Hepatocellular cancer cell lines, Hep-3B and Hep-G2 display the pleiotropic response to resveratrol and berberine
Bibliographic record
Abstract
Human carcinoma cells with different p53 status exposed to a combination of bioactive substances, resveratrol and berberine, revealed different responses in cell viability via p53-dependant apoptosis pathway activation. Using 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) assay, we investigated various and opposing effects in hepatocellular carcinoma cells, Hep-G2 and Hep-3B with different p53-status. Cells decreased in viability after treatment with dose-dependent concentrations of resveratrol and berberine. Hep-3B p53 mutants were more sensitive in comparison to the p53 wild type Hep-G2 cell line. A synergistic effect was observed after treatment of Hep-3B cells with a combination of resveratrol/berberine ratios in favor of resveratrol (2:1, 3:1). The results suggest that an effective concentration of berberine, in the presence of resveratrol, could be decreased even to 50% (half the IC50 for berberine) in cancer treatment. Combined treatment with berberine and resveratrol, at the investigated concentrations and fractions, significantly reduces the viability of wild type p53 Hep-G2 and null p53-mutant Hep-3B cells by 20% and 40%, respectively. Stronger toxic effects on viability and proliferation were observed in Hep-3B cells what is consistent with the assumptions that null p53-mutants activate apoptosis canonical pathway. In conclusion, p53 status in human hepatocellular cancer cell lines modulates responses to plant-derived therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 teacher head, 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".