Toll-like receptor 2 plays a critical role in maintaining mucosal integrity during Citrobacter rodentium-induced colitis
Bibliographic record
Abstract
Inflammatory bowel diseases and infectious gastroenteritis likely occur when the integrity of intestinal barriers is disrupted allowing luminal bacterial products to cross into the intestinal mucosa, stimulating immune cells and triggering inflammation. While specific Toll-like receptors (TLR) are involved in the generation of inflammatory responses against enteric bacteria, their contributions to the maintenance of intestinal mucosal integrity are less clear. These studies investigated the role of TLR2 in a model of murine colitis induced by the bacterial pathogen Citrobacter rodentium. C. rodentium supernatants specifically activated TLR2 in vitro while infected TLR2-/- mice suffered a lethal colitis coincident with colonic mucosal ulcerations, bleeding and increased cell death but not increased pathogen burden. TLR2-/- mice suffered impaired epithelial barrier function mediated via zonula occludens (ZO)-1 in naïve mice and claudin-3 in infected mice, suggesting this could underlie their susceptibility. TLR2 deficiency was also associated with impaired production of IL-6 by bone marrow-derived macrophages and infected colons cultured ex vivo. As IL-6 has antiapoptotic and epithelial repair capabilities, its reduced expression could contribute to the impaired mucosal integrity. These studies report for the first time that TLR2 plays a critical role in maintaining intestinal mucosal integrity during infection by a bacterial pathogen.
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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 | 0.001 |
| 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".