The Cytosolic Microbial Receptor Nod2 Regulates Small Intestinal Crypt Damage and Epithelial Regeneration following T Cell–Induced Enteropathy
Bibliographic record
Abstract
Loss of function in the NOD2 gene is associated with a higher risk of developing Crohn's disease (CD). CD is characterized by activation of T cells and activated T cells are involved in mucosal inflammation and mucosal damage. We found that acute T cell activation with anti-CD3 mAb induced stronger small intestinal mucosal damage in NOD2(-/-) mice compared with wild-type mice. This enhanced mucosal damage was characterized by loss of crypt architecture, increased epithelial cell apoptosis, delayed epithelial regeneration and an accumulation of inflammatory cytokines and Th17 cells in the small intestine. Partial microbiota depletion with antibiotics did not decrease mucosal damage 1 d after anti-CD3 mAb injection, but it significantly reduced crypt damage and inflammatory cytokine secretion in NOD2(-/-) mice 3 d after anti-CD3 mAb injection, indicating that microbial sensing by Nod2 was important to control mucosal damage and epithelial regeneration after anti-CD3 mAb injection. To determine which cells play a key role in microbial sensing and regulation of mucosal damage, we engineered mice carrying a cell-specific deletion of Nod2 in villin and Lyz2-expressing cells. T cell activation did not worsen crypt damage in mice carrying either cell-specific deletion of Nod2 compared with wild-type mice. However, increased numbers of apoptotic epithelial cells and higher expression of TNF-α and IL-22 were observed in mice carrying a deletion of Nod2 in Lyz2-expressing cells. Taken together, our results demonstrate that microbial sensing by Nod2 is an important mechanism to regulate small intestinal mucosal damage following acute T cell activation.
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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 | 0.000 | 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".