Ovariectomy and 17β-estradiol modulate the levels of Alzheimer’s amyloid β peptides in brain
Bibliographic record
Abstract
OBJECTIVE: To test whether female gonadal hormone status and estrogen modulate the metabolism of Abeta peptides in vivo. BACKGROUND: AD is a neurodegenerative disorder characterized by accumulation of aggregated forms of the 40- and 42-amino acid Abeta peptides (Abeta40 and Abeta42). Estrogen replacement therapy in postmenopausal women is associated with decreased risk for AD or delay in disease onset or both. The mechanism by which estrogen exerts this neuroprotective effect is elusive. 17beta-estradiol (E2) was shown to reduce the release of Abeta peptides by primary neuronal cultures of murine and human origin. METHODS: For this purpose, four experimental sets of guinea pigs were used: intact animals, ovariectomized animals (ovx), and ovariectomized animals that received E2 at two different doses (ovx+low-dose E2 and ovx+high-dose E2). Brain Abeta40 and Abeta42 levels were assessed using Abeta40 and Abeta42-specific ELISA assays. RESULTS: Prolonged ovariectomy resulted in uterine atrophy and decreased serum E2 levels and was associated with a pronounced increase in brain Abeta levels. Total brain Abeta in the ovx animals was increased by 1. 5-fold on average as compared to intact controls. E2 treatment of ovariectomized animals led to uterine hypertrophy and a dose-dependent increase in serum E2 levels. In addition, both doses of E2 significantly reversed the ovariectomy-induced increase in brain Abeta levels. The high-dose E2 treatment did not lead to a further decrease in brain Abeta beyond that observed with the low-dose E2 treatment. CONCLUSIONS: Our results infer that cessation of ovarian estrogen production in postmenopausal women might facilitate Abeta deposition by increasing the local concentrations of Abeta40 and Abeta42 peptides in brain. In addition, our finding that E2 treatment is associated with diminution of brain Abeta levels suggests that modulation of Abeta metabolism may be one of the ways by which estrogen replacement therapy prevents or delays the onset of AD or both in postmenopausal 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 | 0.000 |
| 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 | 0.001 |
| 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".