Single-cell genomics illustrates heterogeneous phenotypes of myocardial fibroblasts under ischemic insults
Bibliographic record
Abstract
Myocardial regenerative strategies are promising where the choice of ideal cell population is crucial for successful translational applications. Herein, we explored the regenerative/repair responses of infarct zone cardiac fibroblast(s) (CF) by unveiling their phenotype heterogeneity at single-cell resolution. CF were isolated from the infarct zone of Yucatan miniswine that suffered myocardial infarction, cultured under simulated ischemic and reperfusion, and grouped into control, ischemia, and ischemia/reperfusion. The single-cell RNA sequencing analysis revealed 19 unique cell clusters suggesting distinct subpopulations. The status of gene expression (log2 fold change (log2 FC) > 2 and log2 FC < -2) was used to define the characteristics of each cluster unveiling with diverse features, including the pro-survival/cardioprotective (Clusters 1, 3, 5, 9, and 18), vasculoprotective (Clusters 2 and 5), anti-inflammatory (Clusters 4 and 17), proliferative (Clusters 4 and 5), nonproliferative (Clusters 6, 8, 11, 16, 17, and 18), proinflammatory (Cluster 6), profibrotic/pathologic (Clusters 8 and 19), antihypertrophic (Clusters 8 and 10), extracellular matrix restorative (Clusters 9 and 12), angiogenic (Cluster 16), and normal (Clusters 7 and 15) phenotypes. Further understanding of these unique phenotypes of CF will provide significant translational opportunities for myocardial regeneration and cardiac management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".