Interaction between nitric oxide and renal myogenic autoregulation in normotensive and hypertensive rats
Bibliographic record
Abstract
Blood pressure fluctuates continuously throughout life and autoregulation is the primary mechanism that isolates the kidney from this fluctuation. Compared with Wistar rats, Brown Norway (B-N) rats display impaired renal myogenic autoregulation when blood pressure fluctuation is increased. They also are very susceptible to hypertension-induced renal injury. Because blockade of nitric oxide augments myogenic autoregulation in Wistar rats, we compared the response of the myogenic system in B-N rats to nitric oxide blockade with that of other strains [Wistar, Sprague-Dawley, Long-Evans, spontaneously hypertensive (SHR)]. Renal blood flow dynamics were assessed in isoflurane anesthetized rats before and after inhibition of nitric oxide synthase by Lomega-nitro-arginine methyl-ester (L-NAME, 10 mg/kg, iv). Under control conditions, myogenic autoregulation in the B-N rats was weaker than in the other strains. Myogenic autoregulation was not augmented after L-NAME administration in the SHR, but was augmented in all the normotensive rats. The enhancement was significantly greater in B-N rats so that after L-NAME the efficiency of autoregulation did not differ among the strains. The data suggest that nitric oxide is involved in the impaired myogenic autoregulation seen in B-N rats. Furthermore, the similarity of response in Wistar, Long-Evans, and Sprague-Dawley rats suggests that modulation by nitric oxide is a fundamental property of renal myogenic autoregulation.
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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".