Flaxseed combined with ultra low‐dose estrogen therapy preserves bone mass in ovariectomized rats
Bibliographic record
Abstract
Flaxseed, rich in phytoestrogens and alpha‐linolenic (ALA) acid, that may modulate bone metabolism, is commonly consumed by postmenopausal women in combination with pharmaceuticals such as estrogen replacement therapy. We determined if a 10% FS diet modulates the effect of ultra‐low dose estrogen therapy (ULD) on bone mineral density (BMD) and biomechanical bone strength, a surrogate measure of fracture risk, using the ovariectomized rat model of postmenopausal osteoporosis. Ovariectomized rats (n=48) were randomized to: i. basal diet (BD, AIN93M); ii. BD+ULD implant; or iii. BD containing 10% FS+ ULD for 12 weeks. A sham‐operated control group was fed BD. BMD and strength properties of the lumbar vertebrae (LV), femurs and tibias were analyzed by dual energy x‐ray absorptiometry and biomechanical strength testing, respectively. Bone fatty acid composition was determined by gas chromatography. Unlike ULD, FS+ULD resulted in greater (p<0.05) LV BMD and strength compared to ovariectomy alone, and higher (p<0.05) n‐3 fatty acid levels and lower n‐6 fatty acids levels in LV and tibias compared to all groups. ALA (r=0.52, p=0.03) and total n‐3 fatty acid (r=0.52, p=0.03) levels in LV were positively correlated with LV strength. In conclusion, FS enhances the effect of ULD at the lumbar spine and these benefits are associated with changes in fatty acid composition. Grant Funding Source Supported by NSERC Discovery Grant (W. Ward), NSERC Postgraduate Scholarship (S. Sacco), CONACyT Scholarship (S. Reza‐Lopez).RC
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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 | 0.001 |
| 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 | 0.001 | 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".