Nod1 and Nod2 Regulation of Inflammation in the <i>Salmonella</i> Colitis Model
Bibliographic record
Abstract
The pattern recognition molecules Nod1 and Nod2 play important roles in intestinal homeostasis; however, how these proteins impact on the development of inflammation during bacterial colitis has not been examined. In the streptomycin-treated mouse model of Salmonella colitis, we found that mice deficient for both Nod1 and Nod2 had attenuated inflammatory pathology, reduced levels of inflammatory cytokines, and increased colonization of the mucosal tissue. Nod1 and Nod2 from both hematopoietic and nonhematopoietic sources contributed to the pathology, and all phenotypes were recapitulated in mice deficient for the signaling adaptor protein Rip2. However, the influence of Rip2 was strictly dependent on infection conditions that favored expression of the Salmonella pathogenicity island 2 (SPI-2) type III secretion system (TTSS), as Rip2 was dispensable for inflammation when mice were infected with bacteria grown under conditions that promoted expression of the SPI-1 TTSS. Thus, Nod1 and Nod2 can modulate inflammation and mediate efficient clearance of bacteria from the mucosal tissue during Salmonella colitis, but their role is dependent on the expression of the SPI-2 TTSS.
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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 | 0.001 | 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".