Interleukin-1 (IL-1) Signaling in Intestinal Stromal Cells Controls KC/CXCL1 Secretion, Which Correlates with Recruitment of IL-22-Secreting Neutrophils at Early Stages of Citrobacter rodentium Infection
Bibliographic record
Abstract
Attaching and effacing pathogens, including enterohemorrhagic Escherichia coli in humans and Citrobacter rodentium in mice, raise serious public health concerns. Here we demonstrate that interleukin-1 receptor (IL-1R) signaling is indispensable for protection against C. rodentium infection in mice. Four days after infection with C. rodentium, there were significantly fewer neutrophils (CD11b+ Ly6C+ Ly6G+) in the colons of IL-1R−/− mice than in wild-type mice. Levels of mRNA and protein of KC/CXCL1 were also significantly reduced in colon homogenates of infected IL-1R−/− mice relative to wild-type mice. Of note, infiltrated CD11b+ Ly6C+ Ly6G+ neutrophils were the main source of IL-22 secretion after C. rodentium infection. Interestingly, intestinal stromal cells isolated from IL-1R−/− mice secreted lower levels of KC/CXCL1 than stromal cells from wild-type mice during C. rodentium infection. Similar effects were found when mouse intestinal stromal cells and human nasal polyp stromal cells were treated with IL-1R antagonists (i.e., anakinra) in vitro. These results suggest that IL-1 signaling plays a pivotal role in activating mucosal stromal cells to secrete KC/CXCL1, which is essential for infiltration of IL-22-secreting neutrophils upon bacterial infection.
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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".