Furosemide Dynamics: Influence of Dietary Sodium and of Saralasin
Bibliographic record
Abstract
The influence of dietary sodium and saralasin on the natriuretic and diuretic response to furosemide (5 mg/kg i.v.) was studied in three groups of conscious rabbits maintained for 4 weeks on either a normal sodium diet (NSD), or a low sodium diet (LSD) or a high sodium diet (HSD). Neither the sodium content in the diet nor saralasin affected glomerular filtration rate or renal plasma flow. Compared to the NSD, an LSD did not affect the furosemide-induced increment in urinary excretion of sodium (dUNaV) but increased the increment in urinary excretion (dUV) (p less than 0.05). An HSD reduced the furosemide-induced dUNaV and dUV (p less than 0.05). Plasma renin activity (PRA) increased following furosemide administration in animals on an NSD and an LSD, but not in those on an HSD. Independent of diet, a positive correlation occurred between the increment in PRA and the dUNaV (p less than 0.001). Saralasin increased PRA and decreased baseline urinary excretion of sodium (UNaV). In addition, in rabbits on an LSD, saralasin reduced the furosemide-induced dUNaV and dUV by 34 and 27% (p less than 0.05), respectively. It is concluded that furosemide-induced diuresis is increased in rabbits on an LSD and decreased in rabbits on an HSD. In animals on an LSD, the increase in furosemide response appears to be associated with changes in the activity of the renin-angiotensin system and in rabbits on an HSD, the decrease in furosemide effect is probably the net result of several factors.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".