Protective effect of ω-3 polyunsaturated fatty acids (PUFAs) on sodium nitroprusside–induced nephrotoxicity and oxidative damage in rat kidney
Bibliographic record
Abstract
Sodium nitroprusside (SNP) a nitric oxide (NO) donor has proven toxic effects. Dietary ω-3 polyunsaturated fatty acid (PUFA) has been shown to reduce the severity of numerous ailments. Present study examined whether intake of fish oil (FO)/flaxseed oil (FXO, Omega Nutrition, St Vancouver, Canada) would have protective effect against SNP-induced toxicity. Male Wistar rats (150 ± 10 g) were used in this study. Initially animals were divided into two groups: one fed on normal diet and the other on 15% FO/FXO for 15 days. On the 16th day, SNP (1.5 mg/kg body weight) was administered intraperitoneally for 7 days daily. After 7 days animals were killed, kidneys were harvested for further analysis. SNP induced nephrotoxicity by increasing serum creatinine and blood urea nitrogen, SNP significantly decreased malate dehydrogenase, glucose-6-phosphatase, fructose-1,6-bisphosphatase and malic enzyme but increased lactate dehydrogenase and glucose-6-phosphate dehydrogenase. Brush border membrane enzymes such as alkaline phosphatase, γ-glutamyl transpeptidase and leucine amino peptidase were also decreased. The activity of catalase and glutathione peroxidase decreased concomitantly with increased lipid peroxidation, indicating that the significant kidney damage has been inflicted by SNP. Feeding of FO and FXO with SNP ameliorated the changes in various parameters caused by SNP. The results of the present study suggest that ω-3 PUFA-enriched FO and FXO from seafoods and plant sources, respectively, are similarly effective in reducing SNP-induced nephrotoxicity and oxidative damage. Thus, vegetarians who cannot consume FO can have similar health benefits from plant-derived ω-3 PUFA.
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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 | 0.001 |
| 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".