Therapeutic Effects of Quetiapine on Memory Deficit and Brain β-Amyloid Plaque Pathology in a Transgenic Mouse Model of Alzheimer’s Disease
Bibliographic record
Abstract
Our previous study has shown the preventive effects of quetiapine, an atypical antipsychotic drug, on memory impairment and brain pathological changes in a mouse model of Alzheimer's disease (AD). The aim of the present study was to evaluate the therapeutic effects of quetiapine on memory deficit and neuropathology in an amyloid precursor protein (APP)/presenilin-1 (PS1) double transgenic mouse model of AD. The APP/PS1 mice started to have detectable brain β-amyloid (Aβ) at 3 months of age. Non-transgenic and transgenic mice were treated with quetiapine (0, 2.5, or 5 mg/(kg day)) in drinking water from the age of 4 months. After 8 months of continuous quetiapine administration, memory deficit was reversed and brain Aβ plaque pathology was attenuated in the AD mice. Quetiapine also decreased the soluble Aβ peptide levels in brain and cerebrospinal fluid (CSF), and attenuated the decreased synaptic protein levels in the AD mice. Furthermore, quetiapine normalized the abnormal activity of glycogen synthase kinase-3β (GSK-3β), an AD-involved kinase, in the AD mice. These results suggest that quetiapine can treat and alleviate the neuropathology in an APP/PS1 transgenic mouse model of AD, and indicate that quetiapine may have therapeutic effects in the treatment of AD.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".