Bibliographic record
Abstract
SIGNIFICANCE: The progressive, dose-dependent, and potentially reversible epigenetic changes observed in cancer present new opportunities in cancer risk modification and prevention using dietary and lifestyle factors. Folate, a water-soluble B vitamin, has been of intense interest because of an inverse association between folate status and the risk of several malignancies (particularly colorectal cancer) and its potential to modulate DNA methylation. Aberrant patterns and dysregulation of DNA methylation are mechanistically related to carcinogenesis. RECENT ADVANCES: The effects of folate on DNA methylation patterns have recently been investigated in two important life stages: pre- and early postnatal life and aging. Recent studies have demonstrated that folate exposure in the intrauterine environment and early life and during the aging process may have profound effects on DNA methylation with significant functional ramifications, including the risk of cancer. CRITICAL ISSUES: Evidence from animal, human, and in vitro studies suggest that the epigenetic effects of folate on DNA methylation are highly complex. The effects are gene and site specific and appear to depend on cell type, target organ, stage of transformation, the degree and duration of folate manipulations, interactions with other methyl group donors and dietary factors, and genetic variants in the folate metabolic pathways. FUTURE DIRECTIONS: The potential for folate to modulate DNA methylation and, thus, modify the risk of cancer in humans is worthy of further investigation. Due to the complex relationship between folate exposure and DNA methylation, more elaborate epidemiological, clinical, and mechanistic studies that determine the clinical, biological, and molecular effects of folate are warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".