Bosentan and losartan ameliorate acute renal failure associated with mild but not strong NO blockade
Bibliographic record
Abstract
BACKGROUND: Acute renal failure (ARF) is a devastating illness, especially when it occurs in various conditions with impaired nitric oxide (NO) synthesis, such as arterial hypertension, heart failure and some renal diseases. We have directed our investigations to effects of both angiotensin II (AII) and endothelin (ET) receptor blockade associated with mild or strong NO deficiency on haemodynamic, biochemical and morphological parameters in experimental post-ischaemic ARF. METHODS: In this study, we used bosentan (dual, ETA/ETB-receptor antagonist), losartan (non-peptide, competitive antagonist of type I AII receptor), and NG-nitro-L-arginine methyl ester (L-NAME), inhibitor of NO synthesis. Experiments were performed in anaesthetized, adult male Wistar rats. The right kidney was removed and the renal ischaemia was performed by clamping the left renal artery for 45 min. Experimental groups received receptor antagonists (bosentan or losartan) or vehicle (saline) in the femoral vein 20 min before, during and 20 min after the period of ischaemia. L-NAME was given as i.v. bolus before each antagonist infusion. All parameters were measured 24 h after reperfusion. RESULTS: Our results showed that strong NO blockade overcame effects of both ET and AII receptor blockade in experimental post-ischaemic ARF. In addition, the AII receptor blockade had a harmful effect on this condition, probably due to disturbed autoregulatory renal function. On the other hand, ET and AII receptor blockade in mild NO blockade associated with reperfusion injury, improves the most haemodynamic, biochemical and morphological parameters. CONCLUSIONS: We concluded that experimental post-ischaemic ARF is neither AII nor ET mediated in case of strong NO blockade, but, in more realistic conditions of mild NO deficiency, these peptides represent significant players whose receptor blockade expressed relevant therapeutic potential.
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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) | 0.002 | 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".