", "work_id": "doi-10-1111-jcmm-70725", "qa_index": 4, "question": "Did all five proteins replicate consistently in external assays?", "answer": "No. Western blot and ELISA differed for MCP-1 direction and Neurturin significance/direction. The evidence should be cited as assay-dependent external evaluation, not uniformly concordant validation.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#qa-4", "question_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/3/answer", "answer_sha256": "dc3c76bf729b0a0590e920b5853a1c533a84f1b7bec0ecac0ac698d2c205cfe8", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70725--qa-5", "work_id": "doi-10-1111-jcmm-70725", "qa_index": 5, "question": "What ROC performance was reported?", "answer": "In the article-listed order IL-4, IL-6, MCP-1, Neurturin and Oncostatin-M, AUCs were 0.760, 0.840, 0.800, 0.840 and 0.900. The external group was small and confidence intervals were wide. These are single-marker comparisons, not a combined five-protein model.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#qa-5", "question_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/4/answer", "answer_sha256": "bee3d0d34d85ea3c58789932789ac2848a39ddda164f7bbd9af8faac811e3cbd", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70725--qa-6", "work_id": "doi-10-1111-jcmm-70725", "qa_index": 6, "question": "Does the study prove that these proteins predict rupture or are treatment targets?", "answer": "No. It reports association, small external assay/ROC comparisons and computational annotations, not prospective rupture prediction or therapeutic target validation.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#qa-6", "question_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70725.json#/qa/5/answer", "answer_sha256": "b4ec7533f478524843951db57ea200dc35c3ba853fc3285b1bd5443e8a48eeda", "evidence_refs": [ "KF4", "KF5", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-joim-2025-06-003--qa-1", "work_id": "doi-10-1016-j-joim-2025-06-003", "qa_index": 1, "question": "How was the HCCcrds gene framework derived?", "answer": "Single-cell modules supplied the HCCcrds gene set. Analyzed cells: 11,383; Genes from modules M2/M4/M5: 562. Cells and candidate genes are not patient counts or demonstrated causal regulators.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html#qa-1", "question_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/0/answer", "answer_sha256": "8afffb10ea69fd016fb046c9a29e77040133ab987002fc83c562c0c65534d0d7", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-joim-2025-06-003--qa-2", "work_id": "doi-10-1016-j-joim-2025-06-003", "qa_index": 2, "question": "What role did the circadian reference datasets play?", "answer": "The score was evaluated in separate clock, feeding and sleep-reference data. Reference datasets: GSE10045; GSE150381; GSE39445. Reference-experiment evaluation does not mean HCC patients underwent longitudinal physiological circadian measurements.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html#qa-2", "question_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/1/answer", "answer_sha256": "4033f50a40dae2de95badd34755d5811c47ee3981313d94e56bc42dc268dd22e", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-joim-2025-06-003--qa-3", "work_id": "doi-10-1016-j-joim-2025-06-003", "qa_index": 3, "question": "Which HCC subtypes were associated with clinical outcomes?", "answer": "TCGA-LIHC analysis identified CS-H, CS-L and CS-M, with poorer outcomes associated with CS-H. TCGA-LIHC n: 369; Subtypes: CS-H; CS-L; CS-M. Association does not establish that circadian disruption causes liver cancer or constitute a validated clinical decision rule.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html#qa-3", "question_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/2/answer", "answer_sha256": "da0f15be614a30521481894add0100d51beaf23225ea39c1bc3b47a91867c1ab", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-joim-2025-06-003--qa-4", "work_id": "doi-10-1016-j-joim-2025-06-003", "qa_index": 4, "question": "Were external classification and survival analyses performed in identical cohorts?", "answer": "External subtype and survival analyses used overlapping but different cohort sets. Fig. 5A datasets: ICGC_LIRI; GSE14520; GSE54236; GSE104580; Fig. 5B datasets: ICGC_LIRI; GSE14520; GSE54236; GSE27150. Do not claim that all five cohorts validated survival, or add the two four-cohort analyses as eight independent cohorts.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html#qa-4", "question_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/3/answer", "answer_sha256": "e9cc9e21ccd22172c4daebb1066f62e4480774c338ddba27835c65e721634cf2", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-joim-2025-06-003--qa-5", "work_id": "doi-10-1016-j-joim-2025-06-003", "qa_index": 5, "question": "Do the immune analyses demonstrate immunotherapy benefit?", "answer": "Subtypes differed in proliferation/metabolic programs and inferred immune characteristics. Analyses: Expression enrichment; CIBERSORT; IPS. IPS and immune deconvolution are not an observed immunotherapy-response trial.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html#qa-5", "question_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/4/answer", "answer_sha256": "989173fe43497c5801facab93e621afca561011e3a156835caa23495d9faeab6", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-joim-2025-06-003--qa-6", "work_id": "doi-10-1016-j-joim-2025-06-003", "qa_index": 6, "question": "What evidence supports the nominated molecular markers?", "answer": "NNMT and MARCKSL1 were among subtype-associated candidate genes. Evidence: Expression correlation and network prioritization. This evidence synthesis does not claim independent causal intervention or therapeutic validation of these genes.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-joim-2025-06-003.html#qa-6", "question_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1016-j-joim-2025-06-003.json#/qa/5/answer", "answer_sha256": "5a2bb467ad7b0fb43309a54b005df88089eb842c6cb3e531d191c2dbb612cecc", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s12915-025-02400-x--qa-1", "work_id": "doi-10-1186-s12915-025-02400-x", "qa_index": 1, "question": "What single-cell evidence was analyzed?", "answer": "Four aneurysmal aortic samples yielded 7,343 post-QC cells, 16 populations and nine main cell types. The T-cell analysis included 3,841 cells and eight phenotypes.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#qa-1", "question_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/0/answer", "answer_sha256": "42690b984a1d4d66298d0e22dd80d7fb3ad869115b17159cbac0d15d52da05a7", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s12915-025-02400-x--qa-2", "work_id": "doi-10-1186-s12915-025-02400-x", "qa_index": 2, "question": "What does pseudotime establish and not establish?", "answer": "Monocle inferred a bifurcated trajectory with two terminal fates and three infiltration states. It reconstructs transcriptional relationships and does not directly observe individual cells changing fate over time.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#qa-2", "question_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/1/answer", "answer_sha256": "577ecb8cf2628d3eb94ce95b379e9b88c727437b166199fbffca29bd1925299e", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s12915-025-02400-x--qa-3", "work_id": "doi-10-1186-s12915-025-02400-x", "qa_index": 3, "question": "How was TIRS derived?", "answer": "The analysis used 968 cell-state DE genes, 437 BEAM fate leader genes and 375 trajectory-ordering genes, with a 374-gene intersection and a final bulk-overlapping TIRS of 50 genes.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#qa-3", "question_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/2/answer", "answer_sha256": "e8d24819e4e579e09454f0230d221001d2f724e7a83d4f7414e7fdd269be3d0d", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s12915-025-02400-x--qa-4", "work_id": "doi-10-1186-s12915-025-02400-x", "qa_index": 4, "question": "Which candidate biomarkers were selected?", "answer": "The LASSO and SVM-RFE intersection selected FOSB, JUNB, CST7 and TBC1D4.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#qa-4", "question_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/3/answer", "answer_sha256": "7c2a9bdfe96583d133e11066aabe0920145053c6ad6c71d471ba08e9186652b7", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s12915-025-02400-x--qa-5", "work_id": "doi-10-1186-s12915-025-02400-x", "qa_index": 5, "question": "How did they perform across public cohorts?", "answer": "In FOSB/JUNB/CST7/TBC1D4 order, AUCs were 0.911/0.917/0.926/0.955 in Dataset 1, 0.982/0.911/0.893/0.857 in Dataset 2 and 0.956/0.887/0.506/0.514 in Dataset 3. Discrimination varied by marker and dataset.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#qa-5", "question_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/4/answer", "answer_sha256": "3c873f84fd14a19eb02a53df9f413661fde2d9e0b329adf4d8a6cc0134d19fd4", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s12915-025-02400-x--qa-6", "work_id": "doi-10-1186-s12915-025-02400-x", "qa_index": 6, "question": "Were they evaluated in independent human samples?", "answer": "Yes: aortic wall from 5 AAA and 4 controls, and peripheral blood from 24 AAA and 15 controls. Aortic-wall AUCs were 1.000/1.000/0.600/0.800 and blood AUCs were 0.989/0.906/0.933/0.736 in FOSB/JUNB/CST7/TBC1D4 order. The aortic-wall sample was small.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#qa-6", "question_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/5/answer", "answer_sha256": "7733a8cba51d8b019df3d40ff9cd0ee12441de345fc576f6d3b07b67997dac32", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s12915-025-02400-x--qa-7", "work_id": "doi-10-1186-s12915-025-02400-x", "qa_index": 7, "question": "Does this study establish a clinical diagnostic test or therapy?", "answer": "No. The reported associations, marker discrimination, small human-sample evaluation and supportive mouse expression do not establish prospective diagnostic utility, approved standalone tests or human treatment efficacy.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s12915-025-02400-x.html#qa-7", "question_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1186-s12915-025-02400-x.json#/qa/6/answer", "answer_sha256": "7fcbdc7d4208ee99f4c7ff4e591d331f526e0328e97f0a21edca8a911c190318", "evidence_refs": [ "KF5", "KF6", "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-71321-fy14v342--qa-1", "work_id": "doi-10-71321-fy14v342", "qa_index": 1, "question": "Which cohorts contribute the reported LUAD input count?", "answer": "The counts are TCGA-LUAD 497, GSE72094 442, GSE68465 462, GSE50081 127, GSE42127 133, GSE41271 183 and GSE31210 246. Their arithmetic sum is 2090, without participant-level deduplication. The separate 79 immunotherapy records are not added.", "answer_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#qa-1", "question_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/0/answer", "answer_sha256": "b4b8d8b9564d002618dfd0e8bf8745382fa09f37c8fb7afda169af2ba78cd805", "evidence_refs": [ "KF1", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-71321-fy14v342--qa-2", "work_id": "doi-10-71321-fy14v342", "qa_index": 2, "question": "How were the subtypes developed and assessed across cohorts?", "answer": "NMF selected three TCGA clusters from the reported 2091 CRD-related gene entries. NTP assessed template assignment in the six named GEO cohorts with confidence filtering. Results say five cohorts while listing six; this remains retrospective expression assessment.", "answer_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#qa-2", "question_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/1/answer", "answer_sha256": "c960e9eb1c9fc2e3c3664dd53ff366eeed498cc369049d0dac379c03feae989c", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-71321-fy14v342--qa-3", "work_id": "doi-10-71321-fy14v342", "qa_index": 3, "question": "What survival pattern was reported for C1, C2 and C3?", "answer": "C2 generally had more favorable survival and C1 generally less favorable survival. Cohort-specific plots do not establish identical ranking everywhere. The TCGA log-rank P of 0.0062 is an association result, not a treatment effect or validated decision rule.", "answer_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#qa-3", "question_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/2/answer", "answer_sha256": "991c660cf2434093ca0d657bb6690ceef27c29ad11c2e5652874650fa3f74b43", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-71321-fy14v342--qa-4", "work_id": "doi-10-71321-fy14v342", "qa_index": 4, "question": "Do circadian-related expression differences directly measure a patient clock?", "answer": "No direct circadian-phase, sleep or metabolic-flux measurement is reported. Enrichment associates C1 with proliferation, C2 with lipid-metabolic and circadian sleep-wake gene sets, and C3 with immune programs; it does not establish circadian causation.", "answer_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#qa-4", "question_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/3/answer", "answer_sha256": "41ba2ecedf06d9acf6e62d6363a049262dfdf3e49ac451be96ff1c8b2f5d4ffe", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-71321-fy14v342--qa-5", "work_id": "doi-10-71321-fy14v342", "qa_index": 5, "question": "What genomic features were associated with the clusters?", "answer": "TCGA annotation analyses associated C1 with greater mutation and copy-number-alteration burdens. These comparisons and inferred stemness scores do not show that clock disruption caused TP53 changes, genomic instability or immune escape.", "answer_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#qa-5", "question_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/4/answer", "answer_sha256": "d080dd9275b2fdc0a8001bfdcbbf1f7d9cd46058c815ae828c000819bfebf782", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-71321-fy14v342--qa-6", "work_id": "doi-10-71321-fy14v342", "qa_index": 6, "question": "Why can C3 show high infiltration and a suppressive immune profile?", "answer": "Expression-based analyses report higher infiltration together with lower IPS, higher S-score and higher inferred heterogeneity for C3. Cell abundance and function are different questions; bulk scores do not directly prove suppressive cellular mechanisms.", "answer_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#qa-6", "question_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/5/answer", "answer_sha256": "8e061d818292209e1d7e7d593ff6bbc52b282d49ce44f97c0c54ce548d8ad59e", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-71321-fy14v342--qa-7", "work_id": "doi-10-71321-fy14v342", "qa_index": 7, "question": "Did the study establish immunotherapy benefit for C3 patients?", "answer": "Checkpoint expression, TIS and SubMap similarity support a response hypothesis. The separately reported 79 reference records are incompletely resolved by cohort and diagnosis, and no prospective subtype-guided response or benefit evaluation is reported.", "answer_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#qa-7", "question_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/6/answer", "answer_sha256": "acb672ff508e29f96a1394ef9a1d032ab077e3115eba55d15235955caf24d46e", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-71321-fy14v342--qa-8", "work_id": "doi-10-71321-fy14v342", "qa_index": 8, "question": "What can be concluded from predicted drug-sensitivity differences?", "answer": "Computed displays suggest subtype-associated drug-response metrics. Their axes label estimated AUC while text says IC50, and steroid naming differs between text and supplement. They do not justify clinical chemotherapy or corticosteroid recommendations.", "answer_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#qa-8", "question_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/7/question", "answer_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/7/answer", "answer_sha256": "b255eee2d4f15ed9bbd21c553480a8c57159ba58440bf9346819acc2764e3ce4", "evidence_refs": [ "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-71321-fy14v342--qa-9", "work_id": "doi-10-71321-fy14v342", "qa_index": 9, "question": "How should the 151-signature C-index comparison be interpreted?", "answer": "The article reports TCGA-internal C-index values 0.741 for C1 and 0.698 for C2 under Chen EG (2017), and 0.796 for C3 under Ma B (2020). These are retrospective candidate-selection results, with unresolved exact Chen-model attribution and no established external performance or clinical utility.", "answer_url": "https://drgezhang.com/papers/doi-10-71321-fy14v342.html#qa-9", "question_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/8/question", "answer_source": "data/deep_geo/doi-10-71321-fy14v342.json#/qa/8/answer", "answer_sha256": "3317ce15640f930f84cf9fc8845015df50455ee34a0eacadc26fe872193026e8", "evidence_refs": [ "KF8" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-cbi-2025-111421--qa-1", "work_id": "doi-10-1016-j-cbi-2025-111421", "qa_index": 1, "question": "Is this a patient study?", "answer": "No. It uses cardiac organoids differentiated from commercial human induced pluripotent stem cells. Human cell origin does not make this a clinical validation, and the source does not provide a verified independent donor count. Source location: Journal Pre-proof PDF pp. 6-7, Methods 2.2-2.3.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#qa-1", "question_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/0/answer", "answer_sha256": "72366bd50a9b04f3f68ab76628619c59351953219ccd4bebcd2acc4759e4f74e", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-cbi-2025-111421--qa-2", "work_id": "doi-10-1016-j-cbi-2025-111421", "qa_index": 2, "question": "Which source version supports this evidence page?", "answer": "The reviewed file is the 37-page Journal Pre-proof obtained through the author-authorized ResearchGate file channel. The DOI, title and 14-author order match the formal indexed record. The definitive full text has not been compared, and the two cited supplementary files have not been inspected. Source location: Journal Pre-proof cover p. 1 and title page p. 2; Crossref DOI record checked 2026-10-27; PubMed PMID 39984109.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#qa-2", "question_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/1/answer", "answer_sha256": "77680a663d4d932a19f34e8d5eefc47ffe36836ba32f0f58db58485aa7059c4c", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-cbi-2025-111421--qa-3", "work_id": "doi-10-1016-j-cbi-2025-111421", "qa_index": 3, "question": "What do the n=3 and n=6 labels mean?", "answer": "They are the sample labels reported in individual figure legends. The paper does not clearly distinguish independent donors, differentiation batches and technical repeats, so the labels are retained without assigning a synthetic total n or claiming independent patient replication. Source location: Journal Pre-proof PDF p. 12, Methods 2.14; legends on PDF pp. 16, 18, 20, 22 and 25.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#qa-3", "question_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/2/answer", "answer_sha256": "1b560eb0f83a1a8784b0a04b8137636b8693d7e89c561afe19ee41ff8b14754a", "evidence_refs": [ "KF2", "KF3", "KF4", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-cbi-2025-111421--qa-4", "work_id": "doi-10-1016-j-cbi-2025-111421", "qa_index": 4, "question": "What glucose and lipid conditions were examined?", "answer": "The viability screen used a 48-hour exposure, with palmitate conditions from 50 to 300 micromolar and displayed glucose conditions from 5 to 50 mM. The combined-condition panels use 200 micromolar palmitate and varying glucose. These are culture conditions, not clinical targets or patient dosing instructions. Source location: Journal Pre-proof PDF p. 8, Methods 2.5-2.6; Figs. 2B-C and 3.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#qa-4", "question_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/3/answer", "answer_sha256": "aada6b12be7736d0f186271426568d8c8ec3c5ba7317a55930382f8a5fa1d185", "evidence_refs": [ "KF2", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-cbi-2025-111421--qa-5", "work_id": "doi-10-1016-j-cbi-2025-111421", "qa_index": 5, "question": "What is the defensible injury evidence?", "answer": "The accepted evidence includes CCK-8 signal, BAX/APAF1 transcription, TUNEL staining and selected inflammatory/fibrosis-associated readouts in labeled organoid groups. No exact effect sizes are reconstructed from bars, and these assays do not demonstrate a complete causal mechanism in patients. Source location: Journal Pre-proof PDF pp. 15-22, Figs. 2B-C, 3B-C, 4 and 5; Results 3.3-3.5.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#qa-5", "question_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/4/answer", "answer_sha256": "a5b6f737e9da75e161dee69a9c28a48ca3b355fd727bc5dca1f5e33a9e281a98", "evidence_refs": [ "KF2", "KF3", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-cbi-2025-111421--qa-6", "work_id": "doi-10-1016-j-cbi-2025-111421", "qa_index": 6, "question": "Does the metformin experiment establish a treatment regimen?", "answer": "No. Three labeled groups are compared and selected readouts shift toward control values after metformin, but the acquired file does not state the metformin concentration. The observations cannot establish a reproducible dose-response regimen, safety or human efficacy. Source location: Journal Pre-proof PDF pp. 11, 23-25, Methods 2.12, Results 3.7 and Figs. 7-8.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#qa-6", "question_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/5/answer", "answer_sha256": "6705be08bb55872cb60272a417ede5baf8b53891e459101dc3a3ad8a395d39d4", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-cbi-2025-111421--qa-7", "work_id": "doi-10-1016-j-cbi-2025-111421", "qa_index": 7, "question": "Why are some transcript and mitochondrial conclusions excluded?", "answer": "The broad TNNT2/MYH6 prose descriptions differ from the directions shown in the plots. Methods 2.11 states a red/green JC-1 ratio while Fig. 6B labels green/red. Those details are not reconciled by guesswork or promoted as confirmed findings. Source location: Journal Pre-proof PDF pp. 11, 17-18 and 23-24; Methods 2.11, Results 3.4/3.7, Figs. 3D/H, 6B and 7.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#qa-7", "question_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/6/answer", "answer_sha256": "9c6c3a97419ea3a03c8e1008fa9f6516885c4af89a3d5e6a92a15aa346fef05a", "evidence_refs": [ "KF3", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-cbi-2025-111421--qa-8", "work_id": "doi-10-1016-j-cbi-2025-111421", "qa_index": 8, "question": "Has the study validated a physiologically mature heart or a clinical screening platform?", "answer": "No. Morphology and lineage-marker staining characterize a construct, but do not establish adult-heart maturity, clinical prediction or performance across independently characterized donors. No prospective patient validation or direct comparative test proving superiority to every 2D or animal model is reported. Source location: Journal Pre-proof PDF pp. 12-16, Results 3.1-3.3 and Figs. 1-2; Discussion pp. 26-30.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-cbi-2025-111421.html#qa-8", "question_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/7/question", "answer_source": "data/deep_geo/doi-10-1016-j-cbi-2025-111421.json#/qa/7/answer", "answer_sha256": "eb44def62389fd68a28ef8e94b09019816fb4c6239fed3342ea7c48e26a93af4", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "b4galt2--qa-1", "work_id": "b4galt2", "qa_index": 1, "question": "What is PTMLS in this study?", "answer": "PTMLS is an expression-based post-translational modification learning signature, developed in TCGA-LUAD and evaluated across six GEO survival cohorts using algorithm selection that includes validation-set comparisons.", "answer_url": "https://drgezhang.com/papers/b4galt2.html#qa-1", "question_source": "data/deep_geo/b4galt2.json#/qa/0/question", "answer_source": "data/deep_geo/b4galt2.json#/qa/0/answer", "answer_sha256": "8ee5962da6bb481ba7aaeffb2689128a0608f9e47ef260a027b61c4cd7ac3510", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "b4galt2--qa-2", "work_id": "b4galt2", "qa_index": 2, "question": "Was the prognostic model tested outside the discovery cohort?", "answer": "The article applied it to six GEO LUAD datasets. These are retrospective datasets and not evidence that clinical decisions based on the score improve outcomes.", "answer_url": "https://drgezhang.com/papers/b4galt2.html#qa-2", "question_source": "data/deep_geo/b4galt2.json#/qa/1/question", "answer_source": "data/deep_geo/b4galt2.json#/qa/1/answer", "answer_sha256": "911fb4138738f1f599813ed981d2e1ece5659d11bc98ffbbbeab59c54f3459da", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "b4galt2--qa-3", "work_id": "b4galt2", "qa_index": 3, "question": "Which tumor immune phenotype is linked with high B4GALT2 in patient tissue?", "answer": "In a 171-case institutional LUAD tissue series, higher B4GALT2 expression was associated with CD8-low/desert-like patterns and less favorable survival, without causal assignment.", "answer_url": "https://drgezhang.com/papers/b4galt2.html#qa-3", "question_source": "data/deep_geo/b4galt2.json#/qa/2/question", "answer_source": "data/deep_geo/b4galt2.json#/qa/2/answer", "answer_sha256": "7c294bc802cc6f9d31635d68e43c767ed513f3a452cd9cbb3278c0bcd61b4b9b", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "b4galt2--qa-4", "work_id": "b4galt2", "qa_index": 4, "question": "What does the B4GALT2 knockdown experiment add?", "answer": "It adds culture-based and mouse-tumor perturbation evidence, including increased CD8 effector readouts with anti-PD-1 combination in mice. This does not establish human treatment efficacy.", "answer_url": "https://drgezhang.com/papers/b4galt2.html#qa-4", "question_source": "data/deep_geo/b4galt2.json#/qa/3/question", "answer_source": "data/deep_geo/b4galt2.json#/qa/3/answer", "answer_sha256": "2fd0a244df0e66e098acb7688a67691da322bfdb67cf761e14679137bb96ac81", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "b4galt2--qa-5", "work_id": "b4galt2", "qa_index": 5, "question": "Was Figure 2 corrected after publication?", "answer": "Yes. The original differential-gene heatmap was corrected in an official June 2025 notice (DOI 10.1136/jitc-2024-010787corr1). Use the corrected figure for specific PTM-gene claims.", "answer_url": "https://drgezhang.com/papers/b4galt2.html#qa-5", "question_source": "data/deep_geo/b4galt2.json#/qa/4/question", "answer_source": "data/deep_geo/b4galt2.json#/qa/4/answer", "answer_sha256": "4f704a224b805feace1a3ef1baa136be3ac70a17c65dfffddc66a4ec1347273a", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "b4galt2--qa-6", "work_id": "b4galt2", "qa_index": 6, "question": "Is the mouse inoculation cell count unambiguous?", "answer": "No. Methods reports 2×10^5 cells while the Figure 8H caption reports 1×10^6 cells; the evidence summary does not choose between these conflicting numbers.", "answer_url": "https://drgezhang.com/papers/b4galt2.html#qa-6", "question_source": "data/deep_geo/b4galt2.json#/qa/5/question", "answer_source": "data/deep_geo/b4galt2.json#/qa/5/answer", "answer_sha256": "403f581c71ec254b413db9be666c9202c12ab546da102ce26165b3330431d8d9", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70004--qa-1", "work_id": "doi-10-1002-mdr2-70004", "qa_index": 1, "question": "What does the Stage II DNB signal establish?", "answer": "Stage II had the highest reported network instability signal. DNB genes: 36. Cross-sectional stage comparisons do not establish longitudinal prediction of each patient's future deterioration time.