Sex‐specific benefits of energy supplementation in a rat model of Alzheimer's disease
Bibliographic record
Abstract
BACKGROUND: Consumption of high-carbohydrate-high-fat diet leading to high body mass index either increases or decreases Alzheimer's disease (AD) risk with no clear consensus. We aim to differentiate the relationship between high energy diet and AD in a controlled rat model of AD during early symptomatic phase of the disease when the brain requires increased energy source as it attempts to compensate for neuronal loss. METHOD: We fed 9-month-old TgF344-AD rats resembling early symptomatic phase of human AD a varied high-carbohydrate-high-fat diet for 3- and 6-months. We examined cognitive function using the Barnes Maze. Histological examination of neuronal density, amyloid, hyperphosphorylated tau, myelin and glia were examined. RESULT: Three-month-diet increased brain glucose metabolism. slowed cognitive decline, increased myelin/oligodendrocyte density in TgF344-AD rats without affecting non-transgenic rats; however, it also decreased neuronal density, and promoted deposition of amyloid-beta plaques and tau inclusions. After 6 months on the high-carbohydrate-high-fat diet, detrimental effects on density of neurons, amyloid-beta plaques, and tau inclusions persisted while the beneficial effects on myelin, microglia, and cognitive functions remained albeit with a lower effect size. CONCLUSION: By examining the effect of sex, we found that effects of obesity were stronger in female than in male TgF344-AD rats indicating that consumption of high energy diet during early symptomatic phase of AD is protective in females.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".