Anethole induces anti-oral cancer activity by triggering apoptosis, autophagy and oxidative stress and by modulation of multiple signaling pathways
Bibliographic record
Abstract
Abstract Oral cancer is one of the major public health problems. The aim of this study was to evaluate the effects of anethole, 1-methoxy-4-[(E)-1-propenyl]-benzene, on growth and apoptosis of oral tumor cells, and to identify the signaling pathways involved in its interaction with these cancer cells. Cancer gingival cells (Ca9-22) were treated with different concentrations of anethole. Cell proliferation and cytotoxic effects were measured by MTT and LDH assays. Cell death, autophagy and oxidative stress markers were assessed by flow cytometry while cell migration was determined by a healing capacity assay. The effect of anethole on apoptotic and pro-carcinogenic signaling pathways proteins was assessed by immunoblotting. Our results showed that anethole selectively and in a dose-dependent manner decreases the cell proliferation rate, and conversely induces toxicity and apoptosis in oral cancer cells. This killing effect was mediated mainly through NF-κB, MAPKinases, Wnt, caspase 3, 9 and PARP1 pathways. Anethole showed an ability to induce autophagy, decrease reactive oxygen species (ROS) production and increased intracellular glutathione (GSH) activity. Finally, anethole treatment inhibits the expression of oncogenes (cyclin D1) and up-regulated cyclin-dependent kinase inhibitor (p21WAF1), increases the expression of p53 gene, but inhibits the epithelial-mesenchymal transition markers. These results indicate that anethole could be a potential molecule for the therapy of oral cancer.
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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".