Mycobacteria in Crohn’s disease: how innate immune deficiency may result in chronic inflammation
Bibliographic record
Abstract
Crohn's disease (CD) is often considered to be an autoimmune condition or, alternatively, an autoinflammatory condition, based on the observation of host-directed inflammatory processes. However, the underlying basis of this deleterious inflammatory response remains elusive. Recent findings from genetic and genomic studies have altered the perspective on the pathogenesis of CD, hinting at defects in innate immune sensing of intracellular bacteria and the handling of these organisms through autophagy. These findings are consistent with emerging data from immunological studies that point to a systemic immune deficiency in CD patients. Both sets of data (genetic predisposition and immunodeficiency) are consistent with the longstanding hypothesis that mycobacteria might be involved in the etiology of CD. In this article, we discuss the convergence of these three lines of investigation and highlight important knowledge gaps required in order to address the mycobacterial hypothesis with greater clarity. In the coming years, clinical immunological investigations should focus on defining the specificity of functional immune defects with regards to microbes and their associated ligands. Should CD result from a dysfunctional host-pathogen interaction, elucidation of the microbes that can exploit such defects to induce a chronic inflammatory disease is critical for the development of subsequent diagnostic assays and clinical interventions.
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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) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".