The effect of prolactin and apolipoprotein E gene polymorphism on cognitive functions of menopausal women
Bibliographic record
Abstract
OBJECTIVE: The objective of the study was to analyze a possible association between cognitive functions and level of prolactin in menopausal women with different polymorphisms of apolipoprotein E gene (APOE). The examined population included women from the south-eastern part of Poland; aged 50-65 years; at least 2 years after their last menstruation; in good health; with at least primary education, FSH > 30 mIU/ml. The MoCA test (Montreal Cognitive Assessment Test) allowed us to exclude women with signs of dementia. The cognitive functions assessment was conducted with the CNS-VitalSigns diagnostic equipment (Polish version). The prolactin designations were conducted by SYNEVO--an accredited laboratory. The examination of APOE polymorphism was performed using the multiplex-PCR method. The results were statistically analyzed. RESULTS AND CONCLUSION: Higher level of prolactin turned out to be associated with better test results in the following areas: NCI, memory verbal memory psychomotor speed and concentration. Women with higher level of prolactin had better results in NCI, psychomotor speed and verbal memory tests. The test results of other cognitive function were not unequivocally related to higher levels of prolactin. Thus, it was not possible to conclude that the presence of APOE polymorphism is related to the effect of prolactin on cognitive functions of the examined menopausal women.
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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".