Unraveling the Impact of miR-146a in Pulmonary Arterial Hypertension Pathophysiology and Right Ventricular Function
Bibliographic record
Abstract
Pulmonary arterial hypertension (PAH) is a chronic disorder characterized by excessive pulmonary vascular remodeling, leading to elevated pulmonary vascular resistance and right ventricle (RV) overload and failure. MicroRNA-146a (miR-146a) promotes vascular smooth muscle cell proliferation and vascular neointimal hyperplasia, both hallmarks of PAH. This study aimed to investigate the effects of miR-146a through pharmacological or genetic inhibition on experimental PAH and RV pressure overload animal models. Additionally, we examined the overexpression of miR-146a on human pulmonary artery smooth muscle cells (hPASMCs). Here, we showed that miR-146a genic expression was increased in the lungs of patients with PAH and the plasma of monocrotaline (MCT) rats. Interestingly, genetic ablation of miR-146a improved RV hypertrophy and systolic pressures in Sugen 5415/hypoxia (SuHx) and pulmonary arterial banding (PAB) mice. Pharmacological inhibition of miR-146a improved RV remodeling in PAB-wild type mice and MCT rats, and enhanced exercise capacity in MCT rats. However, overexpression of miR-146a did not affect proliferation, migration, and apoptosis in control-hPASMCs. Our findings show that miR-146a may play a significant role in RV function and remodeling, representing a promising therapeutic target for RV hypertrophy and, consequently, PAH.
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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 | 0.001 | 0.001 |
| 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".