Biomarkers measured in buccal and blood leukocyte DNA as proxies for colon tissue global methylation.
Bibliographic record
Abstract
There is increasing interest in clarifying the role of global DNA methylation levels in colorectal cancer (CRC) etiology. Most commonly, in epidemiologic studies, methylation is measured in DNA derived from blood leukocytes as a proxy measure of methylation changes in colon tissue. However, little is known about the correlations between global methylation levels in DNA derived from colon tissue and more accessible tissues such as blood or buccal cells. This cross-sectional study utilized DNA samples from a screening colonoscopy population to determine to what extent LINE-1 methylation levels (as a proxy for genome-wide methylation) in non-target tissue (e.g., blood, buccal cells) reflected methylation patterns of colon mucosal tissue directly at risk of developing CRC. The strongest Pearson correlation was observed between LINE-1 methylation levels in buccal and blood leukocyte DNA (r = 0.50; N = 67), with weaker correlations for comparisons between blood and colon tissue (r = 0.36; N = 280), and buccal and colon tissue (r = 0.27; N = 72). These findings of weak/moderate correlations have important implications for interpreting and planning future investigations of epigenetic markers and CRC risk.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".