Novel mechanisms through which acute C. jejuni enteritis may exacerbate intestinal inflammation in the intestines of patients with IBD.
Bibliographic record
Abstract
Recent epidemiological analyses indicate that acute bacterial enteritis with C. jejuni incites or exacerbates intestinal inflammatory injury in patients with IBD, via mechanisms that remain obscure (1-3). AIM: To assess how interactions between C. jejuni, the host intestinal epithelium, and non-invasive resident bacteria may contribute to pathogenesis in IBD. Experiments characterized inflammatory gene responses, transepithelial permeability, bacterial translocation, TLR9 signaling, and intestinal inflammation in complementary C. jejuni challenge models of a novel ex vivo human tissue biopsy system, human enterocytes (T84), and mice pre-treated with low levels of DSS. Biopsy samples, infected or not (6h), were collected in RNAlater, and processed for RT-PCR arrays (LUMINEX). C. jejuni-infected mice were tested for bacterial translocation, and confluent T84 monolayers were assessed for internalization of non-invasive E. coli HB101 using differential centrifugation extracts labeled for lipid raft caveolin. T84 monolayers were also assessed for permeability, RT-PCR for TLR2 and TLR9, and tight junctional responses to polar TLR9 agonist (ODN). In an attempt to reproduce exacerbation of inflammation by C. jejuni in a susceptible host, C57bl6 Mice were infected, or not (control), with C. jejuni (81-176) for 7 days, and then given oral DSS 2% daily for another 12 days, before assessment of intestinal inflammation and Th17 cytokines (IL-25 and IL-17).
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".