Quetiapine Modulates Conditioned Anxiety and Alternation Behavior in Alzheimer’s Transgenic Mice
Bibliographic record
Abstract
Quetiapine, an atypical antipsychotic drug, is effective in treating the behavioral and psychological symptoms in Alzheimer's disease (AD). However, it is presently unclear whether quetiapine has beneficial effects on memory and whether the effects of quetiapine on psychological symptoms are associated with its effect on memory in AD. The present study was designed to examine the effect of chronic administration of quetiapine on the conditioned (generalized) anxiety that is related to learning experience of open arm exposure in the elevated T-maze (ETM) test in an amyloid precursor protein (APP)/presenilin 1 (PS1) double transgenic mouse model of AD. In a 2nd experiment, the effect of quetiapine on memory per se was investigated in a Y-maze test in AD mice. Non-transgenic and transgenic mice were treated with quetiapine in drinking water from the age of 2 months. After continuous treatment with quetiapine (5 mg/kg/day) for 10 months, mice were tested for conditioned anxiety on the ETM task. After ETM testing, the expression of brain-derived neurotrophic factor (BDNF), a neuroprotective protein, was examined by immunohistochemistry in the basolateral amygdala (BLA) and hippocampus. In the 2nd experiment, the effect of quetiapine (2.5 or 5 mg/kg/day) on the short-term memory in AD mice was tested in a Y-maze test. After 10 months of administration, quetiapine prevented the decrease of conditioned anxiety and cerebral BDNF in AD mice. In addition, quetiapine also prevented memory impairment in the Y-maze test in AD mice. These findings suggest that the therapeutic mechanism of quetiapine on anxiety in AD may be associated with its beneficial effect on memory and its neuroprotective effect on cerebral BDNF expression.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".