P117 <break /> Macitentan prevents pulmonary fibrosis progression and secondary pulmonary hypertension induced by TGF-β1 overexpression in rats
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis is a progressive disease with unknown cause and limited treatment options. Pulmonary hypertension (PH) is frequent in patients and is a prognostic marker indicating increased mortality risk. We already demonstrated that PH develops in a rat model of overexpression of Transforming-Growth-Factor-β1 (AdTGF-β1). Macitentan (Opsumit®) is an endothelin receptor antagonist which is approved for treatment of pulmonary arterial hypertension, a life-threatening disorder which compromises lungs’ and heart’s function. We hypothesized that Macitentan will improve PH and fibrosis progression induced by AdTGF-β1. Rats received AdTGF-β1 (D0) and daily gavage of macitentan, pirfenidone, their combination or saline (D14-D28). Pulmonary artery pressure (PAP) was measured using a pressure catheter (SPR-407). Fibrosis was evaluated by morphometric measurements coupled with hydroxyproline assay. AdTGF-β1 induced lung fibrosis with an increase in collagen deposition combined with a significant increase in PAP compared to controls. Treatment with pirfenidone prevented fibrosis progression as shown by a reduction in collagen deposition and a decrease in fibrotic areas of the lung at D28. However, pirfenidone treatment did not affect the PAP increase induced by AdTGF-β1. Treatment with macitentan prevented the increase in PAP induced by AdTGF-β1 and also prevented fibrosis progression from D14 to D28 as shown by a reduction in collagen deposition and a decrease in fibrotic areas of the lung. The combination of both drugs prevented PAP increase and fibrosis progression.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".