APOE E2 Carriers Showed Worse Associative Learning Than E3 Carriers in a Cognitively Normal Aging Han Chinese Population
Bibliographic record
Abstract
Abstract Background: Polymorphism in the APOE gene has been shown to be associated with cognitive function, however, the related studies are not consistent. To investigate the relationship between APOE gene polymorphism and cognitive function, we conducted the current cross-sectional study specifically to investigate the effect of different APOE genotypes on cognitive performance in normal elderly adultsMethods: A total of 156 older adults with normal cognitive function were enrolled in the current study. According to different genetic types, they were divided into three groups: 1) E2/2 or E2/3 (APOE E2); 2) E3/3 (APOE E3); and 3) E2/4, E3/4, or E4/4 (APOE E4). Then Montreal Cognitive Assessment (MoCA) and Neuropsychological Test Battery (NTB) were used to assess their global cognitive function and domain-specific cognitive function, respectively. Results: The results of Kruskai-Wallis H test showed that the scores of associative learning in APOE E2 group were lower than that in E3 groups (p<0.05), but there was no statistical difference (p>0.05) in associative learning between E2 group and E4 group, and E3group and E4 group. Similarly, there was no difference (p>0.05) in the global cognitive function among the three groups.Conclusion: APOE E2 is associated with decreased associative learning function than APOE E3 in a cognitively normal aging Han Chinese population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".