Caspase inhibition reduces severe pulmonary hypertension in the AdTGF-1β/SU5416 model of angioproliferative pulmonary hypertension and lung fibrosis
Bibliographic record
Abstract
Pulmonary hypertension (PH) is associated with increased mortality in patients with idiopathic pulmonary fibrosis (IPF). The interaction between the fibrotic process and the pulmonary vasculature is incompletely understood. The current study aimed to investigate whether broad spectrum caspase inhibition can reduce severe angioproliferative PH in the combined model of AdTGF-β1 lung fibrosis and the VEGF receptor inhibitor SU5416. Female Sprague Dawley rats received AdTGF-β1 intratracheally at day 0, as well as one dose of SU5416 s.c. or CMC. Some AdTGF-β1/SU5416 animals received the caspase inhibitor Z-Asp-CH2-DCB or vehicle (DMSO) from day 6-28 At day 28, invasive pulmonary hemodynamics were assessed. The right lung was used for protein and RNA isolation, and the left lung was inflated with formalin and processed for histology. We detected clusters of VWF+ endothelial cells occluding the lumen of small pulmonary arteries in AdTGF-β1/SU5416, together with severe PH in AdTGF-β1/SU5416 rats vs. AdTGF-β1/CMC. At the same time, lung fibrosis was increased, as indicated by elevated mRNA expression of profibrotic and matrix genes. Western blots showed a significant increase in caspase-3 cleavage in AdTGF-β1/SU5416 rats. Treatment with Z-Asp-CH2-DCB reduced right ventricular systolic pressures by 19.4 mmHg in average in AdTGF-β1/SU5416 animals (P<0.05 vs. DMSO). In conclusion, our results indicate that angioproliferative pulmonary vasculopathy was induced in this new model, together with severe fibrosis, and that increased apoptosis contributes to both increased fibrosis and vascular pathology.
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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 | 0.000 |
| 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".