Postmenopausal cognitive changes and androgen levels in the context of apolipoprotein E polymorphism
Bibliographic record
Abstract
The focus of this study was to assess cognitive functions in relation to androgens and specifically testosterone and dehydroepiandrosterone in postmenopausal women as well as the correlation between cognitive functions and these two androgens according to polymorphism of the apolipoprotein E gene (APOE). Material and methods: A group of 402 women was recruited to the study (minimum 2 years after the last menstruation, follicle-stimulating hormone (FSH) more than 30 U/ml and no dementia signs on Montreal Cognitive Assessment). The computerized battery of the Central Nervous System Vital Signs test was used to diagnose cognitive functions. APOE genotyping was performed by multiplex polymerase chain reaction (PCR). Testosterone (TTE) and dehydroepiandrosterone (DHEA) in the blood serum were assessed for further statistical correlations analysis. Results: In the group of postmenopausal women, higher testosterone concentration was associated with lower scores for Neurocognition Index (NCI) (p = 0.028), memory (p = 0.008) and psychomotor speed (p < 0.001). Presence of at least one APOE 4 allele potentiated testosterone's negative influence on cognitive functions (p < 0.05). Woman with a high normal level of DHEA scored significantly better in verbal (p = 0.027) and visual memory (p < 0.001) than other participants. APOE polymorphism did not modify the relationship between DHEA concentration and scores for cognitive functions. Conclusions: Hormonal balance variations after menopause may influence brain processes concerned with cognition, especially memory and psychomotor speed. The observed effects may be related to androgens' influence on higher cortical functions in the changed hormonal dynamics of the postmenopausal period.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".