Interactive modulation of renal myogenic autoregulation by nitric oxide and endothelin acting through ET-B receptors
Bibliographic record
Abstract
In rats, nitric oxide modulates renal autoregulation in steady-state experiments and the myogenic mechanism in dynamic studies. Interactive modulation of autoregulation by nitric oxide and endothelin-1, predominantly involving endothelin B receptors, has been reported although it remains unclear whether the interaction is synergistic or obligatory or whether it affects the myogenic component of autoregulation. Nonselective inhibition of nitric oxide synthase (L(omega)-nitro-l-arginine methyl-ester; l-NAME) with endothelin A and B selective receptor antagonists BQ-123 and BQ-788, all infused into the renal artery, plus time series analysis were used to test the interactive actions of nitric oxide and endothelin on renal vascular conductance and on autoregulation. Nonselective endothelin receptor antagonism blunted the constrictor response to subsequent l-NAME but had no effect on previously established l-NAME-induced vasoconstriction. BQ-123 did not affect conductance and caused only minor reduction in myogenic autoregulatory efficiency. Responses to BQ-123 and l-NAME were additive and not interactive. BQ-788 and l-NAME each caused strong vasoconstriction alone and in the presence of the other, indicating that coupling between nitric oxide- and endothelin B-mediated events is not obligatory. l-NAME augmented myogenic autoregulation, and subsequent BQ-788 did not alter this response. However, BQ-788 infused alone also enhanced myogenic autoregulation but resulted in significant impairment of myogenic autoregulation by subsequent l-NAME. Thus the interaction between nitric oxide and endothelin is clearly nonadditive and, because it is asymmetrical, cannot be explained simply by convergence on a common signal pathway. Instead one must postulate some degree of hierarchical organization and that nitric oxide acts downstream to endothelin B activation.
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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 | 0.000 |
| 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".