Beneficial Effects of Dietary EGCG and Voluntary Exercise on Behavior in an Alzheimer's Disease Mouse Model
Bibliographic record
Abstract
Alzheimer's disease (AD) is a progressive, age-dependent neurodegenerative disorder affecting specific brain regions that control memory and cognitive functions. Epidemiological studies suggest that exercise and dietary antioxidants are beneficial in reducing AD risk. To date, botanical flavonoids are consistently associated with the prevention of age-related diseases. The present study investigated the effects of 4 months of wheel-running exercise, initiated at 2-months of age, in conjunction with the effects of the green tea catechin (-)-epigallocatechin-3-gallate (EGCG) administered orally in the drinking water (50 mg/kg daily) on: (1) behavioral measures: learning and memory performance in the Barnes maze, nest building, open-field, anxiety in the light-dark box; and (2) soluble amyloid-β (Aβ) levels in the cortex and hippocampus in TgCRND8 (Tg) mice. Untreated Tg mice showed hyperactivity, relatively poor nest building behaviors, and deficits in spatial learning in the Barnes maze. Both EGCG and voluntary exercise, separately and in combination, were able to attenuate nest building and Barnes maze performance deficits. Additionally, these interventions lowered soluble Aβ1-42 levels in the cortex and hippocampus. These results, together with epidemiological and clinical studies in humans, suggest that dietary polyphenols and exercise may have beneficial effects on brain health and slow the progression 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 | 0.001 |
| 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".