Flaxseed attenuates the tumor growth stimulating effect of soy protein in ovariectomized athymic mice with MCF‐7 human breast cancer xenografts
Bibliographic record
Abstract
In several epidemiological studies, a phytoestrogen-rich diet containing lignans and isoflavones is associated with reduced breast cancer risk, but experimental findings are controversial. In postmenopausal mammary cancer xenograft model, flaxseed (FS), a rich source of plant lignans, reduced breast cancer growth, while soy protein (SP), a rich source of isoflavones, enhanced it. The intake of phytoestrogens is increasing particularly among postmenopausal women, emphasizing the importance of elucidating their interactive effects on breast cancer. Our study determined the effect of FS and SP diets, alone and in combination, on the established human breast cancer MCF-7 tumor growth in ovariectomized athymic nude mice. Tumor bearing mice were divided into 4 groups and fed for 25 weeks either the basal diet (BD), or BD supplemented with 10% FS, 20% SP or 10% FS and 20% SP. After estrogen deprivation, FS regressed the tumor size similar to that of control. SP initially regressed the tumors but starting at week 13, the tumors regressed significantly less than in control and 43% of the tumors were regrowing until the end of the experiment and were significantly larger in size than in control. The combination of SP with FS reduced the tumor growth similar to that of control, as suggested also by the reduced tumor cell proliferation index. In conclusion, dietary FS did not stimulate the growth of estrogen responsive MCF-7 cancers in ovariectomized mice, while long-term consumption of SP did. Furthermore, FS reduced the tumor growth stimulating effect of SP to the same level as control, suggesting tumor growth attenuating effect of FS.
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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) | 0.000 | 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 | 0.001 |
| 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".