Protective efficacy of <i>Nerium oleander</i> extract on spermatogenesis in streptozotocin-induced diabetic rats
Bibliographic record
Abstract
Summary Men with diabetes frequently experience spermatogenic dysfunction, which is the most significant sign that diabetes has harmed their ability to reproduce. The effect of various doses of the hydro-alcoholic extract of Nerium oleander leaves on the pituitary–gonadal axis, sperm motility and number, antioxidant system, changes in testicular tissue structure, and spermatogenesis in healthy and diabetic rats has been examined in the current study. Eighty male rats that had been streptozotocin-induced diabetic and healthy were divided into eight groups: (1) control, (2) Nerium (50 mg/kg), (3) Nerium (100 mg/kg), (4) Nerium (200 mg/kg), (5) DM (6) DM+Nerium (50 mg/kg), (7) DM+Nerium (100 mg/kg) and (8) DM+Nerium (200 mg/kg) and were administered orally for 48 days consecutive. Following the studies, analysis of the testicular tissues’ antioxidant capacity as well as sperm parameters, Johnsen’s scoring and morphometric evaluation, histology, biochemical and stereology studies were performed. The outcomes showed that Nerium 50 and 100 mg/kg considerably enhanced the testicular morphology, sperm parameters, and reproductive organs to varying degrees in diabetic rats. After Nerium 50 mg/kg administration, glutathione peroxidase (GPX) and catalase (CAT) levels in the testicular tissue were increased whereas malondialdehyde (MDA) levels were markedly decreased. Nerium may help protect against diabetic-induced spermatogenic dysfunction in male rats by enhancing the activities of antioxidant enzymes in lower dosages.
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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 | 0.001 | 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".