Relationship Between Helicobacter pylori IgG Seroprevalence and the Immune Response to Poliovirus Vaccine Among School-Age Children From a Population With Near-Universal Immunity Level
Bibliographic record
Abstract
Objectives To examine the association between Helicobacter pylori seroprevalence and serum pepsinogens (PGs) as markers of gastric inflammation), with high neutralizing antibody titers to poliovirus type 1 and 3 vaccine strains among children age 3–4 years, subsequent to sub-clinical infection acquired during a wild-type poliovirus type 1 outbreak in Israel. Methods A serosurvey was conducted among 336 children aged 5–17 years who were vaccinated with both inactivated polio vaccine and oral polio vaccines. H. pylori serum IgG antibodies and PG concentrations were measured using ELISA. Neutralizing antibodies to poliovirus vaccine strains were measured and children with a titer ≥1:8 were considered immune. High-level immunity was defined as having a serum NA titer >1:2048. Propensity score inverse weighting was used to account for confounders. Results Neutralizing antibodies titers ≥1:8 to poliovirus type 1 and 3 vaccine strains were found in 99.4 and 98.2% of the children, respectively. An inverse association was found between H. pylori seropositivity accompanied by PGI:PGII ratio ≤6.5 (marker of gastric inflammation) and high-level immunity to poliovirus type 1: OR 0.39 (95% CI 0.68–0.91), p = 0.027. The association between H. pylori seropositivity of CagA virulent phenotype and polio high immunity was not significant. The association between H. pylori seropositivity and high neutralizing antibodies to type 3 poliovirus was of low magnitude and not significant. Conclusions H. pylori seroprevalence accompanied by evidence of gastric inflammation was inversely correlated with high titers of neutralizing antibodies to poliovirus in children from a population with near universal polio immunity.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".