A miR-208–Mef2 Axis Drives the Decompensation of Right Ventricular Function in Pulmonary Hypertension
Bibliographic record
Abstract
RATIONALE: Right ventricular (RV) failure is a major cause of morbidity and mortality in pulmonary hypertension, but its mechanism remains unknown. Myocyte enhancer factor 2 (Mef2) has been implicated in RV development, regulating metabolic, contractile, and angiogenic genes. Moreover, Mef2 regulates microRNAs that have emerged as important determinants of cardiac development and disease, but for which the role in RV is still unclear. OBJECTIVE: We hypothesized a critical role of a Mef2-microRNAs axis in RV failure. METHODS AND RESULTS: In a rat pulmonary hypertension model (monocrotaline), we studied RV free wall tissues from rats with normal, compensated, and decompensated RV hypertrophy, carefully defined based on clinically relevant parameters, including RV systolic and end-diastolic pressures, cardiac output, RV size, and morbidity. Mef2c expression was sharply increased in compensating phase of RVH tissues but was lost in decompensation phase of RVH. An unbiased screening of microRNAs in our model resulted to a short microRNA signature of decompensated RV failure, which included the myocardium-specific miR-208, which was progressively downregulated as RV failure progressed, in contrast to what is described in left ventricular failure. With mechanistic in vitro experiments using neonatal and adult RV cardiomyocytes, we showed that miR-208 inhibition, as well as tumor necrosis factor-α, activates the complex mediator of transcription 13/nuclear receptor corepressor 1 axis, which in turn promotes Mef2 inhibition, closing a self-limiting feedback loop, driving the transition from compensating phase of RVH toward decompensation phase of RVH. In our model, serum tumor necrosis factor-α levels progressively increased with time while serum miR-208 levels decreased, mirroring its levels in RV myocardium. CONCLUSIONS: We describe an RV-specific mechanism for heart failure, which could potentially lead to new biomarkers and therapeutic targets.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".