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#qa-1", "question_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/0/answer", "answer_sha256": "4665609628ca6a4de9e6186a402bc1113e973e0b04aa9b4d9f4229b848d9d178", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70004--qa-2", "work_id": "doi-10-1002-mdr2-70004", "qa_index": 2, "question": "Is TCPSLevel already a clinically validated prospective risk tool?", "answer": "TCPSLevel was associated with clinical and outcome differences. Expression bins: 100; Background samplings: 1,000; Reported survival cutoff: 0.4. The reported cutoff is not a cross-cohort locked clinical threshold. Grouping rules used in other analyses are not automatically equivalent.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#qa-2", "question_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/1/answer", "answer_sha256": "dfa6c6a6aad808fd91fa04b049c19315597a1c62687e09f50d6b150d3c40cebe", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70004--qa-3", "work_id": "doi-10-1002-mdr2-70004", "qa_index": 3, "question": "How were the thyroid molecular subtypes evaluated externally?", "answer": "The ensemble analysis yielded three molecular subtypes. Candidate combinations: 20; Selected combination: CV-PAM; Reported external NTP datasets: 6. Methods 2.6 prints GSE333630 whereas other locations use GSE33630. These are not silently rewritten as a fully verified accession inventory.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#qa-3", "question_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/2/answer", "answer_sha256": "267bec98a83c15d4a8aafbaa459dfbb110bd46ff04562b6e1e3167372ef89033", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70004--qa-4", "work_id": "doi-10-1002-mdr2-70004", "qa_index": 4, "question": "Does miniPC classify subtypes or directly prove improved survival?", "answer": "miniPC classified the consensus subtype labels using a compact gene set. Candidate genes: 296; Final genes: 12; Final classifier: Neural network; External classifier cohorts: 5. This is subtype classification, not prospective individual survival-benefit validation. Unverified figure-only accuracy or AUC values are not reconstructed.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#qa-4", "question_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/3/answer", "answer_sha256": "269226959e5fc528eb6505ff7fe243c1eb3519343dc55d453c531c1901e84273", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70004--qa-5", "work_id": "doi-10-1002-mdr2-70004", "qa_index": 5, "question": "How many independent donors support the single-cell analysis?", "answer": "Single-cell analysis localized expression patterns across cellular compartments. Reported donors: 1; Cells in Methods: 17,709; Cells in Results: 17,518; Annotated populations: 7. A single donor and a large cell count do not establish large-population replication. No explanation for the count difference is invented.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#qa-5", "question_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/4/answer", "answer_sha256": "d10b331e5280248b1d786d3f4d9fc5d1f8d15154ed696c0b156ada6e2384a60a", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70004--qa-6", "work_id": "doi-10-1002-mdr2-70004", "qa_index": 6, "question": "What human and experimental evidence supports ASPH?", "answer": "ASPH was evaluated in human tissues and through TPC-1 silencing. Tumor specimens: 48; Adjacent specimens: 48; TPC-1 silencing: Reduced proliferation and migration. Paired tissues are not 96 independent patients. ASCL2-ASPH network inference is not direct binding validation, and cell effects do not establish human targeted-treatment efficacy.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#qa-6", "question_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/5/answer", "answer_sha256": "2a158d5ae30ceb9d49a458ee6a8533dd539e6b9a575c0b7026b61e4956e30ae0", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-mdr2-70004--qa-7", "work_id": "doi-10-1002-mdr2-70004", "qa_index": 7, "question": "Were CMap-nominated compounds shown to benefit patients?", "answer": "IPS and CMap supplied candidate immune/drug-response hypotheses. Evidence: Computational scoring and signature matching. Predicted compounds are not proven effective treatments. IPS is not an observed outcome in patients receiving immunotherapy.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-mdr2-70004.html#qa-7", "question_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1002-mdr2-70004.json#/qa/6/answer", "answer_sha256": "6ee998351261c5829d803f8a4d7faf04cc802b8af364773eecec82a003da7d10", "evidence_refs": [ "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1200-po-24-00875--qa-1", "work_id": "doi-10-1200-po-24-00875", "qa_index": 1, "question": "Does this reply introduce another patient cohort?", "answer": "No. It discusses previous modeling work and contains no new cohort or clinical outcome analysis.", "answer_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00875.html#qa-1", "question_source": "data/deep_geo/doi-10-1200-po-24-00875.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1200-po-24-00875.json#/qa/0/answer", "answer_sha256": "81a86c8a02cfd94f1e33294b73e943471639c8e243032d7c3a6fb7506a95ecab", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1200-po-24-00875--qa-2", "work_id": "doi-10-1200-po-24-00875", "qa_index": 2, "question": "What do 12 and 132 count?", "answer": "They count learners and candidate modeling schemes described from earlier work; they are not numbers of patients or independent validation cohorts.", "answer_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00875.html#qa-2", "question_source": "data/deep_geo/doi-10-1200-po-24-00875.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1200-po-24-00875.json#/qa/1/answer", "answer_sha256": "063f122b2a8cd2012d372cc281aebd0cf22e9a5c49233de19e160e63fe82c483", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1200-po-24-00875--qa-3", "work_id": "doi-10-1200-po-24-00875", "qa_index": 3, "question": "How is model selection explained?", "answer": "The authors describe averaging concordance across validation techniques as part of a consensus strategy for selecting a scheme.", "answer_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00875.html#qa-3", "question_source": "data/deep_geo/doi-10-1200-po-24-00875.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1200-po-24-00875.json#/qa/2/answer", "answer_sha256": "f696069879ee4ce8ac54f7c06a7272a918fce07209d68f85a1350a234913aa48", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1200-po-24-00875--qa-4", "work_id": "doi-10-1200-po-24-00875", "qa_index": 4, "question": "Does the SHAP discussion establish unbiased or causal feature effects?", "answer": "No. It explains the chosen attribution method, without a new experiment proving elimination of bias or causal interpretation.", "answer_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00875.html#qa-4", "question_source": "data/deep_geo/doi-10-1200-po-24-00875.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1200-po-24-00875.json#/qa/3/answer", "answer_sha256": "57066931d9eb8c148b97af63bd410e850ed144e7b8dc66b39883e47857a4696f", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2025-1538574--qa-1", "work_id": "doi-10-3389-fonc-2025-1538574", "qa_index": 1, "question": "How many single-cell patients were studied and how many cells were retained?", "answer": "Eight donor tumor specimens were analyzed (four BRCA1-MT, four BRCA1-WT), generating 32,386 quality-controlled cells; cell counts must not be reported as independent participant counts.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#qa-1", "question_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/0/answer", "answer_sha256": "4f4e1267439999378f8fbe49dd1fb391e1aae611d7668b0bbe69c1fbf21ce3ce", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2025-1538574--qa-2", "work_id": "doi-10-3389-fonc-2025-1538574", "qa_index": 2, "question": "Was there a genotype-matched spatial comparison?", "answer": "Only four BRCA1-WT spatial transcriptomic samples were described. The spatial analysis cannot independently validate BRCA1-MT versus WT spatial differences in a matched specimen design.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#qa-2", "question_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/1/answer", "answer_sha256": "ee75089512a6d0536d0b9bda4d4418dbca6641fdf7a6411eab14bfa66d22917b", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2025-1538574--qa-3", "work_id": "doi-10-3389-fonc-2025-1538574", "qa_index": 3, "question": "What evidence nominates ISG15?", "answer": "ISG15 was associated with myCAF-related modules, spatial expression and paired proteomic observations. These are multi-modal correlations and do not directly prove its functional mediation.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#qa-3", "question_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/2/answer", "answer_sha256": "70790990f8f0f207e04af8a7999a401b511071e594f4babb3f1cd7b53f5e33a9", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2025-1538574--qa-4", "work_id": "doi-10-3389-fonc-2025-1538574", "qa_index": 4, "question": "How well did the ICI response model discriminate?", "answer": "The selected KNN classifier reported AUC 0.60 (95% CI 0.51–0.69) for validation and 0.61 (95% CI 0.51–0.71) for testing in the external-treatment source data.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#qa-4", "question_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/3/answer", "answer_sha256": "cd0ad1eff66549b946fc7e52ac05f4a412a9dc4077fca58a9bccae9cbd55d69f", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2025-1538574--qa-5", "work_id": "doi-10-3389-fonc-2025-1538574", "qa_index": 5, "question": "Was the ICI model validated in treated TNBC patients?", "answer": "No. The Discussion explicitly identifies the lack of validation in ICI-treated TNBC cohorts; it is inappropriate to claim established TNBC treatment selection.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#qa-5", "question_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/4/answer", "answer_sha256": "af3fb4d19503725f046f4c422ac7dd9f80b17c943ab1a077c385134242b73d90", "evidence_refs": [ "KF4", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2025-1538574--qa-6", "work_id": "doi-10-3389-fonc-2025-1538574", "qa_index": 6, "question": "Did the model-selected groups have significantly different TCGA TNBC overall survival?", "answer": "No. The reported TCGA TNBC overall survival comparison was P=0.182, not statistically significant. A nominal METABRIC comparison does not establish ICI clinical benefit.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#qa-6", "question_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/5/answer", "answer_sha256": "7d2e4158077beed43bd997588362217378e1d9ce00a1eca58f7d4961fe39967f", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2025-1538574--qa-7", "work_id": "doi-10-3389-fonc-2025-1538574", "qa_index": 7, "question": "How many ICI cohorts did the authors use?", "answer": "The article is inconsistent: Methods describes 13 pretreatment ICI cohorts (829 records) whereas Results mentions 12 cohorts. Four cohorts pooled as 661 records for the principal development split can be identified; the other cohort count is not silently harmonized.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2025-1538574.html#qa-7", "question_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2025-1538574.json#/qa/6/answer", "answer_sha256": "6590992a4cc29b615295cf48af8e95a5633b1570eb6866a80cc40469d68ab528", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-odi-70054--qa-1", "work_id": "doi-10-1111-odi-70054", "qa_index": 1, "question": "Which three strategies are proposed?", "answer": "Crew dental capability, remotely guided care with virtual and 3D technologies, and adapted AI-driven robotic treatment are proposed.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-odi-70054.html#qa-1", "question_source": "data/deep_geo/doi-10-1111-odi-70054.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1111-odi-70054.json#/qa/0/answer", "answer_sha256": "0e4c18ead0b6df95cb78142363ab06b5222fd6c96a37c012b10523786f7bb532", "evidence_refs": [ "KF1", "KF2", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-odi-70054--qa-2", "work_id": "doi-10-1111-odi-70054", "qa_index": 2, "question": "Why does crew training appear alongside specialist staffing?", "answer": "The authors recognize limited onboard personnel and propose strengthening basic dental training when dedicated specialist staffing is impractical.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-odi-70054.html#qa-2", "question_source": "data/deep_geo/doi-10-1111-odi-70054.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1111-odi-70054.json#/qa/1/answer", "answer_sha256": "42b5dc52663c634108a70e7452ffec681df54e281f18c14bb5e473fe0fd4aa22", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-odi-70054--qa-3", "work_id": "doi-10-1111-odi-70054", "qa_index": 3, "question": "What constraints are acknowledged for remote care?", "answer": "The letter identifies signal delay and distortion, and discusses sensing and communications improvements as proposed responses.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-odi-70054.html#qa-3", "question_source": "data/deep_geo/doi-10-1111-odi-70054.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1111-odi-70054.json#/qa/2/answer", "answer_sha256": "4b044da17b72e2bd2bebb5a882592a3f942dba384fc2f1769218eb1da0653ab2", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-odi-70054--qa-4", "work_id": "doi-10-1111-odi-70054", "qa_index": 4, "question": "Were AI dental robots tested in astronauts or microgravity?", "answer": "No. The letter discusses an external technology example and proposes adaptation, without reporting such an experiment.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-odi-70054.html#qa-4", "question_source": "data/deep_geo/doi-10-1111-odi-70054.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1111-odi-70054.json#/qa/3/answer", "answer_sha256": "c080b1497f567695564dca6d7c607e4dd219148fd225be6dfad5ab1afe027bf4", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-ijn-s522157--qa-1", "work_id": "doi-10-2147-ijn-s522157", "qa_index": 1, "question": "Is this a human DCM treatment trial?", "answer": "No. It uses DOX-injured cell systems and mouse models. Human iPSC-derived cardiomyocytes remain an in-vitro system, not treated patients.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-ijn-s522157.html#qa-1", "question_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/0/answer", "answer_sha256": "581dc4351b96052e16b3360f6833ea9de62bbe2fa99522b87360e6ccce976c69", "evidence_refs": [ "KF3", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-ijn-s522157--qa-2", "work_id": "doi-10-2147-ijn-s522157", "qa_index": 2, "question": "What is being delivered: exosomes or liposomes?", "answer": "The experimental carrier is a peptide-functionalized liposome carrying a miR-185-5p inhibitory payload. The exosome-related title and earlier expression work should not be read as a clinical exosome infusion.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-ijn-s522157.html#qa-2", "question_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/1/answer", "answer_sha256": "7b7aa4782c23e16e2e0df54addc488ffef0686385ef3501acb4c21d25d57157a", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-ijn-s522157--qa-3", "work_id": "doi-10-2147-ijn-s522157", "qa_index": 3, "question": "How were the particles characterized?", "answer": "The loaded formulation had a DLS diameter of 172.35 ± 0.8 nm, encapsulation efficiency of 98.0 ± 1.2% and approximately 80% release at 48 hours. TEM describes approximately 100-nm morphology; that is not the same measurement as hydrodynamic size.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-ijn-s522157.html#qa-3", "question_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/2/answer", "answer_sha256": "b23ca473c9acd70d17b22c34f2afcb184b0567ff5170b46fea12a0df8afaf892", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-ijn-s522157--qa-4", "work_id": "doi-10-2147-ijn-s522157", "qa_index": 4, "question": "What evidence supports cardiac targeting?", "answer": "The targeting-peptide preparation showed greater cardiac fluorescence than the non-targeted preparation in the reported mouse comparison. Fluorescence does not by itself quantify an intact active-drug dose or establish exclusive heart delivery.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-ijn-s522157.html#qa-4", "question_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/3/answer", "answer_sha256": "92742ed8686131787c58880deeadda6a9a660268150804f7f5215c29d81e3dd0", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-ijn-s522157--qa-5", "work_id": "doi-10-2147-ijn-s522157", "qa_index": 5, "question": "What cardiac and cellular outcomes were reported?", "answer": "Mouse echocardiography and histology showed favorable changes under the tested conditions, and cell experiments showed changes in apoptosis- and cuproptosis-associated proteins. These are preclinical readouts, not human outcomes.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-ijn-s522157.html#qa-5", "question_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/4/answer", "answer_sha256": "0a142de1707eb34db6674df67a475800f77eb1ef411097aaac98dd097452ec7c", "evidence_refs": [ "KF3", "KF4", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-ijn-s522157--qa-6", "work_id": "doi-10-2147-ijn-s522157", "qa_index": 6, "question": "Does the article establish safety or a survival benefit in people?", "answer": "No. Its tolerability testing is limited and experimental. Abstract-only survival and percentage claims are not treated here as independently verified key outcomes, and no human treatment cohort is present.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-ijn-s522157.html#qa-6", "question_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-2147-ijn-s522157.json#/qa/5/answer", "answer_sha256": "5873b827ef0a04e748253d53a2e4f6e630b8cf150302c9be2abd8cebf6f5dc33", "evidence_refs": [ "KF3", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "nlrp3-ici--qa-1", "work_id": "nlrp3-ici", "qa_index": 1, "question": "What model was used to study ICI cardiotoxicity?", "answer": "B16F10-bearing female C57BL/6J mice were studied under anti-PD-1 treatment; the study also included a dual anti-PD-1 plus anti-CTLA-4 experiment. Human GSE180045 data provided supportive associations.", "answer_url": "https://drgezhang.com/papers/nlrp3-ici.html#qa-1", "question_source": "data/deep_geo/nlrp3-ici.json#/qa/0/question", "answer_source": "data/deep_geo/nlrp3-ici.json#/qa/0/answer", "answer_sha256": "8d39e7b0d422a583c2b6fbfe3515119f72e344c179c16c0961a835c424f3b86d", "evidence_refs": [ "KF1", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "nlrp3-ici--qa-2", "work_id": "nlrp3-ici", "qa_index": 2, "question": "What cardiac effects were observed after MCC950 in mice?", "answer": "The tested anti-PD-1 mouse experiments reported mitigation of cardiac injury across cTnT, echocardiography, immune infiltration, apoptosis, fibrosis and inflammatory/chemokine readouts.", "answer_url": "https://drgezhang.com/papers/nlrp3-ici.html#qa-2", "question_source": "data/deep_geo/nlrp3-ici.json#/qa/1/question", "answer_source": "data/deep_geo/nlrp3-ici.json#/qa/1/answer", "answer_sha256": "b89fd991ebad80875da1acbf23384e6f9690dc9dc51c0eaee66d7e0018e8594c", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "nlrp3-ici--qa-3", "work_id": "nlrp3-ici", "qa_index": 3, "question": "What does the human GSE180045 analysis contribute?", "answer": "Public human PBMC single-cell data show supportive NLRP3/IL1B patterns in monocytes/neutrophils associated with ICI use/myocarditis. These are associations, not a human MCC950 intervention or efficacy-validation cohort.", "answer_url": "https://drgezhang.com/papers/nlrp3-ici.html#qa-3", "question_source": "data/deep_geo/nlrp3-ici.json#/qa/2/question", "answer_source": "data/deep_geo/nlrp3-ici.json#/qa/2/answer", "answer_sha256": "75d25aee963ceaa3bc01b5f588f545b8409bf37e86aed9203c801dc9352d9830", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "nlrp3-ici--qa-4", "work_id": "nlrp3-ici", "qa_index": 4, "question": "What did cardiac scRNA-seq show?", "answer": "The analysis described 68,058 cells, 14 clusters and eight immune classes. Anti-PD-1 increased Macrophages1/3, while MCC950 reduced them and increased reparative Macrophages2. Six hearts per sample were pooled; cells are not independent mice.", "answer_url": "https://drgezhang.com/papers/nlrp3-ici.html#qa-4", "question_source": "data/deep_geo/nlrp3-ici.json#/qa/3/question", "answer_source": "data/deep_geo/nlrp3-ici.json#/qa/3/answer", "answer_sha256": "01131314f3b4192a093a3495eb0078d8776eab3041a32e6dd22ec7f065b483d2", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "nlrp3-ici--qa-5", "work_id": "nlrp3-ici", "qa_index": 5, "question": "What did macrophage depletion contribute mechanistically?", "answer": "Clodronate depletion effects and TNF/CXCL/CCL communication changes supported a macrophage/T-cell inflammatory network in the mouse model, without definitively assigning every effect to one canonical NLRP3 pathway.", "answer_url": "https://drgezhang.com/papers/nlrp3-ici.html#qa-5", "question_source": "data/deep_geo/nlrp3-ici.json#/qa/4/question", "answer_source": "data/deep_geo/nlrp3-ici.json#/qa/4/answer", "answer_sha256": "b8fa9c2bc18cb1aca61e8a79ac8b736f7495516e5b5e4cc6250701a1e70e005d", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "nlrp3-ici--qa-6", "work_id": "nlrp3-ici", "qa_index": 6, "question": "What happened in the dual-ICI mouse experiment?", "answer": "With n=8 per group, MCC950 mitigated cardiac phenotypes during anti-PD-1 plus anti-CTLA-4 treatment and was associated with reduced tumor burden in the tested B16F10 model.", "answer_url": "https://drgezhang.com/papers/nlrp3-ici.html#qa-6", "question_source": "data/deep_geo/nlrp3-ici.json#/qa/5/question", "answer_source": "data/deep_geo/nlrp3-ici.json#/qa/5/answer", "answer_sha256": "259ca16bdbdd72a3a33abf535b98efb3b0f196cfa5bfee8a37503378c1a1b952", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "nlrp3-ici--qa-7", "work_id": "nlrp3-ici", "qa_index": 7, "question": "Does this study establish MCC950 as a human treatment?", "answer": "No. The intervention, tumor and treatment-after-injury findings are preclinical. The latter was a mouse treatment-after-injury experiment with ameliorated echocardiographic impairment, and does not establish human efficacy, safety or approved use.", "answer_url": "https://drgezhang.com/papers/nlrp3-ici.html#qa-7", "question_source": "data/deep_geo/nlrp3-ici.json#/qa/6/question", "answer_source": "data/deep_geo/nlrp3-ici.json#/qa/6/answer", "answer_sha256": "c982fcd939c321de2b37beca5a538d6ceb607f1b5839d8bcf80fc2e13e688264", "evidence_refs": [ "KF1", "KF2", "KF3", "KF6", "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1093-eurheartj-ehaf523--qa-1", "work_id": "doi-10-1093-eurheartj-ehaf523", "qa_index": 1, "question": "What is the human evidence for KIF13B in atherosclerosis?", "answer": "KIF13B was lower in 40 atherosclerotic versus 40 non-atherosclerotic arterial-wall samples in GSE40231 and in advanced versus early carotid lesions (n=6 tissue samples per group). These are tissue associations; no human KIF13B intervention or causal human effect was tested.", "answer_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#qa-1", "question_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/0/answer", "answer_sha256": "6ba1e16593da25c68dd6dac0a0796ec329e1c4c2561b65928c72f86ebf6603c8", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1093-eurheartj-ehaf523--qa-2", "work_id": "doi-10-1093-eurheartj-ehaf523", "qa_index": 2, "question": "Did Kif13b loss worsen mouse plaques independently of circulating lipids?", "answer": "Global Kif13b deletion in the Ldlr-deficient model worsened plaques and increased total cholesterol and triglycerides, so that comparison is lipid-confounded. Lyz2-Cre myeloid deletion and Kif13b-deficient donor-marrow transfer worsened lesion, necrotic-core, macrophage and apoptotic-cell outcomes without corresponding plasma-lipid changes in their tested mouse models. These