Effects of Antipsychotic Drugs on the Epigenetic Modification of Brain-Derived Neurotrophic Factor Gene Expression in the Hippocampi of Chronic Restraint Stress Rats
Bibliographic record
Abstract
Recent studies have shown that antipsychotic drugs have epigenetic effects. However, the effects of antipsychotic drugs on histone modification remain unclear. Therefore, we investigated the effects of antipsychotic drugs on the epigenetic modification of the BDNF gene in the rat hippocampus. Rats were subjected to chronic restraint stress (6 h/d for 21 d) and then were administered with either olanzapine (2 mg/kg) or haloperidol (1 mg/kg). The levels of histone H3 acetylation and MeCP2 binding at BDNF promoter IV were assessed with chromatin immunoprecipitation assays. The mRNA levels of total BDNF with exon IV, HDAC5, DNMT1, and DNMT3a were assessed with a quantitative RT-PCR procedure. Chronic restraint stress resulted in the downregulation of total and exon IV BDNF mRNA levels and a decrease in histone H3 acetylation and an increase in MeCP2 binding at BDNF promoter IV. Furthermore, there were robust increases in the expression of HDAC5 and DNMTs. Olanzapine administration largely prevented these changes. The administration of haloperidol had no effect. These findings suggest that the antipsychotic drug olanzapine induced histone modification of BDNF gene expression in the hippocampus and that these epigenetic alterations may represent one of the mechanisms underlying the actions of antipsychotic drugs.
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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".