Olanzapine and quetiapine protect PC12 cells from β-amyloid peptide25-35-induced oxidative stress and the ensuing apoptosis
Bibliographic record
Abstract
We previously found that the atypical antipsychotic drugs (APDs) clozapine, olanzapine, quetiapine, and risperidone reduce PC12 cell death induced by hydrogen peroxide, N-methyl-4-phenylpyridinium ion, or beta-amyloid peptide (Abeta(25-35)). Such neurotoxic substances have in common the capability of causing oxidative stress. Atypical APDs have been used in treating schizophrenia and in treating psychotic symptoms of patients with Alzheimer's disease (AD), in which Abeta is involved by causing oxidative stress. Therefore, we hypothesized that atypical APDs might alleviate oxidative stress in PC12 cells, thus protecting them from apoptosis. PC12 cells were seeded in plates or chambers for 24 hr and cultured for another 24 hr with olanzapine or quetiapine in the medium, and then the cells were cultured in the new medium containing Abeta(25-35) and/or olanzapine, quetiapine, but not serum, for various periods. It was shown that cultures treated with olanzapine + Abeta(25-35), or quetiapine + Abeta(25-35), had significantly higher cell viabilities and lower rates of apoptosis compared with the cultures exposed only to Abeta(25-35). In addition, the drugs blocked the activation of caspase-3 caused by Abeta(25-35). Furthermore, olanzapine and quetiapine prevented Abeta(25-35)-induced overproduction of intracellular reactive oxygen species, Abeta(25-35)-induced decrease in mitochondrial membrane potential, and Abeta(25-35)-induced changes in activities of the key antioxidant enzymes superoxide dismutase, catalase, and glutathione peroxidase. In consideration of the wealth of evidence linking oxidative stress to the pathophysiology of schizophrenia and AD, these findings give us a new insight into the therapeutic actions of atypical antipsychotics in patients with the disorders.
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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 | 0.000 | 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".