Regulation of RANTES Promoter Activation in Gastric Epithelial Cells Infected with<i>Helicobacter pylori</i>
Bibliographic record
Abstract
RANTES, a CC chemokine, plays an important role in the inflammatory response associated with Helicobacter pylori infection. However, the mechanism by which H. pylori induces RANTES expression in the gastric mucosa is unknown. We cocultured gastric epithelial cells with wild-type H. pylori, isogenic oipA mutants, cag pathogenicity island (PAI) mutants, or double knockout mutants. Reverse transcriptase PCR showed that RANTES mRNA was induced by H. pylori and that the expression was both OipA and cag PAI dependent. Luciferase reporter gene assays and electrophoretic mobility shift assays showed that maximal H. pylori-induced RANTES gene transcription required the presence of the interferon-stimulated responsive element (ISRE), the cyclic AMP-responsive element (CRE), nuclear factor-interleukin 6 (NF-IL-6), and two NF-kappaB sites. OipA- and cag PAI-dependent pathways included NF-kappaB-->NF-kappaB/NF-IL-6/ISRE pathways, and cag PAI-dependent pathways additionally included Jun N-terminal kinase-->CRE/NF-kappaB pathways. The OipA-dependent pathways additionally included p38-->CRE/ISRE pathways. We confirmed the in vitro effects in vivo by examining RANTES mRNA levels in biopsy specimens from human gastric antral mucosa. RANTES mRNA levels in the antral mucosa were significantly higher for patients infected with cag PAI/OipA-positive H. pylori than for those infected with cag PAI/OipA-negative H. pylori or uninfected patients. The mucosal inflammatory response to H. pylori infection involves different signaling pathways for activation of the RANTES promoter, with both OipA and the cag PAI being required for full activation of the RANTES promoter.
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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 | 0.000 |
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".