Paper context: A gene interaction network-based molecular taxonomy of dilated cardiomyopathy highlighting immune and inflammatory heterogeneity
multicohort omics
Supporting key finding
Four public myocardial datasets supplied discovery and external subtype-assignment data.
Article-reported analysis subsets for DCM network taxonomy; no newly recruited clinical cohort
- discovery subset: GSE5406: 86 DCM and 16 controls
- external subsets: GSE57338: 82/136; GSE116250: 37/14; GSE19303: 40/8 DCM/control samples
- reported sample totals: 245 DCM and 174 controls across four datasets; no verified unique-person total
Original-source locator: KF1 · Methods: Data collection and preprocessing (Par6); Results: Cohort characteristics and interactome construction (Par22); Table 1 (Tab1); Figure 2E-G
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiomyopathy molecular classification; Cardiovascular systems biology
Review topics: Myocardial transcriptomic heterogeneity; Network-based patient stratification
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
7 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What data underpin the DCM network subtypes?
- How were network perturbations constructed?
- How many molecular subtypes were identified?
- Were the immune differences measured directly in individual cells?
- Does EPS1 prove that immunoadsorption will work for a patient?
- What did the AC16-cell experiment validate?
- Can the subtype frequencies be used as population prevalence estimates?
Paper-level research concepts
- dilated cardiomyopathy
- heart failure
- myocardial heterogeneity
- edge perturbation
- gene-interaction network
- consensus clustering
- nearest-template prediction
- WGCNA
- ssGSEA
- Submap
- EPS1
- EPS2
- EPS3
- retrospective transcriptomic subtyping
- computational immune inference
- exploratory treatment-response matching
- AC16-cell expression check
Paper context: A redox-responsive reversible photoacoustic molecular probe for visualizing atherosclerotic plaque redox status in vivo
preclinical multimodal
Supporting key finding
Solution measurements showed concentration-dependent PA signal enhancement with superoxide and attenuation with GSH at 740 nm.
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.
- Signal metric: PA intensity at 740 nm; no validated two-wavelength ratio is defined for these displayed calibrations
- ReP for absorption titration: 10 micromolar
- Superoxide absorption titration: 0-125 micromolar
- Superoxide PA calibration shown: 0, 12.5, 25, 50 and 80 micromolar; R-squared = 0.977
- GSH PA calibration shown: 0, 50, 100, 200 and 300 micromolar; R-squared = 0.982
- Solution preparation: DMSO stocks diluted in PBS at pH 7.4; KO2 in dry DMSO as the superoxide source and fresh GSH in PBS
- Reporting boundary: Calibration replication, detection limit and exact slope are not supplied for these panels
Original-source locator: KF3 · Main PDF pp. 3-4, Results 3.3, Fig. 3b-g; official supplement PDF p. 2, Spectroscopic Measurements; p. 7, Figs. S5-S6.
Paper evidence and provenance Original article DOI Cite
Research fields: Atherosclerosis molecular imaging; Reversible photoacoustic probe research
Review topics: Redox-responsive optical probes; Experimental plaque inflammation imaging
Research & review context
Evidence scope and limitations
Supports
- The reported solution response to superoxide/GSH, bounded by the stated solvent, concentrations, wavelength and interferent panel.
- Relative aortic-region PA signal differences in the stated small ApoE-/- mouse comparison.
- The displayed ex vivo lung and plaque staining observations and limited short-term tolerability observations.
Does not establish:
- Absolute superoxide concentration in living plaques or a validated dual-wavelength PA ratio.
- Clinical sensitivity, specificity, risk discrimination, prediction of plaque rupture or reduced cardiovascular events.
- Human treatment efficacy of dexamethasone or clinical safety, regulatory approval or routine applicability of ReP.
- A universal biological selectivity claim or complete causal demonstration of every proposed lung-to-plaque mechanism.
Limitations
- The evidence consists of chemical solution experiments and mouse imaging/histology. 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.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What experimental systems were actually studied?
- How does ReP respond to superoxide and glutathione?
- What quantitative PA calibration was reported?
- Was an absolute or ratiometric plaque redox measurement validated?
- Which inflammatory and treatment conditions were tested in mice?
- What did histology add to the imaging comparison?
- Does the study show fewer ruptures or clinical treatment benefit?
- What safety conclusion can be supported?
Paper-level research concepts
- ReP
- BODIPY
- catechol redox response
- superoxide anion
- glutathione
- hydrophilic peptide
- photoacoustic intensity at 740 nm
- DLS hydrodynamic diameter
- solution calibration
- aortic-region ROI
- lung wet-to-dry ratio
- ApoE-deficient mouse
- high-fat diet
- LPS
- dexamethasone
- atherosclerosis
- CD68
- caspase-3
- collagen staining
Paper context: Allostatic load-cardiovascular disease associations and the mediating effect of inflammatory factors: a prospective cohort study
clinical cohort
Supporting key finding
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.
- baseline biomarkers: 12
- score range: 0–12
- risk scoring: Quartile-based; low-value direction for HDL and IGF-1
Original-source locator: KF2 · Methods: Assessment of allostatic load
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiovascular epidemiology; Multisystem stress-biomarker research
Review topics: Allostatic load and cardiovascular disease; Inflammatory markers in exposure-outcome associations
Research & review context
Evidence scope and limitations
Supports
- Observational population-level associations between biomarker-defined AL and incident CVD.
- Nonlinearity and exploratory statistical mediation within the analyzed cohort.
Does not establish:
- A causal prevention mechanism or efficacy of anti-inflammatory drugs.
- A prospectively validated individual clinical prediction tool.
- Validated benefits of a stress-management intervention.
Limitations
- Observational design does not establish causality; residual confounding remains possible.
- Missing-data selection limits interpretation of the analytic sample.
- Baseline AL and mediator measurements limit temporal interpretation of mediation.
- Population-specific thresholds may not transfer to other populations.
Full paper evidence scope
5 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Which population and incident outcomes were analyzed?
- What does the allostatic-load score represent?
- What was the adjusted high-versus-zero AL association?
- What do the nonlinear and sensitivity analyses add?
- Does the mediation estimate establish prevention by lowering neutrophils?
Paper-level research concepts
- UK Biobank
- allostatic load
- multisystem biomarkers
- incident cardiovascular disease
- Cox regression
- restricted cubic splines
- mediation analysis
Paper context: Aspirin after PCI in Acute Coronary Syndromes
Letter
Supporting key finding
The authors frame early aspirin withdrawal as a timing question in interpreting the NEO-MINDSET result.
Their interpretation of an existing trial; no new randomization or causal test of withdrawal timing.
- evidence role: Clinical commentary
Original-source locator: KF1 · NEJM 394(10), pp. 1035-1036; Li, Zhang and Liu letter, opening sentence and continuation across the page break; PMID 41780015.
Paper evidence and provenance Original article DOI Cite
Research fields: Antiplatelet therapy after PCI; Interpretation of acute coronary syndrome trials
Review topics: Timing of aspirin de-escalation; Early versus later thrombotic risk
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Which correspondence under this shared DOI is covered?
- What does the 83% figure mean?
- What further investigation do the authors propose?
- Can this letter establish a safe aspirin-withdrawal schedule?
Paper-level research concepts
- interventional cardiology
- clinical trial interpretation
- pharmacodynamic platelet-function testing
- aspirin withdrawal
- P2Y12 inhibitor monotherapy
- stent thrombosis
- time-adaptive de-escalation
Paper context: Circadian Immunity and Vascular Inflammation in Cardiovascular Disease Chronotherapy Windows: Time for a Re-Assessment
narrative review
Key finding from this work
The review places CLOCK-BMAL1, PER/CRY and REV-ERB/ROR feedback loops at the center of temporal regulation of cardiovascular immune biology.
This is a synthesis of prior molecular and experimental literature rather than a new clock experiment.
- Core clock machinery: BMAL1/ARNTL, CLOCK, PER1/2/3, CRY1/2, REV-ERB alpha/beta and ROR alpha/gamma are integrated with redox and epigenetic regulation.
Original-source locator: KF1 · Sections 2.1-2.4; Figures 1-2; Tables 1-2.
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiovascular chronobiology; Immune-vascular regulation
Review topics: Circadian rhythms and vascular inflammation; Cardiovascular chronotherapy evidence and translation
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
11 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What type of article is this?
- Which circadian clock components are central to cardiovascular immune regulation?
- How does circadian disruption interact with NF-kB and NLRP3?
- Which immune cells show circadian trafficking or functional rhythms?
- Which cardiovascular diseases are discussed?
- Does the review prove that REV-ERB agonists treat cardiovascular disease in humans?
- Should all antihypertensive medications be taken at bedtime?
- Does bedtime aspirin have proven myocardial infarction or stroke outcome benefit?
- Are SGLT2-inhibitor, colchicine, MRA or ARNI dosing times clinically established?
- Is this a systematic review or meta-analysis?
- What gaps remain before cardiovascular chronotherapy can become precision medicine?
Paper-level research concepts
- BMAL1 / ARNTL
- CLOCK
- PER1
- PER2
- PER3
- CRY1
- CRY2
- REV-ERBα / NR1D1
- REV-ERBβ / NR1D2
- RORα
- RORγ
- NF-kB
- NLRP3 inflammasome
- NRF2
- SIRT1
- HIF-1alpha
- pattern-recognition receptors
- reactive oxygen species
- IL-1beta
- IL-6
- IL-18
- TNF-alpha
- CCL2-CCR2
- CXCL12-CXCR4
- ICAM1
- VCAM1
- CCR7
- S1PR1
- S1PR5
- neutrophils
- monocytes
- macrophages
- lymphocytes
- dendritic cells
- endothelial cells
- vascular smooth muscle cells
- atherosclerosis
- stroke
- ischemic heart disease
- myocardial infarction
- heart failure
- hypertension
- 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
Paper context: Combining Insulin Resistance and Renal Function to Predict Cardiovascular Events: A Multicenter Cohort Study
multicohort observational
Supporting key finding
The study combined a UK Biobank prospective analysis with an independent clinical association-replication cohort.
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.
- UK Biobank analytic participants: 261,865
- External cohort initially assembled: 1,798
- External complete-case analysis: 328 participants, including 88 MACE outcomes
- External recruitment and follow-up: 2018–2020 enrollment; up to 4 years of follow-up
Original-source locator: KF1 · Methods: Study design and population, Primary cohort and External validation cohort; Results: Population characteristics; Table 1; Figure 5
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiovascular epidemiology; Cardiometabolic–renal markers
Review topics: Combined metabolic and renal risk assessment; External association-replication studies
Research & review context
Evidence scope and limitations
Supports
- Prospective observational associations between the baseline ratio and incident CVD/CHD in the analyzed UK Biobank population.
- Independent association replication for MACE in a small, complete-case hospital cohort.
- Exploratory network analysis and further research into integrated cardiometabolic–renal markers.
Does not establish:
- A causal effect of the ratio on cardiovascular disease or a confirmed biological mechanism.
- A statistically significant highest-versus-lowest-quartile stroke association in fully adjusted Model 3.
- An independently calibrated individual-risk calculator, improved C-statistic/NRI/IDI, or superiority to established risk scores.
- A universal clinical cut-off, treatment efficacy, or benefit from targeting the ratio.
- That exposure-quartile network differences demonstrate within-person disease transitions.
Limitations
- The observational design cannot establish causation and residual confounding remains possible.
- UK Biobank selection and demographic composition limit generalizability.
- The external cohort was from one clinical center; only a complete-case subset entered the fully adjusted analysis, limiting precision and representativeness.
- The source reports different results for continuous, quartile, and spline contrasts; these should not be collapsed into one uniform association.
- Incremental discrimination, calibration, reclassification, and clinical decision benefit beyond established risk scores were not established.
- Exploratory network comparisons between exposure quartiles cannot demonstrate longitudinal within-person phase transitions.
Full paper evidence scope
7 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How many participants contributed to the analyses?
- What does the TyG:eGFRcr-cys ratio combine?
- What was the main prospective CVD association?
- Were all cardiovascular outcomes significantly associated in the quartile comparison?
- What does external validation mean here?
- Does the network analysis establish a pre-disease transition?
- Can the ratio replace established cardiovascular risk scores?
Paper-level research concepts
- Triglyceride–glucose index
- TyG:eGFRcr-cys ratio
- Creatinine–cystatin-C-based estimated GFR
- Incident cardiovascular disease
- Coronary heart disease
- Stroke
- Major adverse cardiovascular events
- UK Biobank
- Prospective cohort
- Cox proportional-hazards model
- Independent association replication
- Dynamic network biomarkers
Paper context: From Disease-Specific Models to Broad Clinical Utility: A Perspective on AI Hybrid Ensemble Frameworks
narrative review
Supporting key finding
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.
- Argument topic: Learner integration
- Evidence basis: Methodological proposal
Original-source locator: KF1 · Section 4.1
Paper evidence and provenance Original article DOI Cite
Research fields: Clinical artificial intelligence methodology; Translational model-evaluation research
Review topics: Clinical ensemble design and evaluation; Interpretation and generalization of clinical AI
Research & review context
Evidence scope and limitations
Supports
- Cite for a context-sensitive ensemble design rationale, not as an original comparison proving that a particular ensemble outperforms alternatives.
- Cite when planning independent-cohort evaluation and model selection; obtain actual validation results from the relevant empirical studies.
- Cite for methodological caution about attribution robustness; SHAP values are not evidence that a feature causally changes an outcome.
- Cite for resource, evaluation and workflow considerations in a translation plan, not as proof of improved patient outcomes.
Does not establish:
- A newly developed model with completed clinical validation or demonstrated cross-disease generalization.
- Original AUC, C-index, ablation or treatment-effect estimates generated in this Perspective.
- Stable causal mechanisms inferred from SHAP feature attributions.
- Proven patient-outcome improvement, clinical guideline status or regulatory approval.
Limitations
- This is a methodological Perspective, not a systematic review or meta-analysis with a reported systematic search protocol.
- Claims about samples and model performance in cited applications require the corresponding primary studies; those studies were not all independently re-audited for this page.
- Proposed independent-cohort evaluation, attribution robustness checks and deployment principles still require empirical implementation and assessment.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What design rationale supports combining complementary learners in a clinical AI ensemble?
