The importance of the renal sympathetic nerves in the natriuretic response to imidazoline receptor agonists
Bibliographic record
Abstract
In our preliminary dose--response study two I1 -imidazoline receptor agonists (rilmenidine and moxonidine) and two _ 2-adrenoceptor agonists (clonidine and guanfacine) were investigated. Based on those studies, we selected rilmenidine (10 nmol/kg/min) and guanfacine (10 nmol/kg/min) for our further studies. The renal sympathetic nerves have been proposed to be important in the renal actions of imidazoline receptor and _2-adrenoceptor agonists. We therefore determined the effects of acute renal denervation on the diuretic and natriuretic actions of rilmenidine, guanfacine and furosemide. The dose of furosemide (0.1 mg/kg) was selected based on the previous experiments in our laboratory. Male Sprague-Dawley rats underwent unilateral nephrectomy 7 to 10 days prior to the experimental day. Animals were anesthetized with pentobarbital. A tracheotomy was performed and the animal allowed breathing spontaneously. The carotid artery was cannulated for blood pressure and heart rate monitoring and the left jugular vein was cannulated for infusion of study drugs. The left kidney was exposed by a flank incision and the ureter was cannulated for the collection of urine. The kidney was denervated surgically and by painting the renal artery with phenol (10%) in 95% ethyl alcohol. (Abstract shortened by UMI.)
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".