Flaxseed and Soy Protein Isolate, Alone and in Combination, Differ in their Effect on Bone Mass, Biomechanical Strength, and Uterus in Ovariectomized Nude Mice with MCF-7 Human Breast Tumor Xenografts
Bibliographic record
Abstract
In our previous study, flaxseed (FS) reduced while soy protein isolate (SPI) stimulated MCF-7 breast tumor growth in ovariectomized mice. In addition, combining SPI and FS resulted in a negation of SPI-induced tumor growth. In this study, the effects of SPI, FS, and their combination were further examined on mouse bone and uterus to further ensure overall safety of the breast cancer treatments. Ovariectomized mice with established MCF-7 xenografts were fed either a basal diet (control), or a basal diet supplemented with 10% FS, 20% SPI, or SPI + FS for 25 wk. Mouse bones were analyzed for mineral and biomechanical strength properties, and uterus weight was measured. The SPI group had a higher femur bone mineral density and biomechanical strength parameters (yield load, stiffness, and peak load) compared to control, while the FS group significantly increased femur stiffness and peak load. The SPI + FS group did not affect femur mineral, but significantly reduced whole femur area and length and increased femur yield load, stiffness, and peak load. Uterus weight was significantly increased by the SPI + FS group, while SPI alone induced an intermediate effect. In conclusion, all dietary treatments induced beneficial effects on bone in a preclinical mouse model of postmenopausal breast cancer. Although the SPI + FS and SPI groups exerted stimulatory effects on uterus weight, other histological parameters need to be measured to determine the overall safety of these breast cancer treatments on the uterus.
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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 | 0.000 | 0.000 |
| 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".