- How does the AI ensemble Perspective propose evaluating and selecting models across independent cohorts?
- Why should clinical AI feature attribution be considered alongside sensitivity analysis and calibration?
- Which deployment constraints does the AI ensemble Perspective identify for clinical translation?
Paper-level research concepts
- Complementary learner integration
- Independent multi-cohort evaluation
- Distribution-dependent feature attribution
- Deployment and clinical workflow constraints
- Cardiovascular disease (discussion context)
- Oncology (discussion context)
- Chronic-disease applications (discussion context)
Paper context: Multimodal AI for cardiovascular care must learn when not to predict
narrative review
Supporting key finding
The correspondence separates distinct problems that are often grouped under multimodal AI.
Conceptual taxonomy of fusion, missing inputs, time, selective prediction and observation mechanisms.
Original-source locator: KF1 · Corrected proof p. 1, opening paragraph
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiovascular AI evaluation; Clinical decision support research
Review topics: Evidence sufficiency before prediction; Evaluation of incomplete multimodal data
Research & review context
Evidence scope and limitations
Supports
- Attribution of the stated evaluation and deferral proposal to this correspondence.
- Literature discussion of missingness, temporal context and prospective evaluation needs.
Does not establish:
- Empirical improvement in discrimination, safety, equity or patient outcomes.
- A validated AI algorithm or universal abstention threshold.
- A consensus guideline, clinical standard or independent external validation cohort.
Limitations
- Conceptual proposal without empirical validation.
- Evidence locators refer to the archived publisher corrected proof. The reviewed passages and Figure 1 caption match the current issue-assigned publisher HTML after removal of proof page headers and formatting; the current publisher PDF was not independently inspected.
- The five evaluation conditions are candidate recommendations, not consensus criteria.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What problem does this correspondence address?
- How does it define the role of deferral?
- Which evaluation conditions does it propose?
- Does it report new model accuracy or a clinical trial?
Paper-level research concepts
- cardiovascular artificial intelligence
- multimodal learning
- selective prediction
- informative missingness
- temporal validity
- evidence sufficiency
- deferral
Paper context: PAPPA2 c.392G>C Heterozygous Mutation Associates Primary Open-Angle Glaucoma in a Chinese Family
preclinical multimodal
Supporting key finding
PAPPA2 c.392G>C expression was associated with lower PAPPA2 protein levels in transfected 293T cells and their culture supernatant, without a statistically significant mRNA difference from wild type.
Equal amounts of wild-type and mutant expression plasmids were compared 48 hours after transfection. The variant encodes p.Gly131Ala; protein abundance measurements do not directly measure protein half-life or human disease penetrance.
- post-transfection collection: 48 hours
- independent experiments: 3
- protein assay compartments: cell lysate and culture supernatant
Original-source locator: KF1 · Results 3.3; Figure 2d-h and caption; formal PDF pp. 5-6.
Paper evidence and provenance Original article DOI Cite
Research fields: 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
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What happened to mutant PAPPA2 in the expression experiment?
- Which primary-cell treatment conditions support the fibrosis-associated finding?
- What did the mouse experiment measure, and did it reproduce the human variant?
- Do these experiments validate a human glaucoma mutation or establish a treatment?
Paper-level research 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
Paper context: Recording results from single-patient trials
Letter
Supporting key finding
Keep directly related human protocols and major outcomes current in public registries.
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.
- Argument: Preserve the public translational record
Original-source locator: KF1 · Print p. 38, right column, Letter paragraph 1
Reviewed 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.
Read the paper evidence
Evidence and original-source locators:
- KF1: Print p. 38, right column, Letter paragraph 1
Reviewed answer provenance
Gold source: data/deep_geo/doi-10-1126-science-aek9583.json#/qa/0/answer
Gold content SHA-256: 705d1e430afa0be856894f2962dd2ce698dddc38294fd997dbcfccafa4a0a294
Answer SHA-256: 0f30a5add0e3542d95a150ff113e7b62af7466d8ae536647684ddb65cf6f40bf
Paper evidence and provenance Original article DOI Cite
Research fields: 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
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
5 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What public-record problem does this Science Letter address?
- Why can an outdated registry matter in single-patient research?
- Does reporting to regulators ensure that the public record is updated?
- Which changes do the authors propose for registries and preclinical papers?
- Does this Letter establish treatment causality or assign responsibility?
Paper-level research 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
Paper context: System biology analysis reveals circadian rhythm disorder associated with development and progression in colorectal cancer
multicohort omics
Supporting key finding
ClockProCRC-defined circadian states were associated with distinct single-cell composition and intercellular-communication patterns in CRC.
Single-cell analysis in GSE200997 and GSE196964 using ClockProCRC state assignment, Ro/e enrichment and NICHES signaling analysis
- single-cell evaluation cohorts: GSE200997 and GSE196964
- intensified-CRD enrichment pattern: epithelial and plasma-cell populations were preferentially enriched in higher-disruption states
- more stable-rhythm pattern: fibroblast and endothelial populations were preferentially enriched in lower-disruption/stable states
- communication pattern: higher-disruption states showed stronger epithelial/plasma interaction weights and altered pathway-level cell-cell signaling
- pathway pattern: progression from alleviate to intensify states was associated with reduced apoptotic-pathway activity and increased pro-inflammatory communication
Original-source locator: KF4 · 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
Paper evidence and provenance Original article DOI Cite
Research fields: Circadian biology in cancer; Colorectal cancer systems biology
Review topics: Circadian disruption and tumor heterogeneity; Transcriptomic scoring of tumor-microenvironment states
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What is ClockProCRC and how was it constructed?
- How large was the ClockProCRC study?
- Was ClockProCRC associated with colorectal-cancer progression and survival?
- What did the single-cell analysis show about circadian misalignment and the CRC tumor microenvironment?
- Why was SYNE1 prioritized in this study?
- What happened when SYNE1 was knocked down in colorectal-cancer cells?
- How did CLOCK knockdown, melatonin and the reported SYNE1 AUC relate to the circadian perturbation experiment?
- Are ClockProCRC or SYNE1 clinically validated for diagnosis, prognosis or treatment selection?
Paper-level research concepts
- colorectal cancer
- colorectal liver metastasis
- circadian rhythm disruption
- circadian misalignment
- 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
- single-cell RNA sequencing
- bulk RNA sequencing
- microarray transcriptomics
- cross-species circadian transcriptomics
- cell-line transcriptomics
- SYNE1
- NFATC2
- CLOCK
- E-cadherin
- ZO-1
- N-cadherin
- epithelial cells
- plasma cells
- fibroblasts
- endothelial cells
- HCT116
- SW480
- circadian rhythmicity
- tumor progression
- cell-cell communication
- migration
- invasion
- colony formation
- epithelial-mesenchymal phenotype
Paper context: 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
clinical cohort
Supporting key finding
A prospective CHARLS analysis identified incident, surrogate-defined cardiovascular–liver–metabolic multimorbidity at follow-up.
Chinese community-dwelling adults without baseline CLMM; component conditions were evaluated at baseline and the follow-up wave, rather than using exact onset dates.
- Analytic participants: 6,534 adults aged 45 years or older
- Exposure and outcome waves: 2011 baseline and 2015 follow-up
- Incident CLMM: 406 participants; 6.2%
- Outcome definition: At least two of CVD, type 2 diabetes, and LAP-based suspected MASLD
Original-source locator: KF1 · Methods: Study population and Outcome assessment (jdi70462-sec-0007; jdi70462-sec-0009); Results 3.1 (jdi70462-sec-0013); Figure 1; Table 1
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiometabolic epidemiology; Metabolic biomarker research
Review topics: Multimorbidity risk-marker evaluation; Obesity-derived biochemical indices
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
7 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Who was included in the analysis?
- What counted as cardiovascular–liver–metabolic multimorbidity?
- How strong was the association with CHG?
- Did CHG-BMI perform better than CHG alone?
- Was this an externally validated clinical prediction model?
- Did high CHG and high BMI interact statistically?
- Can these findings guide a treatment intended to prevent CLMM?
Paper-level research 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
Paper context: Vascular smooth muscle cell-derived KIF13B inhibits proinflammatory responses to protect against atherosclerosis
multicohort omics
Supporting key finding
Lower KIF13B was associated with more advanced or unstable human atherosclerotic plaque states, with prominent differences in VSMCs.
These human tissue and public-dataset observations are associative and do not establish that changing KIF13B alters plaque outcomes in patients.
- Local carotid plaques: 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.
- GSE120521: KIF13B mRNA was lower in unstable than stable regions from four paired carotid plaques: n=4 stable and n=4 unstable.
- PXD062283: KIF13B protein was lower in the JCI stable n=19 versus unstable n=38 plaque comparison.
- Plaque matrix relationship: Human plaque analysis showed lower VSMC KIF13B and lower collagen in advanced regions, with a positive association between VSMC KIF13B signal and collagen content.
- Epigenetic evidence: 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.
Original-source locator: KF1 · Results: Decreased expression of KIF13B in VSMCs is linked to the progression of atherosclerosis in humans; Figure 1; Supplemental Figure 1; Methods: Human studies.
Paper evidence and provenance Original article DOI Cite
Research fields: Atherosclerosis research; Vascular smooth muscle biology
Review topics: Smooth muscle cell phenotypic remodeling; Experimental regulation of plaque stability
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
10 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What is the human evidence linking KIF13B to atherosclerotic plaque severity?
- Did VSMC-specific Kif13b deletion cause worse atherosclerosis in mice?
- What did the single-cell experiment show, and were there five independent replicates per genotype?
- Why does this page not assign one definitive diet duration to all single-cell analyses?
- How does KIF13B affect primary human vascular smooth muscle cells?
- Is KLF4 functionally downstream of KIF13B?
- What evidence supports the KIF13B-KCTD10-KLF4 mechanism?
- Does Kenpaullone prove that KLF4 is a clinically validated treatment target for atherosclerosis?
- How does this JCI study differ from the European Heart Journal KIF13B study?
- Which public datasets and repositories support this evidence page?
Paper-level research 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
Paper context: A Multimodal artificial intelligence framework for mechanistic discovery and digital twin construction in cardiovascular medicine
narrative review
Supporting key finding
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.
- Argument topic: Research agenda
- Evidence basis: Narrative synthesis
Original-source locator: KF1 · Publisher correspondence: To the Editor; Sections 1–2
Paper evidence and provenance Original article DOI Cite
Research fields: Artificial intelligence in cardiovascular medicine; Patient-specific modeling research
Review topics: Multimodal AI for cardiovascular mechanism research; Digital modeling and prospective evaluation requirements
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Which research directions does the cardiovascular AI Correspondence propose for multimodal models?
- How can imaging and molecular information support cardiovascular network and disease-subtyping hypotheses?
- What modeling approaches does the cardiovascular AI Correspondence discuss for patient-specific simulation?
- What requirements does the cardiovascular AI Correspondence identify for translating patient-specific models?
Paper-level research concepts
- Cardiovascular mechanism research
- Cross-modal imaging and molecular interpretation
- Patient-specific physiological simulation
- Longitudinal evaluation and governance
- Cardiovascular disease (discussion context)
Paper context: ABCA1 acts as a protective modulator in amyotrophic lateral sclerosis
multicohort omics
Supporting key finding
A nine-gene ALS classifier showed reduced discrimination when applied to an independent expression cohort.
The RF model was developed and internally tested in GSE112676 and externally evaluated in GSE112680; feature selection and batch heterogeneity constrain generalization.
- Gene signature: 9 genes including ABCA1
- Random forest AUC: Training 1.00; internal test 0.91; independent external dataset 0.75
- Comparator LASSO AUC: Training 0.86; internal test 0.89; external 0.72
Original-source locator: KF1 · 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).
Paper evidence and provenance Original article DOI Cite
Research fields: Neurodegenerative disease genomics; Molecular biomarker research
Review topics: ABCA1 and ALS susceptibility; Blood expression and serum biomarker translation
Research & review context
Evidence scope and limitations
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; day 70 must not be called statistically significant.
- Genetic susceptibility, whole-blood RNA, circulating protein and postmortem tissue are not interchangeable measures.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How did the nine-gene ALS model perform externally?
- Does MR prove ABCA1 upregulation treats ALS?
- How many people were in the serum cohort?
- Was serum ABCA1 associated with functional disability?
- Is ABCA1 significantly upregulated in mouse spinal cord from day 70?
- Are neutrophil and NK findings direct cell counts?
Paper-level research concepts
- Amyotrophic lateral sclerosis
- ABCA1
- Serum biomarker associations
- Nine-gene random forest
- cis-eQTL Mendelian randomization
- ELISA
- External AUC 0.75
- ALSFRS-R nonsignificant association
- Mouse day-70 P-value discrepancy
Paper context: Association between higher estimated glucose disposal rate and reduced prevalence of hyperuricemia and gout
clinical cohort
Supporting key finding
Both outcome analyses use the same selected cross-sectional NHANES sample.
Participant counts are unweighted observations, not weighted prevalence estimates or incident cases.
- analytic participants: 29,340
- NHANES cycles: 6 (2007–2018)
- hyperuricemia cases: 5,433
- self-reported gout cases: 1,346
Original-source locator: KF1 · Methods §2.1 Study design and population (sec7); §2.3 Diagnosis of HUA and gout (sec9); Tables 2 and 3 (tab2, tab3), Continuous case/participants rows
Paper evidence and provenance Original article DOI Cite
Research fields: Metabolic epidemiology; Population-based gout and hyperuricemia research
Review topics: Insulin-resistance proxies and prevalent disease; Survey-weighted cross-sectional associations
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How many participants and which outcomes were analyzed?
- Was every higher eGDR category significantly associated with less gout?
- What did the continuous adjusted analyses report?
- Does this demonstrate that raising eGDR will prevent disease?
Paper-level research concepts
- hyperuricemia
- gout
- US NHANES adults aged at least 20 years
- prevalent hyperuricemia
- self-reported gout
- survey-weighted logistic regression
- cross-sectional analysis
- estimated glucose disposal rate
- survey questionnaires
- serum uric acid
- HbA1c
- waist circumference
- eGDR
- NHANES 2007–2018
Paper context: Association between sleep duration, sleep trouble and all-cause mortality in individuals with hyperuricemia in the United States
clinical cohort
Supporting key finding
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.
