Synergistic Effects of Long-Term Antioxidant Diet and Behavioral Enrichment on -Amyloid Load and Non-Amyloidogenic Processing in Aged Canines
Bibliographic record
Abstract
A long-term intervention (2.69 years) with an antioxidant diet, behavioral enrichment, or the combined treatment preserved and improved cognitive function in aged canines. Although each intervention alone provided cognitive benefits, the combination treatment was additive. We evaluate the hypothesis that antioxidants, enrichment, or the combination intervention reduces age-related beta-amyloid (Abeta) neuropathology, as one mechanism mediating observed functional improvements. Measures assessed were Abeta neuropathology in plaques, biochemically extractable Abeta(40) and Abeta(42) species, soluble oligomeric forms of Abeta, and various proteins in the beta-amyloid precursor protein (APP) processing pathway. The strongest and most consistent effects on Abeta pathology were observed in animals receiving the combined antioxidant and enrichment treatment. Specifically, Abeta plaque load was significantly decreased in several brain regions, soluble Abeta(42) was decreased selectively in the frontal cortex, and a trend for lower Abeta oligomer levels was found in the parietal cortex. Reductions in Abeta may be related to shifted APP processing toward the non-amyloidogenic pathway, because alpha-secretase enzymatic activity was increased in the absence of changes in beta-secretase activity. Although enrichment alone had no significant effects on Abeta, reduced Abeta load and plaque maturation occurred in animals receiving antioxidants as a component of treatment. Abeta measures did not correlate with cognitive performance on any of the six tasks assessed, suggesting that modulation of Abeta alone may be a relatively minor mechanism mediating cognitive benefits of the interventions. Overall, the data indicate that multidomain treatments may be a valuable intervention strategy to reduce neuropathology and improve cognitive function in humans.
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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 | 0.000 | 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".