Cellular mechanisms mediating the anti-cancer effects of carnosol on gingiva carcinoma
Bibliographic record
Abstract
Carnosol, a rosemary polyphenol, displays anticancer properties and is suggested as a safer alternative to conventional surgery, radiotherapy, and chemotherapy. Given that its effects on gingiva carcinoma have not yet been investigated, the aim of this study was to explore its anti-tumor selectivity and to unravel its underlying mechanisms of action. Hence, oral tongue and gingiva carcinoma cell lines exposed to carnosol were analyzed to estimate cytotoxicity, cell viability, cell proliferation, and colony formation potential as compared with those of normal cells. Key cell cycle and apoptotic markers were also measured. Finally, cell migration, oxidative stress, and crucial cell signaling pathways were assessed. Selective anti-gingiva carcinoma activity was disclosed. Overall, carnosol mediated colony formation and proliferation suppression in addition to cytotoxicity induction. Cell cycle arrest was highlighted by the disruption of the c-myc oncogene/p53 tumor suppressor balance. Carnosol also increased apoptosis, oxidative stress, and antioxidant activity. On a larger scale, the alteration of cell cycle and apoptotic profiles was also demonstrated by QPCR array. This was most likely achieved by controlling the STAT5, ERK1/2, p38, and NF-ĸB signaling pathways. Lastly, carnosol reduced inflammation and invasion ability by modulating IL-6 and MMP9/TIMP-1 axes. This study establishes a robust foundation, urging extensive inquiry both in vivo and in clinical settings, to substantiate the efficacy of carnosol in managing gingiva carcinoma.
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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 | 0.001 |
| 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".