Endothelin B Receptor-Mediated Regulation of Endothelin-1 Content and Release in Cultured Porcine Aorta Endothelial Cell
Bibliographic record
Abstract
Several cardiovascular diseases are associated with an increase in circulating levels of endothelin-1 (ET-1). Little is known about the consequences of this increase on endothelial cell responses with respect to ET-1 production and regulation. Confluent, passage 1, cultured porcine aorta endothelial cells were exposed to exogenous ET-1 (0.1 microM) for 24 h. BQ788 (1 microM, ETB receptor antagonist) but not BQ123 (1 microM, ETA receptor antagonist) significantly (p < 0.05) reduced 125I-ET-1 uptake. The effects of BQ788 were mimicked by dansylcadaverine (0.5 mM) but not nystatin (50 microg/ml). Immunoreactive ET-1 endothelial cell content doubled (p < 0.05) after 24 h of exogenous ET-1 treatment. Bosentan (10 microM, dual ETA/B receptor antagonist) reduced (p < 0.05) immunoreactive ET-1 content in control cells. Bosentan prevented exogenous ET-1-induced endothelial cell ET-1 loading, suggesting that exogenous ET-1 is partly recycled. PreproET-1 mRNA levels were reduced (p < 0.05) by exogenous ET-1 after 24 h, an effect blocked by BQ788 and bosentan. When used alone, both receptor antagonists increased mRNA levels. The results of this study suggest that part of ET-1 is recycled through ETB receptors and subsequently released to contribute to constitutive ET-1 overflow. ET-1 exerts a negative feedback on ET-1 gene transcription, which is dependent on ETB receptor activation and internalization of the complex ET-1/ETB receptor. The maintenance of this negative regulatory loop of ET-1 production may be essential for the normal endothelial physiology.
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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 | 0.001 |
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".