Vasoactive intestinal peptide prevents PKCε-induced intestinal epithelial barrier disruption during EPEC infection
Bibliographic record
Abstract
We previously showed that vasoactive intestinal peptide (VIP) protects against bacterial pathogen-induced epithelial barrier disruption and colitis, although the mechanisms remain poorly defined. The aim of the current study was to identify cellular pathways of VIP-mediated protection with use of pharmacological inhibitors during enteropathogenic Escherichia coli (EPEC) infection of Caco-2 cell monolayers and during Citrobacter rodentium-induced colitis. EPEC-induced epithelial barrier disruption involved the PKC pathway but was independent of functional cAMP, Rho, and NF-κB pathways. VIP mediated its protective effects by inhibiting EPEC-induced PKC activity and increasing expression of the junctional protein claudin-4. Short-term treatment with TPA, which is known to activate PKC, was inhibited by VIP pretreatment, while PKC degradation via long-term treatment with TPA mimicked the protective actions of VIP. Immunostaining for specific PKC isotypes showed upregulated expression of PKCθ and PKCε during EPEC infection. Treatment with specific inhibitors revealed a critical role for PKCε in EPEC-induced barrier disruption. Furthermore, activation of PKCε and loss of barrier integrity correlated with claudin-4 degradation. In contrast, inhibition of PKCε by VIP pretreatment or the PKCε inhibitor maintained membrane-bound claudin-4 levels, along with barrier function. Finally, in vivo treatment with the PKCε inhibitor protected mice from C. rodentium-induced colitis. In conclusion, EPEC infection increases intracellular PKCε levels, leading to decreased claudin-4 levels and compromising epithelial barrier integrity. VIP inhibits PKCε activation, thereby attenuating EPEC-induced barrier disruption.
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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".