Proposed cytotoxic mechanisms of the saffron carotenoids crocin and crocetin on cancer cell lines
Bibliographic record
Abstract
We investigated the cytotoxic activities of crocin and crocetin, 2 major carotenoids isolated from the stigma of Crocus sativus (saffron), on 5 human cancer cell lines and proposed their possible anticancer mechanisms. Crocetin, a glycosylated carotenoid, showed approximately 5- to 18-fold higher cytotoxicity than crocin, a carboxylic carotenoid (IC50 of 0.16-0.61 mmol/L for crocetin vs. 2.0-5.5 mmol/L for crocin). This suggests that structural differences account for the different efficacies between them. Fluorescence-activated cell sorting (FACS) analysis showed that crocetin induced a significant level of cellular reactive oxygen species (ROS) in HeLa cells, whereas crocin did not. This ROS induction supported the cytotoxicity of crocetin, but not of crocin. A significant activation of nuclear factor erythroid 2-related factor 2 (Nrf2) was observed in both HeLa cells treated with crocin and crocetin: a 3.0-fold increase by 1 mmol/L crocetin and a 1.6-fold increase by 0.8 mmol/L crocin compared to the control. Furthermore, both crocetin and crocin reduced the protein expression of lactate dehydrogenase A (LDHA), one of the targets for chemoprevention in cancer cells, by 34.2% and 10.5%, respectively, compared to the control in HeLa cells. These findings suggest that crocetin and crocin have different mechanisms for their observed cytotoxicity in cancer cell lines.
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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 | 0.001 | 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".