NOD2 modulates immune tolerance via the GM-CSF–dependent generation of CD103 <sup>+</sup> dendritic cells
Bibliographic record
Abstract
Four decades ago, it was identified that muramyl dipeptide (MDP), a peptidoglycan-derived bacterial cell wall component, could display immunosuppressive functions in animals through mechanisms that remain unexplored. We sought to revisit these pioneering observations because mutations in NOD2 , the gene encoding the host sensor of MDP, are associated with increased risk of developing the inflammatory bowel disease Crohn’s disease, thus suggesting that the loss of the immunomodulatory functions of NOD2 could contribute to the development of inflammatory disease. Here, we demonstrate that intraperitoneal (i.p.) administration of MDP triggered regulatory T cells and the accumulation of a population of tolerogenic CD103 + dendritic cells (DCs) in the spleen. This was found to occur not through direct sensing of MDP by DCs themselves, but rather via the production of the cytokine GM-CSF, another factor with an established regulatory role in Crohn’s disease pathogenesis. Moreover, we demonstrate that populations of CD103-expressing DCs in the gut lamina propria are enhanced by the activation of NOD2, indicating that MDP sensing plays a critical role in shaping the immune response to intestinal antigens by promoting a tolerogenic environment via manipulation of DC populations.
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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 | 0.000 |
| 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".