The α<sub>1</sub>-adrenergic receptor not the DA<sub>1</sub>-dopaminergic receptor mediates cyclosporine–SKF38393 renovascular interaction
Bibliographic record
Abstract
In this study, we investigated the effect of acute exposure to cyclosporine A (CyA) on renal vasodilations evoked by the DA(1) dopaminergic agonist SKF38393 and whether dopamine DA(1) receptors are directly involved in the interaction. Changes evoked by CyA in SKF38393 vasodilations were evaluated in phenylephrine-preconstricted isolated perfused rat kidneys in the absence and presence of SCH23390, a DA(1) receptor antagonist. SKF38393 (3 x 10(-8) to 3 x 10(-6) mol) produced dose-dependent reductions in the renal perfusion pressure that were significantly attenuated in tissues pretreated with SCH23390 or CyA. Unlike SKF38393, the vasodilatory action of sodium nitroprusside, a nitrovasodilator, was not altered by CyA. The attenuating effect of CyA on SKF38393 vasodilations was preserved in preparations pretreated with SCH23390, suggesting that sites other than DA(1) receptors may be involved in CyA-SKF38393 interaction. The study was then extended to investigate the possible involvement of renal alpha1-adrenoceptors in the interaction. Blockade of alpha(1)-adrenoceptors by prazosin (30 nmol/L) significantly reduced the vasodilatory effect of SKF38393 and virtually abolished the CyA-induced attenuation of SKF38393 responses. Further, CyA failed to alter SKF38393 vasodilations when the renal tone was raised with prostaglandin F2alpha (PGF2alpha), a vasoconstrictor whose effect is independent of alpha(1)-adenoceptors. Together, these findings support earlier reports that both DA(1) and alpha(1)-receptors mediate the renal vasodilatory action of SKF38393 and suggest that CyA interacts selectively with the alpha(1)-receptor component to compromise SKF38393 responses.
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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) | 0.002 | 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".