<i>Helicobacter pylori</i> and <i>Campylobacter rectus</i> share a common antigen
Bibliographic record
Abstract
AIM: The aim of this study was to investigate the presence of antigens with immunological cross-reactivity in periodontopathogenic bacteria and Helicobacter pylori, the pathogen associated with gastritis and peptic ulcers in human. MATERIALS AND METHODS/RESULTS: Among the putative periodontopathogens tested (Actinobacillus actinomycetemcomitans, Campylobacter rectus, Fusobacterium nucleatum, Porphyromonas gingivalis, Prevotella intermedia and Treponema denticola), cross-reactive bands were only detected in C. rectus by SDS-PAGE/Western immunoblotting analysis using a polyclonal antibody directed to H. pylori cells. One of these cross-reactive antigens, a 64-kDa band antigen, also reacted with a monoclonal antibody directed to the human heat shock protein (HSP) 60. The N-terminal amino acid sequence of this C. rectus protein revealed a high degree of homology with corresponding regions of other HSPs belonging to the HSP60 family, indicating that the 64-kDa antigen was a GroEL protein. The nucleotide sequence of the C. rectus GroEL protein coded for a 547 amino acid protein with a predicted size of 57.8 kDa. Comparison of the alignment of the deduced amino acid sequence of the GroEL protein of C. rectus with that of H. pylori showed a high degree of similarity throughout its length (76.8%). GroEL protein from C. rectus possessed the ability to stimulate production of IL-6 by a confluent monolayer of human gingival epithelial cells and was cytotoxic when used at a high concentration. CONCLUSIONS: This study reveals an immunological relationship between H. pylori and C. rectus, and clearly indicates that one of the shared antigens is a GroEL protein possessing a biological activity that might play a role in the initiation and progression of periodontal disease.
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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) | 0.002 | 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".