Vasoactive intestinal peptide ameliorates intestinal barrier disruption associated with <i>Citrobacter rodentium</i> -induced colitis
Bibliographic record
Abstract
Attaching and effacing bacterial pathogens attach to the apical surface of epithelial cells and disrupt epithelial barrier function, increasing permeability and allowing luminal contents access to the underlying milieu. Previous in vitro studies demonstrated that the neuropeptide vasoactive intestinal peptide (VIP) regulates epithelial paracellular permeability, and the high concentrations and close proximity of VIP-containing nerve fibers to intestinal epithelial cells would support such a function in vivo. The aim of this study was to examine whether VIP treatment modulated Citrobacter rodentium-induced disruption of intestinal barrier integrity and to identify potential mechanisms of action. Administration of VIP had no effect on bacterial attachment although histopathological scoring demonstrated a VIP-induced amelioration of colitis-induced epithelial damage compared with controls. VIP treatment prevented the infection-induced increase in mannitol flux a measure of paracellular permeability, resulting in levels similar to control mice, and immunohistochemical studies demonstrated that VIP prevented the translocation of tight junction proteins: zonula occludens-1, occludin, and claudin-3. Enteropathogenic Escherichia coli (EPEC) infection of Caco-2 monolayers confirmed a protective role for VIP on epithelial barrier function. VIP prevented EPEC-induced increase in long myosin light chain kinase (MLCK) expression and myosin light chain phosphorylation (p-MLC). Furthermore, MLCK inhibition significantly attenuated bacterial-induced epithelial damage both in vivo and in vitro. In conclusion, our results indicate that VIP protects the colonic epithelial barrier by minimizing bacterial-induced redistribution of tight junction proteins in part through actions on MLCK and MLC phosphorylation.
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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 | 0.000 |
| 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 | 0.001 | 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".