Flaxseed Does Not Enhance the Estrogenic Effect of Low-Dose Estrogen Therapy on Markers of Uterine Health in Ovariectomized Rats
Bibliographic record
Abstract
Flaxseed (FS) is an oilseed rich in phytoestrogens and n-3 polyunsaturated fatty acids, compounds that may attenuate bone loss during aging. We previously demonstrated using the ovariectomized (OVX) rat model of postmenopausal osteoporosis that 10% dietary FS combined with low-dose estrogen therapy (LD) preserves vertebral bone mass and strength more so than either treatment alone. However, it was prudent to also consider the effect of this intervention on uterine tissue as LD, and possibly FS, may have estrogenic, and thus negative, effects on uterine tissue. The present study investigated if FS enhances the estrogenic effect of LD on markers of uterine health in OVX rats. Three-month-old rats were randomized to groups: (1) SHAM, (2) OVX, (3) OVX+FS, (4) OVX+LD, or (5) OVX+FS+LD. Ground FS was added to the AIN-93M diet (100 g/kg of diet), and LD was delivered by subcutaneous implant (0.42 μg of 17β-estradiol/kg of body weight/day) to mimic LD in postmenopausal women. After 12 weeks, histological analyses of uterine tissue demonstrated flattened or cuboidal luminal epithelia organized in a single layer in the OVX group, while FS, LD, and FS+LD induced a single layer of elongated luminal epithelia, columnar in shape. The SHAM group had the greatest epithelial mass. Cell proliferation was similar among all OVX groups. Therefore FS and FS+LD similarly induce estrogen-like effects on the morphology of luminal epithelia that are weaker than in the SHAM group without inducing cell proliferation in OVX rats. Thus, FS does not enhance the estrogenic effect of LD on markers of uterine health in OVX rats.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".