LU135252, an endothelin<sub>A</sub> receptor antagonist did not prevent pulmonary vascular remodelling or lung fibrosis in a rat model of myocardial infarction
Bibliographic record
Abstract
The early intervention with endothelin(A) (ET(A)) receptor antagonists following coronary artery ligation has been shown to reduce the development of pulmonary hypertension, despite a lack of improvement in left ventricular function. The present study examined the contribution of pulmonary vascular remodelling and the progression of lung fibrosis in the development of pulmonary hypertension and the subsequent role of endothelin-1 in these processes in a rat model of myocardial infarction (MI). The administration of 60 mg kg(-1) per day of the specific ET(A) receptor antagonist LU135253 ((+)-(S)-2-(4, 6-dimethoxy-pyrimidin-2-yloxy)-3-methoxy-3,3-diphenyl-propionic acid) 24 h following coronary artery ligation, failed to improve left ventricular contractile indices, but reduced the extent of pulmonary hypertension, as reflected by the significant decrease in right ventricular systolic pressure. The medial wall thickness of small pulmonary arteries (50 - 200 microm) was significantly increased 4 weeks following MI, albeit LU135253 treatment did not ameliorate this pattern of vascular remodelling. The steady-state mRNA levels of collagen, fibronectin, transforming growth factor-beta(1), and -beta(3) were significantly increased in the lungs of MI rats. The treatment with LU135252 did not alter this pattern of gene expression. Thus, these data demonstrate pulmonary vascular remodelling and the increased expression of extracellular matrix proteins represent underlying mechanisms implicated in the development of pulmonary hypertension in the MI rat. Despite the amelioration of the pulmonary hypertensive state, ET(A) receptor blockade was insufficient to reverse pulmonary vascular remodelling, or the development of lung fibrosis in the MI rat.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".