The Protective Effect of Methanol Extract of Rauvolfia vomitoria against the Clastogenicity and Hepatotoxicity of Sodium Arsenite in Mice
Bibliographic record
Abstract
Exposure to arsenic is a public health concern and many strategies are being employed to counter arsenic intoxication. Here, we investigated the effect of methanol leaf extracts of Rauvolfia vomitoria (MRV) on mice exposed to sodium arsenite (SA) using micronucleus assay and monitoring the activities of γ-glutamyltransferase (γ-GT), alkaline phosphate (ALP), aspartate aminotransferase (AST) and alanine-aminotransferase (ALT) in the plasma. In addition, pathological examination of the liver of test and control mice was carried out. Test mice were exposed to 1300, 650 and 325 mg/kg body weight of MRV for seven consecutive days before injection (i.p.) with 1 mg/kg body weight of SA on the seventh day. Negative control mice were given distilled water, while the positive control animals were injected with 1 mg/kg body weight of SA twenty hours before the experiment was terminated on the eighth day. The SA significantly (p < 0.05) increased the frequency of micronucleated polychromatic erythrocyte (mPCE) and the activities of γ-GT, ALP, AST and ALT when compared to the negative control. Mice treated with SA showed portal inflammation and hepatocyte necrosis. Pretreatment with MRV significantly (p< 0.05) reduced the biochemical parameters except ALT that was increased in animals treated with SA and 1300 mg/kg body weight MRV. Histopathological changes induced by SA were prevented by 650 and 325 mg/kg body weight MRV. This suggests that methanol extract of Rauvolfia vomitoria offers some degree of chemo-protection against SA induced clastogenicity and liver damage at lower doses
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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 | 0.001 | 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".