Olanzapine alleviates oxidative stress in the liver of socially isolated rats
Bibliographic record
Abstract
Olanzapine, an antipsychotic drug, is used to treat depressive disorder, but its effects on the liver, the main site of drug metabolism, still remain elusive. We studied the effects of 3 weeks of olanzapine treatment (7.5 mg/kg per day) on the malondialdehyde (MDA) and protein carbonyl (PCO) contents, protein expression of copper/zinc superoxide dismutase (CuZnSOD), and activity of total superoxide dismutase (SOD), as well as catalase (CAT) protein expression and activity levels in the liver cytosol of rats exposed to 6 weeks of chronic social isolation (CSIS), which causes depressive- and anxiety-like behaviors. Increased cytosolic MDA in CSIS rats (vehicle- or olanzapine-treated) indicated hepatic oxidative stress. Increase in PCO and CAT activity associated with unchanged total SOD activity following CSIS also confirm the presence of oxidative stress. Chronic olanzapine treatment in CSIS prevented increase in PCO without an effect on MDA content. Increased SOD activity in olanzapine-treated (controls and CSIS) groups compared with corresponding vehicle-treated groups and decreased CAT activity in olanzapine-treated CSIS rats compared with vehicle-treated CSIS group was found. The data suggest that chronic olanzapine treatment has a protective effect on hepatic protein oxidation and improves antioxidant defense. The beneficial effects of olanzapine may be due to its free radical scavenging properties and antioxidant activity.
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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 | 0.000 | 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".