Abstract 4139371: Treatment of pulmonary arterial hypertension by blocking integrin a5b1, a potential disease-modifying strategy
Bibliographic record
Abstract
Introduction: Pulmonary arterial hypertension (PAH) is marked by pathological remodeling of distal arteries, driven by hyperplasia of pulmonary arterial smooth muscle cells (PASMCs), dysfunction of pulmonary arterial endothelial cells (PAECs), and increased deposition of the extracellular matrix (ECM). Hypothesis: Considering the crucial role of ECM in vascular restructuring, we investigated the potential of therapeutically targeting a5b1, a fibronectin-binding integrin involved in cell proliferation and angiogenesis, for PAH treatment. Aim: To evaluate the therapeutic potential of targeting a5b1 for the treatment of PAH. Methods: We have developed potent, orally bioavailable small molecule inhibitors (SMis) and monoclonal antibodies (mAbs) targeting a5b1 to evaluate its therapeutic potential. The effect of a5b1 inhibition was assessed in cultured PASMCs, human precision-cut lung slices (PCLS), and a rat Sugen/hypoxia PAH model. Results: PAH patients exhibited increased expression of fibronectin and a5b1 in distal pulmonary arteries. Selective inhibition of a5b1 in cultured PASMCs modulated multiple pathways involved in cell cycle regulation at both transcriptional and post-transcriptional levels, thereby blocking cellular proliferation. PCLS treated with a5b1 inhibitors showed decreased expression of pathways involved in ECM deposition and reduced levels of smooth muscle cell markers. In the rat Sugen/hypoxia PAH model, a5b1 inhibition with either an SMi or mAb significantly improved cardiac and vascular function by reducing pulmonary arterial wall thickness, right ventricular hypertrophy, and fibrosis. Cardiac improvement is further evidenced by a reduction in circulating NT-proBNP and NT-proANP levels. Conclusion: These findings reveal a previously underappreciated role for a5b1 in PAH pathogenesis and support the potential of a5b1 inhibition as a disease-modifying therapeutic strategy for managing 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) | 0.001 | 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 | 0.001 | 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".