The Protective Effects of<i>Areca catechu</i>Extract on Cognition and Social Interaction Deficits in a Cuprizone-Induced Demyelination Model
Bibliographic record
Abstract
Schizophrenia is a serious psychiatric illness with an unclear cause. One theory is that demyelination of white matter is one of the main pathological factors involved in the development of schizophrenia. The current study evaluated the protective effects of Areca catechu nut extract (ANE) on a cuprizone-induced demyelination mouse model. Two doses of ANE (1% and 2%) were administered orally in the diet for 8 weeks. Animals subjected to demyelination showed impaired spatial memory and less social activity. In addition, mice subjected to demyelination displayed significant myelin damage in cortex and demonstrated a higher expression of NG2 and PDGFRα and AMPK activation. ANE treatment not only significantly enhanced cognitive ability and social activity, but also protected myelin against cuprizone toxicity by promoting oligodendrocyte precursor cell (OPC) differentiation. In addition, ANE treatment demonstrated significant dephosphorylation of AMPKα, indicating a regulatory role for ANE in schizophrenia. This study showed that ANE treatment may enhance cognitive ability and social activity by facilitating OPC differentiation and protecting against myelin damage in cortex. Results also suggest the AMPK signaling pathway may be involved in this process.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".