approaches are not macrophage-exclusive.", "answer_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#qa-2", "question_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/1/answer", "answer_sha256": "52d4f2ebe9345d846cb02c7ba287c7a540b0150fe1807e41e444a554b23f722a", "evidence_refs": [ "KF2", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1093-eurheartj-ehaf523--qa-3", "work_id": "doi-10-1093-eurheartj-ehaf523", "qa_index": 3, "question": "What do the single-cell experiments show, and how many independent libraries were there?", "answer": "Public datasets and the study-generated aortic comparison implicated macrophage state changes with lower Kif13b. The generated experiment pooled five mice into one library per genotype, not five independent libraries. Its Results describe 20 weeks of Western diet while Figure 3E describes 12 weeks of high-fat diet, so this page does not resolve the duration. Figure 3 uses one GSE155513 library per 8-week and 26-week time point.", "answer_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#qa-3", "question_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/2/answer", "answer_sha256": "099ab862c4fb7a6a9b81101e34db18d0ef33120dd35284a220749c1a2d064ffa", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1093-eurheartj-ehaf523--qa-4", "work_id": "doi-10-1093-eurheartj-ehaf523", "qa_index": 4, "question": "Is MERTK involved in the efferocytosis phenotype, and was it rescued in vivo?", "answer": "Kif13b-deficient BMDMs had lower MERTK protein and impaired efferocytosis. Restoring MERTK in deficient BMDMs improved efferocytosis, supporting functional involvement in cells. This was not a demonstrated in vivo MERTK-restoration therapy or human treatment.", "answer_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#qa-4", "question_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/3/answer", "answer_sha256": "63693c3a7b12d1b0c9d17e3ba4a6c4fb75fbb319b4b41f295503123aa52b0c5d", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1093-eurheartj-ehaf523--qa-5", "work_id": "doi-10-1093-eurheartj-ehaf523", "qa_index": 5, "question": "How certain is the proposed KIF13B–ITCH–CBL–MERTK mechanism?", "answer": "Unchanged Mertk mRNA, faster MERTK protein loss, proteasome-sensitive degradation, increased MERTK ubiquitination, KIF13B–ITCH interaction and ITCH overexpression rescue support a post-translational model. The precise proposed ITCH-mediated CBL ubiquitination/degradation step was not fully demonstrated; alternative routes including CBL self-ubiquitination remain possible.", "answer_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#qa-5", "question_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/4/answer", "answer_sha256": "19763eaf3f427087acb1d56107d321a8dcb32d36976c1f2770dbf28444b7eac5", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1093-eurheartj-ehaf523--qa-6", "work_id": "doi-10-1093-eurheartj-ehaf523", "qa_index": 6, "question": "What did NX-1607 do in cells and mice, and what safety findings were reported?", "answer": "In BMDMs, NX-1607 at 50 nM increased MERTK and 50–100 nM improved efferocytosis. In mice, 5 mg/kg/day was given only for the final 16 weeks of a 20-week Western-diet protocol, reducing plaque-related outcomes without reported lipid change. ALT/AST showed no reported liver-toxicity signal, but white blood cells and lymphocytes declined. This is preclinical intervention, not reversal after 20 completed weeks of established disease.", "answer_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#qa-6", "question_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/5/answer", "answer_sha256": "c47e87046f6c434475cff127f09215937bcd2aba698ce8e27fb294c921c1fc95", "evidence_refs": [ "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1093-eurheartj-ehaf523--qa-7", "work_id": "doi-10-1093-eurheartj-ehaf523", "qa_index": 7, "question": "Has NX-1607 shown clinical benefit for atherosclerosis?", "answer": "No human atherosclerosis treatment efficacy was tested. NCT05107674 is a Phase I advanced-malignancy study, not an atherosclerosis trial; its existence does not establish clinical vascular benefit.", "answer_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#qa-7", "question_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/6/answer", "answer_sha256": "6f6329c82135a4a9f23f837595c29ca919c60b64cbad5b00f994640c0b0c5ada", "evidence_refs": [ "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1093-eurheartj-ehaf523--qa-8", "work_id": "doi-10-1093-eurheartj-ehaf523", "qa_index": 8, "question": "Does NX-1607 prove the endogenous CBL mechanism?", "answer": "No. The article describes NX-1607 as a CBL inhibitor, whereas external authoritative drug-development sources identify it as a CBL-B/CBLB inhibitor. CBL and CBLB are distinct genes. The observed preclinical rescue cannot by itself unambiguously assign the drug effect to the endogenous CBL mechanism proposed in this paper.", "answer_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html#qa-8", "question_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/7/question", "answer_source": "data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/7/answer", "answer_sha256": "747a936e68d3e19b846d3e225fe1a72715edb06b4cc5c5669cc8d5a102058bfc", "evidence_refs": [ "KF6", "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-tox-24284--qa-1", "work_id": "doi-10-1002-tox-24284", "qa_index": 1, "question": "What model did the IPPS study select?", "answer": "A 13-gene Lasso-plus-SuperPC model was selected from 101 candidate combinations. The five GEO evaluation cohorts also contributed to gene screening and algorithm selection.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.html#qa-1", "question_source": "data/deep_geo/doi-10-1002-tox-24284.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1002-tox-24284.json#/qa/0/answer", "answer_sha256": "ffaaf9a262b31a119b5789074da9d3ca1d117e9c89b3290b47aebd42041879bb", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-tox-24284--qa-2", "work_id": "doi-10-1002-tox-24284", "qa_index": 2, "question": "What survival performance can be quoted without resolving the GSE31210 discrepancy?", "answer": "The text and Figure 2H agree on TCGA AUCs of 0.80, 0.79 and 0.78 at 1, 3 and 5 years. They describe the development cohort and must not be presented as independent external performance.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.html#qa-2", "question_source": "data/deep_geo/doi-10-1002-tox-24284.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1002-tox-24284.json#/qa/1/answer", "answer_sha256": "9af38cb86c8611a157374cf24caa1be33c9ddb90cd56458aad0e972a709850d3", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-tox-24284--qa-3", "work_id": "doi-10-1002-tox-24284", "qa_index": 3, "question": "Were the five GEO cohorts untouched independent test sets?", "answer": "No. Results 3.1 uses the six TCGA/GEO cohorts for survival-based gene screening, and Results 3.2 selects the final algorithm using the mean C-index across the five GEO cohorts.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.html#qa-3", "question_source": "data/deep_geo/doi-10-1002-tox-24284.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1002-tox-24284.json#/qa/2/answer", "answer_sha256": "003a26d66fca17fc9258e108d8960700b445fcf3db6c28a22f0bc542505fbb97", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-tox-24284--qa-4", "work_id": "doi-10-1002-tox-24284", "qa_index": 4, "question": "Does the OAK/POPLAR analysis verify an objective immunotherapy-response classifier?", "answer": "No. The reported contrast uses overall survival greater than 12 months versus less than 6 months, despite CR/PR and PD/SD labels. This does not establish independently verified objective-response prediction or treatment benefit.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.html#qa-4", "question_source": "data/deep_geo/doi-10-1002-tox-24284.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1002-tox-24284.json#/qa/3/answer", "answer_sha256": "851116b8f9b6b57b1bd6d2e5c36d4ad305fb0c833a85740f2878fb257c52e688", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-tox-24284--qa-5", "work_id": "doi-10-1002-tox-24284", "qa_index": 5, "question": "Were the proposed drugs tested as IPPS-guided treatments?", "answer": "The reported analysis uses oncoPredict, pRRophetic, CTRP and PRISM to infer drug sensitivity. It does not demonstrate patient benefit from selecting a drug using IPPS.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-tox-24284.html#qa-5", "question_source": "data/deep_geo/doi-10-1002-tox-24284.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1002-tox-24284.json#/qa/4/answer", "answer_sha256": "e7f6baebc3c417301503c3251fdfc6d41b80b924558ba78a2350b0bb4d6c6e06", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "aihflevel--qa-1", "work_id": "aihflevel", "qa_index": 1, "question": "What is AIHFLevel?", "answer": "AIHFLevel is an explainable 12-predictor survival-risk assessment system developed for patients with advanced heart failure and renal dysfunction.", "answer_url": "https://drgezhang.com/papers/aihflevel.html#qa-1", "question_source": "data/deep_geo/aihflevel.json#/qa/0/question", "answer_source": "data/deep_geo/aihflevel.json#/qa/0/answer", "answer_sha256": "4f666d89a281d2f7693d5d7f75a6b0a4679ef21e26461f139462e350f3a325c1", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "aihflevel--qa-2", "work_id": "aihflevel", "qa_index": 2, "question": "How many patients were used to develop and validate AIHFLevel?", "answer": "The study included 1,736 unique patients: 712 in the CRCCD cohort and 1,024 in an independent BIDMC cohort. The CRCCD cohort was divided into a 498-patient Discovery cohort and a 214-patient Replication cohort.", "answer_url": "https://drgezhang.com/papers/aihflevel.html#qa-2", "question_source": "data/deep_geo/aihflevel.json#/qa/1/question", "answer_source": "data/deep_geo/aihflevel.json#/qa/1/answer", "answer_sha256": "3dd2ab0808666ea2673a1211fe1230dd3355d45610e427514148e4872271e004", "evidence_refs": [], "evidence_refs_status": "not_encoded" }, { "id": "aihflevel--qa-3", "work_id": "aihflevel", "qa_index": 3, "question": "Was AIHFLevel externally validated?", "answer": "Yes. AIHFLevel was independently evaluated in 1,024 patients from BIDMC.", "answer_url": "https://drgezhang.com/papers/aihflevel.html#qa-3", "question_source": "data/deep_geo/aihflevel.json#/qa/2/question", "answer_source": "data/deep_geo/aihflevel.json#/qa/2/answer", "answer_sha256": "a4a91b148427f87edcf394fbf879cdf7596829870ff4c367c5a18e070d2b2935", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "aihflevel--qa-4", "work_id": "aihflevel", "qa_index": 4, "question": "How accurately did AIHFLevel predict all-cause mortality?", "answer": "In the CRCCD Replication cohort, AUCs at 6, 12, 24 and 30 months were 0.902, 0.932, 0.932 and 0.903. In the independent BIDMC cohort, AUCs at 1, 2, 3 and 4 years were 0.788, 0.816, 0.824 and 0.846.", "answer_url": "https://drgezhang.com/papers/aihflevel.html#qa-4", "question_source": "data/deep_geo/aihflevel.json#/qa/3/question", "answer_source": "data/deep_geo/aihflevel.json#/qa/3/answer", "answer_sha256": "fd5c6932bc2b1b4fd042d35da1de025896625ccedf387cecc43c2d6b1992802b", "evidence_refs": [ "KF2", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "aihflevel--qa-5", "work_id": "aihflevel", "qa_index": 5, "question": "How was AIHFLevel developed?", "answer": "Ninety-three EHR variables were initially evaluated, 46 candidate survival features entered the modeling framework, and 132 modeling schemes were compared. The selected strategy combined Surv.gbm and Surv.Xgboost with a Filter & Wrapper Hybrid Method.", "answer_url": "https://drgezhang.com/papers/aihflevel.html#qa-5", "question_source": "data/deep_geo/aihflevel.json#/qa/4/question", "answer_source": "data/deep_geo/aihflevel.json#/qa/4/answer", "answer_sha256": "a25b6c736ccb83500a224ad36ad16ebfa2dd6e4bf837b561a13e87dc362bbdda", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "aihflevel--qa-6", "work_id": "aihflevel", "qa_index": 6, "question": "Which clinical variables are included in AIHFLevel?", "answer": "The 12 predictors are age, arrhythmia, coronary artery disease, CKD stage, lymphocyte percentage, MCHC, eGFR, serum creatinine, total bilirubin, cardiac troponin I, left ventricular ejection fraction and stroke volume.", "answer_url": "https://drgezhang.com/papers/aihflevel.html#qa-6", "question_source": "data/deep_geo/aihflevel.json#/qa/5/question", "answer_source": "data/deep_geo/aihflevel.json#/qa/5/answer", "answer_sha256": "e11803858edbeef16e83f342fe82d4fa40a4c47125ffd3ccaf1bc61266659e3d", "evidence_refs": [], "evidence_refs_status": "not_encoded" }, { "id": "aihflevel--qa-7", "work_id": "aihflevel", "qa_index": 7, "question": "How does AIHFLevel stratify prognosis?", "answer": "The conditional inference survival tree defines low risk at AIHFLevel <= 0.435, intermediate risk above 0.435 and up to 1.548, and high risk above 1.548.", "answer_url": "https://drgezhang.com/papers/aihflevel.html#qa-7", "question_source": "data/deep_geo/aihflevel.json#/qa/6/question", "answer_source": "data/deep_geo/aihflevel.json#/qa/6/answer", "answer_sha256": "37d490c1466901547b7e9b0d43e5b8433f319550d66ad935fdb49665521ff677", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "aihflevel--qa-8", "work_id": "aihflevel", "qa_index": 8, "question": "Does the study show that AIHFLevel-guided treatment improves patient outcomes?", "answer": "No. The study establishes prognostic performance in retrospective cohorts. Prospective multicenter validation and randomized studies are still required to determine whether AIHFLevel-guided management improves clinical outcomes.", "answer_url": "https://drgezhang.com/papers/aihflevel.html#qa-8", "question_source": "data/deep_geo/aihflevel.json#/qa/7/question", "answer_source": "data/deep_geo/aihflevel.json#/qa/7/answer", "answer_sha256": "39d1d0a87b5f003f7dfa4d8244db0fa98030d9b91795f15ba93888a206b8641f", "evidence_refs": [], "evidence_refs_status": "not_encoded" }, { "id": "doi-10-18632-aging-205564--qa-1", "work_id": "doi-10-18632-aging-205564", "qa_index": 1, "question": "What samples and modeling split were reported?", "answer": "The article reported 606 human expression samples from 10 datasets; GSE87466 was the model-construction meta-cohort with 87 UC and 21 control expression samples and a random 7:3 split. Expression-sample counts are not a cross-cohort total of unique patients. Exact training/testing counts are not inferred from the split, and case–control classification is not prediction of future disease onset.", "answer_url": "https://drgezhang.com/papers/doi-10-18632-aging-205564.html#qa-1", "question_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/0/answer", "answer_sha256": "e285f227a241d7a089472662f2b8500dc3beb2f10b46e74459d9eea522ff665f", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18632-aging-205564--qa-2", "work_id": "doi-10-18632-aging-205564", "qa_index": 2, "question": "Is the reported classifier based on 12 or 14 genes?", "answer": "The study considered 746 candidate genes and eight learners, applied RF-RFE and named a final 12-gene UCRG panel for a backpropagation neural-network classifier. The Fig. 3E legend separately states that error was minimized with 14 variables. That statement does not silently replace the named final 12-gene panel with a 14-gene model, and the panel is not proof that all 12 genes are causal drivers.", "answer_url": "https://drgezhang.com/papers/doi-10-18632-aging-205564.html#qa-2", "question_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/1/answer", "answer_sha256": "211fe0d791dcce7d3eae449594cadb3007bed3af68f41b2763fd6d35d27c6c6a", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18632-aging-205564--qa-3", "work_id": "doi-10-18632-aging-205564", "qa_index": 3, "question": "What external discrimination was reported?", "answer": "Results reported external UC-versus-control AUCs of 0.930 for GSE47908, 0.942 for GSE59071, 0.934 for GSE75214, 0.988 for GSE92415 and 1.000 for GSE14580. These are article-reported external bulk-expression discrimination results, not independent prospective clinical effectiveness. No individually unresolved confidence intervals or clinical thresholds are supplied, and AUC 1.000 does not mean universally perfect diagnosis.", "answer_url": "https://drgezhang.com/papers/doi-10-18632-aging-205564.html#qa-3", "question_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/2/answer", "answer_sha256": "06215b6f1be6764a612d115e1936d625518193da266da40fa797820d26a81915", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18632-aging-205564--qa-4", "work_id": "doi-10-18632-aging-205564", "qa_index": 4, "question": "Are the classifier, UCRScore and DNB interchangeable?", "answer": "UCRScore used PCoA-related expression information, while DNB analysis showed a higher critical signal in the inactive group. The classifier, UCRScore and DNB are different analytical layers. An executable score is not reconstructed from the incompletely rendered formula, and group comparisons do not establish longitudinal prediction of an individual disease transition.", "answer_url": "https://drgezhang.com/papers/doi-10-18632-aging-205564.html#qa-4", "question_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/3/answer", "answer_sha256": "b7b8ea0568203fd1c491217bff74b287ef34f41b05502a57b0e0cabcc3090885", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18632-aging-205564--qa-5", "work_id": "doi-10-18632-aging-205564", "qa_index": 5, "question": "Were the nominated compounds experimentally shown to treat UC?", "answer": "CMap/eXtreme-Sum signature matching nominated five candidate compounds. These are computational drug-signature hypotheses. Clinical drug efficacy was not established in this study, and no doses or treatment recommendations are provided.", "answer_url": "https://drgezhang.com/papers/doi-10-18632-aging-205564.html#qa-5", "question_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/4/answer", "answer_sha256": "1991afa15ae2019b1b41203f99d7601b5f64133da886f5bd1785f3d0ce445e6f", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18632-aging-205564--qa-6", "work_id": "doi-10-18632-aging-205564", "qa_index": 6, "question": "Can the single-cell extension be verified from the cited accession?", "answer": "The article described three single-cell samples, 10,101 cells and seven populations and cited GSE182272; the source review found that this accession describes mouse tissue-resident memory CD8+ T-cell RNA-seq with CAPvsColl and LCMV/P14 T-cell experiments, not direct confirmation of the described UC extension. The article report and GEO record remain unmatched. No replacement accession, specific cause of the mismatch or research-misconduct inference is established, and this is not verified human or mouse UC single-cell validation.", "answer_url": "https://drgezhang.com/papers/doi-10-18632-aging-205564.html#qa-6", "question_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-18632-aging-205564.json#/qa/5/answer", "answer_sha256": "5b2787fc688b1fb91ed04ba95e80c6b3eec5cf8d50e1b0819beca97013ba6d05", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1200-po-24-00089--qa-1", "work_id": "doi-10-1200-po-24-00089", "qa_index": 1, "question": "What population was RAP-AIscore developed for?", "answer": "Patients with rectal cancer undergoing robot-assisted proctectomy; the study modeled postoperative overall survival retrospectively.", "answer_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#qa-1", "question_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/0/answer", "answer_sha256": "3cb0428cec8ca73a086aa255d1274ce78abedac41a4e0df2236c66f0798e72d2", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1200-po-24-00089--qa-2", "work_id": "doi-10-1200-po-24-00089", "qa_index": 2, "question": "How many independent patients and cohorts were studied?", "answer": "There were 506 unique patients: 384 in NSCVRCS Meta and 122 in independent SYEMH. NSCVRCS Discovery n=268 and Replication n=116 are subsets of Meta, not additional patients.", "answer_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#qa-2", "question_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/1/answer", "answer_sha256": "ef7c1109b36f6c690dc150124659d52d09da6656dce952fa0fe8cffea71c39fd", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1200-po-24-00089--qa-3", "work_id": "doi-10-1200-po-24-00089", "qa_index": 3, "question": "How were 132 modeling schemes compared?", "answer": "The study systematically compared candidate survival-modeling schemes and selected Surv.coxboost + Surv.aorsf, which achieved the highest average C-index, 0.833.", "answer_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#qa-3", "question_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/2/answer", "answer_sha256": "f730f1bbcbe59ec5d05e3fd6cc5fdeb21b72c6b35a26bdcd6b82a0cdd0dc6b3b", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1200-po-24-00089--qa-4", "work_id": "doi-10-1200-po-24-00089", "qa_index": 4, "question": "What performance was observed internally?", "answer": "At 12/36/60/72 months, AUCs were 0.851/0.849/0.902/0.915 in Replication, 0.911/0.924/0.931/0.948 in Meta, and 0.927/0.960/0.949/0.962 in Discovery. These are retrospective time-dependent discrimination results.", "answer_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#qa-4", "question_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/3/answer", "answer_sha256": "86cf80aef37d12ca897c514fb8b8ce1293028745de83ac0010433c6ec54c5894", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1200-po-24-00089--qa-5", "work_id": "doi-10-1200-po-24-00089", "qa_index": 5, "question": "What happened in independent SYEMH validation?", "answer": "In the independent retrospective cohort, 1-/2-/3-year AUCs were 0.587/0.754/0.810. Early discrimination was modest. High-versus-low survival differed at P < 0.0001 and three-state discrimination at P < 0.001.", "answer_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#qa-5", "question_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/4/answer", "answer_sha256": "846b5645e45b424dae9891fc7893260fc9eb3b802612c97f2878356c96182cdb", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1200-po-24-00089--qa-6", "work_id": "doi-10-1200-po-24-00089", "qa_index": 6, "question": "Does RAP-AIscore have proven prospective clinical benefit?", "answer": "No. The retrospective model-development, internal-validation and external-evaluation findings do not establish prospective clinical utility or survival benefit from model-guided care.", "answer_url": "https://drgezhang.com/papers/doi-10-1200-po-24-00089.html#qa-6", "question_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1200-po-24-00089.json#/qa/5/answer", "answer_sha256": "f2e9cb34c52c0cd5142aa85489689bfdffedcaf42eaf62ed8d91b0fdc8721aa2", "evidence_refs": [ "KF1", "KF3", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s10020-024-00963-z--qa-1", "work_id": "doi-10-1186-s10020-024-00963-z", "qa_index": 1, "question": "How many people and cells were represented in the single-cell analysis?", "answer": "The article reports three PAH and six control donor samples, initially containing 31,444 cells, with 28,906 retained after quality control. These are sample and cell counts, not interchangeable participant totals.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#qa-1", "question_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/0/answer", "answer_sha256": "6204802bf3610e9bce204bd00c730b988119b4ab3d03686605e6063f346ff5aa", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s10020-024-00963-z--qa-2", "work_id": "doi-10-1186-s10020-024-00963-z", "qa_index": 2, "question": "Does pseudotime prove that endothelial cells became mesenchymal cells?", "answer": "No. The ordering of 3,165 endothelial cells is inferred from cross-sectional expression. EndMT-related gene programs support a biological hypothesis, but direct lineage tracing or causal perturbation would be needed to establish cell conversion.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#qa-2", "question_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/1/answer", "answer_sha256": "9fcbd6628068c82f3e451b414df65c00757b63a48dd0196a213f9aa2f8557390", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s10020-024-00963-z--qa-3", "work_id": "doi-10-1186-s10020-024-00963-z", "qa_index": 3, "question": "What genes form the final PETS score?", "answer": "The reported score is 2.6926723 × RARRES2 + 0.7410611 × TC2N expression. It was selected from a broader computationally nominated candidate set.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#qa-3", "question_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/2/answer", "answer_sha256": "89733167ba257cc646212b256b4d8e06a0d6cba9c1aedcdfcb1bb5dc0d22db58", "evidence_refs": [ "KF3", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s10020-024-00963-z--qa-4", "work_id": "doi-10-1186-s10020-024-00963-z", "qa_index": 4, "question": "What does the reported model performance mean?", "answer": "In the GSE117261 internal testing subset, Table S7 reports glmNet accuracy 0.8333 and C-index 0.8908. The same subset was used to compare the nine algorithms and select the preferred model, so the reported performance may be optimistic. These are retrospective classification estimates, not prospective clinical accuracy or treatment benefit.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#qa-4", "question_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/3/answer", "answer_sha256": "00326f82b26988680125c1727df0c98d99128e2d88d52d7ab56992665269676e", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s10020-024-00963-z--qa-5", "work_id": "doi-10-1186-s10020-024-00963-z", "qa_index": 5, "question": "Was PETS externally validated in an independent clinical cohort?", "answer": "No independent external clinical validation is established by the reported 7:3 split. Discovery and testing came from GSE117261. The targeted expression experiments provide a different kind of evidence and do not substitute for clinical validation.