Mutagenicity of folic acid deficiency and supplementation is tissue-specific and results in distinct mutation profiles
Bibliographic record
Abstract
Abstract Cancer incidence varies by tissue due to differences in environmental risk factor exposure, gene variant inheritance, and lifetime number of stem cell divisions in a tissue. Folate deficiency is associated with increased risk for colorectal cancer (CRC) and acute lymphocytic leukemia. Conversely, high folic acid (FA) intake has been associated with higher CRC risk. However, the mutagenic potential of FA intake in different tissues has not been characterized. Here we quantified mutations in folate-susceptible somatic tissues, namely bone marrow and colon, from the same MutaMouse mice and determined the FA-induced mutation profiles of both tissues using next generation sequencing. FA-induced mutagenesis was tissue- and dose-specific: FA deficiency increased mutant frequency (MF) in bone marrow while FA supplementation increased MF in colon. Analyses of mutation profiles suggested that FA interacted with mutagenic mechanisms that are unique to each tissue. These data illuminate potential mechanisms underpinning differences in susceptibility to FA-related cancers.
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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 | 0.001 | 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".