The Combination of a Novel Selective Estrogen Receptor Modulator with an Estrogen Protects the Mammary Gland and Uterus in a Rodent Model: The Future of Postmenopausal Women’s Health?
Bibliographic record
Abstract
The Women's Health Initiative Study and other reports have created major uncertainty among postmenopausal women and physicians concerning hormone replacement therapy. We have thus investigated the possibility of replacing the progestin in hormone replacement therapy by a novel selective estrogen receptor (ER) modulator having potent and pure antiestrogenic activity in the mammary gland and uterus. As measured by changes in histology and Cdc47 labeling in the rat model, the present study shows that the stimulatory effect of estradiol in the mammary gland and uterus is efficiently blocked by simultaneous administration of the novel selective ER modulator EM-652, but bone mineral density is preserved and serum cholesterol is decreased. After the administration of 14C-labeled EM-652, we observed that there is no detectable radioactivity in the brain. Moreover, ER alpha immunoreactivity remained constant in the hypothalamus after EM-652 treatment, whereas ER alpha became almost undetectable in the mammary gland and uterus. The present data show the poor or absent access of EM-652 to the brain, whereas the effects of estrogens are efficiently neutralized in the mammary gland and uterus. Such data support the exciting possibility of a novel approach that could meet most of the needs of women's health at menopause, namely control of hot flushes and prevention of breast, uterine, and ovarian cancer as well as osteoporosis and potentially helping brain function and preventing Alzheimer's disease with no identifiable risk or negative effect.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".