Diet enriched in omega‐3 fatty acids alleviates olfactory system deficits in APOE4 transgenic mice
Bibliographic record
Abstract
Olfactory dysfunction is observed in several neurological disorders including Mild Cognitive Impairment (MCI) and Alzheimer disease (AD). These deficits occur early and correlate with global cognitive performance, depression and degeneration of olfactory regions in the brain. Despite extensive human studies, there has been little characterization of the olfactory system in models of AD. In order to determine if olfactory structural and/or molecular phenotypes are observed in a model expressing a genetic risk factor for AD, we assessed the olfactory bulb (OB) in APOE4 transgenic mice. A significant decrease in OB weight was observed at 12 months of age in APOE4 mice concurrent with inflammation and decreased NeuN expression. In order to determine if a diet rich in omega-3s may alleviate the olfactory system phenotypes observed, we assessed WT and APOE4 mice on a docosahexaenoic acid (DHA) diet. APOE4 mice on a DHA diet did not present with atrophy of the OB, and the alterations in NeuN and IBA-1 expression were alleviated. Furthermore, alterations in caspase mRNA and protein expression in the APOE4 OB were not observed with a DHA diet. Similar to the human AD condition, OB atrophy is an early phenotype in the APOE4 mice and concurrent with inflammation. These data support a link between the structural olfactory brain region atrophy and the olfactory dysfunction observed in AD and suggest that inflammation and cell death pathways may contribute to the olfactory deficits observed. Furthermore, the results suggest that diets enriched in DHA may provide benefit to APOE4 allele carriers.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".