Curcumin and resveratrol induce apoptosis and nuclear translocation and activation of p53 in human neuroblastoma.
Bibliographic record
Abstract
BACKGROUND: Neuroblastoma (NB) is an aggressive childhood cancer of the peripheral nervous system arising from neural crest sympathoadrenal progenitor cells. Despite current rigorous treatment protocols, prognosis for high stage NB patients is poor and so there remains a need for more effective, less cytotoxic treatments. Curcumin and resveratrol possess anti-tumor properties in adult cancer models and negligible toxicity in normal cells, but little is known about the effect of these agents on pediatric cancers. MATERIALS AND METHODS: Stage 4 MYCN-amplified NB cell lines, with wild-type or mutant p53, were treated with curcumin and resveratrol and analyzed for effects on proliferation, cell cycle, induction of apoptosis and p53 function. RESULTS: Treatment induced a dose- and time-dependent decrease in cell viability, cell cycle arrest and induction of apoptosis. Treatment transiently up-regulated p53 expression and induced nuclear translocation of p53, followed by induction of p21(WAF-1/CIP-1) and Bax expression. CONCLUSION: Observations suggest that the cytotoxicity, cell cycle arrest and apoptosis induced by curcumin and resveratrol in NB cells may be mediated via functionally activated p53 and merit further study.
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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) | 0.002 | 0.001 |
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".