Studies of methionine cycle intermediates (SAM, SAH), DNA methylation and the impact of folate deficiency on tumor numbers in Min mice
Bibliographic record
Abstract
Several epidemiological studies have suggested a modulatory effect of dietary folate intake on the risk of colorectal cancer. The molecular basis for this inverse association is not clearly understood, but may involve alterations in DNA methylation. In this study, we examined the levels of methylation intermediates [S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH)] and of global DNA methylation in the pre-neoplastic small intestine of Min (multiple intestinal neoplasia) mice. We also studied the effect of folate/choline deficiency on these parameters and on tumor multiplicity in this animal model. In folate-adequate Min mice, we identified positive linear correlations between SAM or SAH and tumor numbers (R(2) = 0.38, P < 0.005; R(2) = 0.26, P = 0.025, respectively). A positive correlation between global DNA hypomethylation and tumor multiplicity was also observed (R(2) = 0.29, P = 0.014). These three biochemical determinants (SAM, SAH and DNA hypomethylation) may, therefore, serve as early markers of cell transformation. Folate/choline deficiency, however, did not produce a consistent effect on tumor numbers in three separate experiments. As an increase in tumor numbers was observed only in folate- and choline-deficient mice with low levels of SAM and DNA hypomethylation, the modulatory role of folate may be dependent on the transformation state of the cell.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".