Astrocyte‐dependent protective effect of quetiapine on <scp>GABA</scp>ergic neuron is associated with the prevention of anxiety‐like behaviors in aging mice after long‐term treatment
Bibliographic record
Abstract
Previous studies have demonstrated that quetiapine (QTP) may have neuroprotective properties; however, the underlying mechanisms have not been fully elucidated. In this study, we identified a novel mechanism by which QTP increased the synthesis of ATP in astrocytes and protected GABAergic neurons from aging-induced death. In 12-month-old mice, QTP significantly improved cell number of GABAegic neurons in the cortex and ameliorated anxiety-like behaviors compared to control group. Complimentary in vitro studies showed that QTP had no direct effect on the survival of aging GABAergic neurons in culture. Astrocyte-conditioned medium (ACM) pretreated with QTP (ACMQTP) for 24 h effectively protected GABAergic neurons against aging-induced spontaneous cell death. It was also found that QTP boosted the synthesis of ATP from cultured astrocytes after 24 h of treatment, which might be responsible for the protective effects on neurons. Consistent with the above findings, a Rhodamine 123 test showed that ACMQTP, not QTP itself, was able to prevent the decrease in mitochondrial membrane potential in the aging neurons. For the first time, our study has provided evidence that astrocytes may be the conduit through which QTP is able to exert its neuroprotective effects on GABAergic neurons. The neuroprotective properties of quetiapine (QTP) have not been fully understood. Here, we identify a novel mechanism by which QTP increases the synthesis of ATP in astrocytes and protects GABAergic neurons from aging-induced death in a primary cell culture model. In 12-month-old mice, QTP significantly improves cell number of GABAegic neurons and ameliorates anxiety-like behaviors. Our study indicates that astrocytes may be the conduit through which QTP exerts its neuroprotective effects on GABAergic neurons.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".