Effects of long-term losartan and<scp>l</scp>-arginine treatment on haemodynamics, glomerular filtration, and SOD activity in spontaneously hypertensive ratsThis article is one of a selection of papers published in the special issue Bridging the Gap: Where Progress in Cardiovascular and Neurophysiologic Research Meet.
Bibliographic record
Abstract
Recently, it has been reported that losartan, an angiotensin II receptor (ATR) antagonist, depresses the angiotensin II-induced production of superoxide radicals. Also, in spontaneously hypertensive rats (SHR) endothelial dysfunction is associated with decreased nitric oxide (NO) synthesis. In this study, we examined the effects of long-term ATR blockade and L-arginine supplementation on the haemodynamic parameters, glomerular filtration, and oxidative status in SHR. Adult male SHR were treated with losartan (10 mg/kg) and with the NO donor L-arginine (2 g/kg) for 4 weeks. The animals were divided into the following experimental groups: control (n = 7), L-arginine (n = 7), losartan (n = 7), and L-arginine + losartan (n = 7). Mean arterial pressure (MAP), regional blood flow, urea clearance, and activity of superoxide dismutase (SOD) were measured at the end of treatment. MAP was significantly reduced in the losartan group compared with the control group (133.3 +/- 7.3 vs. 161.5 +/- 14.5 mm Hg). Aortic blood flow was significantly higher and aortic vascular resistance was significantly lower in all treated groups than in the control. Urea clearance rose significantly in the L-arginine + losartan group compared with control (393.27 +/- 37.58 vs. 218.68 +/- 42.03 microL x min(-1) x 100 g(-1)) as did the activity of SOD (1668.97 +/- 244.57 vs. 1083.18 +/- 169.96 U/g Hb). Our results suggest that the antihypertensive effect of losartan and L-arginine in SHR is not primarily mediated by increased SOD activity. Also, combined treatment with ATR blockade and L-arginine supplementation has a beneficial effect on renal function that is, at least in part, mediated by increased SOD activity in SHR.
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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 | 0.001 |
| 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 | 0.001 | 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".