Flavonoid-Enriched Apple Fraction AF4 Induces Cell Cycle Arrest, DNA Topoisomerase II Inhibition, and Apoptosis in Human Liver Cancer HepG2 Cells
Bibliographic record
Abstract
Apples are a major source of dietary phytochemicals such as flavonoids in the Western diet. Here we report anticancer properties and possible mechanism of action of apple flavonoid-enriched fraction (AF4) isolated from the peels of Northern Spy apples in human hepatocellular carcinoma cells, HepG2. Treatment with AF4 induced cell growth inhibition in HepG2 cells in time- and dose-dependent manner. Concentration of 50 μg/ml (50 μg total monomeric polyphenols/ml) AF4 was sufficient to induce a significant reduction in cell viability within 6 h of treatment (92%, P < 0.05) but had very low toxicity (minimum 4% to maximum 16%) on primary liver and lung cells, which was significantly lower than currently prescribed chemotherapy drug Sorafenib (minimum 29% to maximum 49%, P < 0.05). AF4 induced apoptosis in HepG2 cells within 6 h of treatment via activation of caspase-3. Cell cycle analysis via flow-cytometer showed that AF4 induced G2/M phase arrest. Further, results showed that AF4 acts as a strong DNA topoisomerase II catalytic inhibitor, which may be a plausible reason to drive the cells to apoptosis. Overall, our data suggests that AF4 possesses a significantly stronger antiproliferative and specific action than Sorafenib in vitro and is a potential natural chemotherapy agent for treatment of liver 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".