The impact of IL‐1 deficiency in colitis‐mediated colon cancer
Bibliographic record
Abstract
Inflammatory bowel diseases (IBD) predispose individuals to colon cancer. IL‐1, elevated during IBD, is implicated in cancer development in several models. Our objective was to determine the contribution of IL‐1 to carcinogenesis in a mouse model of colitis‐mediated colon cancer. Wildtype (WT), IL‐1R1 −/− and caspase‐1 −/− mice (n=6–12) were treated with azoxymethane (10 mg/kg) followed by 3 cycles of 3% dextran sulphate sodium. Unlike WT, IL‐1R1 −/− and caspase‐1 −/− mice had significant mortality (40–50%) after the second and third cycles, although inflammation severity in the mid‐colon did not differ between strains. All strains showed non‐invasive colon carcinoma. Cancer incidence did not differ significantly between strains (WT 60%, IL‐1R1 −/− 100% and caspase‐1 −/− 100%), however IL‐1R1 −/− mice had a higher tumor multiplicity compared to WT and caspase‐1 −/− mice (p<0.05). In conclusion, IL‐1R1 −/− and caspase‐1 −/− mice are more susceptible to chronic inflammation, despite histological inflammation scores that are similar to WT. Although cancer incidence did not differ between strains, the higher tumor number in IL‐1R1 −/− mice suggests a protective role for IL‐1 in this model. Funded by Crohn's and Colitis Foundation of Canada
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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 | 0.001 | 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".