Nitric oxide inhibits superoxide-stimulated urea permeability in the rat inner medullary collecting duct
Bibliographic record
Abstract
The inner medullary collecting duct (IMCD) contains relatively high nitric oxide (NO) synthetic capacity, but the effect of NO on IMCD transport remains unclear. We determined the effect of NO on basal and vasopressin (AVP)-stimulated urea (Purea) and water (Pf) permeabilities in isolated, perfused rat IMCD. The NO donor S-nitroso-N-acetylpenicillamine (SNAP) increased cGMP production in IMCD, but neither SNAP (10(-4) M) nor 8-BrcGMP (10(-4) M), the cell-permeable analog of cGMP, affected basal or AVP-stimulated Purea. The free radical superoxide is produced by oxidases in the kidney and can interact with NO. To determine the effect of superoxide generation on transport, IMCDs were incubated with diethyldithiocarbamate (DETC; 10(-3) M), the inhibitor of superoxide dismutase (SOD). DETC significantly increased basal and AVP-stimulated Purea (control: 28.7 +/- 4.5 vs. DETC: 40.9 +/- 6.2 x 10(-5) cm/s; P < 0.001; n = 9). Preincubation of IMCD with SNAP or the SOD mimetic tempol completely inhibited DETC-stimulated Purea. DETC caused a significant increase in superoxide generation by IMCD, and this was blocked by SNAP. Incubation of IMCD with the NO synthase (NOS) substrate l-arginine blocked the stimulatory effect of DETC on Purea, and this was reversed by the neuronal NOS inhibitor 7-nitroindazole. In contrast, neither basal nor AVP-stimulated Pf was affected by NO donors or DETC. In summary, exogenous or endogenously produced NO does not affect basal urea transport in the IMCD but inhibits superoxide-stimulated Purea. In the inner medulla, superoxide generation by local oxidases may stimulate urea transport, and the role of endogenous NO may be to dampen this effect by decreasing superoxide levels.
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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) | 0.001 | 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".