Folate induced mutagenesis and identification of folate-specific mutation profiles in somatic cells
Bibliographic record
Abstract
Folate is an essential water soluble B-vitamin required for the de novo synthesis of purines and dTMP and the synthesis of methionine.Disruption of any of the three folatedependent biosynthetic pathways has been shown to have serious implications in a cell's survival and an individual's disease risk.Folate, generally folate deficiency, has been associated with colorectal cancer (CRC) and acute lymphocytic leukemia (ALL) in epidemiological studies.However, CRC risk has also been associated with high FA intake.Previous studies have shown that FA deficiency induces higher mutant frequency (MF) in bone marrow in addition to increasing chromosomal instability in RBC.Here, we used the MutaMouse model to determine the mutagenic potential of dietary FA in the colon, and to determine if there is a tissue-and diet-specific effect induced by FA intake in colon and bone marrow.Male mice were fed experimental FA defined diets: deficient ( 0mg/kg), understanding, supporting and for embracing my uniqueness and culture ;) .Thank you, Dr. Alex Wong, for all your teachings and being my first formal introduction into programming.You and Dr. MacFarlane are not only two exemplary scientists but also individuals and parents.Also, a special
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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 | 0.001 |
| 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 | 0.001 |
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".