mir-126 contribute to angiogenesis defect in pulmonary arterial hypertension right ventricle failure
Bibliographic record
Abstract
INTRODUCTION: Right Ventricular Failure (RVF) 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 that lead to an imbalance between O2 demand and delivery. MicroRNAs (miRNAs) have emerged as important determinants of angiogenesis especially angio-miR-126, which by inhibiting SPRED-1, triggers VEGF pathway and thus promotes angiogenesis. We hypothesized that specific miR-126 downregulation will promote RV ischemia and the transition from compensated (CRV) to a decompensated (DRV) RV. METHODS/RESULTS: We studied free RV wall tissue from humans with normal RV functions, CRV and PAH (DRV). We used qRT-PCR to study the expression of miR-126 and CD31 immunofluorescence to measure heart microcirculation. As expected, compared to both control and CRV, DRV has decreased miR-126 and microvessels density creating an imbalance between O2 demand and delivery. Interestingly, under the same conditions, miR-126 expression did not fall in LV. miR-126 downregulation in DRV increases SPRED-1, decreasing RAF (P-RAF/RAF) and MAP kinase (P-MAP/MAP) thus decreasing VEGF pathway. Finally, in endothelial cells isolated from human RV, miR-126 up-regulation increased angiogenesis in a PAH model while downregulation of miR-126 in control or CRV mimicked PAH phenotype by decreasing angiogenesis CONCLUSION: We demonstrated for the first time that: 1) specific RV downregulation of miR-126 contributes to ischemic status of the DRV. Targeting miR-126 represents a new avenue of investigation in preventing and reversing failing RV.
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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) | 0.002 | 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".