miR‐126 at the dawn of angiogenic defect seen in PAH right ventricular failure.
Bibliographic record
Abstract
INTRODUCTION Right ventricular (RV) failure is the most important predictor of both morbidity and mortality in pulmonary arterial hypertension (PAH). In PAH patients, hypertrophied RV is relatively ischemic, potentially because of suppressed angiogenesis. MicroRNAs (miRNAs) are important regulator of angiogenesis, especially miR‐126, which by inhibiting SPRED‐1, triggers the VEGF pathway and thus promoting angiogenesis. We hypothesized that specific miR‐126 downregulation in the RV promotes ischemia and triggers the transition from a compensated (CRV) to a decompensated (DRV) RV. Results We studied RV free wall tissues from humans with normal RV (NRV) functions, CRV and PAH (DRV), and rats with NRV and DRV. In both humans and rats, PAH DRV had decreased miR‐126 and microvessels density compared to NRV. Under the same conditions, miR‐126 were unchanged in the LV. In endothelial cells (EC) isolated from human RV, miR‐126 up‐regulation increased angiogenesis in a PAH DRV (matrigel assay), while downregulation of miR‐126 in EC from controls or CRV mimicked the PAH phenotype by decreasing angiogenesis. Artificial miR‐126 up‐regulation in PAH rat model improved RV functions, increased capillarity and decreased fibrosis specifically in RV, with no effect on PAP or lung vascular remodeling. Increasing miR‐126 levels in human PAH DRV endothelial cells also increased angiogenesis (matrigel assay). CONCLUSION We demonstrated that 1) exclusive RV downregulation of miR‐126 contributes to the ischemic status of the DRV; 2) in vivo up‐regulation of miR‐126 specifically improves RV functions. Thus, targeting miR‐126 represents a specific new avenue of investigation in preventing and reversing the failing RV in 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".