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#qa-5", "question_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/4/answer", "answer_sha256": "699ded5067598b7d93370326c9fc6b851816242a6708e40fa0d681973ce249e6", "evidence_refs": [ "KF4", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s10020-024-00963-z--qa-6", "work_id": "doi-10-1186-s10020-024-00963-z", "qa_index": 6, "question": "Do the experiments demonstrate a therapeutic mechanism?", "answer": "No. The reported experiments assess selected expression responses to hypoxia. They do not demonstrate that perturbing a candidate gene reverses EndMT or improves PAH outcomes.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#qa-6", "question_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/5/answer", "answer_sha256": "1146b2b98bce29efbc42538230c1b1968b3eb52b5d2ee1b182e455a66c94f831", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1186-s10020-024-00963-z--qa-7", "work_id": "doi-10-1186-s10020-024-00963-z", "qa_index": 7, "question": "Are all ancillary gene counts internally consistent?", "answer": "No. The main text reports 602 EC3 marker genes, whereas the retrieved Table S4 contains 604 unique gene rows. This page preserves the discrepancy and does not use that marker count as a confirmed scale metric.", "answer_url": "https://drgezhang.com/papers/doi-10-1186-s10020-024-00963-z.html#qa-7", "question_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1186-s10020-024-00963-z.json#/qa/6/answer", "answer_sha256": "400717a32bb4edb0d2a0b405a0fbfdaa9541ca8fb15eab2fb93b7bc2433a1f1c", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-clc-70019--qa-1", "work_id": "doi-10-1002-clc-70019", "qa_index": 1, "question": "Which part of the paper is summarized here?", "answer": "Only the internally consistent depression analysis. The full publication also analyzes anxiety, but its unresolved count and effect-estimate conflicts are explicitly excluded from this page's supported findings.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-clc-70019.html#qa-1", "question_source": "data/deep_geo/doi-10-1002-clc-70019.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1002-clc-70019.json#/qa/0/answer", "answer_sha256": "6051c981118255704ea530a6766eb9972d237c8b761dbdecb50622e59ba9de94", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-clc-70019--qa-2", "work_id": "doi-10-1002-clc-70019", "qa_index": 2, "question": "How were depressive symptoms defined?", "answer": "PHQ-9 score ≥10. The paper reports 1,206 such participants among 13,028 adults in the analytic sample.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-clc-70019.html#qa-2", "question_source": "data/deep_geo/doi-10-1002-clc-70019.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1002-clc-70019.json#/qa/1/answer", "answer_sha256": "0e9adb102b92bedb7ad7ad3d90f92be005ac60791f37fd77219aa45a2a960b0b", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-clc-70019--qa-3", "work_id": "doi-10-1002-clc-70019", "qa_index": 3, "question": "What is the association per 10 LE8 points?", "answer": "The adjusted, survey-weighted depression OR is 0.61 (95% CI 0.58–0.65), P<0.001. It is a prevalence-odds association, not a demonstrated preventive effect.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-clc-70019.html#qa-3", "question_source": "data/deep_geo/doi-10-1002-clc-70019.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1002-clc-70019.json#/qa/2/answer", "answer_sha256": "12f0a638d340c1c7329a6c84043ed56c7e390c8f0e8cd159ed119cadbdb13e31", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-clc-70019--qa-4", "work_id": "doi-10-1002-clc-70019", "qa_index": 4, "question": "What did the category and subscore analyses add?", "answer": "Relative to low LE8, moderate and high groups had ORs 0.36 and 0.08. Per 10 subscore points, health-behavior and health-factor ORs were 0.70 and 0.87. The stated confidence intervals and covariate scope remain essential.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-clc-70019.html#qa-4", "question_source": "data/deep_geo/doi-10-1002-clc-70019.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1002-clc-70019.json#/qa/3/answer", "answer_sha256": "b2a1a99a81e58e3ae997f63287fdb09ad8ac5b9d2fd695bfc2db8c83f83be885", "evidence_refs": [ "KF3", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-clc-70019--qa-5", "work_id": "doi-10-1002-clc-70019", "qa_index": 5, "question": "Does this show that improving cardiovascular health treats depression?", "answer": "No. Concurrent cross-sectional measurements cannot resolve temporal direction, reverse causation or residual confounding. No LE8-targeted treatment was tested.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-clc-70019.html#qa-5", "question_source": "data/deep_geo/doi-10-1002-clc-70019.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1002-clc-70019.json#/qa/4/answer", "answer_sha256": "81fab5a4e3ac1001e5dc45789ac2c7068de9a9c97d7f79e5ca78eb115714b8b2", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jtemb-2024-127543--qa-1", "work_id": "doi-10-1016-j-jtemb-2024-127543", "qa_index": 1, "question": "What population and outcome were actually analyzed?", "answer": "The analytic sample comprised 18,247 NHANES 2005–2018 adults aged 20–60 years; 1,753 had PHQ-9 scores of at least 10. These are unweighted counts. The endpoint was a questionnaire threshold for recent symptoms, not an independently adjudicated diagnosis or new-onset depression.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#qa-1", "question_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/0/answer", "answer_sha256": "94137ac34217bb41de38984001c5819d7a495f42aba0d9e60b0242213ef4a856", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jtemb-2024-127543--qa-2", "work_id": "doi-10-1016-j-jtemb-2024-127543", "qa_index": 2, "question": "Was magnesium measured directly?", "answer": "No direct serum-magnesium comparison was available in this study. MDS combined diuretic use, proton pump inhibitor use, renal-function categories and heavy drinking into a 0–5 proxy score; the reported association does not validate the score against a biochemical deficiency measure.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#qa-2", "question_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/1/answer", "answer_sha256": "001cb51abf68d843c47594dba683258b9aebd940fdaff8d94f9b9166a2596670", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jtemb-2024-127543--qa-3", "work_id": "doi-10-1016-j-jtemb-2024-127543", "qa_index": 3, "question": "What was the fully adjusted per-point association?", "answer": "Survey-weighted Model 3 reported OR 1.15 per MDS point, with 95% CI 1.04–1.26 and P=0.0100. Adjustment included demographics, BMI, smoking, diabetes and dietary energy, calcium and magnesium. This is a concurrent prevalence-odds association, not prospective risk or a causal effect.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#qa-3", "question_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/2/answer", "answer_sha256": "eee2f9ed1730c82c7c7ccb12a324832d9faf6066ef074b042695607c470e6534", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jtemb-2024-127543--qa-4", "work_id": "doi-10-1016-j-jtemb-2024-127543", "qa_index": 4, "question": "Did all MDS categories show the same evidence?", "answer": "No. Compared with MDS 0, Model 3 estimates were 1.03 (0.87–1.21), 1.41 (1.12–1.78) and 1.58 (1.06–2.35) for scores 1, 2 and at least 3. The score-1 interval crosses 1; the highest category included only 368 participants. These categories do not establish a clinical action threshold.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#qa-4", "question_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/3/answer", "answer_sha256": "eea6ea1c79b95a44d2960aa38e51688a53e5809f7b0b34290424d6185d4f6c40", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jtemb-2024-127543--qa-5", "work_id": "doi-10-1016-j-jtemb-2024-127543", "qa_index": 5, "question": "Does the PPI component result show that treatment causes depression?", "answer": "No. The PPI-use estimate was OR 2.24 (95% CI 1.78–2.80) in Model 3, but medication indications, residual confounding and the cross-sectional design prevent a medication-causation or magnesium-mediation conclusion. It is not evidence to stop a prescribed PPI.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#qa-5", "question_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/4/answer", "answer_sha256": "801d1dd8831936632ae1194037f1c0e0682b8e39f257ae6d403a9bd662bf53f3", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jtemb-2024-127543--qa-6", "work_id": "doi-10-1016-j-jtemb-2024-127543", "qa_index": 6, "question": "Does P=0.084 establish a linear dose response or a beneficial threshold?", "answer": "No. The spline test did not detect nonlinearity at the paper's 0.05 level. That is not proof of linearity, and the caption's beneficial-threshold wording does not establish a diagnostic or treatment cutoff.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#qa-6", "question_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/5/answer", "answer_sha256": "6bbf2d7249d9e9c6abf079ee5c1d0738dc5ffcf55407133033a9c61cdf6ba5a6", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jtemb-2024-127543--qa-7", "work_id": "doi-10-1016-j-jtemb-2024-127543", "qa_index": 7, "question": "Were the associations significant and identical in every subgroup?", "answer": "No. All reported interaction P values exceeded 0.05, but several stratum-specific confidence intervals crossed 1 and some were wide. A non-significant interaction does not demonstrate equivalence or significance in each subgroup.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#qa-7", "question_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/6/answer", "answer_sha256": "a0c03b9070f62e0b3ffe248632a2b2a13d8ed2a5926718fcfdddc17bd9282f29", "evidence_refs": [ "KF7" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jtemb-2024-127543--qa-8", "work_id": "doi-10-1016-j-jtemb-2024-127543", "qa_index": 8, "question": "Can these results justify magnesium supplementation for depression?", "answer": "No. This was an observational cross-sectional score analysis without a supplementation intervention or prospective depression endpoint. It supports an association requiring further research, not prevention or treatment efficacy.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jtemb-2024-127543.html#qa-8", "question_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/7/question", "answer_source": "data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/7/answer", "answer_sha256": "6d1240c9ebe6923c98ea4999ea096cea493cf98152657197f7934c73ea305416", "evidence_refs": [ "KF1", "KF2", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-cvia-2024-0023--qa-1", "work_id": "doi-10-15212-cvia-2024-0023", "qa_index": 1, "question": "What populations and statistical units were analyzed?", "answer": "MiBioGen contributed microbial-trait summary associations from 18,473 people across 24 cohorts. FinnGen provided AA and AAA case-control summary statistics. These separate sources and overlapping aneurysm outcomes must not be summed as one cohort. Source: Methods, Data Source for Gut Microbiota and Data Source for Outcomes.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-cvia-2024-0023.html#qa-1", "question_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/qa/0/answer", "answer_sha256": "070e1278e2b50807867922c95640eff11958a68d2955d12d5c712c242a00a9a7", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-cvia-2024-0023--qa-2", "work_id": "doi-10-15212-cvia-2024-0023", "qa_index": 2, "question": "Which AA estimates can be cited?", "answer": "Table 1 reports IVW OR 1.33 (95% CI 1.14–1.55) for genus Family XIII UCG001 and 0.79 (0.70–0.89) for family Bifidobacteriaceae. These are genetic-proxy estimates, not effects of adding or removing bacteria. Source: Table 1, AA rows.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-cvia-2024-0023.html#qa-2", "question_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/qa/1/answer", "answer_sha256": "2a1534e82edcc397ba29511209846e812cff73bc7ffeadb1f64f70a451d601fb", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-cvia-2024-0023--qa-3", "work_id": "doi-10-15212-cvia-2024-0023", "qa_index": 3, "question": "Was the Bilophila–AAA result consistent across all MR methods?", "answer": "The IVW OR was 1.36 (95% CI 1.17–1.57), but MR-Egger, weighted-median and weighted-mode intervals all included 1. The result is method-dependent rather than unanimously confirmed. Source: Table 1, AAA / Genus Bilophila rows.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-cvia-2024-0023.html#qa-3", "question_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/qa/2/answer", "answer_sha256": "981f61539fdee5388a8c37bce7f4b7b7f3e927052d5f5b76c1275e1f9626e8d8", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-cvia-2024-0023--qa-4", "work_id": "doi-10-15212-cvia-2024-0023", "qa_index": 4, "question": "Does this demonstrate that microbiome treatment prevents aneurysm?", "answer": "No. The study analyzed genetic instruments and summary case-control data, without testing treatment or prevention. Interpretation depends on MR relevance, independence and exclusion-restriction assumptions. Source: Methods, Statistical Analysis and Sensitivity Analysis; Table 1.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-cvia-2024-0023.html#qa-4", "question_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/qa/3/answer", "answer_sha256": "9cdda94de60866b3d84044e1df3ecc98cea8b29743857e990aaa503d7d6fefda", "evidence_refs": [ "KF1", "KF2", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-15212-cvia-2024-0023--qa-5", "work_id": "doi-10-15212-cvia-2024-0023", "qa_index": 5, "question": "Why are TAA findings and strong robustness claims omitted?", "answer": "Methods describe the TAA endpoint using thoracoabdominal outcomes, while the title and subtype labels say thoracic. Methods also report 196 taxa but the Results category counts sum to 195. Supplements and equation/figure assets were not retrievable for independent checking. These discrepancies remain open; no TAA estimate or verified absence of pleiotropy is asserted. Source: Methods, Data Source for Outcomes and Sensitivity Analysis; Results, Selection of Instrumental Variables for Gut Microbiomes.", "answer_url": "https://drgezhang.com/papers/doi-10-15212-cvia-2024-0023.html#qa-5", "question_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-15212-cvia-2024-0023.json#/qa/4/answer", "answer_sha256": "c3636b41c7243ef6c488b696685f2913248a85a35067475e314297de36c8db3a", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-18408--qa-1", "work_id": "doi-10-1111-jcmm-18408", "qa_index": 1, "question": "Which pathological stages were compared in the single-cell analysis?", "answer": "Four AIS, eight MIA and nine IAC specimen profiles were described across two public scRNA-seq series. They are specimens at different pathological stages, not serial samples tracking the same person.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#qa-1", "question_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/0/answer", "answer_sha256": "2abdd0274f134d0a8c5dbe1c6876ad0a378e222858fdb31e89a7535945fb42e4", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-18408--qa-2", "work_id": "doi-10-1111-jcmm-18408", "qa_index": 2, "question": "What is the nine-gene LPAS model?", "answer": "LPAS is a retrospective expression-based LUAD survival score containing nine selected genes, including PSMB1. It was developed from TCGA data and evaluated in five additional GEO survival series.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#qa-2", "question_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/1/answer", "answer_sha256": "4638c7224a06f66bc266194cc08ca4696e1483760361b1f1446e895bd953a312", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-18408--qa-3", "work_id": "doi-10-1111-jcmm-18408", "qa_index": 3, "question": "Was LPAS externally evaluated?", "answer": "Five additional GEO LUAD survival datasets were evaluated, with differing reported AUCs and follow-up horizons. This is retrospective external dataset evaluation, not a prospective treatment-impact trial.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#qa-3", "question_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/2/answer", "answer_sha256": "ccbb27b64f70e7c3d1cc1069f6edf10f4b3a99bc3fa22c232627c1576e3c1e31", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-18408--qa-4", "work_id": "doi-10-1111-jcmm-18408", "qa_index": 4, "question": "Does inferred cluster progression prove actual tumor-cell fate transitions?", "answer": "No. InferCNV, changing cluster frequencies and pseudotime reconstruct possible molecular patterns from cross-sectional data; they do not directly track cells through AIS, MIA and IAC.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#qa-4", "question_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/3/answer", "answer_sha256": "8f67ef31b584cd0c7a8583d213367b8140fa2aab1810c3d359e507e673b46358", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-18408--qa-5", "work_id": "doi-10-1111-jcmm-18408", "qa_index": 5, "question": "Can low LPAS identify patients who will benefit from immunotherapy?", "answer": "The article reports in-silico immune scores and SubMap/TIDE comparisons plus treatment-cohort associations, but no prospective LPAS-guided treatment study establishes patient-level clinical benefit.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#qa-5", "question_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/4/answer", "answer_sha256": "a84a3264aaa8432ac2a72752b171636900a976a42e0c2c367daece7bb67ed077", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-18408--qa-6", "work_id": "doi-10-1111-jcmm-18408", "qa_index": 6, "question": "What did the PSMB1 experiments establish?", "answer": "PSMB1 siRNA reduced cell growth, colony formation and motility-related outcomes in A549/H1299 culture experiments. It does not establish in-vivo therapeutic efficacy or a validated drug target in patients.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-18408.html#qa-6", "question_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-18408.json#/qa/5/answer", "answer_sha256": "5a73aa1b0696c964915b19cdbb789a3aae2de2a95c13990be60d313259ec5c76", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s10238-024-01439-4--qa-1", "work_id": "doi-10-1007-s10238-024-01439-4", "qa_index": 1, "question": "How many genes are in ERAS?", "answer": "The signature contains 10 genes selected from 22 survival-associated candidates.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-024-01439-4.html#qa-1", "question_source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/qa/0/answer", "answer_sha256": "5b47cdc14224cc2381f6aa04cafe7bcb0bb2fe29ed32e6876b7e311f84cc717b", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s10238-024-01439-4--qa-2", "work_id": "doi-10-1007-s10238-024-01439-4", "qa_index": 2, "question": "What survival discrimination was reported for the ERAS nomogram?", "answer": "The nomogram AUCs were 0.740, 0.754 and 0.754 at 1, 3 and 5 years in the reported retrospective evaluation.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-024-01439-4.html#qa-2", "question_source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/qa/1/answer", "answer_sha256": "7da51bc75b818c2d617f677ee5626f4c5ea4cefedc81582a52d3a5b5cfdafc3f", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s10238-024-01439-4--qa-3", "work_id": "doi-10-1007-s10238-024-01439-4", "qa_index": 3, "question": "What experimental expression check accompanied ERAS?", "answer": "qPCR compared SERPINH1 and GPR37 in 10 paired LUAD tumor and adjacent tissue samples.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-024-01439-4.html#qa-3", "question_source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/qa/2/answer", "answer_sha256": "e1ac1a52326f8ef75b78d17c63a93860164af63378d5798b63f8821098bd166f", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s10238-024-01439-4--qa-4", "work_id": "doi-10-1007-s10238-024-01439-4", "qa_index": 4, "question": "Does ERAS establish benefit from a selected immunotherapy or chemotherapy?", "answer": "No. The reported survival modeling and two-gene expression experiment do not test whether choosing treatment with ERAS improves outcomes.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s10238-024-01439-4.html#qa-4", "question_source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1007-s10238-024-01439-4.json#/qa/3/answer", "answer_sha256": "82ddd8cc3e56d917009fa22a3690785a5f77f60513d21769ba0002799c5a0230", "evidence_refs": [ "KF1", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "time-cart--qa-1", "work_id": "time-cart", "qa_index": 1, "question": "Did this paper enroll CAR-T-treated patients?", "answer": "No. This is a narrative review synthesizing existing studies and does not report a newly recruited clinical cohort or original therapeutic efficacy estimate.", "answer_url": "https://drgezhang.com/papers/time-cart.html#qa-1", "question_source": "data/deep_geo/time-cart.json#/qa/0/question", "answer_source": "data/deep_geo/time-cart.json#/qa/0/answer", "answer_sha256": "5dc06abfcb898e39d300276a5a2963d8870ac36097bacb712dc30e5c47b3189b", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "time-cart--qa-2", "work_id": "time-cart", "qa_index": 2, "question": "Why do spatial immune-cell patterns matter?", "answer": "Cells that remain in stromal or peripheral compartments may have different relationships with tumor cells than cells infiltrating malignant nests. The review summarizes these patterns from prior studies.", "answer_url": "https://drgezhang.com/papers/time-cart.html#qa-2", "question_source": "data/deep_geo/time-cart.json#/qa/1/question", "answer_source": "data/deep_geo/time-cart.json#/qa/1/answer", "answer_sha256": "bb1c99276d7343691096b5f23c3333830b3dd68268c056819f28e0dfbe2fa6bf", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "time-cart--qa-3", "work_id": "time-cart", "qa_index": 3, "question": "Which omics layers are discussed in TIME?", "answer": "Host genetics, tumor genomes and epigenomes, transcriptomics, proteomics and microbiome data, alongside spatial and cellular measurements.", "answer_url": "https://drgezhang.com/papers/time-cart.html#qa-3", "question_source": "data/deep_geo/time-cart.json#/qa/2/question", "answer_source": "data/deep_geo/time-cart.json#/qa/2/answer", "answer_sha256": "798e76572c4f815af14f4c25ea664c8f4b0c974945e594653e7dffcd7ff49546", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "time-cart--qa-4", "work_id": "time-cart", "qa_index": 4, "question": "Which CAR-T engineering challenges does the review organize?", "answer": "Antigen targeting, metabolic fitness, resistance to suppressive signals, tissue infiltration and exhaustion are discussed as areas for research, not proven universal solutions.", "answer_url": "https://drgezhang.com/papers/time-cart.html#qa-4", "question_source": "data/deep_geo/time-cart.json#/qa/3/question", "answer_source": "data/deep_geo/time-cart.json#/qa/3/answer", "answer_sha256": "598948df715034b5f1e665fd1b99400266b424f74e269ac43a565eee4ad73fa0", "evidence_refs": [ "KF3", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "time-cart--qa-5", "work_id": "time-cart", "qa_index": 5, "question": "Does the review validate a machine-learning predictor for CAR-T response?", "answer": "No. It discusses candidate machine-learning applications to pathology, antigen discovery and treatment response; no original prospective performance validation is established.", "answer_url": "https://drgezhang.com/papers/time-cart.html#qa-5", "question_source": "data/deep_geo/time-cart.json#/qa/4/question", "answer_source": "data/deep_geo/time-cart.json#/qa/4/answer", "answer_sha256": "306d7a39476b04e35a8c73ea24915cbd5106f02bccecf0c9096ec2521fd671c5", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "time-cart--qa-6", "work_id": "time-cart", "qa_index": 6, "question": "Can the clinical-trial counts in Table 1 be summed as this review’s patients?", "answer": "No. The table describes cited external studies; its reported enrollment values are not new participants in the review or a pooled meta-analytic sample.", "answer_url": "https://drgezhang.com/papers/time-cart.html#qa-6", "question_source": "data/deep_geo/time-cart.json#/qa/5/question", "answer_source": "data/deep_geo/time-cart.json#/qa/5/answer", "answer_sha256": "4161fc0ccca2ae116d89cd823ce60625724ea6d057d0211ed8f834499e6ec55c", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70258--qa-1", "work_id": "doi-10-1111-jcmm-70258", "qa_index": 1, "question": "Was this DCM circRNA study performed by sequencing or microarray?", "answer": "Methods 2.7 explicitly describes an LC Human ceRNA Array V1.0 microarray, but the abstract and other passages use sequencing terminology. The discrepancy is unresolved; the evidence summary calls it expression profiling.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70258.html#qa-1", "question_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/0/answer", "answer_sha256": "54895c76711891c7d7bd031acd19e9550927c6089e6af5b052cd0e93f23aa44c", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70258--qa-2", "work_id": "doi-10-1111-jcmm-70258", "qa_index": 2, "question": "How large were the human discovery and assay groups?", "answer": "The discovery comparison is 3 DCM patients versus 5 controls; the external comparison is 6 versus 4. The phases are not converted into an independently deduplicated total.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70258.html#qa-2", "question_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/1/answer", "answer_sha256": "9e8d617d7420cd9011640fb2eed641facd3cedfe137b580f7790cf6bc7f696f5", "evidence_refs": [ "KF1", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70258--qa-3", "work_id": "doi-10-1111-jcmm-70258", "qa_index": 3, "question": "How many differential circRNAs were reported?", "answer": "The final Results/Fig. 2 set contains 49 circRNAs, 27 upregulated and 22 downregulated, among 865 detected circRNAs.