Helicobacter pylori induces MLCK‐ dependent adherens junction disruption in non‐tumorigenic epithelial monolayers
Bibliographic record
Abstract
H. pylori (Hp) infects half of the human population and can cause gastritis, gastroduodenal ulcers, and gastric cancer. The ability of Hp to alter epithelial cell‐cell adhesion may influence the clinical outcome of infection. Disruption of adherens junction (AJ) proteins E‐cadherin and β–catenin have been implicated in carcinogenesis. The effects of Hp on the AJ and whether such changes may involve a known regulator of epithelial barrier function, myosin‐light chain kinase (MLCK), are unclear. Aim: The aim of this study was to characterize the effects of Hp on the AJ in non‐tumorigenic epithelial cell (SCBN) monolayers, and to examine the role of MLCK in these effects. Results: Western blotting revealed increased levels of phosphorylated myosin light chain (MLC) in cells challenged with Hp strain SS1 while myosin light chain‐2 levels remained unchanged. Immunocytochemistry demonstrated disruption of membranous E‐cadherin and redistribution of β–catenin in Hp infected monolayers, but not in controls. Immunoblotting revealed a time‐dependent, Hp‐induced decrease in E‐cadherin expression. Pre‐treatment with a selective MLCK inhibitor (ML‐9) prevented these effects. Conclusion: Hp‐induced phosphorylation of epithelial MLC is associated with AJ disruptions in non‐tumorigenic epithelial cells. These alterations of E‐cadherin and β–catenin are regulated, at least in part, by MLCK
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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".