Protective potential of<i>Tamarindus indica</i>against gentamicin-induced nephrotoxicity
Bibliographic record
Abstract
Abstract Context: Gentamicin is an antibiotic that is effective against Gram-negative microorganisms. However, its clinical applications are often limited due to nephrotoxic effects. Objective: This study investigated the protective effects of aqueous-ethanol extract of Tamarindus indica L. (Leguminosae) fruits against gentamicin-induced renal toxicity. Materials and methods: A daily dose of 200 mg/kg of 70% aqueous-ethanol extract derived from T. indica was employed in male rabbits as a co-therapy with gentamicin (80 mg/kg) for a period of three weeks. Serum and urinary renal function parameters and histological assessments were carried out and compared with one way analysis of variance (Graphpad prism version 5.00, Graphpad Software, San Diego, CA). Results: The results showed that gentamicin-treated animals had significantly elevated blood urea nitrogen (54.1 ± 2.6 mg/dl), serum creatinine (4.0 ± 0.1 mg/dl), serum uric acid (2.3 ± 0.1 mg/dl) and urinary protein excretion (3.8 ± 0.3 mg/dl) with a fall in body weight (10 ± 1%), creatinine clearance (0.7 ± 0.09 ml/min), serum potassium (3.4 ± 0.1 mEq/l), serum calcium (7.6 ± 0.2 mg/dl), urinary volume (126 ± 9 ml/24 h) and urinary lactate dehydrogenase secretion (103.1 ± 4.2 U/l). However, animals treated by co-therapy with gentamicin and T. indica had significantly improved renal structure and function. Discussion and conclusion: Co-therapy of 200 mg/kg/d of T. indica for a period of three weeks successfully prevented functional and morphological derangements caused by gentamicin as assessed by different renal function parameters and histological examinations.
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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) | 0.000 | 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 | 0.000 |
| 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".