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70258.html#qa-3", "question_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/2/answer", "answer_sha256": "546fd42b9cb76ae987aab7dadcf7bbcb513d801036f4a69aef87c5124ae575ac", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70258--qa-4", "work_id": "doi-10-1111-jcmm-70258", "qa_index": 4, "question": "What do the functional analyses establish?", "answer": "They provide predicted target and pathway relationships. They do not demonstrate direct binding, target regulation or causal function in human DCM.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70258.html#qa-4", "question_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/3/answer", "answer_sha256": "3cc1940fd8a77b232280374348d2f07bfe82e99d3886ef07ca2e17401551c6f0", "evidence_refs": [ "KF4", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70258--qa-5", "work_id": "doi-10-1111-jcmm-70258", "qa_index": 5, "question": "Were nine or ten circRNAs evaluated externally?", "answer": "Results 3.7 and Fig. 5 describe nine, while Methods 2.9 lists ten. The website preserves the Results count with the discrepancy stated explicitly.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70258.html#qa-5", "question_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/4/answer", "answer_sha256": "991bb636cc88683bd08c94cc0880c8d104c49651a74ebdb80aedc01eded26aca", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-70258--qa-6", "work_id": "doi-10-1111-jcmm-70258", "qa_index": 6, "question": "Does external expression-profile separation make this a validated diagnostic test?", "answer": "No. The small external assay group and expression-distance/PCoA separation do not establish prospective diagnostic performance or clinical utility.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70258.html#qa-6", "question_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-70258.json#/qa/5/answer", "answer_sha256": "7d7159dd33d4e312e0d707c13396e320a9d8b97f65e6e6b87ea569268b952ee9", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2024-1425895--qa-1", "work_id": "doi-10-3389-fonc-2024-1425895", "qa_index": 1, "question": "How strong is the reported TGFBR2 MR evidence?", "answer": "The forward IVW analysis used four SNPs and reported beta -0.059814, SE 0.02863 and P=0.0366879 in Supplementary Table S1, rounded to beta -0.06 and P=0.04 in the main text. This is nominal evidence within a candidate-selection pipeline and remains dependent on MR assumptions.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2024-1425895.html#qa-1", "question_source": "data/deep_geo/doi-10-3389-fonc-2024-1425895.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2024-1425895.json#/qa/0/answer", "answer_sha256": "a00425c863a11e0ab46c502c43ffeb91a8456aa1903553d83735722f4e9f06ab", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2024-1425895--qa-2", "work_id": "doi-10-3389-fonc-2024-1425895", "qa_index": 2, "question": "Does the tissue figure show higher or lower TGFBR2 in LUAD?", "answer": "Figure 8 shows lower TGFBR2-positive staining in five LUAD specimens than in three controls. The abstract and Results paragraph agree; the Results 3.7 heading says increased and is inconsistent with that evidence. The heading has not been formally corrected in the sources checked.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2024-1425895.html#qa-2", "question_source": "data/deep_geo/doi-10-3389-fonc-2024-1425895.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2024-1425895.json#/qa/1/answer", "answer_sha256": "427fbe13477dff98607c3510678045a2bd6ec58300b9f879f284669b62d38f50", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2024-1425895--qa-3", "work_id": "doi-10-3389-fonc-2024-1425895", "qa_index": 3, "question": "What did the A549 perturbation experiment show?", "answer": "After TGFBR2 knockdown, CCK8 and Transwell-migration readouts increased and the apoptosis readout decreased. Two siRNAs were screened, and the more effective sequence was selected for subsequent assays. These results are from one cultured-cell model.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2024-1425895.html#qa-3", "question_source": "data/deep_geo/doi-10-3389-fonc-2024-1425895.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2024-1425895.json#/qa/2/answer", "answer_sha256": "1589ceca31e9ab6d1a3d07aab536e331229109869e30540496eeedc2e61f37b6", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2024-1425895--qa-4", "work_id": "doi-10-3389-fonc-2024-1425895", "qa_index": 4, "question": "Can these findings guide LUAD diagnosis or treatment now?", "answer": "The study provides candidate-gene evidence, not clinical implementation evidence. A nominal MR association, eight tissue specimens and A549 assays do not establish patient-level diagnostic utility, treatment benefit or drug safety.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2024-1425895.html#qa-4", "question_source": "data/deep_geo/doi-10-3389-fonc-2024-1425895.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2024-1425895.json#/qa/3/answer", "answer_sha256": "fa25ba87eb94a93f4376a08ad66da8385433b2bdd43bf1b19ba2edafe2aa030a", "evidence_refs": [ "KF1", "KF2", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "circadian-ihd--qa-1", "work_id": "circadian-ihd", "qa_index": 1, "question": "What single-cell evidence underlies this coronary expression framework?", "answer": "The analysis of GSE184073 constructed a single-cell co-expression foundation related to coronary disease. Post-QC cells: 2,237; Analyzed samples: 2; Non-grey modules: 8. Cells are not independent patients; two analyzed samples do not establish population-level robustness.", "answer_url": "https://drgezhang.com/papers/circadian-ihd.html#qa-1", "question_source": "data/deep_geo/circadian-ihd.json#/qa/0/question", "answer_source": "data/deep_geo/circadian-ihd.json#/qa/0/answer", "answer_sha256": "f1b31408712dce277412ffe3572515224f77b8b9db0060ebf97ac36634f68687", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "circadian-ihd--qa-2", "work_id": "circadian-ihd", "qa_index": 2, "question": "What does CRDscore measure, and what does it not directly measure?", "answer": "CRDscore was constructed as a research score from target-gene expression and a random background. Formula: CRDscore = Srandom - SCADCRgenes; Random features: 1,000; Single-cell cutoff: 75th percentile; Bulk cutoff: Median. The score does not directly measure an individual's circadian phase, amplitude or period. The two data-layer cutoffs are not one clinical threshold.", "answer_url": "https://drgezhang.com/papers/circadian-ihd.html#qa-2", "question_source": "data/deep_geo/circadian-ihd.json#/qa/1/question", "answer_source": "data/deep_geo/circadian-ihd.json#/qa/1/answer", "answer_sha256": "1de456cc57f5c04d85920c924f32d9f2433d4b38f0a1b4bc29b3a2a035159967", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "circadian-ihd--qa-3", "work_id": "circadian-ihd", "qa_index": 3, "question": "Are all cited reference datasets verified mouse circadian experiments?", "answer": "The article reports external reference-data evaluation, but the use of GSE70049 requires qualification. GSE70049 organism: Danio rerio; GSE70049 experiment: setb morphant expression experiment. The evidence does not establish that all four reference experiments are verified mouse circadian interventions. No intended replacement accession is inferred.", "answer_url": "https://drgezhang.com/papers/circadian-ihd.html#qa-3", "question_source": "data/deep_geo/circadian-ihd.json#/qa/2/question", "answer_source": "data/deep_geo/circadian-ihd.json#/qa/2/answer", "answer_sha256": "bcec4da00ed3520a85900ff90e851999f6b482af03fd106bc7e0ba39fd14a9ef", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "circadian-ihd--qa-4", "work_id": "circadian-ihd", "qa_index": 4, "question": "Does the discovery dataset represent 436 independent patients?", "answer": "Expression-based subtyping of GSE59867 yielded four groups. Type1 samples: 124; Type2 samples: 93; Type3 samples: 87; Type4 samples: 132; Total expression samples: 436. These are expression-sample groups, not 436 independent patients. The grouping does not resolve independence of repeated follow-up samples or outcome analyses.", "answer_url": "https://drgezhang.com/papers/circadian-ihd.html#qa-4", "question_source": "data/deep_geo/circadian-ihd.json#/qa/3/question", "answer_source": "data/deep_geo/circadian-ihd.json#/qa/3/answer", "answer_sha256": "663555201810aee0629dc79e4718e30fd0da31e9dae5c8a533a0673c7189101a", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "circadian-ihd--qa-5", "work_id": "circadian-ihd", "qa_index": 5, "question": "What kind of external validation was performed?", "answer": "NTP was used to evaluate subtype assignment in four external expression datasets. Datasets: GSE20680; GSE20681; GSE43292; GSE62646. External expression-template reproducibility is not prospective risk prediction or demonstrated clinical utility.", "answer_url": "https://drgezhang.com/papers/circadian-ihd.html#qa-5", "question_source": "data/deep_geo/circadian-ihd.json#/qa/4/question", "answer_source": "data/deep_geo/circadian-ihd.json#/qa/4/answer", "answer_sha256": "dd4ba3814db83b66eeff9b0e7c931bb15525120c81af0c45fa8248a168d091a8", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "circadian-ihd--qa-6", "work_id": "circadian-ihd", "qa_index": 6, "question": "Do subtype-associated immune patterns establish treatment benefit?", "answer": "Type2 showed higher CRDscore and immune-inflammatory expression characteristics. Contractile markers: Lower expression; Immune and collagen pathways: Associated enrichment differences. Computational estimates and expression associations do not establish causal plaque transitions or benefit from immunotherapy or chronotherapy.", "answer_url": "https://drgezhang.com/papers/circadian-ihd.html#qa-6", "question_source": "data/deep_geo/circadian-ihd.json#/qa/5/question", "answer_source": "data/deep_geo/circadian-ihd.json#/qa/5/answer", "answer_sha256": "0380bb62f51937637805d7b73eea3e4947676cc65727bf34712d1220b2333ec9", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s13402-023-00912-8--qa-1", "work_id": "doi-10-1007-s13402-023-00912-8", "qa_index": 1, "question": "Which biomarker layers are distinguished in the review?", "answer": "Its biomarker overview distinguishes genomic, epigenomic, transcriptomic and proteomic information. These are categories of prior molecular research, not four new validation cohorts.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s13402-023-00912-8.html#qa-1", "question_source": "data/deep_geo/doi-10-1007-s13402-023-00912-8.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1007-s13402-023-00912-8.json#/qa/0/answer", "answer_sha256": "a4ac7fd51d8759f7d01a2fd6c86b86dea487a66ba87b33c4295a06fff7fb7869", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s13402-023-00912-8--qa-2", "work_id": "doi-10-1007-s13402-023-00912-8", "qa_index": 2, "question": "Does this review validate a new multi-omics classifier?", "answer": "No. It discusses published integration and spatial-profiling approaches. Performance or treatment-response claims for any particular classifier must be checked in the cited primary study.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s13402-023-00912-8.html#qa-2", "question_source": "data/deep_geo/doi-10-1007-s13402-023-00912-8.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1007-s13402-023-00912-8.json#/qa/1/answer", "answer_sha256": "3973c2445e9dc7e9b72d30a0e82a75d8bb673026e34e9bf60c34e296a3d7a068", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s13402-023-00912-8--qa-3", "work_id": "doi-10-1007-s13402-023-00912-8", "qa_index": 3, "question": "Which clinical-trial design frameworks are compared?", "answer": "The review compares basket, umbrella, platform and N-of-1 designs. This comparison provides context for molecularly informed trial design; it does not supply a pooled efficacy estimate.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s13402-023-00912-8.html#qa-3", "question_source": "data/deep_geo/doi-10-1007-s13402-023-00912-8.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1007-s13402-023-00912-8.json#/qa/2/answer", "answer_sha256": "75e8230cf5c9bb61c3ea227cb3333094f953853e40fa815a9b08827ae1dd35e8", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1007-s13402-023-00912-8--qa-4", "work_id": "doi-10-1007-s13402-023-00912-8", "qa_index": 4, "question": "What prevents a molecular classification from automatically becoming a treatment recommendation?", "answer": "The review identifies complex data integration, the need for clinical interpretability and limitations of preclinical models. Its discussion of AI, organoids and three-dimensional models is a research agenda, not clinical proof of benefit.", "answer_url": "https://drgezhang.com/papers/doi-10-1007-s13402-023-00912-8.html#qa-4", "question_source": "data/deep_geo/doi-10-1007-s13402-023-00912-8.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1007-s13402-023-00912-8.json#/qa/3/answer", "answer_sha256": "978e395735ce20c420c90a232c330bc9ded06b5fa307f5bc1fb56ef3ab73373c", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-ejso-2024-108527--qa-1", "work_id": "doi-10-1016-j-ejso-2024-108527", "qa_index": 1, "question": "How many independent patients were included?", "answer": "The single-center series reports 23 patients. The endoscopic, direct-surgery, neoadjuvant-plus-surgery and conservative groups are subdivisions of those same patients.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-ejso-2024-108527.html#qa-1", "question_source": "data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/0/answer", "answer_sha256": "6c06e005dbeb3f22e3b0416d7065306141d1ae5133905f02e4782494d0e8631d", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-ejso-2024-108527--qa-2", "work_id": "doi-10-1016-j-ejso-2024-108527", "qa_index": 2, "question": "How were treatment approaches distributed?", "answer": "There were 15 endoscopic resections, five direct operations, two operations after neoadjuvant imatinib, and one conservatively managed patient. The surgical total of seven already includes the two neoadjuvant-treated patients.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-ejso-2024-108527.html#qa-2", "question_source": "data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/1/answer", "answer_sha256": "526c348c0cf723ad28adf9d9b30d4cdc4899b61f2efff59d19c8d596f0b65d50", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-ejso-2024-108527--qa-3", "work_id": "doi-10-1016-j-ejso-2024-108527", "qa_index": 3, "question": "What endoscopic procedures and lesion sizes were reported?", "answer": "The 15 endoscopic procedures included nine STER, four ESD and two EMBL. Twelve tumors in this group were reported as no larger than 30 mm. This selected experience does not validate a universal treatment cutoff.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-ejso-2024-108527.html#qa-3", "question_source": "data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/2/answer", "answer_sha256": "9a42f98c99c972ffe4d82b599934ab9225ddc16ff1e8640d1bdfab1aee40e785", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-ejso-2024-108527--qa-4", "work_id": "doi-10-1016-j-ejso-2024-108527", "qa_index": 4, "question": "Does the study show that endoscopy is safer or more effective than surgery?", "answer": "No. Clinicians selected treatment according to tumor and patient features, and the groups differed in case mix. Two reported endoscopic adverse events in a small retrospective sample do not establish comparative safety or survival benefit.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-ejso-2024-108527.html#qa-4", "question_source": "data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/3/answer", "answer_sha256": "3d9d41f3e2e842d25220ebbbf87004ee04e7ed216358084ce6c36598ac54d2ca", "evidence_refs": [ "KF2", "KF3", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-ejso-2024-108527--qa-5", "work_id": "doi-10-1016-j-ejso-2024-108527", "qa_index": 5, "question": "What follow-up observation can be cited?", "answer": "The reported mean follow-up was 48.2 ± 24.2 months. Patient No. 16 developed recurrence at 15 months after surgery and died at 29 months. These observations are not a randomized treatment effect or a validated survival prediction.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-ejso-2024-108527.html#qa-5", "question_source": "data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/4/answer", "answer_sha256": "3a0baf37935262f415d6df88efd9db5ac90d7c75b30e5ffb47f73b72e9a5f3e1", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "olink-dcm--qa-1", "work_id": "olink-dcm", "qa_index": 1, "question": "How many participants were included in the DCM-HF Olink proteomics study?", "answer": "The article reports 103 local participants: 50 DCM-HF patients and 53 healthy controls. Thirty-eight participants formed the Olink discovery cohort, and a separate 65 participants formed the ELISA validation cohort.", "answer_url": "https://drgezhang.com/papers/olink-dcm.html#qa-1", "question_source": "data/deep_geo/olink-dcm.json#/qa/0/question", "answer_source": "data/deep_geo/olink-dcm.json#/qa/0/answer", "answer_sha256": "2b56c1fadd7e4a0497faaae7f0eb6b03144936182eeda039506ddd71af971764", "evidence_refs": [ "KF1", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "olink-dcm--qa-2", "work_id": "olink-dcm", "qa_index": 2, "question": "How many proteins were profiled with Olink in DCM-HF?", "answer": "The Olink Cardiovascular III panel measured 92 targeted cardiovascular-related plasma proteins in 20 DCM-HF patients and 18 healthy controls.", "answer_url": "https://drgezhang.com/papers/olink-dcm.html#qa-2", "question_source": "data/deep_geo/olink-dcm.json#/qa/1/question", "answer_source": "data/deep_geo/olink-dcm.json#/qa/1/answer", "answer_sha256": "ee14fda85662b29a2daf0f102739b3087ce9512e737c7acb3bdbab5edc6b12b5", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "olink-dcm--qa-3", "work_id": "olink-dcm", "qa_index": 3, "question": "Which plasma proteins were prioritized for validation?", "answer": "SPP1, IGFBP7, F11R, CHI3L1 and PLAUR were prioritized from the differential-protein analysis for focused validation.", "answer_url": "https://drgezhang.com/papers/olink-dcm.html#qa-3", "question_source": "data/deep_geo/olink-dcm.json#/qa/2/question", "answer_source": "data/deep_geo/olink-dcm.json#/qa/2/answer", "answer_sha256": "7db6bf99bb3acf179c8b2b9a2a691d8c073679c66c78c28850559fc8fa6fa05f", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "olink-dcm--qa-4", "work_id": "olink-dcm", "qa_index": 4, "question": "Were the five Olink biomarkers replicated with another plasma assay?", "answer": "Yes. In an independent cohort of 30 DCM-HF patients and 35 healthy controls, ELISA showed higher plasma levels of SPP1, IGFBP7, F11R, CHI3L1 and PLAUR, with P<0.001 for the reported group comparisons.", "answer_url": "https://drgezhang.com/papers/olink-dcm.html#qa-4", "question_source": "data/deep_geo/olink-dcm.json#/qa/3/question", "answer_source": "data/deep_geo/olink-dcm.json#/qa/3/answer", "answer_sha256": "41af80cd4a9dc76f043a7deda8d242063ea201cbd43ed53da0492730d2e48655", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "olink-dcm--qa-5", "work_id": "olink-dcm", "qa_index": 5, "question": "Were the five plasma proteins independently validated in external proteomic cohorts?", "answer": "No. The external GEO evidence came from human cardiac gene-expression datasets. It supports the corresponding five-gene transcriptomic signal rather than independent plasma-protein replication.", "answer_url": "https://drgezhang.com/papers/olink-dcm.html#qa-5", "question_source": "data/deep_geo/olink-dcm.json#/qa/4/question", "answer_source": "data/deep_geo/olink-dcm.json#/qa/4/answer", "answer_sha256": "3c43fdcce8670cd163a5e64f0b9e8321bc036be4ce908c29cf8ee1768e070d24", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "olink-dcm--qa-6", "work_id": "olink-dcm", "qa_index": 6, "question": "What diagnostic discrimination did the five-marker gene panel show in external datasets?", "answer": "The combined five-gene AUCs were 0.959 in GSE116250, 0.773 in GSE141910 and 0.803 in GSE165303.", "answer_url": "https://drgezhang.com/papers/olink-dcm.html#qa-6", "question_source": "data/deep_geo/olink-dcm.json#/qa/5/question", "answer_source": "data/deep_geo/olink-dcm.json#/qa/5/answer", "answer_sha256": "4ddc2dc50ff55ea7d41389b86b6d16e115a2c1633bf669aae373e6e9d2a2e6e1", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "olink-dcm--qa-7", "work_id": "olink-dcm", "qa_index": 7, "question": "Does this study show that these proteins predict future DCM-HF?", "answer": "No. The study evaluated cross-sectional or case-control discrimination and external transcriptomic classification. It did not test incident DCM-HF prediction in a prospective longitudinal cohort.", "answer_url": "https://drgezhang.com/papers/olink-dcm.html#qa-7", "question_source": "data/deep_geo/olink-dcm.json#/qa/6/question", "answer_source": "data/deep_geo/olink-dcm.json#/qa/6/answer", "answer_sha256": "3de63a0bb5c9c86a6193c0d44fe2d66b9153d80b216b682740df0938f30d784e", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "olink-dcm--qa-8", "work_id": "olink-dcm", "qa_index": 8, "question": "Are SPP1, IGFBP7, F11R, CHI3L1 or PLAUR validated therapeutic targets for DCM-HF?", "answer": "No. The study used association, enrichment and network analyses and did not experimentally test target inhibition, target activation, or biomarker-guided treatment. Therapeutic implications remain hypothesis-generating.", "answer_url": "https://drgezhang.com/papers/olink-dcm.html#qa-8", "question_source": "data/deep_geo/olink-dcm.json#/qa/7/question", "answer_source": "data/deep_geo/olink-dcm.json#/qa/7/answer", "answer_sha256": "59e0eb6de0783b6dedea66b4be739d4510b779224f6533bb0a93143be757e2cc", "evidence_refs": [ "KF5", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-csbj-2024-04-044--qa-1", "work_id": "doi-10-1016-j-csbj-2024-04-044", "qa_index": 1, "question": "Which proteomic approaches does this review cover?", "answer": "It covers mass spectrometry, aptamer-based assays, proximity extension assays, protein microarrays and combined single-cell techniques.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-csbj-2024-04-044.html#qa-1", "question_source": "data/deep_geo/doi-10-1016-j-csbj-2024-04-044.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1016-j-csbj-2024-04-044.json#/qa/0/answer", "answer_sha256": "ba35f0cfdd69232f7f179d96e7980fa5a0e911ea99e07f7919a8a69c432e3fe8", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-csbj-2024-04-044--qa-2", "work_id": "doi-10-1016-j-csbj-2024-04-044", "qa_index": 2, "question": "What role does data integration play in the review?", "answer": "Integration connects protein measurements with other molecular layers; the review illustrates approaches including TieDIE, PCA and NMF.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-csbj-2024-04-044.html#qa-2", "question_source": "data/deep_geo/doi-10-1016-j-csbj-2024-04-044.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1016-j-csbj-2024-04-044.json#/qa/1/answer", "answer_sha256": "a55bcd9254424f3ef3e9ec01ad26c26239e7e366bf8ee89213436addfebe5edd", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-csbj-2024-04-044--qa-3", "work_id": "doi-10-1016-j-csbj-2024-04-044", "qa_index": 3, "question": "Which precision-oncology applications are discussed?", "answer": "The review discusses molecular subtyping, primary-site identification, biomarkers, mechanisms and immunotherapy applications using published examples.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-csbj-2024-04-044.html#qa-3", "question_source": "data/deep_geo/doi-10-1016-j-csbj-2024-04-044.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1016-j-csbj-2024-04-044.json#/qa/2/answer", "answer_sha256": "fc3593012b7a531f65fed8329eef37c593c8e2801bb47754f5b615879b4bb6ee", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-csbj-2024-04-044--qa-4", "work_id": "doi-10-1016-j-csbj-2024-04-044", "qa_index": 4, "question": "Can this article be cited as a new clinical validation study?", "answer": "No. It is a narrative synthesis; quantitative claims about individual biomarkers or therapies should be checked against the original primary studies.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-csbj-2024-04-044.html#qa-4", "question_source": "data/deep_geo/doi-10-1016-j-csbj-2024-04-044.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1016-j-csbj-2024-04-044.json#/qa/3/answer", "answer_sha256": "e9d361ec86acf9ce7ad8cb7a684d77cb5cdff8a438a11d04f4b1df73b7a8ac07", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-canlet-2024-217083--qa-1", "work_id": "doi-10-1016-j-canlet-2024-217083", "qa_index": 1, "question": "Is this an original clinical study?", "answer": "No. It is a narrative review of published evidence and safety concerns, with one conceptual figure. The FDA reports and cited patients are not an original cohort recruited by these authors. Source location: Cancer Letters 597 (2024) 217083, publisher-typeset PDF p. 1, Section 1 (Introduction), and p. 4, Section 5 (Conclusions); reference 1, FDA safety communication dated 28 November 2023.