Effects of folate supplementation on two provisional molecular markers of colon cancer: a prospective, randomized trial
Bibliographic record
Abstract
OBJECTIVES: Dietary folate intake is inversely associated with the risk of colorectal cancer. This study investigated the effect of folate supplementation on genomic DNA methylation and DNA strand breaks in exons 5-8 of the p53 gene of the colonic mucosa, two provisional biomarkers of colon cancer. METHODS: Twenty subjects with adenomas were randomized to receive either folate (5 mg/day) or placebo for 1 yr after polypectomy. At baseline, 6 months and 1 yr, systemic and colonic measures of folate status were determined, as were the biomarkers mentioned earlier. RESULTS: Folate supplementation increased serum, red blood cell and colonic mucosal folate concentrations (p < 0.02). Folate supplementation also increased the extent of genomic DNA methylation at 6 months and 1 yr (p = 0.001), whereas placebo administration was associated with an increase in the extent of genomic DNA methylation only at 1 yr. Similarly, folate supplementation decreased the extent of p53 strand breaks in exons 5-8 at 6 months and 1 yr (p < 0.02), whereas placebo administration was associated with a decrease in the extent of p53 strand breaks only at 1 yr. CONCLUSIONS: Both of these provisional biomarkers of colon cancer underwent accelerated improvement at 6 months with folate supplementation. However, these markers also improved with placebo at 1 yr. Therefore, potential confounding factors that seem to modulate these biomarkers need to be identified and corrected in order for these markers to serve as suitable surrogate endpoints in folate chemoprevention 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".