Molecular mechanisms in colitis-associated colorectal cancer
Bibliographic record
Abstract
Sustained chronic inflammation of the large intestine leads to tissue damage and repair, which is associated with an increased incidence of colitis-associated colorectal cancer (CAC). The genetic makeup of CAC is somewhat similar to sporadic colorectal carcinoma (sCRC), but there are differences in the sequence and timing of alterations in the carcinogenesis process. Several models have been developed to explain the development of CAC, particularly the "field cancerization" model, which proposes that chronic inflammation accelerates mutagenesis and selects for the clonal expansion of phenotypically normal, pro-tumorigenic cells. In contrast, the "Big Bang" model posits that tumorigenic clones with multiple driver gene mutations emerge spontaneously. The details of CAC tumorigenesis-and how they differ from sCRC-are not yet fully understood. In this Review, we discuss recent genetic, epigenetic, and environmental findings related to CAC pathogenesis in the past five years, with a focus on unbiased, high-resolution genetic profiling of non-dysplastic field cancerization in the context of inflammatory bowel disease (IBD).
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".