- comparison: <7 h versus 7–9 h
- model: Fully adjusted Model 3
- hazard ratio: 1.25
- reported 95 percent CI: 1.04–1.51
Original-source locator: KF2 · Results 3.2; Table 2
Paper evidence and provenance Original article DOI Cite
Research fields: Sleep epidemiology; Chronic-disease population research
Review topics: Sleep duration and mortality; Sleep-related associations in adults with hyperuricemia
Research & review context
Evidence scope and limitations
Supports
- Survey-weighted associations of self-reported sleep duration with all-cause mortality in the analyzed population.
- A separate sleep-trouble estimate and a dataset-derived nonlinear turning point.
Does not establish:
- That 7.23 h is a precise personal target for everyone.
- That extending or shortening sleep has been proven to reduce deaths.
- A clinical prediction model or absence of risk from all sleep disorders.
Limitations
- Self-reported exposure and a single baseline assessment limit exposure characterization.
- Residual confounding and reverse causation remain possible.
- Complex-survey weighting must be retained; raw counts and weighted percentages are not interchangeable.
- The data-derived turning point is non-causal and not an intervention-validated target.
- Self-reported sleep duration is not a direct circadian-rhythm measurement.
Full paper evidence scope
5 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What design, sample and mortality follow-up were used?
- How was short sleep associated with mortality?
- How was long sleep associated with mortality?
- What did the sleep-trouble analysis show?
- Should 7.23 hours be interpreted as a prescribed individual target?
Paper-level research concepts
- NHANES
- hyperuricemia
- sleep duration
- self-reported sleep trouble
- all-cause mortality
- survey-weighted Cox regression
- restricted cubic splines
Paper context: Current status, hotspots, and trends in cancer prevention, screening, diagnosis, treatment, and rehabilitation: A bibliometric analysis
bibliometric corpus
Supporting key finding
The study describes a defined English-language oncology literature corpus rather than a patient cohort.
Title-based Web of Science Core Collection search; published corpus counts are reported without independently rerunning the subscription database query.
- documents after deduplication: 17,293
- eligible publication interval: 1 March 2014 to 1 March 2024
- reported database access date: 25 December 2024
Original-source locator: KF1 · 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
Paper evidence and provenance Original article DOI Cite
Research fields: Oncology bibliometrics; Cancer research mapping
Review topics: Publication distribution across cancer management; Keyword attention in oncology literature
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What literature did this bibliometric study analyze?
- How were the retrieved documents distributed across cancer-management topics?
- Which treatment-related keyword frequencies are directly reported?
- Can this study establish which cancer treatment works best?
Paper-level research concepts
- bibliometrics
- oncology research mapping
- title-based literature search
- keyword co-occurrence
- co-citation analysis
- descriptive frequency analysis
- Web of Science Core Collection
- VOSviewer
- CiteSpace
- Bibliometrix
Paper context: Deciphering the Proteomic Landscape of Circulating Extracellular Vesicles in Human Abdominal Aortic Aneurysm
multicohort omics
Key finding from this work
The study combined a 15-person in-house comparison with a 12-person external comparison.
Two-center human case-control evidence; no longitudinal prediction of incident AAA or rupture.
- In-house AAA / controls: 10 / 5
- External AAA / controls: 8 / 4
- Article-reported total AAA / controls: 18 / 9
Original-source locator: KF1 · Abstract; Methods 2.1; Results 3.4; Fig. 6
Paper evidence and provenance Original article DOI Cite
Research fields: Vascular biomarker research; Extracellular-vesicle protein research
Review topics: Blood-based biomarker candidates in abdominal aortic aneurysm; Targeted circulating EV proteomics
Research & review context
Evidence scope and limitations
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. No cause of these differences is established by this evidence page.
- Venous-plasma, serum-EV and intraoperative-aortic-blood descriptions appear in different sections, and isolation methods differ between discovery and external-validation descriptions.
- The targeted 92-protein panel does not establish an unbiased circulating proteome.
- Case-control ROC discrimination and pathway enrichment do not establish prospective prediction, clinical screening utility or causality.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How many participants were studied?
- Was this unbiased plasma proteomics?
- Which proteins were prioritized?
- Did all five proteins replicate consistently in external assays?
- What ROC performance was reported?
- Does the study prove that these proteins predict rupture or are treatment targets?
Paper-level research concepts
- abdominal aortic aneurysm
- circulating extracellular vesicles
- EV-associated proteins
- Olink proximity extension assay
- Western blot
- ELISA
- ROC analysis
- IL-4
- IL-6
- MCP-1 / CCL2
- Neurturin / NRTN
- Oncostatin-M / OSM
- case-control biomarker discovery
- external assay evaluation
- assay-dependent replication
Paper context: Integrated-omics analysis defines subtypes of hepatocellular carcinoma based on circadian rhythm
multicohort omics
Supporting key finding
TCGA-LIHC analysis identified CS-H, CS-L and CS-M, with poorer outcomes associated with CS-H.
Retrospective TCGA-LIHC subtype and outcome analysis.
- TCGA-LIHC n: 369
- Subtypes: CS-H; CS-L; CS-M
Original-source locator: KF3 · Author-deposited full text: Results 3.3-3.4; Fig. 4
Paper evidence and provenance Original article DOI Cite
Research fields: Cancer systems biology; Hepatocellular carcinoma molecular research
Review topics: Circadian-related cancer heterogeneity; Transcriptomic subtypes and retrospective outcomes
Research & review context
Evidence scope and limitations
Supports
- Single-cell modules supplied the HCCcrds gene set.
- The score was evaluated in separate clock, feeding and sleep-reference data.
- TCGA-LIHC analysis identified CS-H, CS-L and CS-M, with poorer outcomes associated with CS-H.
- External subtype and survival analyses used overlapping but different cohort sets.
- Subtypes differed in proliferation/metabolic programs and inferred immune characteristics.
- NNMT and MARCKSL1 were among subtype-associated candidate genes.
Does not establish:
- 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.
Limitations
- 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.
- 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.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How was the HCCcrds gene framework derived?
- What role did the circadian reference datasets play?
- Which HCC subtypes were associated with clinical outcomes?
- Were external classification and survival analyses performed in identical cohorts?
- Do the immune analyses demonstrate immunotherapy benefit?
- What evidence supports the nominated molecular markers?
Paper-level research concepts
- hepatocellular carcinoma
- HCCcrds
- NNMT
- MARCKSL1
- transcriptomic subtyping
- LRA clustering
- NTP
- immune deconvolution
- retrospective outcome association
Paper context: Machine learning combined with omics-based approaches reveals T-lymphocyte cellular fate imbalance in abdominal aortic aneurysm
multicohort omics
Key finding from this work
Human AAA single-cell profiling characterized a heterogeneous cellular landscape.
Four human aneurysmal aortic samples; cells are analytical units and are not independent participants.
- aneurysmal aortic samples: 4
- post-QC cells: 7,343
- populations: 16
- main cell types: 9
Original-source locator: KF1 · Results: Single-cell transcriptome profiles of human AAA; Fig. 1
Paper evidence and provenance Original article DOI Cite
Research fields: 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
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
7 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What single-cell evidence was analyzed?
- What does pseudotime establish and not establish?
- How was TIRS derived?
- Which candidate biomarkers were selected?
- How did they perform across public cohorts?
- Were they evaluated in independent human samples?
- Does this study establish a clinical diagnostic test or therapy?
Paper-level research concepts
- abdominal aortic aneurysm
- T lymphocytes
- T-cell state heterogeneity
- immune microenvironment
- single-cell RNA sequencing
- Monocle pseudotime
- bulk transcriptomics
- LASSO
- SVM-RFE
- TIRS
- FOSB
- JUNB
- CST7
- TBC1D4
Paper context: Mapping heterogeneous molecular subtypes of circadian misalignment underlying lung adenocarcinoma risk
multicohort omics
Supporting key finding
Retrospective transcriptomic analysis selected three CRD-expression clusters in TCGA-LUAD and assessed transfer of template features to six GEO cohorts.
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.
- Reported CRD-related gene entries: 2091
- TCGA-LUAD input records: 497
- Expression clusters: 3
- Named external GEO cohorts: GSE72094; GSE68465; GSE50081; GSE42127; GSE41271; GSE31210
- Candidate NMF ranks: 2-7
- Iterations stated in Methods: 100
- NMF method: lee
- NTP confidence handling: FDR <0.05; text says records with FDR >0.05 excluded
Original-source locator: KF1 · 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.
Paper evidence and provenance Original article DOI Cite
Research fields: Lung adenocarcinoma molecular research; Cancer transcriptomic systems biology
Review topics: Circadian-related expression subtypes in LUAD; Retrospective subtype associations and treatment-response hypotheses
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
9 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Which cohorts contribute the reported LUAD input count?
- How were the subtypes developed and assessed across cohorts?
- What survival pattern was reported for C1, C2 and C3?
- Do circadian-related expression differences directly measure a patient clock?
- What genomic features were associated with the clusters?
- Why can C3 show high infiltration and a suppressive immune profile?
- Did the study establish immunotherapy benefit for C3 patients?
- What can be concluded from predicted drug-sensitivity differences?
- How should the 151-signature C-index comparison be interpreted?
Paper-level research concepts
- Circadian-related tumor expression
- LUAD heterogeneity
- NMF clusters
- Nearest template prediction
- Proliferation enrichment
- Lipid-metabolic pathways
- Somatic mutation
- Copy-number alteration
- Inferred immune infiltration
- Retrospective survival association
- TIS
- SubMap
- Predicted drug response
- Within-cohort C-index comparison
Paper context: Modeling Diabetic Cardiomyopathy Using Human Cardiac Organoids: Effects of High Glucose and Lipid Conditions
preclinical multimodal
Supporting key finding
The investigators generated hiPSC-derived three-dimensional cardiac organoids and documented growth and cardiac-lineage marker staining.
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.
- Reported geometry: 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.
- Lineage readouts: MLC2A, MLC2V, cTnT, CD31 and WT1 immunofluorescence.
- Cell source: Commercial human induced pluripotent stem cells; independent donor count and detailed line identity are not specified.
- Timing boundary: 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.
Original-source locator: KF1 · 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.
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiac disease modeling; Human stem-cell-derived organoids
Review topics: Glucose and palmitate injury experiments; Three-dimensional cellular assay systems
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Is this a patient study?
- Which source version supports this evidence page?
- What do the n=3 and n=6 labels mean?
- What glucose and lipid conditions were examined?
- What is the defensible injury evidence?
- Does the metformin experiment establish a treatment regimen?
- Why are some transcript and mitochondrial conclusions excluded?
- Has the study validated a physiologically mature heart or a clinical screening platform?
Paper-level research concepts
- Human induced pluripotent stem cells
- Cardiac organoids
- Diabetic cardiomyopathy model
- Glucose
- Sodium palmitate
- Metformin
- CCK-8
- BAX
- APAF1
- TUNEL
- Inflammatory transcripts
- Masson staining
- In vitro evidence
- Biological versus technical replication
- Journal Pre-proof version
- Protocol reporting gaps
Paper context: Novel post-translational modification learning signature reveals B4GALT2 as an immune exclusion regulator in lung adenocarcinoma
multicohort omics
Supporting key finding
A PTM-related expression score stratified retrospective LUAD prognosis across discovery and GEO cohorts.
TCGA discovery and six GEO retrospective reapplications; selecting models by validation-set C-index may yield optimistic model ranking.
- Development: TCGA-LUAD
- GEO prognosis evaluation: 6 cohorts
- Algorithm selection: Stepcox (both) + SuperPC; mean C-index across evaluated cohorts
- Feature discovery: 31 survival-associated PTM-related genes
Original-source locator: KF1 · 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.
Paper evidence and provenance Original article DOI Cite
Research fields: Lung adenocarcinoma immunology; Molecular prognostic modeling
Review topics: B4GALT2 and immune exclusion; Post-translational modification signatures
Research & review context
Evidence scope and limitations
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. Do not reproduce or interpret the old version as the corrected source.
- Human tissue and mixed-cancer immunotherapy cohorts do not establish prospective predictive efficacy in LUAD.
- The published LLC inoculation cell number differs between Methods (2×10^5) and Figure 8H caption (1×10^6); no value is silently chosen.
- Cell and mouse interventions are not human trials; treatment benefit, optimal dosing, safety and validated target engagement remain unknown.
- A coauthor ORCID differs from another article; preserve the existing site bibliographic source until formally resolved.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What is PTMLS in this study?
- Was the prognostic model tested outside the discovery cohort?
- Which tumor immune phenotype is linked with high B4GALT2 in patient tissue?
- What does the B4GALT2 knockdown experiment add?
- Was Figure 2 corrected after publication?
- Is the mouse inoculation cell count unambiguous?
Paper-level research concepts
- Lung adenocarcinoma
- CD8 spatial exclusion
- Immune-desert phenotype
- B4GALT2
- Post-translational modification signature
- Stepcox and SuperPC
- Archival pathology cohort
- Mouse anti-PD-1 combination
- Published Figure 2 correction
Paper context: Optimized Dynamic Network Biomarker Deciphers a High-Resolution Heterogeneity Within Thyroid Cancer Molecular Subtypes
multicohort omics
Supporting key finding
The ensemble analysis yielded three molecular subtypes.
Consensus framework selection and external NTP evaluation.
- Candidate combinations: 20
- Selected combination: CV-PAM
- Reported external NTP datasets: 6
Original-source locator: KF3 · Methods 2.6-2.7; Results 3.3; Fig. 3
Paper evidence and provenance Original article DOI Cite
Research fields: Cancer systems biology; Thyroid cancer molecular research
Review topics: Molecular heterogeneity and cancer subtyping; Expression-network analysis of disease progression
Research & review context
Evidence scope and limitations
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. Unverified figure-only accuracy or AUC values are not reconstructed.
- A single donor and a large cell count do not establish large-population replication. No explanation for the count difference is invented.
- 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.
- Predicted compounds are not proven effective treatments. 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.
Full paper evidence scope
7 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What does the Stage II DNB signal establish?
- Is TCPSLevel already a clinically validated prospective risk tool?
