Cytotoxic activity and anti-cancer potential of Ontario grown onion extracts against breast cancer cell lines
Bibliographic record
Abstract
Background: Breast cancer is the most commonly diagnosed cancer and the second leading cause of cancer deaths among Canadian women. Cancer management through changes in lifestyle, such as increased intake of foods rich in dietary flavonoids, have been shown to decrease the risk associated with breast, liver, colorectal, and upper-digestive cancers in epidemiologic studies. Onions are high in flavonoid content and one of the most common vegetables. Additionally, onions are used in most Canadian cuisines.Methods: We investigated the effect of five prominent Ontario grown onion (Stanley, Ruby Ring, LaSalle, Fortress, and Safrane) extracts on two subtypes of breast cancer cell lines: a triple negative breast cancer line MDA-MB-231 and an ER+ breast cancer line MCF-7.Results: These onion extracts elicited strong anti-proliferative, anti-migratory, and cytotoxic activities on both the cancer cell lines. Flavonoids present in these onion extracts induced apoptosis, cell cycle arrest in the G2/M phase, and a reduction in mitochondrial membrane potential at dose-dependent concentrations. Onion extracts were more effective against MDA-MB-231 compared to the MCF-7 cell line. Conclusion: In this study, we investigated the extracts synthesized from Ontario-grown onion varieties in inducing anti-migratory, cytostatic, and cytotoxic activities in two sub-types of human breast cancer cell lines. Anti-tumor activity of these extracts depends upon the varietal and can be formulated into nutraceuticals and functional foods for the wellbeing of cancer patients. Overall, the results suggest that onion extracts are a good source of flavonoids with anti-cancerous properties.Keywords: onion extracts; flavonoids; anti-proliferative; breast cancer; cytotoxic activity
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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".