Expression of microRNA miR-17-3p inhibits mouse cardiac fibroblast senescence by targeting Par4
Bibliographic record
Abstract
The microRNA miR-17-92 cluster plays a fundamental role in heart development. The aim of this study was to investigate the effect of a member of this cluster, miR-17, on cardiac senescence. We examined the roles of miR-17 in senescence and demonstrated that miR-17-3p attenuates cardiac aging in the myocardium by targeting Par4 (also known as PAWR). This upregulates the downstream proteins CEBPB, FAK, N-cadherin, vimentin, Oct4 and Sca-1 (also known as stem cell antigen-1), and downregulates E-cadherin. Par4 has been reported as a tumor suppressor gene that induces apoptosis in cancer cells, but not in normal cells. Repression of Par4 by miR-17-3p enhances the transcription of CEBPB and FAK, which promotes mouse cardiac fibroblast (MCF) epithelial-to-mesenchymal transition (EMT) and self-renewal, resulting in cellular senescence and apoptosis resistance. We conclude that Par4 can bind to the CEBPB promoter and inhibit its transcription. Decreased Par4 expression increases the amount of CEBPB, which binds to the FAK promoter and enhances FAK transcription. Par4, CEBPB and FAK form a senescence signaling pathway, playing roles in modulating cell survival, growth, apoptosis, EMT and self-renewal. Through this novel senescence signaling axis, miR-17-3p represses Par4 expression, acting pleiotropically as a negative modulator of cardiac aging and cardiac fibroblast cellular senescence.
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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 | 0.001 | 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".