Expression of brain‐derived neurotrophic factor mRNA in rat hippocampus after treatment with antipsychotic drugs
Bibliographic record
Abstract
Typical and atypical antipsychotic drugs, though both effective, act on different neurotransmitter receptors and are dissimilar in some clinical effects and side effects. The typical antipsychotic drug haloperidol has been shown to cause a decrease in the expression of brain-derived neurotrophic factor (BDNF), which plays an important role in neuronal cell survival, differentiation, and neuronal connectivity. However, it is still unknown whether atypical antipsychotic drugs similarly regulate BDNF expression. We examined the effects of chronic (28 days) administration of typical and atypical antipsychotic drugs on BDNF mRNA expression in the rat hippocampus using in situ hybridization. Quantitative analysis revealed that the typical antipsychotic drug haloperidol (1 mg/kg) down-regulated BDNF mRNA expression in both CA1 (P < 0.05) and dentate gyrus (P < 0.01) regions compared with vehicle control. In contrast, the atypical antipsychotic agents clozapine (10 mg/kg) and olanzapine (2.7 mg/kg) up-regulated BDNF mRNA expression in CA1, CA3, and dentate gyrus regions of the rat hippocampus compared with their respective controls (P < 0.01). These findings demonstrate that the typical and atypical antipsychotic drugs differentially regulate BDNF mRNA expression in rat hippocampus.
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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".