<i>Campylobacter jejuni</i> ‐induced transcytosis of commensal <i>Escherichia coli</i> across enterocytes requires plasma membrane cholesterol
Bibliographic record
Abstract
Bacterial gastroenteritis has been implicated as a risk factor for the subsequent development of inflammatory bowel disease (IBD); however the mechanism by which this occurs is unknown. As there is compelling evidence that IBD is associated with an exaggerated immune response to commensal gut flora, we examined whether a common intestinal pathogen, Campylobacter jejuni , can induce translocation of commensal bacteria across enterocytes. Confluent, polarized enterocyte monolayers (T84) were inoculated with non‐invasive E. coli HB101 ± C. jejuni 81–176 and assayed for translocation and internalization of E. coli and epithelial permeability. Compared to the control treatment, C. jejuni induced a significant increase in E. coli translocation. This was associated with increased internalization of E. coli as determined by a gentamicin protection assay. There was no effect on epithelial permeability to a fluorescent dextran probe (3000 MW). Translocation of E. coli was prevented by treatment with the cholesterol‐disrupting drugs methyl‐â‐cyclodextrin plus lovastatin. Thus, C. jejuni may contribute to the pathogenesis of IBD by inducing translocation of non‐invasive commensal bacteria across the intestinal epithelium to the underlying mucosa via a transcellular process involving lipid‐rafts. Research supported by NSERC and the Crohn’s and Colitis Foundation of Canada.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".