The Effect of Secoisolariciresinol Diglucoside and Flaxseed Oil, Alone and in Combination, on MCF-7 Tumor Growth and Signaling Pathways
Bibliographic record
Abstract
Flaxseed (FS), an oilseed containing high amounts of the phytoestrogen lignan, secoisolariciresinol diglucoside (SDG), and n-3 fatty acid, alpha-linolenic acid-rich oil (FO), has been shown to inhibit the growth of established human breast tumors (MCF-7) in ovariectomized (OVX) athymic mice. However, the major FS component responsible for this effect and the mechanism(s) of its action are unclear. Hence, this study determined, in a 2 x 2 factorial design, the effect of SDG and FO, alone or in combination, on the growth of established human estrogen receptor positive (ER+) breast tumors and the potential mechanism(s) of its action. OVX mice with established ER+ human breast tumors (MCF-7) were treated for 8 wk with basal diet (BD, control) or BD supplemented with SDG (1 g/kg), FO (38.5 g/kg), or SDG + FO. All treatments reduced the tumor growth, but SDG had the greatest effect primarily through reducing tumor cell proliferation rather than increasing apoptosis. SDG had a main effect in the reduction of PS2, BCL2, and IGF-1R mRNA expression, whereas FO had a main effect only in PAKT reduction. SDG alone also lowered the ERalpha, ERbeta, EGFR, BCL2 mRNA, and PMAPK protein, indicating that its effect involves the modulation of the ER- and growth factor receptor-mediated signaling 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".