Abstract 77: MiR-125b Regulates Myofibroblast Transition and Cardiac Fibrosis
Bibliographic record
Abstract
Transforming growth factor-β (TGF-β)-induced fibroblast-to-myofibroblast transition (FMT) is a critical determinant of cardiac fibrosis. However, the contribution of microRNAs leading to TGF-β-induced FMT and cardiac fibrosis are not well-understood. Our results elucidate that blocking the canonical TGF-β pathway protects from FMT in primary cultures of human cardiac fibroblasts and that miR-125b is significantly upregulated during cardiac FMT. Furthermore, we observed significant upregulation of miR-125b in fibrotic human myocardium and two murine models of cardiac fibrosis. Importantly, we discovered that miR-125b is sufficient to induce cardiac FMT. In contrast, the knockdown of miR-125b using an antagomir approach attenuated TGF-β-induced FMT. In silico analysis and biochemical analysis revealed that miR-125b directly targets multiple anti-fibrotic mediators including p53 and apelin. In addition, miR-125b also plays a potent role in the regulation of fibroblast proliferation, an important cause of cardiac fibrosis. Finally, miR-125b was successfully inhibited in vivo by the systemic delivery of locked nucleic acid (LNA) targeted against miR-125b both in the presence and absence of Angiotensin II (Ang II). These results demonstrated that LNA-125b protected against Ang II-induced proliferation and fibrosis in the mouse heart in vivo. We conclude that TGF-β-induced miR-125b is an important regulator of both fibroblast proliferation and FMT, and miR-125b inhibits key anti-fibrotic mediators to promote cardiac fibrosis. We propose that miR-125b may serve as a novel therapeutic target for the preventative therapy for fibrosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".