Mycobacteria in Crohnʼs disease: A persistent hypothesis
Bibliographic record
Abstract
Efforts to explore a mycobacterial origin for Crohn's disease typically have involved an epidemiological approach, searching for Mycobacterium avium subsp. paratuberculosis in patient tissue. An alternative approach involves consideration of genetic and experimental data regarding host resistance to mycobacteria. From human and mycobacterial genetics, it is known that mycobacterial diseases depend on both pathogen and host factors and that tuberculosis and leprosy are effectively genetic diseases. The discovery of a number of Crohn's susceptibility genes, including NOD2/CARD15, demonstrates that Crohn's also is a complex genetic disease. Mutations in NOD2/CARD15 do not necessarily lead to Crohn's disease, so other mitigating factors, genetic and/or environmental, probably are required to produce illness. Recent work has shown that NOD2/CARD15 serves a role in bacterial sensing and activation of innate immune responses, providing a link between Crohn's genetics and an environmental factor, potentially a bacterial trigger. In this review, we discuss the current understanding of mycobacterial and Crohn's genetic susceptibility and review the evidence that NOD2/CARD15 may mediate host resistance to mycobacterial infection.
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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 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".