Endothelial PRMT7 prevents dysfunction, promotes revascularization and enhances cardiac recovery post-myocardial infarction
Bibliographic record
Abstract
Myocardial infarction (MI) induces ischemic damage, triggering endothelial cell (EC) dysfunction that impairs revascularization and cardiac recovery. A key contributor to this dysfunction is excessive endoplasmic reticulum (ER) stress, which is activated by MI and exacerbates EC apoptosis and impaired angiogenesis. Here we investigate the role of endothelial-specific protein arginine methyltransferase 7 (PRMT7) in mitigating ER stress and promoting vascular homeostasis after MI. We demonstrate that PRMT7 expression is upregulated in ECs under tumor necrosis factor α or tunicamycin treatment, while its inhibition exacerbates ER stress and induces EC death. Using endothelial-specific PRMT7-knockout models, we show that PRMT7 deficiency increases apoptosis and fibrosis, impairing cardiac recovery. Transcriptomic analysis reveals that PRMT7 loss leads to the upregulation of pro-apoptotic pathways and suppression of angiogenic and proliferative signaling. Conversely, PRMT7 overexpression or treatment with the PRMT7-inducing drug bindarit restores EC function, suppresses ER stress and enhances revascularization and cardiac repair after MI. These findings establish endothelial PRMT7 as a critical regulator of EC survival and function, highlighting its potential as a therapeutic target to mitigate ER stress and improve post-MI cardiac recovery.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".