ET <sub>B</sub> Receptor Blockade Potentiates the Pressor Response to Big Endothelin-1 But Not Big Endothelin-2 in the Anesthetized Rabbit
Bibliographic record
Abstract
The precursor of endothelin-1, big endothelin-1, is considered to be a more reliable marker of systemic production of vasoactive peptide. However, it is largely unclear whether ET(B) receptor-dependent clearance and endothelium-derived relaxing factors affect the precursor in a similar manner to mature ET-1. These ET(B)-dependent modulations of big ET-1 and big ET-2 pressor properties were therefore studied in the anesthetized rabbit. When injected into the left cardiac ventricle, ET-1 and ET-2 (0.01 to 1 nmol/kg) each induced biphasic responses (a depressor followed by a pressor response), whereas big ET-1 and big ET-2 (0.1 to 3 nmol/kg) caused only protracted pressor responses. The highest dose of big ET-1 caused significantly greater responses than ET-1, ET-2, or big ET-2. A selective ET(A) receptor antagonist, BQ-123 (1 mg/kg), markedly reduced pressor responses to all 4 peptides, whereas blockade of ET(B) receptors with BQ-788 (0.25 mg/kg) sharply potentiated the responses to ET-1, ET-2, and big ET-1, but not to big ET-2. Indomethacin (10 mg/kg) sharply potentiated the pressor response to ET-1 (1 nmol/kg), but not big ET-1, at all time points. In control animals, ET-1, but not big ET-1, also triggered an indomethacin-sensitive increase in circulating prostacyclin. Finally, systemically administered big ET-1, but not big ET-2, induced a phosphoramidon-sensitive increase in plasma IR-ET. Our results suggest a significant limiting role of ET(B) receptors on pressor responses to big ET-1. In contrast, the same receptor entities do not modulate the hemodynamic properties of the ET-2 precursor, given that, unlike big ET-1, it is poorly converted in the pulmonary or systemic circulation in anesthetized rabbits.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".