Increased endothelin-1 and endothelin receptor expression in myocytes of ischemic and reperfused rat hearts and ventricular myocytes exposed to ischemic conditions and its inhibition by nitric oxide generation
Bibliographic record
Abstract
Endothelin-1 (ET-1) and nitric oxide (NO) exert opposite effects in the cardiovascular system, and there is evidence that the NO counters the potential deleterious effects of ET-1. We investigated whether NO affects the increased mRNA expression of ET-1 and endothelin receptors induced by (i) 30 min of ischemia with or without 30 min reperfusion in myocytes from isolated rat hearts or (ii) ischemic conditions (acidosis or hypoxia) in cultured rat neonatal ventricular myocytes. Ischemia with or without reperfusion produced more than a twofold increase in mRNA expression of ET-1 as well as the ET(A) and ET(B) receptor (P < 0.05), although these effects were completely blocked by the NO donor 3-morpholinosydnonimine (SIN-1; 1 microM). To assess the possible factors regulating ET expression, myocytes were exposed to acidosis (pH 6.8-6.2) or to hypoxic conditions in an anaerobic chamber for 24 h in the presence or absence of SIN-1. At all acidic pHs, ET-1 and ET(A) receptor mRNA expression was significantly (P < 0.05) elevated approximately threefold, although the magnitude of elevation was independent of the degree of acidosis. These effects were completely prevented by SIN-1. ET(B) receptor expression was unaffected by acidosis. Hypoxia increased ET-1 as well as ET(A) and ET(B) receptor expression threefold (P < 0.05), although this was unaffected by SIN-1. Our results demonstrate that myocardial ischemia and reperfusion upregulate the ET system, which is inhibited by NO. Although increased expression of the ET system can be mimicked by both acidosis and hypoxia, only the effects of the former are NO sensitive. NO may serve an endogenous inhibitory factor which regulates the expression of the ET system under pathological conditions.
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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) | 0.000 | 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 | 0.000 | 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".