<i>Helicobacter pylori</i>Disrupts STAT1-Mediated Gamma Interferon-Induced Signal Transduction in Epithelial Cells
Bibliographic record
Abstract
Infection with Helicobacter pylori is chronic despite a vigorous mucosal immune response characterized by gastric T-helper type 1 cell expansion and gamma interferon (IFN-gamma) production. IFN-gamma signals by activation and nuclear translocation of signal transducer and activator of transcription 1 (STAT1); however, the effect of H. pylori infection on IFN-gamma-STAT1 signaling is unknown. We infected human gastric (MKN45 and AGS) and laryngeal (HEp-2) epithelial cell lines with type 1 and type 2 H. pylori strains and then stimulated them with IFN-gamma. Western blotting of whole-cell protein extracts revealed that infection with live, but not heat-killed, H. pylori time-dependently decreased IFN-gamma-induced STAT1 tyrosine phosphorylation. Electrophoretic mobility shift assay of nuclear protein extracts demonstrated that H. pylori infection reduced IFN-gamma-induced STAT1 DNA binding. STAT1 was unable to translocate from the cytoplasm to the nucleus in H. pylori-infected HEp-2 cells examined by immunofluorescence, and reverse transcription-PCR showed that IFN-gamma-induced interferon regulatory factor 1 expression was inhibited. These effects were independent of the cagA, cagE, and VacA status of the infecting H. pylori strain. Furthermore, neither H. pylori culture supernatants nor conditioned medium from H. pylori-infected MKN45 cells inhibited IFN-gamma-induced STAT1 tyrosine phosphorylation, suggesting that inhibition is independent of a soluble epithelial or bacterial factor but is dependent on bacterial contact with epithelial cells. H. pylori disruption of IFN-gamma-STAT1 signaling in epithelial cells may represent a mechanism by which the bacterium modifies mucosal immune responses to promote its survival in the human host.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".