Role for RUNX2/HDAC6 Axis in Pulmonary Arterial Hypertension
Bibliographic record
Abstract
Introduction Pulmonary arterial hypertension (PAH) is a vascular remodeling disease characterized by enhanced pulmonary artery smooth muscle cells (PASMC) proliferation, migration, calcification and suppressed apoptosis. Numerous biological pathways have been implicated in this phenotype, including HIF‐1α. Recent studies have shown that miR‐204 downregulation upregulates the expression of RUNX2. RUNX2 is implicated in many features seen in PAH‐PASMC in part through the activation of HIF‐1α by a HDAC6‐depepdent mechanism. Thus we hypothesis that miR‐204‐dependent upregulation of RUNX2/HDAC6 axis promotes HIF‐1 α and development of PAH. Results Using human lungs, distal PAs and isolated PASMC from both control and PAH patients, we demonstrated a significant upregulation of RUNX2 and HDAC6 in PAH. Gain and loss of functions experiments in PASMC showed that downregulation of miR‐204 in controls PASMC increase RUNX2 expression, while increases miR‐204 in PAH‐PASMC decrease it. In controls PASMC, RUNX2 upregulation increases calcification,migration, proliferation, resistance to apoptosis through an HDAC6 and HIF‐1α dependent mechanism, as both tubastatin A (HDAC6 inhibitor) and siHIF‐1α blocks RUNX2 effects. Similarly in PAH‐PASMC siRUNX2 has the opposite effects. Finally, in sugen/hypoxia rat model of PAH, nebulization of siRUNX2 decreased mean PA pressure, pulmonary vascular resistance and increased compliance and cardiac output. Conclusion Taken together, our study uncovers a new miR‐204 dependent up regulation of RUNX2/HDAC6 axis contributing to calcification and to normoxic activation of HIF‐1α leading to proliferation, migration and resistance to apoptosis in PAH‐PASMC.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".