- How were the thyroid molecular subtypes evaluated externally?
- Does miniPC classify subtypes or directly prove improved survival?
- How many independent donors support the single-cell analysis?
- What human and experimental evidence supports ASPH?
- Were CMap-nominated compounds shown to benefit patients?
Paper-level research concepts
- differentiated thyroid carcinoma
- DNB
- TCPSLevel
- miniPC
- ASPH
- ASCL2
- network analysis
- consensus clustering
- NTP
- subtype classification
- tissue association
- in-vitro perturbation
Paper context: Reply to: Addressing Bias in Feature Importance: A Hybrid Approach for Risk Prediction in Prognostic Survival Models
narrative review
Supporting key finding
The reply describes the breadth of the authors' earlier hybrid modeling framework.
A retrospective account of previous work, not a new model-comparison experiment in this correspondence.
- learners: 12
- candidate modeling schemes: 132
Original-source locator: KF1 · Reply PDF-text rendition p. 1, opening paragraph; reference 2 on p. 2 identifies the original proctectomy study.
Paper evidence and provenance Original article DOI Cite
Research fields: Survival prediction methodology; Clinical machine learning interpretation
Review topics: Hybrid model-selection rationale; Feature-importance criticism and replies
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Does this reply introduce another patient cohort?
- What do 12 and 132 count?
- How is model selection explained?
- Does the SHAP discussion establish unbiased or causal feature effects?
Paper-level research concepts
- clinical prediction methodology
- hybrid survival modeling
- consensus model selection
- SHAP
- feature importance
- concordance index
- interpretability
- overfitting
Paper context: Resolving tumor microenvironment heterogeneity to forecast immunotherapy response in triple-negative breast cancer through multi-scale analysis
multicohort omics
Supporting key finding
The TNBC single-cell series revealed BRCA1-associated differences in annotated tumor immune and stromal states.
Observed four versus four specimens allow exploratory group comparison; 32,386 cells are nested within eight donors and are not independent patients.
- TNBC samples: 4 BRCA1-MT and 4 BRCA1-WT
- QC-retained cells: 32,386; 18,182 mutant-group and 14,204 wild-type-group
- Broad annotated lineages: 7 principal populations
Original-source locator: KF1 · 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.
Paper evidence and provenance Original article DOI Cite
Research fields: Breast cancer single-cell genomics; Immunotherapy response modeling
Review topics: BRCA1-associated TNBC microenvironment; ISG15 and cancer-associated fibroblasts
Research & review context
Evidence scope and limitations
Supports
- Cell-state and CAF-associated transcriptomic differences between the eight sampled BRCA1 groups.
- Spatially associated ISG15 and myCAF signals within the four BRCA1-WT spatial specimens.
- Retrospective mixed-cancer ICI response model discrimination near AUC 0.60–0.61 under the described analysis.
Does not establish:
- Causal BRCA1 control of CAF differentiation or a verified ISG15 immune-response mechanism from the multi-omics associations.
- Independently validated or clinically useful ICI prediction specifically for treated TNBC patients.
- Excellent predictive discrimination, proven chemotherapy/ICI treatment efficacy or a validated treatment-selection cut-off.
- A statistically significant TCGA TNBC overall-survival contrast (reported P=0.182).
- A verified universal count of distinct participants across cell, spatial, paired protein and ICI cohorts.
Limitations
- The main BRCA1 genotype comparison is only 4 versus 4 tissue donors; cells are not independent participant replicates.
- Spatial transcriptome mapping used four BRCA1-WT cases and therefore is not a genotype-balanced spatial replication.
- ICI cohort descriptions conflict (13 cohorts n=829 in Methods vs 12 in Results), requiring scope-limited cohort reporting.
- The selected KNN internal validation/test AUCs are approximately 0.60–0.61, not high discrimination; use and model selection on validation data constrain performance interpretation.
- No ICI-treated TNBC response cohort directly validates this cross-cancer model.
- The article reports TCGA TNBC overall-survival P=0.182; this comparison is nonsignificant.
Full paper evidence scope
7 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How many single-cell patients were studied and how many cells were retained?
- Was there a genotype-matched spatial comparison?
- What evidence nominates ISG15?
- How well did the ICI response model discriminate?
- Was the ICI model validated in treated TNBC patients?
- Did the model-selected groups have significantly different TCGA TNBC overall survival?
- How many ICI cohorts did the authors use?
Paper-level research concepts
- Triple-negative breast cancer
- BRCA1 mutation status
- Cancer-associated fibroblasts
- Single-cell and spatial transcriptomics
- Paired tissue proteomics
- ISG15
- Cross-cancer KNN response model
- AUC approximately 0.61
- No treated TNBC validation
Paper context: Space Dentistry Combined With Remote and AI Technologies, a Necessity for Long-Term Stays: Thoughts of US Astronauts' Unexpected Stay
narrative review
Supporting key finding
The letter proposes strengthening onboard dental capability through crew expertise or additional basic dental training.
Crew size constrains specialist staffing; this is an operational recommendation without a measured treatment effect.
- strategy position: First of three proposals
Original-source locator: KF1 · Online-first typeset text p. 1, paragraph introducing three strategies and describing crew staffing and dental training.
Paper evidence and provenance Original article DOI Cite
Research fields: Spaceflight oral health; Remote dental care research
Review topics: Crew dental capability; Adaptation of digital dentistry to spaceflight
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Which three strategies are proposed?
- Why does crew training appear alongside specialist staffing?
- What constraints are acknowledged for remote care?
- Were AI dental robots tested in astronauts or microgravity?
Paper-level research concepts
- space dentistry
- remote dental guidance
- 3D printing
- AI-driven robotics
- crew training
- microgravity adaptation
- communication delay
- dental emergencies
Paper context: Targeted Delivery of Exosome-Derived miRNA-185-5p Inhibitor via Liposomes Alleviates Apoptosis and Cuproptosis in Dilated Cardiomyopathy
preclinical multimodal
Supporting key finding
The loaded formulation improved reported echocardiographic readouts in the DOX-associated mouse cardiac injury model.
Animal intervention evidence only. Abstract percentage-change wording is not converted into absolute percentage-point effects.
- Main groups: Control, DOX, empty liposome plus DOX, loaded liposome plus DOX
- Reported direction: Higher EF/FS and reduced LVEDD/LVESD compared with DOX injury under the tested conditions
- Fig. 3 sample label: n=10
Original-source locator: KF3 · Result and Discussion: Therapeutic Efficacy of Lipo@miR-185-5p Inhibitor with Targeting Peptide in DCM Mouse Model; Fig. 3A-B
Paper evidence and provenance Original article DOI Cite
Research fields: Cardio-oncology; Cardiac drug-delivery research
Review topics: Anthracycline-associated cardiac injury; Liposomal delivery of inhibitory microRNA payloads
Research & review context
Evidence scope and limitations
Supports
- Formulation characterization and labeled-preparation biodistribution in the tested experiments.
- Improvement in reported cardiac function and histology in the DOX-associated mouse model.
- Changes in cell-death-associated readouts in H9C2 and iPSC-derived cardiomyocyte experiments.
- Limited tolerability observations within the tested settings.
Does not establish:
- Human treatment efficacy, clinical safety or approval of the liposomal miR-185-5p intervention.
- A universally effective therapy for all etiologies of dilated cardiomyopathy.
- Exosome infusion or clinical transplantation of patient-derived vesicles.
- Exclusive cardiac targeting or an intact-drug tissue dose inferred solely from fluorescence.
- Complete miRNA-target/pathway-specific causality from marker changes alone.
- An independently verified quantitative survival advantage or harmonized percentage-effect estimate from the abstract alone.
Limitations
- The experimental disease model is DOX-associated injury; generalization to other causes of human DCM is unestablished.
- The main text and abstract differ in quantitative presentation; abstract-only survival language and percentage effects are not elevated to independently verified key findings.
- The printed animal-model dosing description requires source/author clarification before experimental reproduction; no corrected dose or protocol recommendation is supplied.
- Human iPSC-derived cells, cultured-cell replicates and assay-specific mouse n values are not interchangeable biological units.
- Fluorescence targeting, marker changes and limited organ testing do not establish clinical biodistribution, complete causal mechanism or human safety.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Is this a human DCM treatment trial?
- What is being delivered: exosomes or liposomes?
- How were the particles characterized?
- What evidence supports cardiac targeting?
- What cardiac and cellular outcomes were reported?
- Does the article establish safety or a survival benefit in people?
Paper-level research concepts
- doxorubicin-associated cardiotoxicity
- experimental DCM-like cardiac dysfunction
- liposome
- cardiac-targeting peptide
- miR-185-5p inhibitor
- H9C2 cells
- iPSC-derived cardiomyocytes
- C57BL/6 mice
- echocardiography
- myocardial fibrosis
- apoptosis-associated markers
- cuproptosis-associated markers
- preclinical intervention
- in-vitro evidence
- experimental tolerability
Paper context: Targeting the NLRP3 inflammasome abrogates cardiotoxicity of immune checkpoint blockers
preclinical multimodal
Supporting key finding
Anti-PD-1 cardiac injury was accompanied by NLRP3/IL1B activation in the mouse model, with supportive human PBMC associations.
B16F10-bearing mouse anti-PD-1 model plus GSE180045 public human PBMC single-cell analysis; human findings are associations only.
- mouse evidence: Anti-PD-1 cardiac injury and NLRP3/IL1B activation
- human GSE180045 evidence: NLRP3/IL1B expression patterns in monocytes/neutrophils and association with ICI use/myocarditis; no human intervention
Original-source locator: KF1 · Fig. 1; Supplementary Fig. 1
Paper evidence and provenance Original article DOI Cite
Research fields: Cardio-oncology; Immune-mediated cardiac injury
Review topics: Immune-checkpoint-inhibitor cardiotoxicity; Inflammasome-related cardiac immune states
Research & review context
Evidence scope and limitations
Supports
- Experimental NLRP3 involvement in ICI-associated cardiac injury in the tested mouse models.
- Preclinical cardiac effects of MCC950.
- Cardiac macrophage/T-cell state remodeling.
- Preclinical dual-ICI experiments.
- Supportive human PBMC single-cell association.
- A preclinical mouse treatment-after-injury experiment.
Does not establish:
- MCC950 efficacy in human ICI myocarditis or cardiotoxicity.
- Safety in humans or approved clinical use.
- Human antitumor efficacy or universal effects across tumor models.
- Clinical efficacy of combining 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.
Full paper evidence scope
7 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What model was used to study ICI cardiotoxicity?
- What cardiac effects were observed after MCC950 in mice?
- What does the human GSE180045 analysis contribute?
- What did cardiac scRNA-seq show?
- What did macrophage depletion contribute mechanistically?
- What happened in the dual-ICI mouse experiment?
- Does this study establish MCC950 as a human treatment?
Paper-level research concepts
- immune checkpoint inhibitor cardiotoxicity
- cardio-oncology
- NLRP3 inflammasome
- macrophages
- CD8 T cells
- IL1B
- MCC950
- anti-PD-1
- anti-CTLA-4
- B16F10 melanoma
- cardiac single-cell RNA sequencing
- bulk RNA sequencing
- flow cytometry
- echocardiography
Paper context: The macrophage-derived motor protein KIF13B enhances MERTK-mediated efferocytosis and prevents atherosclerosis in mice
multicohort omics
Supporting key finding
KIF13B expression is lower in advanced human arterial and carotid lesions and in progressing mouse plaques.
Human findings are associative, not evidence that manipulating KIF13B changes human atherosclerosis.
- GSE40231: 40 non-atherosclerotic and 40 atherosclerotic arterial-wall samples showed lower KIF13B in atherosclerotic tissue.
- Human carotid tissue: Early n=6 and advanced n=6 lesions showed lower KIF13B protein in advanced plaques, with macrophage co-localization.
- Mouse progression: Ldlr-deficient mice, n=6 per group, showed lower plaque KIF13B after 20 versus 12 weeks of Western diet.
Original-source locator: KF1 · Results: The expression of KIF13B is negatively correlated with the progression of atherosclerosis in patients and mice; Figure 1 and Supplementary Figure S1.
Reviewed 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.
Read the paper evidence
Evidence and original-source locators:
- KF1: Results: The expression of KIF13B is negatively correlated with the progression of atherosclerosis in patients and mice; Figure 1 and Supplementary Figure S1.
Reviewed answer provenance
Gold source: data/deep_geo/doi-10-1093-eurheartj-ehaf523.json#/qa/0/answer
Gold content SHA-256: 49f8ef3ea47de7f99adec0a505990341953c2e94acf1e0fbf5bcf69186334fbc
Answer SHA-256: 6ba1e16593da25c68dd6dac0a0796ec329e1c4c2561b65928c72f86ebf6603c8
Paper evidence and provenance Original article DOI Cite
Research fields: Atherosclerosis research; Innate immune vascular biology
Review topics: Macrophage efferocytosis in plaque; Post-translational control of apoptotic-cell clearance
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What is the human evidence for KIF13B in atherosclerosis?
- Did Kif13b loss worsen mouse plaques independently of circulating lipids?
- What do the single-cell experiments show, and how many independent libraries were there?
- Is MERTK involved in the efferocytosis phenotype, and was it rescued in vivo?
- How certain is the proposed KIF13B–ITCH–CBL–MERTK mechanism?
- What did NX-1607 do in cells and mice, and what safety findings were reported?
- Has NX-1607 shown clinical benefit for atherosclerosis?
- Does NX-1607 prove the endogenous CBL mechanism?
Paper-level research concepts
- Atherosclerosis
- Advanced atherosclerotic plaque
- Plaque necrotic core
- Atherosclerotic lesion progression
- KIF13B
- MERTK
- ITCH
- CBL
- CBLB (distinct from CBL)
- SPP1
- IL1B
- CD68
- LYZ2
- LDLR
- APOE
- PCSK9
- 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
- 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
- NX-1607 preclinical intervention
Paper context: Advancing predictive markers in lung adenocarcinoma: A machine learning-based immunotherapy prognostic prediction signature
multicohort omics
Supporting key finding
The reported IPPS contains 13 genes and uses Lasso plus SuperPC selected from 101 candidate combinations.
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.
