Treatment with flaxseed oil induces apoptosis in cultured malignant cells
Bibliographic record
Abstract
Flaxseed oil is widely recognized for its exceptional nutritional value, high concentration of fiber-based lignans and large amounts of ω-fatty acids. It is one of a generic group of functional foods that is often taken by cancer patients as a potential treatment. We have examined the anti-cancer effects of flaxseed oil by studying its direct effects on cancer cell growth in vitro . Treatment of a variety of cancer cell lines with flaxseed oil decreased their growth in a dose-dependent manner while non-malignant cell lines showed small increases in cell growth. Cells treated with a mixture of fatty acids, including α-linolenic acid, docosahexaenoic acid, and eicosapentaenoic acid and lignans including enterodiol and enterolactone was also able to decrease the growth of cancer cells. Treatment of B16-BL6 murine melanoma and MCF-7 breast cancer cells with flaxseed oil induced apoptosis as determined by changes in cell morphology, annexin V staining, DNA fragmentation and/or caspase activation. In addition, treatment with flaxseed oil also disrupted mitochondrial function in B16-BL6 and MCF-7 cells. These results indicate that flaxseed oil can specifically inhibit cancer cell growth and induce apoptosis in some cancer cells and suggests it has further potential in anti-cancer therapy.
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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 | 0.000 | 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 | 0.000 |
| 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".