Elevated Incidence of Polyp Formation in APCMin/+Msh2−/− Mice Is Independent of Nitric Oxide-Induced DNA Mutations
Bibliographic record
Abstract
Gut microbiota has been linked to a number of human diseases including colon cancer. However, the mechanism through which gut bacteria influence colon cancer development and progression remains unclear. Perturbation of the homeostasis between the host immune system and microbiota leads to inflammation and activation of macrophages which produce large amounts of nitric oxide that acts as a genotoxic effector molecule to suppress bacterial growth. However, nitric oxide also has genotoxic effects to host cells by producing mutations that can predispose to colon cancer development. The major DNA lesions caused by nitric oxide are 8oxoG and deamination of deoxycytosine bases. Cellular glycosylases that belong to the base excision repair pathway have been demonstrated to repair these mutations. Recent evidence suggests that the mismatch repair pathway (MMR) might also repair nitric oxide-induced DNA damage. Since deficiency in MMR predisposes to colon cancer, we hypothesized that MMR-deficient colon epithelial cells are incapable of repairing nitric-oxide induced genetic lesions that can promote colon cancer. Indeed, we found that the MMR pathway repairs nitric oxide-induced DNA mutations in cell lines. To test whether nitric oxide promotes colon cancer, we genetically ablated the inducible nitric oxide synthase (iNOS) or inhibited iNOS activity in the APC(Min/+)Msh2(-/-) mouse model of colon cancer. However, despite the fact that nitric oxide production was strongly reduced in the colon using both approaches, colon cancer incidence was not affected. These data show that nitric oxide and iNOS do not promote colon cancer in APC(Min/+)Msh2(-/-) mice.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".