Evaluation of Endothelin-1–Induced Pulmonary Vasoconstriction Following Myocardial Infarction
Bibliographic record
Abstract
Endothelin (ET) levels are elevated in congestive heart failure secondary to myocardial infarction (MI) and correlate well with the severity of pulmonary hypertension (PH), suggesting that the ET peptide could contribute to the pathophysiology of venous PH. Alterations of pulmonary vasoreactivity to ET after MI and the respective roles of the ET(A) and ET(B) receptors (ET(A)-R and ET(B)-R) have never been evaluated, to our knowledge. MI was induced in rats. Three weeks later, small pulmonary resistance arteries were mounted on a microvascular myograph. Cumulative concentration-response curves to ET-1 and sarafotoxin 6c (S6c) were performed. Response to ET was also assessed in the presence of ET-R antagonists. Heterodimerization of receptors was evaluated by immunoprecipitation of the ET(B)-R, followed by western blotting for the expression of the ET(A)-R. Maximal vasoconstriction and sensitivity to ET-1 were similar in sham and MI with values of 88 +/- 3.9% and 80 +/- 3.8%, respectively. The response to S6c was similarly less in both sham (67 +/- 5.7%) and MI groups (60 +/- 6.6%). When administered alone, the ET(A)-R antagonist (10 nM A-147627.1) and the ET(B)-R antagonist (1 microM A-192621.1) had no significant effect. However, their combination markedly reduced vaso-constriction (52 +/- 5.3%; P < 0.001). The endothelial and medial distribution of ET-Rs was similar in sham and MI groups. In vitro studies demonstrated co-immunoprecipitation of the ET(A)-R and ET(B)-R. Vasoconstriction of isolated resistance pulmonary arteries to ET agonists is not altered after MI. Dual antagonism results in optimal blockade of vasoconstriction, possibly because the ET(A)-R and ET(B)-R can form functional heterodimers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 | 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".