Protective Effect of Resveratrol against Hexavalent Chromium-Induced Genotoxic Damage in Hsd:ICR Male Mice
Bibliographic record
Abstract
The aim of this study is to examine the ability of resveratrol to counteract hexavalent chromium [Cr(VI)]-induced genetic damage, as well as the possible pathways associated with this protection. Hsd:ICR male mice are divided into groups of the following five individuals each: (a) control 1, distilled water; (b) control 2, ethanol 30%; (c) resveratrol, 50 mg/kg by gavage; (d) CrO3, 20 mg/kg intraperitoneally; (e) resveratrol + CrO3, resveratrol administered 4 h prior to CrO3. The assessment is performed on peripheral blood. Micronuclei (MN) kinetics are measured from 0 to 72 h, while 8-hydroxydeoxyguanosine (8-OHdG) adduct repair levels, endogenous antioxidant system biomarkers, and apoptosis frequency were quantified after 48 h. Resveratrol reduces the frequency of Cr(VI)-induced MN and shows significant effects on the 8-OHdG adduct levels, suggesting that cell repair could be enhanced by this polyphenol. Concomitant administration of resveratrol and Cr(VI) results in a return of the activities of glutathione peroxidase and catalase to control levels, accompanied by modifications of superoxide dismutase activity and glutathione levels. Thus, antioxidant properties might play an important role in resveratrol-mediated inhibition of Cr(VI)-induced oxidant genotoxicity. The increase in apoptotic cells and the decrease in necrosis further confirmed that resveratrol effectively blocks the actions of Cr(VI).
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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 | 0.001 |
| 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 | 0.001 |
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".