Dietary Flaxseed Interaction With Tamoxifen Induced Tumor Regression in Athymic Mice With MCF-7 Xenografts by Downregulating the Expression of Estrogen Related Gene Products and Signal Transduction Pathways
Bibliographic record
Abstract
Our previous short-term study has shown that 10% flaxseed (FS) inhibits the growth of human estrogen dependent estrogen receptor positive breast tumors (MCF-7) xenografts in ovariectomized (OVX) athymic mice and enhances the tumor inhibitory effect of tamoxifen (TAM). This study determined the long-term effect of 5% and 10% FS, with or without TAM, on the growth of MCF-7 xenografts in athymic mice and the potential mechanisms of actions. OVX mice with established MCF-7 tumors were treated with basal diet (control), 5% FS (5FS), 10% FS (10FS), and TAM (5 mg/pellet, 60-day release), alone or in combination, for 16 wk without estrogen supplementation. Tumor growth was monitored weekly. At sacrifice, the tumors were analyzed by immunohistochemistry for cell proliferation, apoptosis, and expression of estrogen-related genes and signal transduction pathways. Both 5FS and 10FS regressed the pretreatment tumor size by over 90% similar to control. TAM initially regressed the tumors but then induced a regrowth; thus, only a final 6% reduction from pretreatment tumor size was achieved, which was attenuated by combining TAM with 10FS but not with 5FS. TAM combined with 10FS regressed tumors to 55% of pretreatment tumor size due to decreased cell proliferation and increased apoptosis. The expressions of cyclin D1, estrogen receptor alpha, human epidermal growth factor receptor 2, and insulin-like growth factor I receptor in the TAM group were significantly reduced when TAM was combined with 5FS or 10FS. In conclusion, after long-term treatment, FS did not stimulate tumor growth and combined with TAM, regressed tumor size in part due to downregulation of the expression of estrogen-related gene products and signal transduction pathways.
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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) | 0.002 | 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".