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#qa-1", "question_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/0/answer", "answer_sha256": "d4a25674cbc5509b049160a61d2037e5f58c2b6affd2d765ea4dcbe6e94d77fd", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-canlet-2024-217083--qa-2", "work_id": "doi-10-1016-j-canlet-2024-217083", "qa_index": 2, "question": "Which mechanisms does the review discuss?", "answer": "It discusses integration-related disruption of growth regulation, persistent activation and an inflammatory environment, alongside host susceptibility and treatment history. These are candidate explanations, not mechanisms newly proven by this article. Source location: Cancer Letters 597 (2024) 217083, PDF p. 2, Section 3.1 (Insertional mutagenesis), references 14-23; p. 3, Figure 1A (conceptual schematic, not an experiment). Cancer Letters 597 (2024) 217083, PDF p. 2, Section 3.2 (Sustained T-cell activation and inflammation-related cytokine-rich environment), references 24-33; p. 3, Figure 1A. Cancer Letters 597 (2024) 217083, PDF pp. 2 and 4, Section 3.3 (Potential susceptibility and bridging therapy considerations), references 34-52; p. 3, Figure 1B (hypothesis, not a statistical comparison).", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#qa-2", "question_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/1/answer", "answer_sha256": "df355cf25dea7918ebe08a3f55f6f0d5f96853003a7ab7e487d2e48b2cec6012", "evidence_refs": [ "KF2", "KF3", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-canlet-2024-217083--qa-3", "work_id": "doi-10-1016-j-canlet-2024-217083", "qa_index": 3, "question": "Does Figure 1B establish that CAR-T therapy is not associated with T-cell malignancy?", "answer": "No. Panel B is a conceptual depiction of a competing explanation. The review supplies no original statistical comparison supporting its 'not significantly associated' wording. Source location: Cancer Letters 597 (2024) 217083, PDF pp. 2 and 4, Section 3.3 (Potential susceptibility and bridging therapy considerations), references 34-52; p. 3, Figure 1B (hypothesis, not a statistical comparison).", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#qa-3", "question_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/2/answer", "answer_sha256": "012e999c021594c6748b2b1555135d3b03eb54574f54d7934f45ec72a4526572", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-canlet-2024-217083--qa-4", "work_id": "doi-10-1016-j-canlet-2024-217083", "qa_index": 4, "question": "Can the clinical case numbers be used to calculate incidence?", "answer": "No. The cited populations differ, the review mixes units in reference 36 and follow-up populations in reference 37, and spontaneous safety reports lack a compatible denominator. No pooled rate is calculated or endorsed here. Source location: Cancer Letters 597 (2024) 217083, PDF pp. 2 and 4, Section 3.3, references 36, 37, 40 and 46; p. 4, Sections 4-5. Numerical cross-check: reference 36, DOI 10.1182/blood.2022015728, Abstract, Results and Table 4 (PMC9346960); reference 37, DOI 10.1182/blood-2023-182817, Background versus Results.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#qa-4", "question_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/3/answer", "answer_sha256": "fb43be103b29da53903f95e4f43c075bf9dc6d7be090b196068640ab37cd531d", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-canlet-2024-217083--qa-5", "work_id": "doi-10-1016-j-canlet-2024-217083", "qa_index": 5, "question": "Does CAR positivity prove a specific carcinogenic mechanism?", "answer": "No. It can inform the relationship of a tumor to engineered cells, but integration, clonal history and other molecular evidence are needed to assess mechanism. CAR negativity also does not by itself exclude every indirect treatment contribution. Source location: Cancer Letters 597 (2024) 217083, PDF pp. 2 and 4, Section 3.3, references 36, 37, 40 and 46; p. 4, Sections 4-5. Numerical cross-check: reference 36, DOI 10.1182/blood.2022015728, Abstract, Results and Table 4 (PMC9346960); reference 37, DOI 10.1182/blood-2023-182817, Background versus Results.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#qa-5", "question_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/4/answer", "answer_sha256": "11fa41fe74a6e68144a4ca30e9605e04a9a406dd01d2c13cef05d80f4ef146e4", "evidence_refs": [ "KF4", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-canlet-2024-217083--qa-6", "work_id": "doi-10-1016-j-canlet-2024-217083", "qa_index": 6, "question": "Does this paper establish HHV-6 as the cause of a secondary T-cell cancer?", "answer": "No. Section 3.1 brings viral reactivation into the discussion, but the review does not demonstrate that reactivation caused a secondary lymphoma after CAR-T treatment. Source location: Cancer Letters 597 (2024) 217083, PDF p. 2, Section 3.1 (Insertional mutagenesis), references 14-23; p. 3, Figure 1A (conceptual schematic, not an experiment).", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#qa-6", "question_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/5/answer", "answer_sha256": "720948d7d52f2ab4fffe2fbde5e40f3d367bcb6a940e99aeab9fefbdfe1261b7", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-canlet-2024-217083--qa-7", "work_id": "doi-10-1016-j-canlet-2024-217083", "qa_index": 7, "question": "What safety conclusion can be cited to this review?", "answer": "It supports a 2024 discussion of unresolved mechanisms and the need for continued investigation. It does not provide an independently validated risk estimate or justify a universal claim that CAR-T therapy is safe or unrelated to secondary cancer. Source location: Cancer Letters 597 (2024) 217083, publisher-typeset PDF p. 1, Section 1 (Introduction), and p. 4, Section 5 (Conclusions); reference 1, FDA safety communication dated 28 November 2023. Cancer Letters 597 (2024) 217083, PDF pp. 2 and 4, Section 3.3, references 36, 37, 40 and 46; p. 4, Sections 4-5. Numerical cross-check: reference 36, DOI 10.1182/blood.2022015728, Abstract, Results and Table 4 (PMC9346960); reference 37, DOI 10.1182/blood-2023-182817, Background versus Results.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#qa-7", "question_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/6/answer", "answer_sha256": "3a130dd2a0adc2b26bcf007c4bf997f13132c27e0731f2cade83293ff3c84036", "evidence_refs": [ "KF1", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-canlet-2024-217083--qa-8", "work_id": "doi-10-1016-j-canlet-2024-217083", "qa_index": 8, "question": "Are the disputed source counts silently corrected into new findings?", "answer": "No. They are disclosed as citation-level inconsistencies and excluded from the review's quantitative claims. The original studies must be cited directly for their populations, events, assay results and follow-up windows. Source location: Cancer Letters 597 (2024) 217083, PDF pp. 2 and 4, Section 3.3, references 36, 37, 40 and 46; p. 4, Sections 4-5. Numerical cross-check: reference 36, DOI 10.1182/blood.2022015728, Abstract, Results and Table 4 (PMC9346960); reference 37, DOI 10.1182/blood-2023-182817, Background versus Results.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-canlet-2024-217083.html#qa-8", "question_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/7/question", "answer_source": "data/deep_geo/doi-10-1016-j-canlet-2024-217083.json#/qa/7/answer", "answer_sha256": "d2ba4e8ade1c6454852c05b3c8822b856793fc6564580c87b4f95be381bf5577", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-cia-s462542--qa-1", "work_id": "doi-10-2147-cia-s462542", "qa_index": 1, "question": "Who was included in the analyzed cohort?", "answer": "The analysis included 717 adults with advanced chronic HF, study-defined renal dysfunction and repeated HF hospitalization at one center. The 815 initially included patients also contained 98 who were lost to follow-up.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#qa-1", "question_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/0/answer", "answer_sha256": "7e2451cf8b3499c5187c78cbc1856e20ee9b521bc8e1d893e8face68516cec7f", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-cia-s462542--qa-2", "work_id": "doi-10-2147-cia-s462542", "qa_index": 2, "question": "Were the MACEs and mortality groups independent cohorts?", "answer": "No. The two outcome-specific cutoffs regrouped the same 717 analyzed patients. Their group sizes must not be added together as independent participants.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#qa-2", "question_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/1/answer", "answer_sha256": "90d76a99953b631a28cf1a51553705f76429cb51319621c8933931af6113315c", "evidence_refs": [ "KF1", "KF2", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-cia-s462542--qa-3", "work_id": "doi-10-2147-cia-s462542", "qa_index": 3, "question": "What was the reported MACEs association?", "answer": "High versus low TyG at the 8.48 threshold had an adjusted hazard ratio of 5.402 (95% CI 3.771–7.739). This is a relative hazard association, not an absolute event rate.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#qa-3", "question_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/2/answer", "answer_sha256": "bf173130aac91bf6e6c13d1c70888ab348cc790e2fcc19431c47aa0348885c66", "evidence_refs": [ "KF2", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-cia-s462542--qa-4", "work_id": "doi-10-2147-cia-s462542", "qa_index": 4, "question": "Was the composite limited to cardiovascular death, infarction and stroke?", "answer": "No. The Methods define a broad composite including non-cardiovascular death, worsening-HF rehospitalization, transplantation, circulatory support and other events. Interpretation should preserve that study-specific definition.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#qa-4", "question_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/3/answer", "answer_sha256": "407ddcfc252adfab0ec0a43139a2cbe9570168a634651a96f0f17c2304671176", "evidence_refs": [ "KF1", "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-cia-s462542--qa-5", "work_id": "doi-10-2147-cia-s462542", "qa_index": 5, "question": "Was the mortality association evaluated separately?", "answer": "Yes. At the mortality-specific cutoff of 8.50, the adjusted hazard ratio was 5.062 (95% CI 3.268–7.839), with ROC AUC 0.700 in the same cohort.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#qa-5", "question_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/4/answer", "answer_sha256": "5873815c91ddeac943ed8acdd98f95c988204c70985a4b0ce7c2804f79ef4b81", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-2147-cia-s462542--qa-6", "work_id": "doi-10-2147-cia-s462542", "qa_index": 6, "question": "Does the study show that treatment to lower TyG improves survival?", "answer": "No. It is a retrospective observational association study, with thresholds chosen from the source cohort. Prospective and external studies are needed before using the findings to direct treatment.", "answer_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#qa-6", "question_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/5/answer", "answer_sha256": "664a9f3048143ddfc92baf195153f795c0b680380148ad9770c0d7e08f81ed7c", "evidence_refs": [ "KF1", "KF2", "KF3", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "apvs--qa-1", "work_id": "apvs", "qa_index": 1, "question": "What is APVS?", "answer": "APVS is a 14-gene atherosclerotic plaque vulnerability signature derived from 96 dysregulated co-expression pattern genes using an integrative nine-learner machine-learning framework.", "answer_url": "https://drgezhang.com/papers/apvs.html#qa-1", "question_source": "data/deep_geo/apvs.json#/qa/0/question", "answer_source": "data/deep_geo/apvs.json#/qa/0/answer", "answer_sha256": "1161f72425cbf7ee104d670a6fa16762fd887841fc2d682d0e057252af4adca2", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "apvs--qa-2", "work_id": "apvs", "qa_index": 2, "question": "Can APVS distinguish STEMI from chronic coronary syndrome?", "answer": "Yes. The APVS classifier achieved AUCs of 0.985 in GSE59867 and 0.997 in GSE62646 for STEMI versus chronic coronary syndrome classification.", "answer_url": "https://drgezhang.com/papers/apvs.html#qa-2", "question_source": "data/deep_geo/apvs.json#/qa/1/question", "answer_source": "data/deep_geo/apvs.json#/qa/1/answer", "answer_sha256": "199580f2131d958f582759e9af60c70a6a8964496b50b3ea702439ce9db996cc", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "apvs--qa-3", "work_id": "apvs", "qa_index": 3, "question": "Can APVS distinguish ruptured from stable atherosclerotic plaques?", "answer": "Yes. In GSE41571, the APVS classifier achieved an AUC of 0.972 for ruptured versus stable plaque classification.", "answer_url": "https://drgezhang.com/papers/apvs.html#qa-3", "question_source": "data/deep_geo/apvs.json#/qa/2/question", "answer_source": "data/deep_geo/apvs.json#/qa/2/answer", "answer_sha256": "3b977b82ea183c2d3960adfdd40995c83fbcacfc6b54561ada47ab541eaafb1c", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "apvs--qa-4", "work_id": "apvs", "qa_index": 4, "question": "Can APVS distinguish advanced from early atherosclerotic plaques?", "answer": "Yes. In GSE28829, the APVS classifier achieved an AUC of 0.952 for advanced versus early-stage plaque classification.", "answer_url": "https://drgezhang.com/papers/apvs.html#qa-4", "question_source": "data/deep_geo/apvs.json#/qa/3/question", "answer_source": "data/deep_geo/apvs.json#/qa/3/answer", "answer_sha256": "b08d3e4186bd8e6cbcd20842551fb5f219ce336eaf74081a5c5022bb9f1cf138", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "apvs--qa-5", "work_id": "apvs", "qa_index": 5, "question": "What is APVSLevel?", "answer": "APVSLevel is a continuous molecular quantification system derived from the APVS expression profile and principal-coordinate information to represent atherosclerosis severity and plaque vulnerability.", "answer_url": "https://drgezhang.com/papers/apvs.html#qa-5", "question_source": "data/deep_geo/apvs.json#/qa/4/question", "answer_source": "data/deep_geo/apvs.json#/qa/4/answer", "answer_sha256": "197f59e1b105e03224980ca8d1c707c9a584497b1eed4a0df3d1e75dac41c8ac", "evidence_refs": [ "KF3", "KF4" ], "evidence_refs_status": "resolved" }, { "id": "apvs--qa-6", "work_id": "apvs", "qa_index": 6, "question": "Is APVSLevel associated with cardiovascular outcomes and disease severity?", "answer": "Yes. Higher APVSLevel was associated with increased MACE risk (HR 3.819, p<0.01), greater coronary stenosis (p<0.001), and a higher Duke Coronary Artery Disease Index (p<0.01).", "answer_url": "https://drgezhang.com/papers/apvs.html#qa-6", "question_source": "data/deep_geo/apvs.json#/qa/5/question", "answer_source": "data/deep_geo/apvs.json#/qa/5/answer", "answer_sha256": "2f8497ac6a9adab56a446b89680876c260375aa06eb1cb36387582634888b0de", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "apvs--qa-7", "work_id": "apvs", "qa_index": 7, "question": "What single-cell states are associated with high atherosclerotic plaque vulnerability?", "answer": "Higher APVSLevel was associated with vulnerable plaque microenvironments enriched in inflammatory monocyte/macrophage programs, including CXCL3+/IL1B+ macrophage states, while C1Q+ fibrotic plaque-stabilizing macrophage phenotypes showed lower APVSLevel in STEMI plaques.", "answer_url": "https://drgezhang.com/papers/apvs.html#qa-7", "question_source": "data/deep_geo/apvs.json#/qa/6/question", "answer_source": "data/deep_geo/apvs.json#/qa/6/answer", "answer_sha256": "85d5b5dee15a399814e68856668275446d3d8337636a9182ca1245b72a576c9f", "evidence_refs": [ "KF4", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "apvs--qa-8", "work_id": "apvs", "qa_index": 8, "question": "Is APVS or APVSLevel ready to replace clinical plaque assessment?", "answer": "No. The evidence is primarily retrospective and transcriptomics-based. Prospective multicenter validation, direct comparison with established clinical biomarkers, and additional experimental validation are required before clinical translation.", "answer_url": "https://drgezhang.com/papers/apvs.html#qa-8", "question_source": "data/deep_geo/apvs.json#/qa/7/question", "answer_source": "data/deep_geo/apvs.json#/qa/7/answer", "answer_sha256": "0910164b5be47d2feb6fb9f76c21432e80343d5a08af82e5fd5b0dc930e9d027", "evidence_refs": [], "evidence_refs_status": "not_encoded" }, { "id": "doi-10-1016-j-jma-2023-05-007--qa-1", "work_id": "doi-10-1016-j-jma-2023-05-007", "qa_index": 1, "question": "Was this a human cardiovascular stent trial?", "answer": "No. The reported work used material tests, cultured cells and 15 rats implanted with alloy wires in the abdominal aorta. No treated human patients or clinical efficacy endpoint were reported.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#qa-1", "question_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/0/answer", "answer_sha256": "bb6a565cb91b4776bcffe700afe0018f1c3e726f3b3cf24dbe55fa78c20c24b9", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jma-2023-05-007--qa-2", "work_id": "doi-10-1016-j-jma-2023-05-007", "qa_index": 2, "question": "What is the coating made from?", "answer": "An Mg-Zn-Y-Nd alloy had an MgF2 layer, an adhesive polydopamine layer and an exosome-containing surface treatment.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#qa-2", "question_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/1/answer", "answer_sha256": "6f8968f0e71f75100c8e2b7522d28e0f156a96bda88afd09b435ee1c5d81a2b0", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jma-2023-05-007--qa-3", "work_id": "doi-10-1016-j-jma-2023-05-007", "qa_index": 3, "question": "What vascular endothelial outcomes were assessed?", "answer": "The paper reports cell adhesion/growth, CD31, nitric oxide and migration assays under culture conditions, with differences between coated and bare material groups.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#qa-3", "question_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/2/answer", "answer_sha256": "933c57adaa24c0372dd182e8d130b3277a95b4e39ad8b5fc13a7a0cc12df54dc", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jma-2023-05-007--qa-4", "work_id": "doi-10-1016-j-jma-2023-05-007", "qa_index": 4, "question": "How long were the exosome-associated release effects observed?", "answer": "The article reports an experimental release window of approximately 5–7 days; this should not be interpreted as an established clinical delivery period.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#qa-4", "question_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/3/answer", "answer_sha256": "80bd06f5a86178557c3ada7467df168c9bed6dcb7a5076f10f1a5a4450bc0ef4", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jma-2023-05-007--qa-5", "work_id": "doi-10-1016-j-jma-2023-05-007", "qa_index": 5, "question": "What did the 21-day animal experiment measure?", "answer": "Fifteen rats were assigned across three abdominal-aorta wire conditions, with representative H&E tissue sections at day 21. This is not quantitative human stent patency evidence.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#qa-5", "question_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/4/answer", "answer_sha256": "6097170d770d07f39e636a24d53bfbf6d4cb423ef49b263bac941e92dd7d9216", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1016-j-jma-2023-05-007--qa-6", "work_id": "doi-10-1016-j-jma-2023-05-007", "qa_index": 6, "question": "Is every figure-level source available?", "answer": "No. The original Figure S1 for full Western blot imaging was not in the source pack, so its content is not used as verified evidence in this summary.", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-jma-2023-05-007.html#qa-6", "question_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1016-j-jma-2023-05-007.json#/qa/5/answer", "answer_sha256": "7239e5bc917ccea58636bdb48893e9a9edfc041d328626aa0a0ec5350ee445f1", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-17789--qa-1", "work_id": "doi-10-1111-jcmm-17789", "qa_index": 1, "question": "What kind of DCM evidence does this paper provide?", "answer": "Human case-control plasma miRNA expression profiling with an external assay phase; it is not a treatment trial or prospective prediction study.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html#qa-1", "question_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/0/answer", "answer_sha256": "9f97fa2ea5829902f3de826a63654baf0eebae1153cdaa70daf4c5780626e323", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-17789--qa-2", "work_id": "doi-10-1111-jcmm-17789", "qa_index": 2, "question": "How many differential miRNA features were reported?", "answer": "The final Results screen reports 92 features, split into 48 upregulated and 44 downregulated, using absolute logFC >0.5 and P<0.05. Fig. 3A prints a different logFC threshold; this discrepancy is not silently reconciled.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html#qa-2", "question_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/1/answer", "answer_sha256": "3332619770d042d320cd64f04770efc84deb248a3c62c877a65caade0f1ad957", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-17789--qa-3", "work_id": "doi-10-1111-jcmm-17789", "qa_index": 3, "question": "Were the predicted pathways and miRNA targets experimentally established?", "answer": "No. Target, enrichment and network analyses nominate relationships; the 55-node, 59-edge miRNA-mRNA network does not establish direct target binding or pathway causality.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html#qa-3", "question_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/2/answer", "answer_sha256": "dfc041055b744d6f09ff7913409981982ff758103033f9f185d0d6be1db4faf5", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-17789--qa-4", "work_id": "doi-10-1111-jcmm-17789", "qa_index": 4, "question": "What was evaluated in the external population?", "answer": "Ten selected hub miRNAs were assessed by qRT-PCR in 10 DCM patients and 6 healthy controls. Expression-distance and PCoA analyses supported group differences, not clinical diagnostic utility.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html#qa-4", "question_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/3/answer", "answer_sha256": "2e79488d967094d56ec6e58ca17667cc11cd37c6b8d589214fe25087b032ee13", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-17789--qa-5", "work_id": "doi-10-1111-jcmm-17789", "qa_index": 5, "question": "Was miR-185-5p one of the externally tested hub miRNAs?", "answer": "No. It appears in Table 1 with logFC 1.04 and P=0.0322 and in the predicted-network discussion, but is absent from the 10-miRNA external qRT-PCR list.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html#qa-5", "question_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/4/answer", "answer_sha256": "b016e44e656bd00ba5716077c94b79453341de0f0a395aff35611845b2f61ba7", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1111-jcmm-17789--qa-6", "work_id": "doi-10-1111-jcmm-17789", "qa_index": 6, "question": "Can the results be treated as a measured whole-plasma or myocardial tissue signature?", "answer": "No. The reported study concerns isolated plasma vesicle-associated RNA. It does not establish myocardial origin or interchangeability with whole-plasma RNA measurements.", "answer_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-17789.html#qa-6", "question_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1111-jcmm-17789.json#/qa/5/answer", "answer_sha256": "8a9627884e1dac1dfc768cc2dfa314c09c6375157e4366f36c2e487c49e3ab3a", "evidence_refs": [ "KF1", "KF2" ], "evidence_refs_status": "resolved" }, { "id": "idebenone-ferroptosis--qa-1", "work_id": "idebenone-ferroptosis", "qa_index": 1, "question": "What cellular injury model was used?", "answer": "Idebenone pretreatment reduced reported H2O2-associated injury in H9c2 cells, assessed using cell viability, ROS and lipid-peroxidation readouts. H2O2-associated cell death is not exclusively ferroptosis, and these observations do not exclude other protective actions.", "answer_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#qa-1", "question_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/0/question", "answer_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/0/answer", "answer_sha256": "da93ebf3716541345d29540443fecc141a3359b5beeb47ab4b973f08e348159c", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "idebenone-ferroptosis--qa-2", "work_id": "idebenone-ferroptosis", "qa_index": 2, "question": "What evidence specifically addresses ferroptosis?", "answer": "RSL3 experiments, ferroptosis-related interventions and GPX4/FTH1/FPN1 readouts supported ferroptosis involvement; DFO/ferrostatin-1-related controls were described in the text. This is experimental mechanistic support. Marker changes do not by themselves establish a complete, specific causal chain.", "answer_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#qa-2", "question_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/1/question", "answer_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/1/answer", "answer_sha256": "c5a153eb112fd2986937207cbe439e3fe561f4f6d6dd65fb9d5cf9290b600c03", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "idebenone-ferroptosis--qa-3", "work_id": "idebenone-ferroptosis", "qa_index": 3, "question": "How strong is the proposed autophagy/AMPK-mTOR pathway evidence?", "answer": "Metformin/rapamycin experiments and AMPK-mTOR-related readouts supported the proposed pathway, alongside LC3/p62 and autophagy-associated observations. Pharmacologic perturbations are not complete gene-specific validation. These results do not imply that all ferroptosis depends on autophagy.", "answer_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#qa-3", "question_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/2/question", "answer_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/2/answer", "answer_sha256": "f64370934f421bdb6b263d81be790360f7cc81dc2d1eddca399b51f1030e53a3", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "idebenone-ferroptosis--qa-4", "work_id": "idebenone-ferroptosis", "qa_index": 4, "question": "Was idebenone started only after myocardial infarction?", "answer": "The LAD-ligation model used three main groups—sham+vehicle, MI+vehicle and MI+idebenone—with dosing 24 h and 2 h before surgery followed by continued dosing and short- and longer-term observations. This is a pretreatment-containing perioperative regimen, not a validated rescue regimen initiated exclusively after myocardial infarction. No dose recommendation or cross-species conversion is supplied.", "answer_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#qa-4", "question_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/3/question", "answer_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/3/answer", "answer_sha256": "06a1d79f4dbd3f39a7127d987ed4a368563fec89ac408887aba2091adfbc6a28", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "idebenone-ferroptosis--qa-5", "work_id": "idebenone-ferroptosis", "qa_index": 