Molecular pathogenesis of inflammatory bowel disease: Genotypes, phenotypes and personalized medicine
Bibliographic record
Abstract
Crohn's disease (CD) and ulcerative colitis (UC), also known as inflammatory bowel diseases (IBD), are characterized by chronic inflammation of the gastrointestinal tract. IBD is among the few complex diseases for which several genomic regions and specific genes have been identified and confirmed in multiple replication studies. We will review the different loci implicated in disease risk in the context of three proposed mechanisms leading to chronic inflammation of the gut mucosa: 1) deregulation of the innate immune response to enteric microflora or pathogens; 2) increased permeability across the epithelial barrier; and 3) defective regulation of the adaptive immune system. As our knowledge of genetic variation, analytical approaches and technology improves, additional genetic risk factors are expected to be identified. With the identification of novel risk variants, additional pathophysiological mechanisms are likely to emerge. The resulting discoveries will further our molecular understanding of IBD, potentially leading to improved disease classification and rational drug design. Moreover, these approaches and tools can be applied in the context of variable drug response with the goal of providing more personalized clinical management of patients with IBD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".