Dual ET<sub>A</sub>/ET<sub>B</sub> blockade with macitentan improves both vascular remodeling and angiogenesis in pulmonary arterial hypertension
Bibliographic record
Abstract
Dysregulated metabolism and rarefaction of the capillary network play a critical role in pulmonary arterial hypertension (PAH) etiology. They are associated with a decrease in perfusion of the lungs, skeletal muscles, and right ventricle (RV). Previous studies suggested that endothelin‐1 (ET‐1) modulates both metabolism and angiogenesis. We hypothesized that dual ETA/ETB receptors blockade improves PAH by improving cell metabolism and promoting angiogenesis. Five weeks after disease induction, Sugen/hypoxic rats presented severe PAH with pulmonary artery (PA) remodeling, RV hypertrophy and capillary rarefaction in the lungs, RV, and skeletal muscles (microCT angiogram, lectin perfusion, CD31 staining). Two‐week treatment with dual ETA/ETB receptors antagonist macitentan (30 mg/kg/d) significantly improved pulmonary hemodynamics, PA vascular remodeling, and RV function and hypertrophy compared to vehicle‐treated animals (all P = 0.05). Moreover, macitentan markedly increased lung, RV and quadriceps perfusion, and microvascular density (all P = 0.05). In vitro, these effects were associated with increases in oxidative phosphorylation (oxPhox) and markedly reduced cell proliferation of PAH‐PA smooth muscle cells (PASMCs) treated with macitentan without affecting apoptosis. While macitentan did not affect oxPhox, proliferation, and apoptosis of PAH–PA endothelial cells (PAECs), it significantly improved their angiogenic capacity (tube formation assay). Exposure of control PASMC and PAEC to ET‐1 fully mimicked the PAH cells phenotype, thus confirming that ET‐1 is implicated in both metabolism and angiogenesis abnormalities in PAH. Dual ETA/ETB receptor blockade improved the metabolic changes involved in PAH‐PASMCs’ proliferation and the angiogenic capacity of PAH‐PAEC leading to an increased capillary density in lungs, RV, and skeletal muscles.
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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) | 0.001 | 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".