5, "question": "What mouse cardiac-function result was reported?", "answer": "At four weeks, Results reported EF of 21.82% in MI and 33.76% in MI+idebenone, with Fig. 8 reporting n=5; histological/fibrosis readouts also improved qualitatively. The percentages are EF values themselves, not relative percentage improvements. Mouse cardiac-function and histological observations do not establish human survival benefit or clinical utility.", "answer_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#qa-5", "question_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/4/question", "answer_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/4/answer", "answer_sha256": "51f7d9864a44bf30e1e6d6386444d233a032cd72b18afcc6ba3dfb8503b7ef04", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "idebenone-ferroptosis--qa-6", "work_id": "idebenone-ferroptosis", "qa_index": 6, "question": "Do myocardial molecular changes establish human clinical efficacy?", "answer": "Myocardial oxidative, iron-handling and autophagy-associated readouts changed with intervention, including ROS/MDA/Fe2+, GPX4/FTH1/FPN1, LC3/p62 and tissue observations. Readouts from different timepoints and materials cannot be treated as one continuous causal chain in a patient. Ambiguous fold-change wording is not recalculated into new effect sizes, and these tissue findings are not human clinical efficacy evidence.", "answer_url": "https://drgezhang.com/papers/idebenone-ferroptosis.html#qa-6", "question_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/5/question", "answer_source": "data/deep_geo/idebenone-ferroptosis.json#/qa/5/answer", "answer_sha256": "9ea6d9471c1e929d3f9eb053a8aa246d377ac4c05f55da2ff60f3cdce7841059", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18063-ijb-740--qa-1", "work_id": "doi-10-18063-ijb-740", "qa_index": 1, "question": "Is this an original patient study of printed vascular grafts?", "answer": "No. It is a narrative review of materials, printing processes and translation challenges. It has no newly recruited clinical cohort and no pooled patient-effect estimate.", "answer_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#qa-1", "question_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/0/answer", "answer_sha256": "9f1020f9a423172254a2da758dd719b6f43361b152a19b57e7f413a5c44067fe", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18063-ijb-740--qa-2", "work_id": "doi-10-18063-ijb-740", "qa_index": 2, "question": "Why is printing a hollow channel insufficient for a vascular graft?", "answer": "The review connects vessel geometry with endothelial function, supportive smooth muscle and fibroblast roles, extracellular matrix, mechanical behavior and nutrient transport. A channel alone does not establish patency or clinical durability.", "answer_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#qa-2", "question_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/1/answer", "answer_sha256": "82d0acfcb59b006ecdcd631a87114527f8d63684bf23b194c1bdd5410eeaa4a0", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18063-ijb-740--qa-3", "work_id": "doi-10-18063-ijb-740", "qa_index": 3, "question": "What is the difference between supportive and sacrificial materials?", "answer": "Supportive materials help form and stabilize the construct. Sacrificial materials create temporary templates that can be removed to leave a lumen. The role depends on formulation and fabrication strategy.", "answer_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#qa-3", "question_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/2/answer", "answer_sha256": "b98158f3bfd71c6501e3c79ae9a79f24937a287d07454687f44b513b22a8c242", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18063-ijb-740--qa-4", "work_id": "doi-10-18063-ijb-740", "qa_index": 4, "question": "Why does increasing ink viscosity not solve every printing problem?", "answer": "Higher viscosity can help preserve geometry but may require higher extrusion pressure and increase cell stress. Crosslinking, cell loading and transport also matter, so printability and biological performance must be balanced.", "answer_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#qa-4", "question_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/3/answer", "answer_sha256": "405409e76e28fae6278ed453260e14e0dd242ca42bb50190709de5a9d60f89b3", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18063-ijb-740--qa-5", "work_id": "doi-10-18063-ijb-740", "qa_index": 5, "question": "Which fabrication approaches are compared?", "answer": "The review summarizes extrusion, material jetting and vat polymerization, then discusses FRESH as an embedded-support strategy. Their constraints differ and the review is not a controlled clinical comparison.", "answer_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#qa-5", "question_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/4/answer", "answer_sha256": "d0cc6d1cd1d29c201d53a0e77af07bc331f7f3faa7ab946228cff2845377f0d5", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18063-ijb-740--qa-6", "work_id": "doi-10-18063-ijb-740", "qa_index": 6, "question": "What does the 199 +/- 41 micrometre FRESH value describe?", "answer": "It is the diameter of a representative alginate filament in the cited Hinton et al. technical experiment. It is not a patient outcome, a graft lumen diameter or a measurement newly generated by this review.", "answer_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#qa-6", "question_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/5/answer", "answer_sha256": "b8df17951126973ba87df7fa182a20e62b41fa366aeec9be1fe905edebf83e1b", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-18063-ijb-740--qa-7", "work_id": "doi-10-18063-ijb-740", "qa_index": 7, "question": "Does the review demonstrate clinical benefit or regulatory approval?", "answer": "No. It describes engineering and preclinical evidence and translation barriers. Its statement about the absence of reported clinical cases is tied to the 2023 review context and is not an updated inventory of every trial or product.", "answer_url": "https://drgezhang.com/papers/doi-10-18063-ijb-740.html#qa-7", "question_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-18063-ijb-740.json#/qa/6/answer", "answer_sha256": "c80e64270db3c20dcf4929473a564f4623d9eeff45cd14aa9310bf9f8ab5d7cc", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "smc-fate--qa-1", "work_id": "smc-fate", "qa_index": 1, "question": "How heterogeneous are vascular smooth muscle cells in human atherosclerotic plaques?", "answer": "The study retained 11,756 post-QC plaque cells from four donors. Among 5,419 SMCs analyzed in depth, nine transcriptionally distinct SMC clusters were identified, with differences in contractile, inflammatory, matrix-associated and other state-related programs.", "answer_url": "https://drgezhang.com/papers/smc-fate.html#qa-1", "question_source": "data/deep_geo/smc-fate.json#/qa/0/question", "answer_source": "data/deep_geo/smc-fate.json#/qa/0/answer", "answer_sha256": "6371db1ce233f3cc0e62bf94548190d61de256ac604e29e807cfbae4f717f672", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "smc-fate--qa-2", "work_id": "smc-fate", "qa_index": 2, "question": "How were SMC fate transitions reconstructed in this study?", "answer": "Monocle2 pseudotime analysis organized plaque SMCs into five computational differentiation states. SMC4 and SMC6 were enriched near the beginning of the trajectory, SMC2, SMC5 and SMC7 in intermediate high-plasticity states, and SMC1, SMC8 and SMC9 in terminal states.", "answer_url": "https://drgezhang.com/papers/smc-fate.html#qa-2", "question_source": "data/deep_geo/smc-fate.json#/qa/1/question", "answer_source": "data/deep_geo/smc-fate.json#/qa/1/answer", "answer_sha256": "48aaf013f07fdda0fddcc039ac72e1455d0555f2a174e971bcfd264027f4da3c", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "smc-fate--qa-3", "work_id": "smc-fate", "qa_index": 3, "question": "What is the SMC cell fate decision signature (SCFDS)?", "answer": "SCFDS was derived after identifying 1,072 SMC cell-fate leader genes and grouping them into eight temporal Mfuzz modules. Progressively upregulated and downregulated modules, identified as Cluster 2 and Cluster 6, were used to represent SMC cell-fate-associated transcriptional programs.", "answer_url": "https://drgezhang.com/papers/smc-fate.html#qa-3", "question_source": "data/deep_geo/smc-fate.json#/qa/2/question", "answer_source": "data/deep_geo/smc-fate.json#/qa/2/answer", "answer_sha256": "fe767a18461bebd2f4788c53d472c3ffadc49a7bf3d20bec4407981ad417c4ba", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "smc-fate--qa-4", "work_id": "smc-fate", "qa_index": 4, "question": "Can SMC fate-associated signatures define molecular subtypes of atherosclerosis?", "answer": "In the retrospective discovery analysis, SCFDS supported three molecular subtypes: C1 DNA-damage repair type, C2 immune-activated type and C3 stromal-rich type. These subtypes showed distinct pathway and coronary stenosis patterns.", "answer_url": "https://drgezhang.com/papers/smc-fate.html#qa-4", "question_source": "data/deep_geo/smc-fate.json#/qa/3/question", "answer_source": "data/deep_geo/smc-fate.json#/qa/3/answer", "answer_sha256": "3cf0337d859a7072c35603d13de1c6306303b45637d1aeb4b779fb3ad55da4b2", "evidence_refs": [ "KF4", "KF6" ], "evidence_refs_status": "resolved" }, { "id": "smc-fate--qa-5", "work_id": "smc-fate", "qa_index": 5, "question": "Which SCFDS subtype was associated with more severe coronary stenosis?", "answer": "C2, the immune-activated subtype, showed greater coronary stenosis severity in the discovery analysis, whereas C3 showed lower severity. This was an association and does not establish that the subtype causes the difference in stenosis.", "answer_url": "https://drgezhang.com/papers/smc-fate.html#qa-5", "question_source": "data/deep_geo/smc-fate.json#/qa/4/question", "answer_source": "data/deep_geo/smc-fate.json#/qa/4/answer", "answer_sha256": "a3eb295bdafc7b058915e973a766790364a1fcafe64321bfba1c4889ff7f7644", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "smc-fate--qa-6", "work_id": "smc-fate", "qa_index": 6, "question": "What biological programs distinguish C1, C2 and C3?", "answer": "C1 was enriched for DNA-repair, replication and oxidative-phosphorylation programs; C2 for immune and inflammatory activation; and C3 for stromal, extracellular-matrix and fibrous programs with a relatively immune-suppressed microenvironment.", "answer_url": "https://drgezhang.com/papers/smc-fate.html#qa-6", "question_source": "data/deep_geo/smc-fate.json#/qa/5/question", "answer_source": "data/deep_geo/smc-fate.json#/qa/5/answer", "answer_sha256": "2d2dd5495f9181315e4fb81452a2bde9c7976f34d21bba6b85d4621f1bae725a", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "smc-fate--qa-7", "work_id": "smc-fate", "qa_index": 7, "question": "Were the SCFDS subtypes externally validated?", "answer": "Their expression-template structure was evaluated by nearest-template prediction across five independent retrospective transcriptomic cohorts from different platforms. This supports cross-cohort reproducibility but is not prospective clinical validation.", "answer_url": "https://drgezhang.com/papers/smc-fate.html#qa-7", "question_source": "data/deep_geo/smc-fate.json#/qa/6/question", "answer_source": "data/deep_geo/smc-fate.json#/qa/6/answer", "answer_sha256": "39ac7bf18b7cacbe98aca2ab7e5a51a7e66e664f6fe93beb21de4f4b51bd31cb", "evidence_refs": [ "KF5" ], "evidence_refs_status": "resolved" }, { "id": "smc-fate--qa-8", "work_id": "smc-fate", "qa_index": 8, "question": "Has SCFDS been prospectively validated for clinical decision-making or treatment selection?", "answer": "No. The study was retrospective and primarily computational. The authors explicitly called for additional experimental validation and prospective multicenter studies before clinical relevance or treatment-guided utility can be established.", "answer_url": "https://drgezhang.com/papers/smc-fate.html#qa-8", "question_source": "data/deep_geo/smc-fate.json#/qa/7/question", "answer_source": "data/deep_geo/smc-fate.json#/qa/7/answer", "answer_sha256": "0d8167a621a08d5d695793ad04c1f2bf6cc0dec969fcbf67be7fe68987d55378", "evidence_refs": [], "evidence_refs_status": "not_encoded" }, { "id": "doi-10-1002-ehf2-14003--qa-1", "work_id": "doi-10-1002-ehf2-14003", "qa_index": 1, "question": "Which datasets identified the shared COVID-19 and HF genes?", "answer": "The comparison used independent COVID-19 and HF transcriptomic datasets, principally GSE147507 for the human COVID-19 lung component and GSE26887 for HF left-ventricular tissue. These were separate disease datasets, not samples from a simultaneous-comorbidity cohort.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#qa-1", "question_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/0/answer", "answer_sha256": "ad7455fac69f7d7a95fb38c47d226330982befcb36de7d83151c93af288f83c0", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ehf2-14003--qa-2", "work_id": "doi-10-1002-ehf2-14003", "qa_index": 2, "question": "What were the 12 shared COVID-19 and HF genes?", "answer": "S100A8, ABCB1, S100A11, PTGS2 (called COX2 in the article), LY96, XCL1, RORA, CCL11, CCL4, S100A12, BCL2 and AQP9 were shared at |log2FC| > 1 and adjusted P < 0.05 across the separate expression analyses.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#qa-2", "question_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/1/answer", "answer_sha256": "280d1d1cbc6245f7a21f5920e8585d02e325c8833e0c9bfcab33f75bef6923e3", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ehf2-14003--qa-3", "work_id": "doi-10-1002-ehf2-14003", "qa_index": 3, "question": "Which genes were prioritized as network hubs?", "answer": "The PPI analysis prioritized TLR4, TLR2, CXCL8, IL10, STAT3, IL1B, TLR1, TP53, CCL20 and CXCL10; seven cytoHubba algorithms converged on TLR4, TLR2, IL10 and STAT3. Network centrality is not proof of causal disease drivers.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#qa-3", "question_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/2/answer", "answer_sha256": "a61c19ecfcd6d3f6771af04890dcc24179bb38fceeb46a8a5241f7d19032f972", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ehf2-14003--qa-4", "work_id": "doi-10-1002-ehf2-14003", "qa_index": 4, "question": "Did the study analyze patients with both COVID-19 and HF, and what does ‘genetic links’ mean?", "answer": "No dedicated cohort simultaneously affected by COVID-19 and HF was analyzed. In this paper, ‘genetic links’ refers to shared transcriptomic, gene-expression, molecular and predicted regulatory signatures across independent datasets, not germline genetic correlation, GWAS, Mendelian randomization or genetic causality.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#qa-4", "question_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/3/answer", "answer_sha256": "dc128d9d2e983b28a70e0bd644182f43f54bb1edb54bf4dadaeb425d136b5e4f", "evidence_refs": [ "KF1", "KF3", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ehf2-14003--qa-5", "work_id": "doi-10-1002-ehf2-14003", "qa_index": 5, "question": "Was the five-gene signature clinically validated, and do 96.0% and 93.2% mean diagnostic accuracy?", "answer": "No prospective clinical validation or diagnostic-accuracy study was reported. The 96.0% COVID-19 and 93.2% HF values, alongside 89.9% for merged data, are variance explained by the first two PCA components in the five-gene analysis; they are not AUC, accuracy, sensitivity or specificity.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#qa-5", "question_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/4/question", "answer_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/4/answer", "answer_sha256": "90b1396d1e477bddf81e5ba76d125b469e946740b50da757c7a715109c351da2", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ehf2-14003--qa-6", "work_id": "doi-10-1002-ehf2-14003", "qa_index": 6, "question": "Did the study prove a gut-microbiome or circulating-LPS mechanism?", "answer": "No. Gut-heart and LPS discussion is hypothesis-generating; stool microbiome composition, intestinal permeability and circulating LPS were not directly measured in this analysis.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#qa-6", "question_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/5/question", "answer_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/5/answer", "answer_sha256": "bbc9a9fb05786084d89245845b3b6b012871d5c03e8abeac0bec3fa0b90cc52b", "evidence_refs": [ "KF2", "KF5" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ehf2-14003--qa-7", "work_id": "doi-10-1002-ehf2-14003", "qa_index": 7, "question": "Did glutathione or muramyl dipeptide treat COVID-19 or heart failure in this study?", "answer": "No treatment efficacy was tested or demonstrated. Glutathione and muramyl dipeptide were DSigDB-prioritized in-silico drug-signature candidates based on five genes, requiring experimental and clinical evaluation before any therapeutic claim.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#qa-7", "question_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/6/question", "answer_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/6/answer", "answer_sha256": "60e5fb2227770d14d508f28973310ae0c58584027608089f4025319f9f76ecc8", "evidence_refs": [ "KF6" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-1002-ehf2-14003--qa-8", "work_id": "doi-10-1002-ehf2-14003", "qa_index": 8, "question": "Why does Figure 1 mention GSE26687, and which HF dataset was used?", "answer": "GSE26687 in the Figure 1 caption appears to be an accession typo. The Methods and Results, together with the formal GEO identity, identify GSE26887 as the HF cardiac-tissue dataset; the apparent typo is recorded for provenance and is not treated as a second dataset.", "answer_url": "https://drgezhang.com/papers/doi-10-1002-ehf2-14003.html#qa-8", "question_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/7/question", "answer_source": "data/deep_geo/doi-10-1002-ehf2-14003.json#/qa/7/answer", "answer_sha256": "0743f3df3741ad0d2d10dad69e07414d72eb1c6d2ed03badb84953351eb4cede", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2021-659217--qa-1", "work_id": "doi-10-3389-fonc-2021-659217", "qa_index": 1, "question": "Why do enrollment, safety and efficacy denominators differ?", "answer": "Thirty-two patients enrolled; six withdrew before treatment, leaving 26 in the FAS/safety population and 24 in the efficacy analysis. The unique total of 32 is enrollment only, not the response-rate denominator. Enrollment, treated and efficacy populations overlap and must not be added together.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2021-659217.html#qa-1", "question_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/qa/0/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/qa/0/answer", "answer_sha256": "320f59ab8150af46c0587621352e5bb152c0d2521997944593c85e8dd6314746", "evidence_refs": [ "KF1" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2021-659217--qa-2", "work_id": "doi-10-3389-fonc-2021-659217", "qa_index": 2, "question": "What response and disease-control results were reported?", "answer": "Among 24 efficacy-evaluable patients, responses were CR 1, PR 4, SD 10 and PD 9; ORR was 20.8% and DCR was 62.5%. These are observations without a concurrent control. ORR uses the reported percentage interval; DCR uses the Results-reported percentage interval, not the survival-day interval printed in the abstract.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2021-659217.html#qa-2", "question_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/qa/1/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/qa/1/answer", "answer_sha256": "8d11b3ae7830c05c68d7a3ece148dd06fb9185e7aac1eed56d4d87bddb4af5e7", "evidence_refs": [ "KF2" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2021-659217--qa-3", "work_id": "doi-10-3389-fonc-2021-659217", "qa_index": 3, "question": "Do the survival estimates establish comparative benefit?", "answer": "Median PFS was 95 days (reported 95% CI 79.70–154.34 days), and median OS was 250 days (reported 95% CI 112.86–387.14 days). Without a concurrent comparison, these observed survival times do not establish a survival gain or comparative benefit.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2021-659217.html#qa-3", "question_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/qa/2/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/qa/2/answer", "answer_sha256": "17b33b96eb4e0657ff9aaa1d0a33dd6132f58c80fd74e8a48683de3d7950f1bc", "evidence_refs": [ "KF3" ], "evidence_refs_status": "resolved" }, { "id": "doi-10-3389-fonc-2021-659217--qa-4", "work_id": "doi-10-3389-fonc-2021-659217", "qa_index": 4, "question": "Were all toxicities mild, and what safety denominator was used?", "answer": "In the safety population of 26, myelosuppression, hypertension and proteinuria were reported in 69.2%, 57.7% and 46.2%; Grade 3 hypertension and leukopenia each occurred in three patients. No Grade 4 events or drug-related deaths were reported. Adverse-event categories overlap and cannot be summed as independent patients; absence of observed events in a small sample does not establish absence of risk.", "answer_url": "https://drgezhang.com/papers/doi-10-3389-fonc-2021-659217.html#qa-4", "question_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/qa/3/question", "answer_source": "data/deep_geo/doi-10-3389-fonc-2021-659217.json#/qa/3/answer", "answer_sha256": "90bfda4f932eb1c1c157078fba63f31d3bc428b28a6338cec4927ffbcbe6f63a", "evidence_refs": [ "KF4" ], "evidence_refs_status": "resolved" } ], "intent_layer_version": 1, "intent_sources": [ { "id": "hf-omics-hf-ai-review-2018", "title": "Artificial Intelligence in Cardiology", "doi": "10.1016/j.jacc.2018.03.521", "url": "https://doi.org/10.1016/j.jacc.2018.03.521", "year": 2018, "locator": "Clinician-oriented AI/ML methods, cardiovascular applications and incorporation into practice." }, { "id": "hf-omics-hf-ml-review-2017", "title": "Heart Failure: Diagnosis, Severity Estimation and Prediction of Adverse Events Through Machine Learning Techniques", "doi": "10.1016/j.csbj.2016.11.001", "url": "https://doi.org/10.1016/j.csbj.2016.11.001", "year": 2016, "locator": "The actual review separates detection, subtypes, severity, adverse events, rehospitalisation and mortality. Its summary discusses differing data sources and comparison of methods." }, { "id": "hf-omics-tripod-ai-2024", "title": "TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods", "doi": "10.1136/bmj-2023-078378", "url": "https://doi.org/10.1136/bmj-2023-078378", "year": 2024, "locator": "The checklist covers development/evaluation context and transparent reporting; model evaluation, discrimination, calibration and clinical role are distinct information needs." }, { "id": "hf-omics-cvd-multiomics-2021", "title": "Systems biology in cardiovascular disease: a multiomics approach", "doi": "10.1038/s41569-020-00477-1", "url": "https://doi.org/10.1038/s41569-020-00477-1", "year": 2020, "locator": "The review combines network theory with gene regulation, proteomics, metabolomics, lipidomics and phenomics; independent biological validation accompanies integration." }, { "id": "hf-omics-multiomics-review-2017", "title": "Multi-omics approaches to disease", "doi": "10.1186/s13059-017-1215-1", "url": "https://doi.org/10.1186/s13059-017-1215-1", "year": 2017, "locator": "The review organises integrative analyses as genome-first, phenotype-first and environment-first, with study design, phenotyping, analytical integration and resolution as recurring needs." }, { "id": "hf-omics-proteomics-review-2026", "title": "Proteomics in cardiology: research and practice", "doi": "10.1136/heartjnl-2025-326751", "url": "https://doi.org/10.1136/heartjnl-2025-326751", "year": 2026, "locator": "Recent review structures applications around disease mechanisms, prediction/detection, patient stratification and therapeutic-target prioritisation. It highlights reliable measurement, multiple platforms, longitudinal sampling and ancestry diversity." }, { "id": "vsmc-circadian-vc1", "title": "Vascular Smooth Muscle Cells in Atherosclerosis", "doi": "10.1161/CIRCRESAHA.115.306361", "url": "https://doi.org/10.1161/CIRCRESAHA.115.306361", "year": 2016, "locator": "PMC4762053 body/sec[@id=\"S2\"]; PMC4762053 body/sec[@id=\"S4\"]; PMC4762053 body/sec[@id=\"S8\"]" }, { "id": "vsmc-circadian-vc2", "title": "Vascular smooth muscle cells in atherosclerosis", "doi": "10.1038/s41569-019-0227-9", "url": "https://doi.org/10.1038/s41569-019-0227-9", "year": 2019, "locator": "Publisher indexed Abstract and Key points; Figures1–4 captions; PubMed31243391 abstract" }, { "id": "vsmc-circadian-vc3", "title": "Vascular smooth muscle cells in atherosclerosis: time for a re-assessment", "doi": "10.1093/cvr/cvab046", "url": "https://doi.org/10.1093/cvr/cvab046", "year": 2021, "locator": "Publisher Abstract; PubMed33576407 abstract" }, { "id": "vsmc-circadian-vc4", "title": "Vascular smooth muscle cell metabolic reprogramming and phenotypic remodeling in atherosclerosis", "doi": "10.1038/s41420-025-02932-9", "url": "https://doi.org/10.1038/s41420-025-02932-9", "year": 2025, "locator": "PMC12847746 body/sec[@id=\"Sec3\"]; PMC12847746 body/sec[@id=\"Sec27\"]; PMC12847746 body/sec[@id=\"Sec32\"]" }, { "id": "vsmc-circadian-vc5", "title": "Efferocytosis in health and disease", "doi": "10.1038/s41577-019-0240-6", "url": "https://doi.org/10.1038/s41577-019-0240-6", "year": 2019, "locator": "Publisher Abstract; Publisher Figure2 caption and references74–78; PubMed31822793 abstract" }, { "id": "vsmc-circadian-cr1", "title": "Circadian rhythms and the molecular clock in cardiovascular biology and disease", "doi": "10.1038/s41569-019-0167-4", "url": "https://doi.org/10.1038/s41569-019-0167-4", "year": 2019, "locator": "PubMed30796369 / official bibliographic abstract; cardiovascular cell-type, physiology/disease and timing structure" }, { "id": "vsmc-circadian-cr2", "title": "Clocking