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Record W1644750267 · doi:10.1080/19490976.2015.1016691

Insights into<i>Campylobacter jejuni</i>colonization of the mammalian intestinal tract using a novel mouse model of infection

2015· review· en· W1644750267 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGut Microbes · 2015
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsChild and Family Research InstituteBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsCampylobacter jejuniBiologyMicrobiologyVirulencePathogenPathogenesisInnate immune systemImmune systemImmunologyGastrointestinal tractMucusBacteriaGeneGenetics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.109
GPT teacher head0.303
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it