Anticancer and antioxidant effects of red cabbage on three cancerous cell lines and comparison with a normal cell line (HFF-3)
Bibliographic record
Abstract
Red cabbage or scientifically Brassica oleracea is a rich source of anthocyanins exhibiting enormous antioxidant properties creating a perspective of its applications in healthcare sector. The aim of this study was the evaluation of antioxidant properties of red cabbage extract by DPPH radical scavenging assay, and exploration of its anticancer activity on the growth and viability of the desired human cancer cells by in vitro assay to detect cytotoxic activity. The results showed enhanced effects with increasing concentration exhibiting highest value of IC90+ at the concentration of 2500 µg/ml when it is compared with IC50 value of red cabbage extract at a concentration of 750 µg/ml. The polyphenol compounds were found 39.55 mg GAE/100 g of red cabbage extract and red cabbage extract increases the death rate of cancer cells and the cytotoxicity effect was dose dependent. It can be concluded that red cabbage extract should be used at lower concentrations than 6.4 mg/ml in order to prevent the normal human cell damage. Thus, it can be considered as a healthy foodstuff due to numerous phenolic compounds and powerful antioxidant and anticancer activity when it is used in moderate amount.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".