in to immunity", "doi": "10.1038/s41577-018-0008-4", "url": "https://doi.org/10.1038/s41577-018-0008-4", "year": 2018, "locator": "PubMed29662121 / official bibliographic abstract; immunity mechanisms and chrono-immunotherapy scope" }, { "id": "vsmc-circadian-cr3", "title": "The emerging link between cancer, metabolism, and circadian rhythms", "doi": "10.1038/s41591-018-0271-8", "url": "https://doi.org/10.1038/s41591-018-0271-8", "year": 2018, "locator": "PMC6535395 body/sec[@id=\"S1\"]; PMC6535395 body/sec[@id=\"S5\"]; PMC6535395 body/sec[@id=\"S8\"]" }, { "id": "vsmc-circadian-cr4", "title": "Metabolic rivalry: circadian homeostasis and tumorigenesis", "doi": "10.1038/s41568-020-0291-9", "url": "https://doi.org/10.1038/s41568-020-0291-9", "year": 2020, "locator": "PubMed32895495 abstract; publisher abstract and Figure5 temporal communication description" }, { "id": "vsmc-circadian-cr5", "title": "Role of Circadian Health in 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Immunoscore in cancer prognosis and therapeutic efficacy", "doi": "10.1038/s41568-020-0285-7", "url": "https://doi.org/10.1038/s41568-020-0285-7", "year": 2020, "locator": "PubMed32753728 Abstract; Publisher indexed abstract; Figure1 heading only" }, { "id": "onco-agent-onco-s4", "title": "2022 ESC Guidelines on cardio-oncology developed in collaboration with the European Hematology Association (EHA), the European Society for Therapeutic Radiology and Oncology (ESTRO) and the International Cardio-Oncology Society (IC-OS)", "doi": "10.1093/eurheartj/ehac244", "url": "https://doi.org/10.1093/eurheartj/ehac244", "year": 2022, "locator": "Official ESC guideline title/date/scope description; Publisher contents section5.5.9 identity" }, { "id": "onco-agent-onco-s5", "title": "Immune-checkpoint inhibitor-mediated myocarditis: CTLA4, PD1 and LAG3 in the heart", "doi": "10.1038/s41568-024-00715-5", "url": "https://doi.org/10.1038/s41568-024-00715-5", "year": 2024, "locator": "PubMed38982146 Abstract; EuropePMC core record38982146 abstractText" } ], "intents": [ { "id": "ai-heart-failure", "question": "How can AI support heart failure risk prediction, and how should prognostic models be validated?", "question_zh": "人工智能如何支持心衰风险预测，预后模型应如何接受验证？", "source_ids": [ "hf-omics-hf-ai-review-2018", "hf-omics-hf-ml-review-2017", "hf-omics-tripod-ai-2024" ], "focused_queries": [ { "id": "ai-heart-failure-1", "question": "Which interpretable survival models have been evaluated in heart failure with kidney dysfunction?", "question_zh": "哪些可解释生存模型在合并肾功能异常的心衰人群中接受过评估？", "work_refs": [ { "work_id": "aihflevel", "question_ids": [ "aihflevel--qa-1", "aihflevel--qa-3", "aihflevel--qa-4", "aihflevel--qa-7" ], "preview_question_id": "aihflevel--qa-1", "paper_url": "https://drgezhang.com/papers/aihflevel.html", "doi": "10.1038/s41467-024-50415-9", "doi_url": "https://doi.org/10.1038/s41467-024-50415-9", "scope_url": "https://drgezhang.com/papers/aihflevel.html#ev-scope", "citation_url": "https://drgezhang.com/papers/aihflevel.html#cite-this-paper" } ] }, { "id": "ai-heart-failure-2", "question": "What should be reported when comparing discrimination, calibration and external validation in heart failure models?", "question_zh": "比较心衰模型区分度、校准度和外部验证时应报告哪些证据？", "work_refs": [ { "work_id": "aihflevel", "question_ids": [ "aihflevel--qa-3", "aihflevel--qa-4", "aihflevel--qa-5" ], "preview_question_id": "aihflevel--qa-3", "paper_url": "https://drgezhang.com/papers/aihflevel.html", "doi": "10.1038/s41467-024-50415-9", "doi_url": "https://doi.org/10.1038/s41467-024-50415-9", "scope_url": "https://drgezhang.com/papers/aihflevel.html#ev-scope", "citation_url": "https://drgezhang.com/papers/aihflevel.html#cite-this-paper" } ] }, { "id": "ai-heart-failure-3", "question": "How can cardiovascular AI be evaluated when important modalities are missing or clinical data are out of date?", "question_zh": "关键模态缺失或临床数据过时时，心血管AI应怎样评估？", "work_refs": [ { "work_id": "doi-10-1016-j-medd-2026-100004", "question_ids": [ "doi-10-1016-j-medd-2026-100004--qa-1", "doi-10-1016-j-medd-2026-100004--qa-2", "doi-10-1016-j-medd-2026-100004--qa-3" ], "preview_question_id": "doi-10-1016-j-medd-2026-100004--qa-1", "paper_url": "https://drgezhang.com/papers/doi-10-1016-j-medd-2026-100004.html", "doi": "10.1016/j.medd.2026.100004", "doi_url": "https://doi.org/10.1016/j.medd.2026.100004", "scope_url": "https://drgezhang.com/papers/doi-10-1016-j-medd-2026-100004.html#ev-scope", "citation_url": "https://drgezhang.com/papers/doi-10-1016-j-medd-2026-100004.html#cite-this-paper" } ] } ] }, { "id": "vascular-cell-states", "question": "How do vascular cell states shape atherosclerotic plaque heterogeneity and stability?", "question_zh": "血管细胞状态如何影响动脉粥样硬化斑块的异质性与稳定性？", "source_ids": [ "vsmc-circadian-vc1", "vsmc-circadian-vc2", "vsmc-circadian-vc3", "vsmc-circadian-vc4", "vsmc-circadian-vc5" ], "focused_queries": [ { "id": "vascular-cell-states-1", "question": "Which smooth muscle cell states and transitions are found in human atherosclerotic plaques?", "question_zh": "人类粥样硬化斑块中存在哪些平滑肌细胞状态与状态转换？", "work_refs": [ { "work_id": "smc-fate", "question_ids": [ "smc-fate--qa-1", "smc-fate--qa-2", "smc-fate--qa-4", "smc-fate--qa-6" ], "preview_question_id": "smc-fate--qa-1", "paper_url": "https://drgezhang.com/papers/smc-fate.html", "doi": "10.1186/s12967-022-03795-9", "doi_url": "https://doi.org/10.1186/s12967-022-03795-9", "scope_url": "https://drgezhang.com/papers/smc-fate.html#ev-scope", "citation_url": "https://drgezhang.com/papers/smc-fate.html#cite-this-paper" } ] }, { "id": "vascular-cell-states-2", "question": "What connects inflammatory versus matrix-preserving smooth muscle programs with plaque stability?", "question_zh": "炎症型与基质维持型平滑肌程序如何关联斑块稳定性？", "work_refs": [ { "work_id": "doi-10-1172-jci194175", "question_ids": [ "doi-10-1172-jci194175--qa-2", "doi-10-1172-jci194175--qa-5", "doi-10-1172-jci194175--qa-6", "doi-10-1172-jci194175--qa-7" ], 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"work_id": "doi-10-1172-jci194175", "question_ids": [ "doi-10-1172-jci194175--qa-5", "doi-10-1172-jci194175--qa-6", "doi-10-1172-jci194175--qa-7", "doi-10-1172-jci194175--qa-9" ], "preview_question_id": "doi-10-1172-jci194175--qa-5", "paper_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html", "doi": "10.1172/jci194175", "doi_url": "https://doi.org/10.1172/jci194175", "scope_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#ev-scope", "citation_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#cite-this-paper" }, { "work_id": "doi-10-1093-eurheartj-ehaf523", "question_ids": [ "doi-10-1093-eurheartj-ehaf523--qa-2", "doi-10-1093-eurheartj-ehaf523--qa-4", "doi-10-1093-eurheartj-ehaf523--qa-5" ], "preview_question_id": "doi-10-1093-eurheartj-ehaf523--qa-4", "paper_url": "https://drgezhang.com/papers/doi-10-1093-eurheartj-ehaf523.html", "doi": "10.1093/eurheartj/ehaf523", "doi_url": "https://doi.org/10.1093/eurheartj/ehaf523", "scope_url": 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vascular disease biomarkers?", "question_zh": "循环细胞外囊泡蛋白组学能为血管疾病标志物提供什么线索？", "work_refs": [ { "work_id": "doi-10-1111-jcmm-70725", "question_ids": [ "doi-10-1111-jcmm-70725--qa-2", "doi-10-1111-jcmm-70725--qa-3", "doi-10-1111-jcmm-70725--qa-4", "doi-10-1111-jcmm-70725--qa-5" ], "preview_question_id": "doi-10-1111-jcmm-70725--qa-3", "paper_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html", "doi": "10.1111/jcmm.70725", "doi_url": "https://doi.org/10.1111/jcmm.70725", "scope_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#ev-scope", "citation_url": "https://drgezhang.com/papers/doi-10-1111-jcmm-70725.html#cite-this-paper" } ] }, { "id": "cardiovascular-biomarkers-3", "question": "What evidence links insulin-resistance markers and renal function with cardiovascular outcomes?", "question_zh": "胰岛素抵抗指标与肾功能和心血管结局之间有哪些研究证据？", "work_refs": [ { "work_id": "doi-10-2147-cia-s462542", "question_ids": [ "doi-10-2147-cia-s462542--qa-1", "doi-10-2147-cia-s462542--qa-3", 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of fusion, missing inputs, time, selective prediction and observation mechanisms.", "evidence": [ { "label": "problem categories", "value": "5" } ], "source_locator": "Corrected proof p. 1, opening paragraph", "source": "data/deep_geo/doi-10-1016-j-medd-2026-100004.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1016-j-medd-2026-100004.html#kf1" }, "key_finding_basis": "question_evidence_ref", "source": "data/deep_geo/doi-10-1016-j-medd-2026-100004.json#/qa/0/question", "profile_type": "narrative_review", "narrative_genre": "correspondence", "concepts": [ "cardiovascular artificial intelligence", "multimodal learning", "selective prediction", "informative missingness", "temporal validity", "evidence sufficiency", "deferral" ], "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1016-j-medd-2026-100004.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1016-j-medd-2026-100004.ris", "citation_csl_json_url": 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The variant encodes p.Gly131Ala; protein abundance measurements do not directly measure protein half-life or human disease penetrance.", "evidence": [ { "label": "post-transfection collection", "value": "48 hours" }, { "label": "independent experiments", "value": "3" }, { "label": "protein assay compartments", "value": "cell lysate and culture supernatant" } ], "source_locator": "Results 3.3; Figure 2d-h and caption; formal PDF pp. 5-6.", "source": "data/deep_geo/doi-10-1155-humu-5591097.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1155-humu-5591097.html#kf1" }, "key_finding_basis": "question_evidence_ref", "source": "data/deep_geo/doi-10-1155-humu-5591097.json#/qa/0/question", "profile_type": "preclinical_multimodal", "narrative_genre": null, "concepts": [ "primary open-angle glaucoma", "PAPPA2", "IGFBP5", "293T expression assay", "primary human trabecular-meshwork cells", "Pappa2-deficient mice", "qPCR", "western blotting", "immunofluorescence", "intraocular pressure measurement", "Masson staining" ], "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1155-humu-5591097.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1155-humu-5591097.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1155-humu-5591097.csl.json", "field_entry": [ "Experimental glaucoma biology", "Trabecular extracellular matrix regulation" ], "review_topics": [ "PAPPA2 and IGFBP5 in ocular fibrosis-associated responses", "Comparison of variant-expression assays and gene-deficiency models" ], "discovery_url": "https://drgezhang.com/papers/doi-10-1155-humu-5591097.html#paper-discovery", "evidence_scope_kind": "does_not_establish", "evidence_scope": "Independently reconciled family-wide counts, complete segregation, population allele frequency, penetrance or clinical pathogenicity of PAPPA2 c.392G>C." }, { "id": "doi-10-1126-science-aek9583", "title": "Recording results from single-patient trials", "doi": "10.1126/science.aek9583", "paper_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html", "question": "What public-record problem does this Science Letter address?", "answer_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#qa-1", "answer_preview": { "answer": "The authors describe a gap between a previously reported human outcome and the registry or preclinical publication, and argue that directly related human protocols and major outcomes should remain visible in current public records. The case is contextual evidence from other sources, not a new study in this Letter.", "source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/0/answer", "source_content_sha256": "705d1e430afa0be856894f2962dd2ce698dddc38294fd997dbcfccafa4a0a294", "answer_sha256": "0f30a5add0e3542d95a150ff113e7b62af7466d8ae536647684ddb65cf6f40bf", "evidence_refs": [ "KF1" ], "evidence_sources": [ { "id": "KF1", "source": "data/deep_geo/doi-10-1126-science-aek9583.json#/key_findings/0", "source_locator": "Print p. 38, right column, Letter paragraph 1", "evidence_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#kf1" } ], "does_not_establish": [ "A new clinical trial or a clinical dataset generated by the Letter's authors.", "The safety, efficacy or causal effect of an individualized genetic therapy.", "A quantitative reduction in reporting gaps or improved patient outcomes from the proposals.", "An independent adjudication of the reported case, blame or legal responsibility." ], "scope_source": "data/deep_geo/doi-10-1126-science-aek9583.json#/evidence_scope/does_not_establish" }, "key_finding": { "id": "KF1", "claim": "Keep directly related human protocols and major outcomes current in public registries.", "context": "The opening paragraph contrasts the previously reported human outcome with the registry and preclinical publication as described by the Letter. This is an attributed reporting-gap example, not an independently reconstructed clinical investigation.", "evidence": [ { "label": "Argument", "value": "Preserve the public translational record" } ], "source_locator": "Print p. 38, right column, Letter paragraph 1", "source": "data/deep_geo/doi-10-1126-science-aek9583.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#kf1" }, "key_finding_basis": "question_evidence_ref", "source": "data/deep_geo/doi-10-1126-science-aek9583.json#/qa/0/question", "profile_type": "narrative_review", "narrative_genre": "correspondence", "publication_type": "Letter", "concepts": [ "Public trial registry", "Human protocol disclosure", "Translational record linkage", "Dated publication notice", "Single-patient research context", "Treatment-emergent event reporting", "Event occurrence versus causality" ], "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1126-science-aek9583.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1126-science-aek9583.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1126-science-aek9583.csl.json", "field_entry": [ "Individualized genetic therapy research", "Clinical trial registration and reporting" ], "review_topics": [ "Reporting major human outcomes in individualized genetic therapies", "Linking preclinical publications and human trial records" ], "discovery_url": "https://drgezhang.com/papers/doi-10-1126-science-aek9583.html#paper-discovery", "evidence_scope_kind": "does_not_establish", "evidence_scope": "A new clinical trial or a clinical dataset generated by the Letter's authors." }, { "id": "doi-10-1038-s41698-026-01699-1", "title": "System biology analysis reveals circadian rhythm disorder associated with development and progression in colorectal cancer", "doi": "10.1038/s41698-026-01699-1", "paper_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html", "question": "What did the single-cell analysis show about circadian misalignment and the CRC tumor microenvironment?", "answer_url": "https://drgezhang.com/papers/doi-10-1038-s41698-026-01699-1.html#qa-4", "key_finding": { "id": "KF4", "claim": "ClockProCRC-defined circadian states were associated with distinct single-cell composition and intercellular-communication patterns in CRC.", "context": "Single-cell analysis in GSE200997 and GSE196964 using ClockProCRC state assignment, Ro/e enrichment and NICHES signaling analysis", "evidence": [ { "label": "single-cell evaluation cohorts", "value": "GSE200997 and GSE196964" }, { "label": "intensified-CRD enrichment pattern", "value": "epithelial and plasma-cell populations were preferentially enriched in higher-disruption states" }, { "label": "more stable-rhythm pattern", "value": "fibroblast and endothelial populations were preferentially enriched in lower-disruption/stable states" }, { "label": "communication pattern", "value": "higher-disruption states showed stronger epithelial/plasma interaction weights and altered pathway-level cell-cell signaling" }, { "label": "pathway pattern", "value": "progression from alleviate to intensify states was associated with reduced apoptotic-pathway activity and increased pro-inflammatory communication" } ], "source_locator": "Results: Dissecting the circadian rhythm disorder of colorectal cancer from single-cell resolution, Fig. 4A-G and Supplementary Fig. 3C-E; 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component conditions were evaluated at baseline and the follow-up wave, rather than using exact onset dates.", "evidence": [ { "label": "Analytic participants", "value": "6,534 adults aged 45 years or older" }, { "label": "Exposure and outcome waves", "value": "2011 baseline and 2015 follow-up" }, { "label": "Incident CLMM", "value": "406 participants; 6.2%" }, { "label": "Outcome definition", "value": "At least two of CVD, type 2 diabetes, and LAP-based suspected MASLD" } ], "source_locator": "Methods: Study population and Outcome assessment (jdi70462-sec-0007; jdi70462-sec-0009); Results 3.1 (jdi70462-sec-0013); Figure 1; Table 1", "source": "data/deep_geo/doi-10-1111-jdi-70462.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#kf1" }, "key_finding_basis": "question_evidence_ref", "source": "data/deep_geo/doi-10-1111-jdi-70462.json#/qa/0/question", "profile_type": "clinical_cohort", "narrative_genre": null, "concepts": [ "Cardiovascular–liver–metabolic multimorbidity", "Cardiovascular disease", "Type 2 diabetes", "LAP-based suspected MASLD", "Cholesterol–HDL–glucose index", "CHG-BMI", "Triglyceride–glucose index", "CHARLS", "Prospective observational cohort", "Logistic regression", "Apparent ROC discrimination" ], "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1111-jdi-70462.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1111-jdi-70462.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1111-jdi-70462.csl.json", "field_entry": [ "Cardiometabolic epidemiology", "Metabolic biomarker research" ], "review_topics": [ "Multimorbidity risk-marker evaluation", "Obesity-derived biochemical indices" ], "discovery_url": "https://drgezhang.com/papers/doi-10-1111-jdi-70462.html#paper-discovery", "evidence_scope_kind": "does_not_establish", "evidence_scope": "A causal effect of CHG, obesity, or inflammation on multimorbidity." }, { "id": "doi-10-1172-jci194175", "title": "Vascular smooth muscle cell-derived KIF13B inhibits proinflammatory responses to protect against atherosclerosis", "doi": "10.1172/jci194175", "paper_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html", "question": "What is the human evidence linking KIF13B to atherosclerotic plaque severity?", "answer_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#qa-1", "key_finding": { "id": "KF1", "claim": "Lower KIF13B was associated with more advanced or unstable human atherosclerotic plaque states, with prominent differences in VSMCs.", "context": "These human tissue and public-dataset observations are associative and do not establish that changing KIF13B alters plaque outcomes in patients.", "evidence": [ { "label": "Local carotid plaques", "value": "Six CEA patients contributed paired advanced and adjacent regions; Figure 1 reports lower KIF13B in advanced regions, with scRNA analysis n=4 per condition and protein/histologic analyses n=6 per condition." }, { "label": "GSE120521", "value": "KIF13B mRNA was lower in unstable than stable regions from four paired carotid plaques: n=4 stable and n=4 unstable." }, { "label": "PXD062283", "value": "KIF13B protein was lower in the JCI stable n=19 versus unstable n=38 plaque comparison." }, { "label": "Plaque matrix relationship", "value": "Human plaque analysis showed lower VSMC KIF13B and lower collagen in advanced regions, with a positive association between VSMC KIF13B signal and collagen content." }, { "label": "Epigenetic evidence", "value": "Supplementary public-dataset reanalysis associated higher KIF13B methylation with atherosclerotic versus control tissue and symptomatic versus asymptomatic plaque; this does not establish methylation as the cause of lower KIF13B." } ], "source_locator": "Results: Decreased expression of KIF13B in VSMCs is linked to the progression of atherosclerosis in humans; Figure 1; Supplemental Figure 1; Methods: Human studies.", "source": "data/deep_geo/doi-10-1172-jci194175.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#kf1" }, "key_finding_basis": "question_evidence_ref", "source": "data/deep_geo/doi-10-1172-jci194175.json#/qa/0/question", "profile_type": "multicohort_omics", "narrative_genre": null, "concepts": [ "KIF13B", "KCTD10", "KLF4", "CUL3-associated ubiquitin ligase", "protein ubiquitination", "proteasomal degradation", "vascular smooth muscle cell", "VSMC phenotypic switching", "VSMC-Fib", "fibrous-cap VSMC", "contractile VSMC", "matrix-producing VSMC", "proinflammatory fibroblast-like VSMC", "atherosclerotic lesion burden", "plaque stability", "fibrous cap", "collagen content", "necrotic core", "macrophage infiltration", "apoptosis", "vascular contractility", "Tagln-Cre Kif13b VSMC-specific knockout", "AAV8-PCSK9-D377Y", "Ldlr-deficient mouse", "Ldlr-deficient Kif13b-deficient mouse", "Western diet", "primary HASMC", "oxLDL", "siKIF13B", "KIF13B overexpression", "siKLF4", "KCTD10 overexpression", "Kenpaullone", "MG132", "cycloheximide", "GSE314838", "GSE120521", "PXD062283", "GSE274572", "human plaque DNA methylation datasets", "JCI Supporting Data Values", "atherosclerosis", "atherosclerotic cardiovascular disease", "carotid atherosclerotic plaque", "advanced plaque", "unstable plaque", "plaque vulnerability" ], "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-1172-jci194175.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-1172-jci194175.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-1172-jci194175.csl.json", "field_entry": [ "Atherosclerosis research", "Vascular smooth muscle biology" ], "review_topics": [ "Smooth muscle cell phenotypic remodeling", "Experimental regulation of plaque stability" ], "discovery_url": "https://drgezhang.com/papers/doi-10-1172-jci194175.html#paper-discovery", "evidence_scope_kind": "does_not_establish", "evidence_scope": "That low KIF13B expression or KIF13B methylation causes plaque instability in humans." }, { "id": "doi-10-1016-j-curpro-2025-100054", "title": "A Multimodal artificial intelligence framework for mechanistic discovery and digital twin construction in cardiovascular medicine", "doi": "10.1016/j.curpro.2025.100054", "paper_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html", "question": "Which research directions does the cardiovascular AI Correspondence propose for multimodal models?", "answer_url": "https://drgezhang.com/papers/doi-10-1016-j-curpro-2025-100054.html#qa-1", "key_finding": { "id": "KF1", "claim": "Develop multimodal AI along two directions: mechanism-oriented research and individualized digital twins.", "context": "The authors propose complementary research directions rather than introduce a clinically validated digital twin product.", "evidence": [ { "label": "Argument topic", "value": "Research agenda" }, { "label": "Evidence basis", "value": "Narrative synthesis" } ], "source_locator": "Publisher correspondence: To the Editor; 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the initial included population is not the analyzed sample size.", "evidence": [ { "label": "Initially included", "value": "815 patients" }, { "label": "Lost to follow-up", "value": "98 patients (12.0%)" }, { "label": "Analyzed", "value": "717 patients" }, { "label": "Median follow-up (IQR)", "value": "21.58 (17.98–25.39) months" }, { "label": "Renal dysfunction definition", "value": "eGFR <90 mL/min/1.73 m²" } ], "source_locator": "PMC11068055: Method — Study and Population, Inclusion Criteria, Exclusion Criteria, and Follow-Up; Figure 1; Results — Baseline Characteristics.", "source": "data/deep_geo/doi-10-2147-cia-s462542.json#/key_findings/0", "evidence_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#kf1" }, "key_finding_basis": "question_evidence_ref", "source": "data/deep_geo/doi-10-2147-cia-s462542.json#/qa/0/question", "profile_type": "clinical_cohort", "narrative_genre": null, "concepts": [ "Advanced chronic heart failure", "Renal dysfunction", "Cardiorenal risk", "Triglyceride-glucose index", "Insulin-resistance surrogate", "Retrospective cohort", "Cox proportional-hazards regression", "ROC threshold selection", "Prognostic association" ], "citation_bibtex_url": "https://drgezhang.com/citations/doi-10-2147-cia-s462542.bib", "citation_ris_url": "https://drgezhang.com/citations/doi-10-2147-cia-s462542.ris", "citation_csl_json_url": "https://drgezhang.com/citations/doi-10-2147-cia-s462542.csl.json", "field_entry": [ "Cardiorenal medicine", "Clinical prognosis" ], "review_topics": [ "Metabolic biomarkers in advanced heart failure", "Risk assessment with impaired kidney function" ], "discovery_url": "https://drgezhang.com/papers/doi-10-2147-cia-s462542.html#paper-discovery", "evidence_scope_kind": "does_not_establish", "evidence_scope": "Causality between insulin resistance and the observed events." }, { "id": "apvs", "title": "Atherosclerotic plaque vulnerability quantification system for clinical and biological interpretability", "doi": "10.1016/j.isci.2023.107587", "paper_url": "https://drgezhang.com/papers/apvs.html", "question": "What transcriptomic machine-learning signatures have been developed to characterize atherosclerotic plaque vulnerability?", "answer_url": "https://drgezhang.com/papers/apvs.html#cu1", "key_finding": { "id": "KF1", "claim": "The integrative machine-learning program reduced 96 dysregulated co-expression pattern genes to a 14-gene APVS signature.", "context": "APVS generation and model selection across nine classical machine-learning learners", "evidence": [ { "label": "candidate DCPGs", "value": "96" }, { "label": "machine-learning learners", "value": "9" }, { "label": "selected APVS genes", "value": "14" }, { "label": "optimal learners", "value": "random forest and backpropagation neural network" }, { "label": "learner evaluation", "value": "10-fold cross-validation with 100 repetitions" }, { "label": "feature selection", "value": "RF-RFE with 10-fold, 10-repeated cross-validation" } ], "source_locator": "Results: Machine learning-based integrative program generates APVS; 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