[P3–317]: DHA BRAIN UPTAKE AND <i>APOE4</i> STATUS: A PET STUDY WITH [1‐<sup>11</sup>C]‐DHA
Bibliographic record
Abstract
The APOE ɛ4 (APOE4) allele is the strongest genetic risk factor identified for developing Alzheimer's disease (AD). Among brain lipids, alteration in the omega-3 (ω-3) polyunsaturated fatty acid docosahexaenoic acid (DHA) homeostasis is implicated in AD pathogenesis. APOE4 may influence both brain DHA metabolism and cognitive outcomes. Using positron emission tomography (PET), regional coefficients (K*), rates (Jin) of DHA incorporation from plasma into the brain using [1-C]DHA, and regional cerebral blood flow (rCBF) using [O]water were measured in 22 younger healthy adults (mean age 35). Data were partial volume error corrected for brain atrophy. APOE4 phenotype was determined by protein expression and unesterified DHA concentrations were quantified in plasma. An exploratory post-hoc analysis of the effect of APOE4on DHA brain kinetics was performed. In this group, (APOE4 non-carriers, n=13, carriers, n=9), the mean global gray matter DHA incorporation coefficient, K*, was significantly higher (16%) among APOE4 carriers (n=13) compared to non-carriers (n=9, p=0.046). A significantly higher global DHA incorporation coefficient was observed in several brain regions, particularly in the entorhinal subregion, an area affected early in AD pathogenesis. Cerebral blood flow, unesterified plasma DHA, and whole brain DHA incorporation rate (Jin) did not differ significantly comparing the APOEgroups. Significantly greater values of K* for DHA in APOE4 carriers suggests an alteration in brain DHA homeostasis. These findings may contribute to understanding how APOE4 genotypes affect AD risk.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".