Early midlife ovarian removal is associated with lower posterior hippocampal function
Bibliographic record
Abstract
INTRODUCTION: Women with early bilateral salpingo-oophorectomy (BSO) have greater Alzheimer's disease (AD) risk than women with spontaneous menopause (SM), but the pathway toward this risk is understudied. Considering associative memory deficits may reflect early signs of AD, we studied how BSO affected brain activity underlying associative memory. METHODS: Early midlife women with BSO (with and without 17β-estradiol therapy [ET]) and age-matched controls (AMCs) with intact ovaries completed a face-name associative memory task during functional magnetic resonance imaging. Hippocampal activity along the anteroposterior axis during associative encoding and retrieval was compared among three groups (BSO [n = 28], BSO+ET [n = 35], AMCs [n = 40]). RESULTS: Both BSO groups (with and without ET) showed lower posterior hippocampal activation during encoding compared to the AMC group. However, this difference in activation was not significantly correlated with associative memory task performance. DISCUSSION: Early 17β-estradiol loss may influence posterior hippocampal activity during associative encoding, possibly presaging late-life AD. HIGHLIGHTS: After ovarian removal, changes in hippocampal function may affect dementia risk. Midlife ovarian removal is associated with less activation in the posterior hippocampus. Estradiol therapy may ameliorate alterations in brain function during learning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".