Arecoline attenuates memory impairment and demyelination in a cuprizone-induced mouse model of schizophrenia
Bibliographic record
Abstract
Cerebral demyelination is possibly one of the main pathological factors involved in the development of schizophrenia. Our previous studies have showed that Areca catechu nut extract could ameliorate cognitive decline by facilitating myelination processes in the frontal cortex in a cuprizone (CPZ)-induced mouse model of schizophrenia. The aim of the present study was to evaluate the effects of arecoline, one of the alkaloids in A. catechu nut extract, on memory impairment and cerebral demyelination in CPZ-treated mice. Mice were treated with CPZ (0 or 0.2%) in chow food and arecoline hydrobromide (0, 2.5, or 5 mg/kg/day) in drinking water for 12 weeks before Y-maze behavioral test. After the behavioral test, the mice were sacrificed for the measurement of myelin basic protein in the frontal cortex. We showed that arecoline-attenuated spatial working memory impairment, concurrent with attenuated demyelination related to vehicle-treated CPZ mice for the first time. Arecoline is one of the primary active ingredients in A. catechu nut responsible for attenuating memory impairment and demyelination in CPZ mice, cerebral demyelination may have a role in memory impairment, and modulation of cerebral demyelination could be a useful strategy in schizophrenia treatment.
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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 | 0.002 | 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".