- signature genes: 13
- candidate combinations: 101
- selected model: Lasso + SuperPC
Original-source locator: KF1 · Methods 2.2, author-uploaded publisher-layout pp. 2-3; Results 3.1-3.2, pp. 3-5; Figure 1D-E; Figure 2A.
Paper evidence and provenance Original article DOI Cite
Research fields: Computational oncology; LUAD prognostic modeling
Review topics: Immune-associated transcriptomic signatures; Validation leakage in molecular survival models
Research & review context
Evidence scope and limitations
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. No claim is based on an unseen supplementary result.
Full paper evidence scope
5 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What model did the IPPS study select?
- What survival performance can be quoted without resolving the GSE31210 discrepancy?
- Were the five GEO cohorts untouched independent test sets?
- Does the OAK/POPLAR analysis verify an objective immunotherapy-response classifier?
- Were the proposed drugs tested as IPPS-guided treatments?
Paper-level research concepts
- lung adenocarcinoma
- survival modeling
- Lasso
- supervised principal components
- time-dependent ROC analysis
- IPPS
- oncoPredict
- pRRophetic
- TCGA-LUAD
- GSE13213
- GSE26939
- GSE30219
- GSE31210
- GSE42127
- OAK
- POPLAR
Paper context: AI hybrid survival assessment for advanced heart failure patients with renal dysfunction
clinical cohort
Key finding from this work
The selected hybrid modeling strategy achieved the highest average C-index among evaluated schemes.
Comprehensive evaluation of 132 candidate modeling schemes
Original-source locator: KF1 · Results: Survival assessment system AIHFLevel; Fig. 2b
Paper evidence and provenance Original article DOI Cite
Research fields: Artificial intelligence in cardiovascular medicine; Heart failure research
Review topics: Heart failure risk prediction; Cardiorenal prognostic stratification
Research & review context
Evidence scope and limitations
Supports
- Mortality-risk estimation in the studied advanced-heart-failure and renal-dysfunction population.
- Internal and independent external evaluation of AIHFLevel.
- Association between higher AIHFLevel and poorer prognosis.
- Three-state prognostic stratification.
- Patient-level interpretation of predictor contributions.
Does not establish:
- That AIHFLevel-guided treatment improves survival or other clinical outcomes.
- That predictors included in AIHFLevel are causal determinants of mortality.
- That model performance is identical in every healthcare setting or population.
- That AIHFLevel replaces clinical judgment.
Limitations
- The study was retrospective and observational.
- Prospective multicenter validation is still warranted.
- Randomized studies would be required to establish whether AIHFLevel-guided treatment improves patient outcomes.
- Some echocardiographic predictors may not be uniformly available in primary-care settings.
- Direct methodological reproduction of every comparator risk model was not possible.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What is AIHFLevel?
- How many patients were used to develop and validate AIHFLevel?Question-level finding references are not encoded; consult the paper context and provenance.
- Was AIHFLevel externally validated?
- How accurately did AIHFLevel predict all-cause mortality?
- How was AIHFLevel developed?
- Which clinical variables are included in AIHFLevel?Question-level finding references are not encoded; consult the paper context and provenance.
- How does AIHFLevel stratify prognosis?
- Does the study show that AIHFLevel-guided treatment improves patient outcomes?Question-level finding references are not encoded; consult the paper context and provenance.
Paper-level research concepts
- advanced heart failure
- renal dysfunction
- chronic kidney disease
- coronary artery disease
- arrhythmia
- adults with advanced heart failure and renal dysfunction
- all-cause mortality
- major adverse cardiovascular events
- survival machine learning
- Cox regression
- time-dependent ROC analysis
- calibration analysis
- decision curve analysis
- SHAP
- conditional inference survival tree
- electronic health records
- clinical variables
- laboratory measurements
- echocardiography
- AIHFLevel
- Surv.gbm
- Surv.Xgboost
- CRCCD
- BIDMC
- MIMIC-III
Paper context: An assessment system for clinical and biological interpretability in ulcerative colitis
multicohort omics
Supporting key finding
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.
- candidate compounds: 5
- method: CMap/eXtreme-Sum signature matching
Original-source locator: KF5 · Results: Construction of global regulatory landscape and therapeutic discovery; Fig. 6C
Paper evidence and provenance Original article DOI Cite
Research fields: Inflammatory bowel disease molecular research; Computational disease characterization
Review topics: Gene-expression approaches to ulcerative colitis; Classifier evaluation and biological interpretation
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What samples and modeling split were reported?
- Is the reported classifier based on 12 or 14 genes?
- What external discrimination was reported?
- Are the classifier, UCRScore and DNB interchangeable?
- Were the nominated compounds experimentally shown to treat UC?
- Can the single-cell extension be verified from the cited accession?
Paper-level research concepts
- ulcerative colitis
- UCRGs
- UCRScore
- RF-RFE
- neural-network classification
- PCoA
- CMap
- DNB
- retrospective expression classification
- external dataset evaluation
Paper context: Artificial Intelligence Hybrid Survival Assessment System for Robot-Assisted Proctectomy: A Retrospective Cohort Study
clinical cohort
Supporting key finding
The study constructed RAP-AIscore using a systematic comparison of 132 candidate survival-modeling schemes in a double-center retrospective cohort.
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.
- total unique patients: 506
- NSCVRCS Meta: 384
- Discovery: 268
- Replication: 116
- SYEMH: 122
- modeling schemes: 132
Original-source locator: KF1 · Abstract: Methods; Methods: Data Sources and Study Population; Results: Outcome and Treatment of Missing Values
Paper evidence and provenance Original article DOI Cite
Research fields: Artificial intelligence in oncology; Rectal cancer prognosis
Review topics: Machine learning for postoperative survival; Interpretable cancer risk stratification
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What population was RAP-AIscore developed for?
- How many independent patients and cohorts were studied?
- How were 132 modeling schemes compared?
- What performance was observed internally?
- What happened in independent SYEMH validation?
- Does RAP-AIscore have proven prospective clinical benefit?
Paper-level research concepts
- rectal cancer
- robot-assisted proctectomy
- survival machine learning
- hybrid model selection
- SHAP
- conditional inference tree
- overall survival
- postoperative risk stratification
- internal validation
- independent external validation
Paper context: Assessing personalized molecular portraits underlying endothelial-to-mesenchymal transition within pulmonary arterial hypertension
multicohort omics
Supporting key finding
Single-cell profiling showed PAH-associated heterogeneity across nine annotated lung cell types.
The observations are at cell and donor-sample levels in a small retrospective human lung series; cell counts are not participant counts.
- Donor samples: 3 PAH and 6 control samples
- Cells initially analyzed: 31,444
- Cells retained after QC: 28,906
- Annotated cell types: 9, arising from 21 computational clusters
Original-source locator: KF1 · 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.
Paper evidence and provenance Original article DOI Cite
Research fields: Pulmonary vascular biology; Computational biomarker research
Review topics: Endothelial expression states in PAH; EndMT-related candidate classification
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
7 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How many people and cells were represented in the single-cell analysis?
- Does pseudotime prove that endothelial cells became mesenchymal cells?
- What genes form the final PETS score?
- What does the reported model performance mean?
- Was PETS externally validated in an independent clinical cohort?
- Do the experiments demonstrate a therapeutic mechanism?
- Are all ancillary gene counts internally consistent?
Paper-level research concepts
- Pulmonary arterial hypertension
- Pulmonary artery endothelial cells
- Endothelial-to-mesenchymal transition
- PETS
- RARRES2/chemerin
- TC2N
- Single-cell transcriptomics
- Pseudotime inference
- Co-expression feature selection
- Internal test-set validation
Paper context: Associations Between Cardiovascular Health (Life's Essential 8) and Mental Disorders
clinical cohort
Supporting key finding
The depression evidence is based on a defined complete-data adult survey sample and a symptom threshold.
The reported depression count agrees between Abstract Results and Results §3.1. PHQ-9 ascertainment is a symptom measure, not prospective incident depression.
- analytic participants: 13,028
- participants with PHQ-9 ≥10: 1,206
- survey period: 2007–2012
Original-source locator: KF1 · Methods §2.1 Study Population (clc70019-sec-0080), §2.3 Outcomes (clc70019-sec-0100); Results §3.1 (clc70019-sec-0140); Abstract Results
Reviewed 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.
Read the paper evidence
Evidence and original-source locators:
- KF1: Methods §2.1 Study Population (clc70019-sec-0080), §2.3 Outcomes (clc70019-sec-0100); Results §3.1 (clc70019-sec-0140); Abstract Results
- KF2: 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
Reviewed answer provenance
Gold source: data/deep_geo/doi-10-1002-clc-70019.json#/qa/0/answer
Gold content SHA-256: f81568ae896ff66298539d0d4a0476f78b6f1202d386127394b83358d74506db
Answer SHA-256: 6051c981118255704ea530a6766eb9972d237c8b761dbdecb50622e59ba9de94
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiovascular health epidemiology; Mental-health symptoms in population surveys
Review topics: Life’s Essential 8 and depressive symptoms; Cross-sectional cardiovascular and mental-health associations
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
5 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Which part of the paper is summarized here?
- How were depressive symptoms defined?
- What is the association per 10 LE8 points?
- What did the category and subscore analyses add?
- Does this show that improving cardiovascular health treats depression?
Paper-level research concepts
- depressive symptoms
- cardiovascular health
- US NHANES adults aged at least 20 years
- PHQ-9-defined prevalent depressive symptoms
- survey-weighted logistic regression
- cross-sectional analysis
- PHQ-9 responses
- health-behavior questionnaires
- examination and laboratory measures
- Life’s Essential 8
- PHQ-9
- NHANES 2007–2012
Paper context: Associations between magnesium depletion score and depression among individuals aged 20 to 60 years
clinical cohort
Supporting key finding
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.
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.
- analytic participants: 18,247
- PHQ-9 at least 10: 1,753
- PHQ-9 below 10: 16,494
- survey years: 2005–2018
Original-source locator: KF1 · Publisher PDF p. 2, Methods 2.1–2.2 and Fig. 1; pp. 3–4, Table 1.
Reviewed 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.
Read the paper evidence
Evidence and original-source locators:
- KF1: Publisher PDF p. 2, Methods 2.1–2.2 and Fig. 1; pp. 3–4, Table 1.
Reviewed answer provenance
Gold source: data/deep_geo/doi-10-1016-j-jtemb-2024-127543.json#/qa/0/answer
Gold content SHA-256: c7e2608ac267bdf46ae4c11e0835ea464d3d4d8e3ea7bf10dbd82e6fc3067c6d
Answer SHA-256: 94137ac34217bb41de38984001c5819d7a495f42aba0d9e60b0242213ef4a856
Paper evidence and provenance Original article DOI Cite
Research fields: Nutritional epidemiology; Population mental-health research
Review topics: Magnesium depletion proxies and depressive symptoms; Medication and renal-function components in cross-sectional nutritional scores
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What population and outcome were actually analyzed?
- Was magnesium measured directly?
- What was the fully adjusted per-point association?
- Did all MDS categories show the same evidence?
- Does the PPI component result show that treatment causes depression?
- Does P=0.084 establish a linear dose response or a beneficial threshold?
- Were the associations significant and identical in every subgroup?
- Can these results justify magnesium supplementation for depression?
Paper-level research concepts
- NHANES 2005–2018
- adults aged 20–60 years
- magnesium depletion score
- proton pump inhibitor use
- renal function
- heavy drinking
- PHQ-9
- depressive symptoms
- cross-sectional prevalence
- survey-weighted logistic regression
- restricted cubic splines
- interaction analysis
Paper context: Causal Associations Between the Gut Microbiome and Aortic Aneurysm: A Mendelian Randomization Study
multicohort observational
Supporting key finding
The study paired microbial genetic instruments with separate AA and AAA outcome summary statistics.
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.
- Exposure source: MiBioGen: 18,473 participants, 24 multi-ethnic cohorts
- AA cases / controls: 7,395 / 349,539
- AAA cases: 3,548
- Reported SNP entries: 2,031
Original-source locator: KF1 · 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
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiovascular genetics; Microbiome epidemiology
Review topics: Gut microbial traits and aneurysm; Two-sample Mendelian randomization
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
5 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What populations and statistical units were analyzed?
- Which AA estimates can be cited?
- Was the Bilophila–AAA result consistent across all MR methods?
- Does this demonstrate that microbiome treatment prevents aneurysm?
- Why are TAA findings and strong robustness claims omitted?
Paper-level research concepts
- Aortic aneurysm
- Abdominal aortic aneurysm
- Two-sample Mendelian randomization
- GWAS summary statistics
- Inverse-variance weighting
- Horizontal pleiotropy
- Multiple testing
- Family XIII UCG001
- Bifidobacteriaceae
- Bilophila
Paper context: Deciphering lung adenocarcinoma evolution: Integrative single-cell genomics identifies the prognostic lung progression associated signature
multicohort omics
Supporting key finding
Two single-cell series identified heterogeneous epithelial states across early LUAD pathological categories.
Single-cell cross-sectional profiles; inferCNV and trajectory scores estimate rather than observe clonal evolution.
- Pathological specimens: 4 AIS, 8 MIA and 9 IAC in GSE189357/GSE150938
- Computational annotation: 12 broad cell types; 8 re-clustered inferred tumor epithelial groups
Original-source locator: KF1 · PMC11149493: Methods §2.1 Data set source (jcmm18408-sec-0003); Results §3.1 (jcmm18408-sec-0024); Figure 2A–H.
Paper evidence and provenance Original article DOI Cite
Research fields: Lung cancer molecular pathology; Computational oncology
Review topics: Cell states in early lung adenocarcinoma; Transcriptomic survival risk signatures
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Which pathological stages were compared in the single-cell analysis?
- What is the nine-gene LPAS model?
- Was LPAS externally evaluated?
- Does inferred cluster progression prove actual tumor-cell fate transitions?
- Can low LPAS identify patients who will benefit from immunotherapy?
- What did the PSMB1 experiments establish?
Paper-level research concepts
- Lung adenocarcinoma
- Adenocarcinoma in situ
- Minimally invasive adenocarcinoma
- Single-cell transcriptomics
- inferCNV and pseudotime
- Retrospective survival modeling
- Cluster 6
- LPAS
- PSMB1 knockdown
Paper context: Deciphering the prognostic role of endoplasmic reticulum stress in lung adenocarcinoma: integrating prognostic prediction and immunotherapy strategies
multicohort omics
Supporting key finding
A 10-gene ERAS signature was selected from 22 survival-associated genes.
