A Diet Enriched with the Omega-3 Fatty Acid Docosahexaenoic Acid Reduces Amyloid Burden in an Aged Alzheimer Mouse Model
Bibliographic record
Abstract
Epidemiological studies suggest that increased intake of the omega-3 (n-3) polyunsaturated fatty acid (PUFA) docosahexaenoic acid (DHA) is associated with reduced risk of Alzheimer's disease (AD). DHA levels are lower in serum and brains of AD patients, which could result from low dietary intake and/or PUFA oxidation. Because effects of DHA on Alzheimer pathogenesis, particularly on amyloidosis, are unknown, we used the APPsw (Tg2576) transgenic mouse model to evaluate the impact of dietary DHA on amyloid precursor protein (APP) processing and amyloid burden. Aged animals (17-19 months old) were placed in one of three groups until 22.5 months of age: control (0.09% DHA), low-DHA (0%), or high-DHA (0.6%) chow. beta-Amyloid (Abeta) ELISA of the detergent-insoluble extract of cortical homogenates showed that DHA-enriched diets significantly reduced total Abeta by >70% when compared with low-DHA or control chow diets. Dietary DHA also decreased Abeta42 levels below those seen with control chow. Image analysis of brain sections with an antibody against Abeta (amino acids 1-13) revealed that overall plaque burden was significantly reduced by 40.3%, with the largest reductions (40-50%) in the hippocampus and parietal cortex. DHA modulated APP processing by decreasing both alpha- and beta-APP C-terminal fragment products and full-length APP. BACE1 (beta-secretase activity of the beta-site APP-cleaving enzyme), ApoE (apolipoprotein E), and transthyretin gene expression were unchanged with the high-DHA diet. Together, these results suggest that dietary DHA could be protective against beta-amyloid production, accumulation, and potential downstream toxicity.
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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 | 0.001 | 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) | 0.002 | 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".