Insights into<i>Campylobacter jejuni</i>colonization of the mammalian intestinal tract using a novel mouse model of infection
Bibliographic record
Abstract
A lack of relevant disease models for Campylobacter jejuni has long been an obstacle to research into this common enteric pathogen. We recently published that mice deficient in Single IgG Interleukin-1 related receptor (SIGIRR), a repressor of MyD88-dependent innate immune signaling, were highly susceptible to enteric infection by murine bacterial pathogens. Subsequently, we successfully employed these mice as an animal model for the human pathogen C. jejuni and gained substantial new insights into infection by this pathogen. The infected mice developed significant intestinal inflammation, primarily via TLR4 stimulation. Furthermore, the resulting gastroenteritis was dependent on C. jejuni pathogenesis as bacterial strains suffering mutations in key virulence factors were attenuated in causing disease. The ability to infect SIGIRR-deficient mice with C. jejuni sheds new light onto how these bacteria colonize the mucus layer of the intestinal tract, invade epithelial cells, and raises new prospects for studying the virulence strategies and pathogenesis of C. jejuni.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".