Univariate Cox screening followed by LASSO in the TCGA development dataset; public-dataset survival evaluation was not uniformly significant.
- screened prognostic genes: 22
- final ERAS genes: 10
- named survival datasets: 8 including TCGA
Original-source locator: KF1 · Methods: Dataset source; Results: Model construction and evaluation, Par17; Fig. 4A-C; Supplementary Fig. 1 (MOESM1)
Paper evidence and provenance Original article DOI Cite
Research fields: Lung cancer genomics; Computational oncology
Review topics: Stress-associated prognostic signatures; Retrospective molecular risk models
Research & review context
Evidence scope and limitations
Supports
- Retrospective LUAD prognostic signature development and public-dataset evaluation.
- Reported nomogram discrimination within the analyzed data.
- Limited tumor-adjacent expression validation.
Does not establish:
- Prospective clinical utility or improved survival from ERAS-guided care.
- Observed benefit from immunotherapy or chemotherapy selected using ERAS.
- A causal tumor-promoting effect inferred from expression or survival association alone.
Limitations
- Retrospective public data and heterogeneous molecular datasets limit clinical transportability.
- No prospective ERAS-guided intervention was evaluated; public-dataset survival separation and retrospective AUCs do not establish clinical utility.
- The Results text calls seven named GEO cohorts six. Methods and Figure 4C identify the seven named GEO datasets; no pooled participant total is inferred.
- Survival separation was not uniformly significant: Figure 4C reports a log-rank P value of 0.091 for GSE29016. 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.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How many genes are in ERAS?
- What survival discrimination was reported for the ERAS nomogram?
- What experimental expression check accompanied ERAS?
- Does ERAS establish benefit from a selected immunotherapy or chemotherapy?
Paper-level research concepts
- lung adenocarcinoma
- LASSO Cox regression
- survival analysis
- single-cell transcriptomics
- ERAS
- SERPINH1
- GPR37
Paper context: Deciphering the tumor immune microenvironment from a multidimensional omics perspective: insight into next-generation CAR-T cell immunotherapy and beyond
narrative review
Supporting key finding
The review identifies barriers to carrying omics-informed CAR-T strategies into clinical solid-tumor use.
Scientific possibilities remain conditional on tumor type, product design, toxicity, patient selection and independent evidence.
- Unresolved themes: Heterogeneous TIME, immune suppression, trafficking and cellular exhaustion
- Clinical questions: Safety, reproducibility, patient benefit and scalable integrated analysis
- Article time scope: Review perspective published 2024
Original-source locator: KF5 · PMC11201788: Perspective and conclusion (Sec27); Figure 4 and cited studies.
Reviewed answer: No. This is a narrative review synthesizing existing studies and does not report a newly recruited clinical cohort or original therapeutic efficacy estimate.
Read the paper evidence
Evidence and original-source locators:
- KF5: PMC11201788: Perspective and conclusion (Sec27); Figure 4 and cited studies.
Reviewed answer provenance
Gold source: data/deep_geo/time-cart.json#/qa/0/answer
Gold content SHA-256: bad86772c3590f90edab80055a5764230521c6240c6471e64415d94fb27b01f0
Answer SHA-256: 5dc06abfcb898e39d300276a5a2963d8870ac36097bacb712dc30e5c47b3189b
Paper evidence and provenance Original article DOI Cite
Research fields: Cancer immunotherapy; Tumor immune spatial biology
Review topics: Multi-omics tumor immune microenvironment; Engineering strategies for CAR-T cells
Research & review context
Evidence scope and limitations
Supports
- The published literature discusses spatially distinct immune phenotypes and diverse omics representations of TIME.
- Candidate CAR-T design and analytic strategies can be organized by antigen selection, cell fitness, infiltration and exhaustion.
- The review offers a historical research framework for questions about TIME and CAR-T engineering.
Does not establish:
- A new prospective study, newly recruited CAR-T treatment cohort or randomized comparison.
- A systematic review protocol, exhaustive meta-analysis or pooled clinical effect estimate.
- That any cited experimental design is universally safe, approved or superior in clinical solid tumors.
- A validated individual-patient CAR-T response model or definite clinical care recommendation.
Limitations
- Narrative inclusion of research examples does not satisfy systematic search or risk-of-bias assessment criteria.
- Statements about specific clinical trials refer to original cited publications and may have changed since the 2024 review.
- Cited cell, mouse and clinical evidence differ in population, design, endpoints and translational readiness.
- No new external clinical dataset, treated cohort, novel model performance estimate or clinical benefit is generated by this review.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Did this paper enroll CAR-T-treated patients?
- Why do spatial immune-cell patterns matter?
- Which omics layers are discussed in TIME?
- Which CAR-T engineering challenges does the review organize?
- Does the review validate a machine-learning predictor for CAR-T response?
- Can the clinical-trial counts in Table 1 be summed as this review’s patients?
Paper-level research concepts
- Tumor immune microenvironment
- Immune-excluded tumors
- Tertiary lymphoid structures
- Spatial immunology
- Proteomics and transcriptomics
- Host genetics and microbiome
- CAR-T cell therapy
- Neoantigen selection
- T cell exhaustion
Paper context: Differential Expression Spectrum of circRNA in Plasma Exosomes in Dilated Cardiomyopathy With Heart Failure
multicohort omics
Supporting key finding
The study describes a small discovery comparison and an external assay phase, but its platform terminology is internally inconsistent.
Methods specifies a microarray; sequencing labels elsewhere are not silently converted into a harmonized RNA-seq claim.
- Discovery participants: 3 DCM; 5 healthy controls
- External participants: 6 DCM; 4 healthy controls
- Methods 2.7 platform: LC Human ceRNA Array V1.0 (Agilent array workflow)
- Reporting difference: Abstract and other passages use sequencing terminology
Original-source locator: KF1 · Methods 2.1 and 2.7; Fig. 1A; Results 3.7
Paper evidence and provenance Original article DOI Cite
Research fields: Extracellular-vesicle biomarker research; Dilated cardiomyopathy and heart failure
Review topics: Circulating RNA biomarkers in cardiomyopathy; Plasma vesicle-associated circular RNA profiling
Research & review context
Evidence scope and limitations
Supports
- Exploratory circRNA expression differences in the analyzed DCM-HF and healthy samples.
- A reported final set of 49 differential circRNAs.
- Computational target, PPI and pathway prioritization.
- An external qRT-PCR comparison of the panel described in Results and Fig. 5.
Does not establish:
- A definitively verified RNA-sequencing platform across all source descriptions.
- A fully reconciled network hub count or a ten-circRNA validation result.
- Direct biochemical circRNA-miRNA-target binding or a causal DCM mechanism.
- Prospective diagnostic sensitivity, specificity, AUC or clinical utility.
- Cardiac tissue origin of every circulating vesicle-associated circRNA.
- Clinical treatment efficacy from the identified circRNA candidates.
Limitations
- The discovery (3 versus 5) and external (6 versus 4) groups are small.
- Methods 2.7 describes a ceRNA microarray, while the abstract and other passages describe sequencing; neither description is silently erased.
- The Results/Fig. 5 nine-circRNA panel differs from the ten candidates listed in Methods 2.9.
- Results 3.6, Fig. 4 and Table 2 contain differing node/hub descriptions; no corrected hub total is invented.
- The source uses the name hsa-circ-76,771 in some passages and hsa-circ-0076771 in Table 1. These are not silently assigned an authoritative database identity.
- Expression differences and predicted networks do not establish prospective diagnostic utility, tissue of origin or a causal mechanism.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Was this DCM circRNA study performed by sequencing or microarray?
- How large were the human discovery and assay groups?
- How many differential circRNAs were reported?
- What do the functional analyses establish?
- Were nine or ten circRNAs evaluated externally?
- Does external expression-profile separation make this a validated diagnostic test?
Paper-level research concepts
- dilated cardiomyopathy
- chronic heart failure
- plasma extracellular vesicles
- exosomal circRNAs
- ceRNA microarray
- qRT-PCR
- target prediction
- protein-protein interaction network
- PCoA
- circRNA
- CD9
- CD63
- case-control expression profiling
- external assay evaluation
Paper context: Identification of potential biomarkers for lung adenocarcinoma: a study based on bioinformatics analysis combined with validation experiments
preclinical multimodal
Supporting key finding
TGFBR2 showed a nominal inverse association with LUAD in the reported forward MR analysis.
The IVW estimate used four genetic instruments after a multi-stage candidate-selection pipeline. This is a conditional genetic association under MR assumptions, not proof of universal protection or a validated diagnostic test.
- IVW beta, rounded in main text: -0.06
- main-text P value: 0.04
- Supplementary Table S1 IVW values: beta -0.059814; SE 0.02863; P 0.0366879; 4 SNPs
Original-source locator: KF1 · Results 3.4; Figure 5A-C; Supplementary Table S1, TGFBR2 IVW row.
Paper evidence and provenance Original article DOI Cite
Research fields: LUAD molecular candidates; Experimental TGFBR2 biology
Review topics: Integration of expression screening and MR; Tissue staining and single-cell-line functional validation
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How strong is the reported TGFBR2 MR evidence?
- Does the tissue figure show higher or lower TGFBR2 in LUAD?
- What did the A549 perturbation experiment show?
- Can these findings guide LUAD diagnosis or treatment now?
Paper-level research concepts
- lung adenocarcinoma
- TGFBR2
- GIMAP6
- CAV1
- PECAM1
- A549 cells
- two-sample Mendelian randomization
- immunohistochemistry
- siRNA perturbation
- CCK8 assay
- Transwell migration
- apoptosis flow cytometry
Paper context: Molecular subtypes of ischemic heart disease based on circadian rhythm
multicohort omics
Supporting key finding
The analysis of GSE184073 constructed a single-cell co-expression foundation related to coronary disease.
GSE184073 single-cell expression analysis.
- Post-QC cells: 2,237
- Analyzed samples: 2
- Non-grey modules: 8
Original-source locator: KF1 · Results: Construction of WGCNA network in scRNA-seq dataset; Fig. 1
Paper evidence and provenance Original article DOI Cite
Research fields: Coronary disease systems biology; Circadian-related cardiovascular research
Review topics: Molecular heterogeneity in ischemic heart disease; Expression-based coronary disease subtyping
Research & review context
Evidence scope and limitations
Supports
- The analysis of GSE184073 constructed a single-cell co-expression foundation related to coronary disease.
- CRDscore was constructed as a research score from target-gene expression and a random background.
- The article reports external reference-data evaluation, but the use of GSE70049 requires qualification.
- Expression-based subtyping of GSE59867 yielded four groups.
- NTP was used to evaluate subtype assignment in four external expression datasets.
- Type2 showed higher CRDscore and immune-inflammatory expression characteristics.
Does not establish:
- Direct measurement of physiological circadian phase, amplitude or period.
- A discovery cohort of 436 independent patients.
- Verification that all cited reference experiments are mouse circadian interventions.
- Prospectively validated clinical risk prediction or clinical utility.
- Benefit from treatment or chronotherapy.
- An independently verified mortality hazard ratio, AUC or clinical cutoff; adverse-prognosis wording is not a verified all-cause mortality model.
Limitations
- GSE184073 cells are not independent patients. GSE59867 contains repeated follow-up of 111 STEMI patients and 46 stable CAD controls; its 436 expression samples are not 436 independent patients. Follow-up represents post-infarction recovery time points, not 24-hour circadian monitoring of the same individual. External dataset counts are article-reported samples and are not summed into a deduplicated participant total. External validation means retrospective expression-template evaluation, not prospective clinical utility. GSE70049 is a Danio rerio setb morphant expression experiment, not a verified mouse circadian perturbation.
- Cells are not independent patients; two analyzed samples do not establish population-level robustness.
- The score does not directly measure an individual's circadian phase, amplitude or period. The two data-layer cutoffs are not one clinical threshold.
- The evidence does not establish that all four reference experiments are verified mouse circadian interventions. No intended replacement accession is inferred.
- These are expression-sample groups, not 436 independent patients. The grouping does not resolve independence of repeated follow-up samples or outcome analyses.
- External expression-template reproducibility is not prospective risk prediction or demonstrated clinical utility.
- Computational estimates and expression associations do not establish causal plaque transitions or benefit from immunotherapy or chronotherapy.
- Direct measurement of physiological circadian phase, amplitude or period.
- A discovery cohort of 436 independent patients.
- Verification that all cited reference experiments are mouse circadian interventions.
- Prospectively validated clinical risk prediction or clinical utility.
- Benefit from treatment or chronotherapy.
- An independently verified mortality hazard ratio, AUC or clinical cutoff; adverse-prognosis wording is not a verified all-cause mortality model.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What single-cell evidence underlies this coronary expression framework?
- What does CRDscore measure, and what does it not directly measure?
- Are all cited reference datasets verified mouse circadian experiments?
- Does the discovery dataset represent 436 independent patients?
- What kind of external validation was performed?
- Do subtype-associated immune patterns establish treatment benefit?
Paper-level research concepts
- coronary artery disease
- ischemic heart disease
- single-cell RNA sequencing
- co-expression network
- NTP
- CRDscore
- CADCR genes
- transcriptomic subtyping
- repeated measurements
Paper context: Omics-based molecular classifications empowering in precision oncology
narrative review
Supporting key finding
The review organizes molecular diagnosis across genomic and epigenomic, transcriptomic and proteomic biomarkers.
Section 2 synthesizes earlier biomarker research; the article does not perform a new diagnostic-accuracy comparison.
- Illustrated biomarker layers: 4 in Fig. 1: genomic, epigenomic, transcriptomic and proteomic
Original-source locator: KF1 · Section 2.1, Molecular understanding of tumor biomarkers; subsections 2.1.1-2.1.3; Fig. 1A-D and its caption (author-uploaded full text).
Paper evidence and provenance Original article DOI Cite
Research fields: Cancer molecular classification; Translational oncology
Review topics: Biomarker-directed research designs; Integrative omics interpretation
Research & review context
Evidence scope and limitations
Supports
- A conceptual overview of omics biomarker layers and molecular classification in oncology.
