Subtle Alterations in DNA Methylation Patterns in Normal Cells in Response to Dietary Stilbenoids
Bibliographic record
Abstract
SCOPE: Searching for correlations between dietary polyphenols and risk of chronic diseases has been a challenge due to the lack of quantitative evaluation methods of long-term exposure. We previously observed substantial DNA methylation changes in human cancer cells upon treatment with polyphenols of the stilbenoid class. When induced in normal cells, such molecular changes may persist and reflect chronic exposure. METHODS AND RESULTS: Illumina 450K microarray is used to delineate a genome wide DNA methylation landscape in MCF10A human immortalized mammary epithelial cells exposed to resveratrol (RSV) at noncytotoxic 15 μM dose for 9 days. Subtle alterations are observed suggesting remodeling of DNA methylation patterns rather than switch on/off changes. Using pyrosequencing, DNA methylation is quantitatively measured at eight CpG sites located within KCNJ4, RNF169, BCHE, DAOA, HOXA9, RUNX3, KRTAP2-1, and TAGAP, upon exposure to RSV or pterostilbene and shows similar differences induced by both stilbenoids. Two of the probes, Runx3 and Kcnj4, are successfully verified in whole blood DNA from healthy rats on diets supplemented with stilbenoids. CONCLUSIONS: The study provides strong support for testing the utility of polyphenol-mediated changes in DNA methylation as quantitative measures of long-term dietary exposures in nutritional epidemiology and clinical trials.
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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 | 0.000 |
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".