Essential role of Rip2 in the modulation of innate and adaptive immunity triggered by Nod1 and Nod2 ligands
Bibliographic record
Abstract
Muramyl peptides are the building blocks of bacterial peptidoglycan, and their biological functions in mammals have been extensively studied. In particular, muramyl peptides trigger inflammation, contribute to host defense against microbial infections, and modulate the adaptive immune response to antigens. These bacterial molecules are detected by nucleotide oligomerization domain 1 (Nod1) and Nod2, and recent evidence suggests that muramyl dipeptide also activates NLRP3 and NLRP1 inflammasomes. Here, we investigated the role of Rip2, the adaptor for Nod1- and Nod2-dependent signaling, in multiple aspects of the host response to muramyl peptides in vivo, such as inflammatory cytokine secretion, activation and recruitment of macrophages and neutrophils to the site of injection, systemic activation of myeloid, T and B cells in the spleen, adjuvanticity and capacity to polarize the adaptive response to ovalbumin. Our results demonstrate that Rip2 was crucial for all the biological functions studied. We also identified CD11c(int) CD11b(+) inflammatory dendritic cells as a major myeloid cell population responding to Nod stimulation in vivo. Together, our results highlight the importance of Rip2 for Nod-dependent induction of innate and adaptive immunity.
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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) | 0.001 | 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 | 0.001 |
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".