- Context for discussing biomarker-oriented trial designs and translation challenges.
Does not establish:
- A new patient cohort, newly validated classifier or new therapeutic experiment.
- A pooled treatment effect, diagnostic accuracy or causal benefit of molecular classification.
- Clinical superiority of multi-omics for every cancer or independent confirmation of all cited primary-study results.
- Systematic completeness of the literature search or a meta-analysis.
Limitations
- This is a narrative synthesis without a reported systematic search or pooled effect estimation.
- Results from cited cohorts, trials and experiments remain secondary evidence here; no new primary cohort or validation is reported.
- The public ResearchGate text reproduces a typeset copy uploaded by Zhaokai Zhou on 2 February 2024. The publisher record confirms article identity, but publisher-PDF byte equivalence was not verified.
- Only structural and qualitative review claims are summarized. Numerical results from individual cited studies and the table's assignment of particular trials to design categories are not independently validated.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Which biomarker layers are distinguished in the review?
- Does this review validate a new multi-omics classifier?
- Which clinical-trial design frameworks are compared?
- What prevents a molecular classification from automatically becoming a treatment recommendation?
Paper-level research concepts
- Precision oncology
- Multi-omics
- Molecular classification
- Proteogenomics
- Spatial omics
- Liquid biopsy
- Biomarker-oriented trial design
- Organoids
- Three-dimensional tumor models
Paper context: Optimal Management Options for Esophageal Gastrointestinal Stromal Tumors (E-GIST)
clinical cohort
Supporting key finding
The report describes 23 patients with pathologically confirmed esophageal gastrointestinal stromal tumors at one hospital.
Retrospective clinical records from the First Affiliated Hospital of Zhengzhou University. The total and sex counts agree across the abstract and Table 1; the exact 2023 enrollment cutoff differs between Methods and Results and is not resolved here.
- patients: 23
- male / female: 12 / 11
- mean age ± SD: 56.7 ± 12.0 years
Original-source locator: KF1 · Publisher-layout PDF p. 1, Abstract; p. 2, Methods 2.1; p. 3, Results 3.1 and Table 1.
Reviewed answer: The single-center series reports 23 patients. The endoscopic, direct-surgery, neoadjuvant-plus-surgery and conservative groups are subdivisions of those same patients.
Read the paper evidence
Evidence and original-source locators:
- KF1: Publisher-layout PDF p. 1, Abstract; p. 2, Methods 2.1; p. 3, Results 3.1 and Table 1.
- KF2: Publisher-layout PDF p. 2, Methods 2.3; pp. 3–4, Results 3.2; p. 4, Table 2 and Table 3 headings.
Reviewed answer provenance
Gold source: data/deep_geo/doi-10-1016-j-ejso-2024-108527.json#/qa/0/answer
Gold content SHA-256: b9e8a6e4904ed302c22b1ca3a72574d169ac1398dacfdb07f0863a0b963a9dc2
Answer SHA-256: 6c06e005dbeb3f22e3b0416d7065306141d1ae5133905f02e4782494d0e8631d
Paper evidence and provenance Original article DOI Cite
Research fields: Gastrointestinal surgical oncology; Esophageal GIST
Review topics: Management of rare esophageal mesenchymal tumors; Selection bias in endoscopic and surgical case series
Research & review context
Evidence scope and limitations
Supports
- The reported 23-patient case series and its mutually exclusive treatment allocations.
- The three endoscopic techniques, lesion-size distribution, reported endoscopic events and specific follow-up observations.
- Discussion of how clinician-selected case mix limits comparisons between endoscopic and surgical approaches.
Does not establish:
- Superior safety, survival or oncologic equivalence of endoscopy versus surgery.
- A validated universal size cutoff, treatment algorithm or replacement for clinical guidelines.
- A causal effect of imatinib or any procedure on recurrence or survival.
- Prospective, multicenter or externally validated outcomes.
- A reconciled 2023 enrollment cutoff or corrected mitotic-index category.
Limitations
- The study is retrospective and includes 23 patients at one center. Treatment was chosen by experienced clinicians on the basis of tumor size, location, origin and growth pattern, creating strong selection differences between treatment groups.
- No randomized comparison, adjusted treatment-effect estimate or external validation establishes superiority or oncologic equivalence. The discussion’s procedural suggestions are not independently validated selection rules.
- The abstract and Methods 2.1 specify January 2017 to August 2023, whereas Results 3.1 says January 2017 to December 2023. No exact corrected end date is adopted.
- Results 3.2 describes the highest mitotic-index category as >5/50 HPF, while Table 2 labels it >10/50 HPF. This category is excluded from the quantitative findings rather than silently corrected.
- The manuscript discusses an earlier procedure and suspected recurrence in patient No. 21 without the original postoperative pathology. It is not used to derive an additional event rate, survival curve or effect estimate.
- Postoperative adverse-event counts and follow-up are reported observations in small selected groups. No unreported confidence interval, standardized quality-of-life score or recurrence-rate estimate is generated.
- The complete six-page publisher-layout PDF was reviewed. It contains no identified supplementary-results appendix or supplementary-file citation needed for the findings reproduced here; this does not assert that no supplementary resource exists elsewhere.
Full paper evidence scope
5 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How many independent patients were included?
- How were treatment approaches distributed?
- What endoscopic procedures and lesion sizes were reported?
- Does the study show that endoscopy is safer or more effective than surgery?
- What follow-up observation can be cited?
Paper-level research concepts
- Esophageal gastrointestinal stromal tumor
- E-GIST
- Retrospective case series
- Endoscopic resection
- Submucosal tunneling endoscopic resection
- Endoscopic submucosal dissection
- Endoscopic mucosal band ligation
- Surgery
- Neoadjuvant imatinib
- Conservative management
Paper context: Plasma Olink Proteomics Reveals Novel Biomarkers for Prediction and Diagnosis in Dilated Cardiomyopathy with Heart Failure
multicohort omics
Key finding from this work
Targeted plasma proteomics identified a focused DCM-HF-associated protein signature.
Olink Cardiovascular III profiling in the 38-participant discovery cohort
- discovery cohort: 20 DCM-HF and 18 healthy controls
- proteins profiled: 92
- overall abundance direction: 75 higher and 17 lower in DCM-HF
- proteins at p<0.05: 33
- focused DEP set: 13 proteins; all higher in DCM-HF
- focused DEP significance: P<0.001 in Results; remained significant after FDR correction
- Fig. 1D display threshold: absolute logFC >0.5 and p<0.05
Original-source locator: KF1 · Results 3.2: Identification of Cardiovascular-Related Biomarkers Using Olink; Fig. 1A-D; Fig. 2; Table S1
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiovascular biomarker research; Dilated cardiomyopathy and heart failure
Review topics: Blood protein biomarkers in cardiomyopathy; Targeted proteomics for biomarker discovery
Research & review context
Evidence scope and limitations
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; the linkage to this DCM-HF proteomics study is therefore unresolved.
- Although the Introduction refers to human plasma and mouse models, the study Methods and Results do not describe an original animal experiment; mouse evidence discussed in the article derives from cited prior studies.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How many participants were included in the DCM-HF Olink proteomics study?
- How many proteins were profiled with Olink in DCM-HF?
- Which plasma proteins were prioritized for validation?
- Were the five Olink biomarkers replicated with another plasma assay?
- Were the five plasma proteins independently validated in external proteomic cohorts?
- What diagnostic discrimination did the five-marker gene panel show in external datasets?
- Does this study show that these proteins predict future DCM-HF?
- Are SPP1, IGFBP7, F11R, CHI3L1 or PLAUR validated therapeutic targets for DCM-HF?
Paper-level research concepts
- dilated cardiomyopathy
- DCM-HF
- heart failure
- chronic heart failure
- ventricular systolic dysfunction
- 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
- LVEF
- NT-proBNP
- CRP
- eGFR
- LDL-C
- albumin
- heart rate
- inflammation
- extracellular-matrix remodeling
- fibrosis
- cell adhesion
- fibrinolysis
- tissue repair
- cell migration
- cell proliferation
- platelet aggregation
- apoptosis-related programs
- plasma targeted proteomics
- plasma ELISA
- human cardiac transcriptomics
- clinical phenotypes
- Olink Cardiovascular III
- proximity extension assay
- Normalized Protein eXpression
- NPX
- ELISA
- OlinkAnalyze
- false-discovery-rate correction
- Pearson correlation
- Gene Ontology
- KEGG
- STRING
- Cytoscape
- CytoHubba
- NetworkAnalyst
- binary logistic regression
- ROC analysis
- GSE116250
- GSE141910
- GSE165303
- biomarker discovery
- independent assay replication
- diagnostic discrimination
- cross-modality external evaluation
- hypothesis-generating biological interpretation
Paper context: Proteomics appending a complementary dimension to precision oncotherapy
narrative review
Supporting key finding
The review distinguishes major proteomic assay families and their measurement principles.
Secondary technical overview; no head-to-head accuracy comparison is performed.
- technology subsection groups: 5: mass spectrometry, aptamers, proximity extension assay, protein microarrays, combined single-cell techniques
Original-source locator: KF1 · Proteomics analysis technology subsections; Fig. 1A-D
Paper evidence and provenance Original article DOI Cite
Research fields: Cancer proteomics; Precision oncology methods
Review topics: Proteomic technology selection; Multi-omics clinical translation
Research & review context
Evidence scope and limitations
Supports
- An overview of assay principles and integration strategies.
- Secondary contextualization of published precision-oncology examples.
Does not establish:
- A new patient cohort, pooled treatment benefit or meta-analytic accuracy estimate.
- Clinical superiority of one assay platform for every cancer or use case.
- Independent validation of all biomarkers discussed in cited primary studies.
Limitations
- Narrative coverage does not establish a systematic or exhaustive evidence search.
- No pooled participant denominator or comparative effect estimate is reported.
- Translation depends on specimen availability, cost and application-specific validation.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Which proteomic approaches does this review cover?
- What role does data integration play in the review?
- Which precision-oncology applications are discussed?
- Can this article be cited as a new clinical validation study?
Paper-level research concepts
- proteomics
- precision oncology
- mass spectrometry
- proximity extension assay
- aptamer assays
- multi-omics integration
Paper context: The underlying mechanism of chimeric antigen receptor (CAR)-T cell therapy triggering secondary T-cell cancers: Mystery of the Sphinx?
narrative review
Supporting key finding
The review frames secondary T-cell malignancy after CAR-T therapy as a safety question requiring mechanistic investigation and continued surveillance.
Its starting point is the FDA's historical safety communication, not a new patient cohort assembled by the authors. Regulatory reports are a signal and do not supply a denominator for incidence in this article.
- Historical trigger: FDA communication of 28 November 2023
- Therapy classes discussed: BCMA-directed and CD19-directed autologous CAR-T therapies
- Article evidence level: 2024 narrative review; no original clinical safety estimate
Original-source locator: KF1 · 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.
Paper evidence and provenance Original article DOI Cite
Research fields: Cellular immunotherapy safety; Hematologic oncology
Review topics: Secondary T-cell malignancy after CAR-T therapy; Mechanistic and treatment-history explanations
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Is this an original clinical study?
- Which mechanisms does the review discuss?
- Does Figure 1B establish that CAR-T therapy is not associated with T-cell malignancy?
- Can the clinical case numbers be used to calculate incidence?
- Does CAR positivity prove a specific carcinogenic mechanism?
- Does this paper establish HHV-6 as the cause of a secondary T-cell cancer?
- What safety conclusion can be cited to this review?
- Are the disputed source counts silently corrected into new findings?
Paper-level research concepts
- CAR-T cell therapy
- Secondary T-cell malignancy
- Long-term safety surveillance
- Insertional mutagenesis
- Persistent cellular activation
- Inflammatory microenvironment
- Tumor transgene testing
- Host susceptibility
- Treatment-history confounding
Paper context: TYG Index as a Novel Predictor of Clinical Outcomes in Advanced Chronic Heart Failure with Renal Dysfunction Patients
clinical cohort
Supporting key finding
The analysis comprised 717 patients after follow-up losses, with outcome follow-up of about two years.
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.
- Initially included: 815 patients
- Lost to follow-up: 98 patients (12.0%)
- Analyzed: 717 patients
- Median follow-up (IQR): 21.58 (17.98–25.39) months
- Renal dysfunction definition: eGFR <90 mL/min/1.73 m²
Original-source locator: KF1 · PMC11068055: Method — Study and Population, Inclusion Criteria, Exclusion Criteria, and Follow-Up; Figure 1; Results — Baseline Characteristics.
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiorenal medicine; Clinical prognosis
Review topics: Metabolic biomarkers in advanced heart failure; Risk assessment with impaired kidney function
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Who was included in the analyzed cohort?
- Were the MACEs and mortality groups independent cohorts?
- What was the reported MACEs association?
- Was the composite limited to cardiovascular death, infarction and stroke?
- Was the mortality association evaluated separately?
- Does the study show that treatment to lower TyG improves survival?
Paper-level research 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
Paper context: Atherosclerotic plaque vulnerability quantification system for clinical and biological interpretability
multicohort omics
Key finding from this work
The integrative machine-learning program reduced 96 dysregulated co-expression pattern genes to a 14-gene APVS signature.
APVS generation and model selection across nine classical machine-learning learners
- candidate DCPGs: 96
- machine-learning learners: 9
- selected APVS genes: 14
- optimal learners: random forest and backpropagation neural network
- learner evaluation: 10-fold cross-validation with 100 repetitions
- feature selection: RF-RFE with 10-fold, 10-repeated cross-validation
Original-source locator: KF1 · Results: Machine learning-based integrative program generates APVS; Fig. 2A-E; Methods: APVS generated from an integrative program
Paper evidence and provenance Original article DOI Cite
Research fields: Atherosclerosis research; Computational cardiovascular medicine
Review topics: Molecular assessment of plaque vulnerability; Transcriptomic characterization of coronary disease
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What is APVS?
- Can APVS distinguish STEMI from chronic coronary syndrome?
- Can APVS distinguish ruptured from stable atherosclerotic plaques?
- Can APVS distinguish advanced from early atherosclerotic plaques?
