Crohn's disease adherent-invasive <i>Escherichia coli</i> colonize and induce strong gut inflammation in transgenic mice expressing human CEACAM
Bibliographic record
Abstract
Abnormal expression of CEACAM6 is observed at the apical surface of the ileal epithelium in Crohn's disease (CD) patients, and CD ileal lesions are colonized by pathogenic adherent-invasive Escherichia coli (AIEC). We investigated the ability of AIEC reference strain LF82 to colonize the intestinal mucosa and to induce inflammation in CEABAC10 transgenic mice expressing human CEACAMs. AIEC LF82 virulent bacteria, but not nonpathogenic E. coli K-12, were able to persist in the gut of CEABAC10 transgenic mice and to induce severe colitis with reduced survival rate, marked weight loss, increased rectal bleeding, presence of erosive lesions, mucosal inflammation, and increased proinflammatory cytokine expression. The colitis depended on type 1 pili expression by AIEC bacteria and on intestinal CEACAM expression because no sign of colitis was observed in transgenic mice infected with type 1 pili-negative LF82-Delta fimH isogenic mutant or in wild-type mice infected with AIEC LF82 bacteria. These findings strongly support the hypothesis that in CD patients having an abnormal intestinal expression of CEACAM6, AIEC bacteria via type 1 pili expression can colonize the intestinal mucosa and induce gut inflammation. Thus, targeting AIEC adhesion to gut mucosa represents a new strategy for clinicians to prevent and/or to treat ileal CD.
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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 | 0.001 |
| 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".