Antipsychotic drugs cause glial cell line–derived neurotrophic factor secretion from C6 glioma cells
Bibliographic record
Abstract
OBJECTIVE: Atypical antipsychotic drugs have been shown to protect PC12 cells from cell death induced by a variety of stimuli in culture. Recently, it has been postulated that trophic factors, such as brain-derived neurotrophic factor (BDNF), play a role in preventing cell death. It has been shown that antipsychotic drugs attenuate the decrease in rat hippocampal BDNF that results from immobilization-induced stress. We aimed to determine whether the neuroprotective effects of antipsychotic drugs could be mediated through glial cell line-derived neurotrophic factor (GDNF). METHODS: We investigated the effects of the atypical antipsychotic drugs quetiapine and clozapine and the typical antipsychotic haloperidol on the secretion of GDNF from rat C6 glioma cells. RESULTS: All 3 drugs increased the amount of GDNF secreted from C6 glioma cells into the medium after 48-hour culture. The intracellular content of GDNF was not altered by treatment with any of the antipsychotic drugs. None of the antipsychotic drugs decreased cell number. CONCLUSION: This study suggests that stimulation of GDNF release from glial cells by antipsychotic drugs might underlie some of their neuroprotective properties in situ.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".