- What is APVSLevel?
- Is APVSLevel associated with cardiovascular outcomes and disease severity?
- What single-cell states are associated with high atherosclerotic plaque vulnerability?
- Is APVS or APVSLevel ready to replace clinical plaque assessment?Question-level finding references are not encoded; consult the paper context and provenance.
Paper-level research concepts
- atherosclerosis
- coronary artery disease
- acute myocardial infarction
- ST-elevation myocardial infarction
- chronic coronary syndrome
- acute coronary syndrome
- atherosclerotic plaque vulnerability
- stable plaque
- ruptured plaque
- early-stage plaque
- advanced plaque
- atherosclerotic core
- fibrous plaque
- major adverse cardiovascular events
- coronary stenosis
- plaque rupture
- restenosis after PCI
- 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
- APVS
- APVS classifier
- APVSLevel
- monocyte/macrophage
- vascular smooth muscle cell
- myofibroblast
- endothelial cell
- B cell
- plasma cell
- mast cell
- neutrophil
- foam cell
- inflammation
- coagulation
- extracellular matrix degradation
- fibrosis
- oxidative stress
- cellular senescence
- DNA damage
- Notch signaling
- TLR signaling
- TNF signaling
- heme metabolism
- cholesterol homeostasis
- CXCL3
- IL1B
- C1Q
- IL34
- CTSK
- IL6
- SOCS3
- AGT
- SPP1
- APOE
- CXCL2
- CDKN1A
- ADM
- CCL2
- NRG1
- FOS
- ITGB2
- FN1
- MIF
- VCAM
- GSE59867
- GSE62646
- GSE28829
- GSE41571
- GSE48060
- GSE60993
- GSE141512
- GSE21545
- GSE159677
- GSE184073
Paper context: Biodegradable Mg alloy modified with bioactive exosomes for cardiovascular stent application
preclinical multimodal
Supporting key finding
A short rat aortic wire-implant experiment showed descriptive vessel-wall histological differences.
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.
- Rodent design: 15 SD rats; bare-Mg, MgF2 and MgF2–PDA/exosome wire groups, n=5 each
- Site and time: Rat abdominal aorta; 21-day histology
- Endpoint limitation: Qualitative H&E representative sections only in Figure 12
Original-source locator: KF6 · 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).
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiovascular biomaterials; Biodegradable stent research
Review topics: Exosome-functionalized magnesium alloys; Preclinical endothelial compatibility
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Was this a human cardiovascular stent trial?
- What is the coating made from?
- What vascular endothelial outcomes were assessed?
- How long were the exosome-associated release effects observed?
- What did the 21-day animal experiment measure?
- Is every figure-level source available?
Paper-level research concepts
- Biodegradable magnesium alloy
- MgF2–PDA/exosome coating
- Vascular scaffold surfaces
- Endothelialization surrogates
- Macrophage phenotype
- Smooth muscle cell markers
- Corrosion bench tests
- Rat aortic wire histology
- Supplement Figure S1 absent
Paper context: Differential expression profiles of plasma exosomal microRNAs in dilated cardiomyopathy with chronic heart failure
multicohort omics
Key finding from this work
The study combined human DCM-HF plasma miRNA discovery with a separate external expression-assay comparison.
Human disease-versus-healthy comparison; no prospective clinical intervention.
- Disease phenotype: DCM with chronic heart failure
- Discovery assay: Small-RNA library sequencing on Illumina HiSeq2500
- External qRT-PCR sample: 10 DCM patients; 6 healthy controls
Original-source locator: KF1 · Methods 2.1, 2.8 and 2.9; Results 3.10; Fig. 6
Paper evidence and provenance Original article DOI Cite
Research fields: Extracellular-vesicle biomarker research; Dilated cardiomyopathy and heart failure
Review topics: Circulating RNA biomarkers in cardiomyopathy; Human plasma exosomal microRNA profiling
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What kind of DCM evidence does this paper provide?
- How many differential miRNA features were reported?
- Were the predicted pathways and miRNA targets experimentally established?
- What was evaluated in the external population?
- Was miR-185-5p one of the externally tested hub miRNAs?
- Can the results be treated as a measured whole-plasma or myocardial tissue signature?
Paper-level research concepts
- dilated cardiomyopathy
- chronic heart failure
- plasma extracellular vesicles
- exosomal miRNAs
- small-RNA sequencing
- qRT-PCR
- miRNA target prediction
- PCoA
- miR-185-5p
- CD63
- CD81
- case-control molecular profiling
- external assay evaluation
Paper context: Idebenone attenuates ferroptosis by inhibiting excessive autophagy via the ROS-AMPK-mTOR pathway to preserve cardiac function after myocardial infarction
preclinical multimodal
Supporting key finding
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.
- model: LAD ligation
- main groups: sham+vehicle; MI+vehicle; MI+idebenone
- preoperative dosing: 24 h and 2 h before surgery
- subsequent dosing: Continued after surgery
- observation windows: Short-term and longer-term
Original-source locator: KF4 · Author-deposited full text: Methods 2.11-2.12; Results 3.6; Fig. 8A
Paper evidence and provenance Original article DOI Cite
Research fields: Myocardial injury research; Regulated cell death in cardiovascular disease
Review topics: Ferroptosis and autophagy in myocardial infarction; Preclinical cardioprotection and intervention timing
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
6 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- What cellular injury model was used?
- What evidence specifically addresses ferroptosis?
- How strong is the proposed autophagy/AMPK-mTOR pathway evidence?
- Was idebenone started only after myocardial infarction?
- What mouse cardiac-function result was reported?
- Do myocardial molecular changes establish human clinical efficacy?
Paper-level research concepts
- experimental myocardial infarction
- idebenone
- ferroptosis
- autophagy
- oxidative injury
- AMPK
- mTOR
- GPX4
- pretreatment-containing animal intervention
- cellular pharmacology
Paper context: Three-dimensional bioprinting of artificial blood vessel: Process, bioinks, and challenges
narrative review
Supporting key finding
The review identifies unresolved steps between printed constructs and clinical vascular grafts.
Translational appraisal as of the 2023 review, informed by cited in vitro and animal examples rather than new clinical outcome data
- evidence level: review of engineering and preclinical demonstrations; no new patient cohort or clinical trial
- historical statement: the authors reported no clinical vessel-bioprinting cases in their review context at publication in 2023
- barriers discussed: mechanical durability, endothelial function, maturation, reproducible manufacturing, sterilization and safety
- time boundary: the historical statement is not an independently updated 2026 claim about every product, trial or regulatory authorization
Original-source locator: KF6 · 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)
Paper evidence and provenance Original article DOI Cite
Research fields: Cardiovascular tissue engineering; Vascular biomaterials
Review topics: Bioink design for vascular constructs; Printing processes and translation barriers
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
7 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Is this an original patient study of printed vascular grafts?
- Why is printing a hollow channel insufficient for a vascular graft?
- What is the difference between supportive and sacrificial materials?
- Why does increasing ink viscosity not solve every printing problem?
- Which fabrication approaches are compared?
- What does the 199 +/- 41 micrometre FRESH value describe?
- Does the review demonstrate clinical benefit or regulatory approval?
Paper-level research concepts
- tissue-engineered vascular grafts
- vascular bioprinting
- coronary bypass graft context
- hyaluronic acid
- collagen
- gelatin methacryloyl
- decellularized extracellular matrix
- alginate
- Pluronic F-127
- modified polyethylene glycol
- material extrusion
- material jetting
- vat polymerization
- FRESH
- sacrificial templating
- crosslinking
- shear thinning
- yield stress
- cell compatibility
- endothelial function
- mechanical durability
- nutrient transport
Paper context: Smooth muscle cell fate decisions decipher a high-resolution heterogeneity within atherosclerosis molecular subtypes
multicohort omics
Key finding from this work
Human atherosclerotic plaques showed substantial vascular smooth muscle cell transcriptional heterogeneity.
Single-cell profiling of diseased right-coronary-artery segments from four human donors
- single-cell donors: 4
- post-QC plaque cells: 11,756
- major plaque cell populations: 8
- SMCs analyzed: 5,419
- SMC clusters: 9
Original-source locator: KF1 · Results: The landscapes of human atherosclerotic plaques revealed by scRNA-seq analysis, Fig. 2A; Results: SMC lineages' phenotypic and functional heterogeneity, Fig. 3A-E
Paper evidence and provenance Original article DOI Cite
Research fields: Vascular biology; Single-cell atherosclerosis research
Review topics: Smooth muscle cell heterogeneity in human plaque; Cell-state programs and molecular disease subtypes
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- How heterogeneous are vascular smooth muscle cells in human atherosclerotic plaques?
- How were SMC fate transitions reconstructed in this study?
- What is the SMC cell fate decision signature (SCFDS)?
- Can SMC fate-associated signatures define molecular subtypes of atherosclerosis?
- Which SCFDS subtype was associated with more severe coronary stenosis?
- What biological programs distinguish C1, C2 and C3?
- Were the SCFDS subtypes externally validated?
- Has SCFDS been prospectively validated for clinical decision-making or treatment selection?Question-level finding references are not encoded; consult the paper context and provenance.
Paper-level research concepts
- atherosclerosis
- coronary artery disease
- coronary stenosis
- stable coronary artery disease
- acute myocardial infarction
- vascular smooth muscle cell phenotypic switching
- SMC differentiation
- SMC cell fate
- plaque remodeling
- atherosclerotic plaque microenvironment
- extracellular matrix remodeling
- inflammation
- vascular smooth muscle cells
- monocytes/macrophages
- endothelial cells
- T cells
- B cells
- mast cells
- plasma cells
- contractile-like SMC state
- inflammatory SMC state
- synthetic/ECM-associated SMC state
- fibroblast-like SMC state
- single-cell RNA sequencing
- bulk transcriptomics
- coronary stenosis phenotype
- Seurat
- UMAP
- CellChat
- Monocle2
- pseudotime analysis
- Mfuzz
- MOVICS
- nearest template prediction
- over-representation analysis
- gene set enrichment analysis
- GSVA
- xCell
- SMC cell fate decision signature
- SCFDS
- C1 DNA-damage repair type
- C2 immune-activated type
- C3 stromal-rich type
- ACTA2
- MYH11
- CNN1
- TAGLN
- ENG
- NT5E
- extracellular matrix
- collagen signaling
- CXCL signaling
- TGF-beta signaling
- inflammatory response
- base-excision repair
- DNA replication
- nucleotide-excision repair
- oxidative phosphorylation
- AGE-RAGE signaling
- SRP199578
- GSE20680
- GSE20681
- GSE21545
- GSE59867
- GSE62646
- GSE90074
Paper context: Uncovering the Genetic Links of SARS-CoV-2 Infections on Heart Failure Co-Morbidity by a Systems Biology Approach
multicohort omics
Supporting key finding
Independent COVID-19 and HF expression analyses yielded a 12-gene shared transcriptomic signature.
Overlap was calculated across separately profiled disease datasets, not in a cohort of people with both COVID-19 and HF.
- DEG threshold: |log2FC| > 1 and adjusted P < 0.05
- COVID-19 DEGs: 102
- HF DEGs: 253
- shared genes: 12: S100A8, ABCB1, S100A11, PTGS2 (COX2), LY96, XCL1, RORA, CCL11, CCL4, S100A12, BCL2 and AQP9
Original-source locator: KF1 · Results: Identification of shared transcriptomic signature between HF and COVID-19; Figure 1B-D
Paper evidence and provenance Original article DOI Cite
Research fields: Inflammation in cardiovascular disease; Cross-disease systems biology
Review topics: COVID-19 and heart failure inflammatory biology; Shared disease-associated expression programs
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
8 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Which datasets identified the shared COVID-19 and HF genes?
- What were the 12 shared COVID-19 and HF genes?
- Which genes were prioritized as network hubs?
- Did the study analyze patients with both COVID-19 and HF, and what does ‘genetic links’ mean?
- Was the five-gene signature clinically validated, and do 96.0% and 93.2% mean diagnostic accuracy?
- Did the study prove a gut-microbiome or circulating-LPS mechanism?
- Did glutathione or muramyl dipeptide treat COVID-19 or heart failure in this study?
- Why does Figure 1 mention GSE26687, and which HF dataset was used?
Paper-level research concepts
- COVID-19
- SARS-CoV-2 infection
- heart failure
- ischemic cardiomyopathy
- non-ischemic cardiomyopathy
- GSE147507
- GSE26887
- GSE164805
- GSE9128
- GDS3115
- 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
- lung-biopsy transcriptomics
- cardiac-tissue transcriptomics
- pooled PBMC microarrays
- 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
- Toll-like receptor signaling
- NF-κB signaling
- chemokine signaling
- cytokine signaling
- IL-17 signaling
- neutrophil chemotaxis
- monocyte chemotaxis
- inflammatory response
- response to lipopolysaccharide
- gut-heart axis
- gut microbiome dysbiosis
- microbial-product translocation
- lipopolysaccharide
Paper context: Efficacy and Safety of Apatinib Treatment for Advanced Cholangiocarcinoma After Failed Gemcitabine-Based Chemotherapy: An Open-Label Phase II Prospective Study
clinical cohort
Supporting key finding
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.
- median PFS: 95 days
- PFS reported 95 percent CI: 79.70–154.34 days
- median OS: 250 days
- OS reported 95 percent CI: 112.86–387.14 days
Original-source locator: KF3 · Results: Efficacy of Apatinib Treatment; Fig. 1
Paper evidence and provenance Original article DOI Cite
Research fields: Biliary tract oncology; Early-phase cancer treatment evidence
Review topics: Cholangiocarcinoma after chemotherapy failure; Single-arm phase II activity and toxicity reporting
Research & review context
Evidence scope and limitations
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.
Full paper evidence scope
4 reviewed questions — direct answers and evidence
Open the reviewed answer and supporting evidence on the paper page.
- Why do enrollment, safety and efficacy denominators differ?
- What response and disease-control results were reported?
- Do the survival estimates establish comparative benefit?
- Were all toxicities mild, and what safety denominator was used?
Paper-level research concepts
- advanced cholangiocarcinoma
- apatinib
- single-arm phase II
- open-label study
- objective response
- disease control
- PFS
- OS
- adverse events