Preventing Colitis-Associated Colon Cancer With Antioxidants: A Systematic Review
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) patients have an increased risk of developing colitis-associated colon cancer (CAC); however, the basis for inflammation-induced genetic damage requisite for neoplasia is unclear. Several studies have shown that IBD patients have signs of increased oxidative damage, which could be a result of genetic and environmental factors such as an excess in oxidant molecules released during chronic inflammation, mitochondrial dysfunction, a failure in antioxidant capacity, or oxidant promoting diets. It has been suggested that chronic oxidative environment in the intestine leads to the DNA lesions that precipitate colon carcinogenesis in IBD patients. Indeed, several preclinical and clinical studies show that different endogenous and exogenous antioxidant molecules are effective at reducing oxidation in the intestine. However, most clinical studies have focused on the short-term effects of antioxidants in IBD patients but not in CAC. This review article examines the role of oxidative DNA damage as a possible precipitating event in CAC in the context of chronic intestinal inflammation and the potential role of exogenous antioxidants to prevent these cancers.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".