Neuropeptide Y enhances potassium excretion by mechanisms distinct from those controlling sodium excretion
Bibliographic record
Abstract
Neuropeptide Y (NPY) is an established modulator of renal function. Although NPY reduces renal blood flow and does not alter glomerular filtration rate, it enhances diuresis and natriuresis. Although initial studies on natriuresis did not detect kaliuresis, we now report that a retrospective analysis of previous studies regarding natriuresis demonstrates NPY-induced kaliuresis under several experimental conditions. Kaliuresis was observed despite a marked reduction in urinary potassium concentrations, which may explain why it has not been noted in some initial studies. In a direct comparison of NPY-induced kaliuresis and natriuresis, both effects were slow in onset (requiring >45 min to develop fully) and blocked by the cyclooxygenase inhibitor indomethacin. While natriuresis occurred solely via a Y5 receptor, kaliuresis involved a Y1 receptor and an additional receptor subtype, possibly Y2. The L-type Ca2+ entry blocker nifedipine abolished natriuresis but did not inhibit kaliuresis. A combination of experiments with the bradykinin B2 receptor antagonist icatibant, the angiotensin II receptor antagonist losartan, and the converting enzyme inhibitor ramiprilat revealed that NPY-induced natriuresis involves bradykinin while kaliuresis involves angiotensin II. We conclude that NPY-induced kaliuresis is much less pronounced than natriuresis and is mediated by distinct mechanisms.
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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".