Quantitative proteomics reveals differentially expressed proteins in murine preneoplastic intestine in a model of intestinal tumorigenesis induced by low dietary folate and MTHFR deficiency
Bibliographic record
Abstract
Colorectal cancer risk is increased when dietary folate intake is low, with or without a deficiency in methylenetetrahydrofolate reductase (MTHFR). We have observed that intestinal tumors are induced in mice fed low-folate diets, and that tumor incidence is increased when these mice also have MTHFR deficiency. This study was undertaken to identify differentially expressed proteins in conditions favoring initial steps of murine carcinogenesis in normal preneoplastic intestine. We compared the proteome of BALB/c normal intestine in Mthfr(+/+) mice fed control diets for 1 year (low susceptibility to tumorigenesis) with the proteome of Mthfr(+/-) animals fed low folate diets (higher tumor susceptibility). Our data suggest that the NuRD complex, KRAS-related proteins, the protein synthetic machinery, and fatty acid-related metabolic proteins are upregulated in the early stages of tumorigenesis. These proteins may serve as biomarkers or targets for colorectal cancer diagnosis or therapy.
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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 | 0.000 | 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) | 0.001 | 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".