<i>Campylobacter jejuni</i> Drives MyD88-Independent Interleukin-6 Secretion via Toll-Like Receptor 2
Bibliographic record
Abstract
Gastrointestinal disease caused by Campylobacter jejuni is characterized by localized inflammation and the destruction of the epithelial cell barrier that forms host innate protection against pathogens. This can lead to an imbalance in fluid transport across the gastrointestinal tract, resulting in severe diarrhea. The mechanisms of host cell receptor recognition of C. jejuni and downstream immune signaling pathways leading to this inflammatory disease, however, remain unclear. The aim of this study was to analyze the mechanisms involved in C. jejuni induction of the acute-phase inflammatory response regulator interleukin-6 (IL-6). Polarized intestinal epithelial Caco-2 monolayers responded to infections with Salmonella enterica serovar Typhimurium and eight isolates of C. jejuni by an increase in levels of expression and secretion of IL-6. No such IL-6 response, however, was produced upon infection with the human commensal organism Lactobacillus rhamnosus GG. The IL-6 signaling pathway was further characterized using short interfering RNA complexes to block gene expression. The inhibition of myeloid differentiation primary response protein 88 (MyD88) expression in this manner did not affect C. jejuni-induced IL-6 secretion, suggesting a MyD88-independent route to IL-6 signal transduction in C. jejuni-infected human epithelial cells. However, a significant reduction in levels of IL-6 was evident in the absence of Toll-like receptor 2 (TLR-2) expression, implying a requirement for TLR-2 in C. jejuni recognition. Caco-2 cells were also treated with heat-inactivated and purified membrane components of C. jejuni to isolate the factor responsible for triggering IL-6 signaling. The results demonstrate that C. jejuni surface polysaccharides induce IL-6 secretion from intestinal epithelial cells via TLR-2 in a MyD88-independent manner.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".