Comparative Hepatoprotective Effect of Vitamins A and E Against Gasoline Vapor Toxicity in Male and Female Rats
Bibliographic record
Abstract
BACKGROUND: of PMS blend unleaded gasoline vapors (UGV) for 6 hr/day, 5 days/week for 20 weeks have been reported to cause hepatotoxicity in rats. METHODS: In this study, the comparative hepatoprotective effect of vitamins A (retinol) and E (α-tocopherol) against UGV-induced toxicity was assessed in male and female rats. Retinol and α-tocopherol at prophylactic dosage (400 and 200 IU/kg/day, respectively) were separately administered orally to the test rats concomitant with exposure to UGV in the last two weeks of the experiment. RESULTS: The results of this study indicated that exposure to UGV caused significant increase (P < 0.05) in the activities of serum ALT, AST, ALP, GGT and bilirubin in male and female rats. Oral administration of prophylactic doses of retinol and α-tocopherol produced a significant decrease (P < 0.05) in the activities of these parameters in male and female test rats, compared with the non-treated test rats; but insignificant increase(P ≥ 0.05), compared with the control. However, the hepatoprotective effect of α-tocopherol was observed to be more potent than that of retinol. CONCLUSIONS: The result of this study demonstrated that the hepatoprotective potency of α-tocopherol against gasoline vapors toxicity was higher than that of retinol in male and female rats, although the female gender of the animal model responded to treatment with both vitamins better than the males. Hence, the work suggested the beneficial effects of both vitamins against hepatotoxicity in individuals frequently exposed to gasoline vapors.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".