Ageing perspective on cognitive outcomes from ancillary reproductive hormone adjustments
Bibliographic record
Abstract
In addition to primary reproductive functions, gonadal hormones play an important role in an array of neural mechanisms across the human lifespan. The ageing-related decline in their activity has been linked to the deterioration of cognitive functions in otherwise healthy women, associated with menopause transition, contributing to higher incidents of post-menopause dementia. Given the growing utility of gonadal steroids for birth control, as well as for compensatory treatment of menopause and oophorectomy symptoms, and adjuvant transgender therapy, their long-term effects on neural mechanisms warrant comprehensive assessment. In this article, we present an ageing perspective on the cognitive outcomes from contraceptive and replacement therapeutic use of gonadal hormones and discuss their effects on the risk of developing Alzheimer's and Parkinson's dementia. Despite rising data supporting the ameliorative effects of reproductive hormones on cognitive facilities, their impact varies depending on study design and type of intervention, thus, implying dynamic neuro-endocrine interactions with complex compensatory mechanisms. Elucidating differential effects of reproductive hormone adjustments on cognition with underlying mechanisms is expected not only to shed light on important aspects of brain ageing and dementia but to facilitate their use in personalized medicine with improved safety margins and therapeutic outcomes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".