Brown Norway rats show impaired nNOS-mediated information transfer in renal autoregulationThis article is part of a Special Issue on Information Transfer in the Microcirculation.
Bibliographic record
Abstract
Nonselective inhibition of NO synthase (NOS) augments myogenic autoregulation of renal blood flow (RBF) and profoundly reduces RBF. Previously in Wistar rats, we showed that augmented autoregulation, but not vasoconstriction, is duplicated by intrarenal inhibition of neuronal NOS (nNOS), whereas intrarenal inhibition of inducible NOS (iNOS) has no effect on RBF or on RBF dynamics. Thus macula densa nNOS transfers information from tubuloglomerular feedback to the afferent arteriole. This information flow requires that macula densa nNOS can sufficiently alter ambient NO concentration, that is, that endothelial NOS (eNOS) and iNOS do not alter local NO concentration. Because the Brown Norway rat often shows exaggerated responses to NOS inhibition and has peculiarities of renal autoregulation that are related to NO, we used this strain to study systemic and renal vascular responses to NOS inhibition. The first experiment showed transient blood pressure reduction by bolus i.v. acetylcholine that was dose-dependent in both strains and substantially prolonged in Brown Norway rats. The depressor response decayed more rapidly after nonselective NOS inhibition and the difference between strains was lost, indicating a greater activity of eNOS in Brown Norway rats. In Brown Norway rats, selective inhibition of iNOS reduced RBF (-16% +/- 7%) and augmented myogenic autoregulation, whereas nNOS inhibition reduced RBF (-25% +/- 4%) and did not augment myogenic autoregulation. The significant responses to intrarenal iNOS inhibition, the reduced modulation of autoregulation by nNOS inhibition, and the enhanced endothelial depressor response suggest that physiological signalling by NO within the kidney is impaired in Brown Norway rats because of irrelevant or inappropriate input of NO by eNOS and iNOS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".