Epidermal growth factor receptor inhibits colitis-associated cancer in mice
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) is a chronic illness caused by complex interactions between genetic and environmental factors that propagate inflammation and damage to the gastrointestinal epithelium. This state of chronic inflammation increases the risk for development of colitis-associated cancer in IBD patients. Thus, the development of targeted therapeutics that can disrupt the cycle of inflammation and epithelial injury is highly attractive. However, such biological therapies, including those targeting epidermal growth factor receptor pathways, pose a risk of increasing cancer rates. Using two mouse models of colitis-associated cancer, we found that epidermal growth factor receptor inactivation accelerated the incidence and progression of colorectal tumors. By modulating inflammation and epithelial regeneration, epidermal growth factor receptor optimized the response to chronic inflammation and limited subsequent tumorigenesis. These findings provide important insights into the pathogenesis of colitis-associated cancer and suggest that epidermal growth factor-based therapies for IBD may reduce long-term cancer risk.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".