Epidermal Growth Factor Inhibits <i>Campylobacter jejuni</i> -Induced Claudin-4 Disruption, Loss of Epithelial Barrier Function, and <i>Escherichia coli</i> Translocation
Bibliographic record
Abstract
Campylobacter jejuni is a leading cause of acute bacterial enteritis in humans. Poultry serves as a major reservoir of C. jejuni and is thought to act as a principal vehicle of transmission to humans. Epidermal growth factor (EGF) is a small amino acid peptide that exerts a broad range of activities on the intestinal epithelium. The aims of this study were to determine the effect of EGF on C. jejuni intestinal colonization in newly hatched chicks and to characterize its effects on C. jejuni-induced intestinal epithelial barrier disruption. White Leghorn chicks were treated with EGF daily, starting 1 day prior to C. jejuni infection, and were compared to control and C. jejuni-infected, EGF-treated chicks. Infected chicks shed C. jejuni in their feces throughout the study period. C. jejuni colonized the small intestine and cecum, disseminated to extraintestinal organs, and caused jejunal villus atrophy. EGF reduced jejunal colonization and dissemination of C. jejuni to the liver and spleen. In EGF-treated C. jejuni-infected chicks, villus height was not significantly different from that in untreated C. jejuni-infected chicks or controls. In vitro, C. jejuni attached to and invaded intestinal epithelial cells, disrupted tight junctional claudin-4, and increased transepithelial permeability. C. jejuni also promoted the translocation of noninvasive Escherichia coli C25. These C. jejuni-induced epithelial abnormalities were abolished by pretreatment with EGF, and the effect was dependent upon activation of the EGF receptor. These findings highlight EGF's ability to alter colonization of C. jejuni in the intestinal tract and to protect against pathogen-induced barrier defects.
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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) | 0.001 | 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".