Flaxseed Does not Antagonize the Effect of Ultra-Low-Dose Estrogen Therapy on Bone Mineral Density and Biomechanical Bone Strength in Ovariectomized Rats
Bibliographic record
Abstract
A previous study showed that flaxseed (FS) combined with low-dose (LD) estrogen therapy, resembling LD transdermal estrogen therapy in postmenopaual women, inhibited loss of bone mineral density (BMD), bone mineral content (BMC), and strength in lumbar vertebrae in ovariectomized rats. Whether FS combined with an even lower dose of estrogen is effective at preserving bone or whether FS interferes with the effect of this lower dose of estrogen is unknown. Thus, this study determined whether an ultra-low-dose (ULD) estrogen therapy, half the dose previously studied, in combination with FS preserved bone mass and strength in the lumbar vertebrae in ovariectomized rats. Rats were treated for 12 wk with (1) basal diet (BD) (ovariectomized control), (2) BD + ULD estrogen implant, or (3) BD containing 10% FS + ULD estrogen implant. A sham-operated control group was fed BD. Unlike ULD, FS + ULD attenuated loss of BMD and strength at the lumbar vertebrae and BMD in femurs and tibias. FS + ULD resulted in higher percentages of n-3 fatty acids including alpha-linolenic acid and eicosapentaenoic acid and lower percentages of n-6 fatty acids including linoleic acid compared to all other groups. Differences in fatty acid composition at the lumbar vertebrae and tibia were significantly related to BMD, BMC, and strength. No treatment-induced effects on uterus weight were observed, but histological analyses are needed to confirm safety. In conclusion, FS did not antagonize the activity of ULD, and their combination attenuated the loss of BMD and strength at the lumbar vertebrae, which was associated with differences in bone fatty acid composition.
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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 | 0.001 | 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".