Montelukast protects against testes ischemia/reperfusion injury in rats
Bibliographic record
Abstract
INTRODUCTION: In this study, we investigate the effect of montelukast on histologic damage induced by testicular torsion-detorsion in rats. METHODS: Twenty-one male Sprague-Dawley rats were separated into 3 groups, each containing 7 rats. A sham operation was performed in group 1 (control). In group 2 (ischemia-reperfusion [IR]/untreated), 1-hour detorsion of the testis was performed after 6 hours of unilateral testicular torsion. In group 3 (I-R/dextroamphetamine), after performing the same surgical procedures as in group 2, montelukast was given intraperitoneally. In all experimental rats, ipsilateral orchiectomies were performed for histological examination and tissue malondialdehyde (MDA), glutathione and myeloperoxidase assays. RESULTS: Montelukast treatment significantly decreased the I-R-induced elevation in testes tissue MDA and glutathione levels were found to be preserved. The level of myeloperoxidase (MPO) activity was significantly increased in the testes tissue of the IR/untreated group. However, in I-R/montelukast treatment group significantly decreased testes tissue MPO level. Histopathologically, the in the group 2 rats, edema, congestion, hemorrhage between seminiferous tubules and necrosis of the germinal cells were predominant features in sections. However, most of the specimens in the montelukast treated group 3 showed grades-I and II injury. Additionally, the testicular injury score was lower in group 3 rats compared with group 2. CONCLUSION: The current findings demonstrate that the montelukast decreased the severity of testicular injury by reversing the oxidative effects of testes I-R.
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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 | 0.001 |
| 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".