Antioxidant and anti-inflammatory properties of alpha-lipoic acid protect against valproic acid–induced liver injury
Bibliographic record
Abstract
Valproic acid (VPA) is one of the most used antiepileptic drugs despite of its many adverse effects such as anemia, leucopenia, thrombocytopenia, and liver toxicity. The hepatoprotective effect of alpha-lipoic acid (ALA) was confirmed. The aim of this study was to detect the protective effect of ALA against the adverse effects of VPA. To study this, 30 white albino Wistar male rats were divided into four groups. Group I was the control group; Group II included rats that received ALA (100 mg·kg−1·day−1) orally for 14 days; Group III and Group IV included rats that received VPA (500 mg·kg−1·day−1) for 15 days intraperitoneally, but Group IV rats received ALA (100 mg·kg−1·day−1) orally for 14 days prior to VPA. Blood samples were collected and livers were excised from rats for colorimetric analysis and quantitative real-time PCR. The rats that received VPA showed leucopenia, thrombocytopenia, a significant decrease of superoxide dismutase, glutathione, nuclear factor erythroid 2-related factor 2, and sirtuin 1, besides a significant increase of malondialdehyde and tumor necrosis factor α. Prior treatment with ALA prevented all these results; ALA protected against VPA-induced liver damage and hematological disturbance via antioxidant and anti-inflammatory properties.
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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) | 0.000 | 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) | 0.001 | 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".