Defining Transcriptomic Heterogeneity between Left and Right Ventricle-Derived Cardiac Fibroblasts
Bibliographic record
Abstract
Cardiac fibrosis is a key aspect of heart failure, leading to reduced ventricular compliance and impaired electrical conduction in the myocardium. Various pathophysiologic conditions can lead to fibrosis in the left ventricle (LV) and/or right ventricle (RV). Despite growing evidence to support the transcriptomic heterogeneity of cardiac fibroblasts (CFs) in healthy and diseased states, there have been no direct comparisons of CFs in the LV and RV. Given the distinct natures of the ventricles, we hypothesized that LV- and RV-derived CFs would display baseline transcriptomic differences that influence their proliferation and differentiation following injury. Bulk RNA sequencing of CFs isolated from healthy murine left and right ventricles indicated that LV-derived CFs may be further along the myofibroblast transdifferentiation trajectory than cells isolated from the RV. Single-cell RNA-sequencing analysis of the two populations confirmed that Postn+ CFs were more enriched in the LV, whereas Igfbp3+ CFs were enriched in the RV at baseline. Notably, following pressure overload injury, the LV developed a larger subpopulation of pro-fibrotic Thbs4+/Cthrc1+ injury-induced CFs, while the RV showed a unique expansion of two less-well-characterized CF subpopulations (Igfbp3+ and Inmt+). These findings demonstrate that LV- and RV-derived CFs display baseline subpopulation differences that may dictate their diverging responses to pressure overload injury. Further study of these subpopulations will elucidate their role in the development of fibrosis and inform on whether LV and RV fibrosis require distinct treatments.
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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".