A Large Portion of Meningococcal Antigen Typing System-Negative Meningococcal Strains from Spain Is Killed by Sera from Adolescents and Infants Immunized with 4CMenB
Bibliographic record
Abstract
A new vaccine (the 4CMenB 4-component protein vaccine [Bexsero], which includes PorA, factor H-binding protein [fHbp], neisserial heparin-binding antigen [NHBA], and Neisseria adhesin A [NadA]) against serogroup B meningococci has recently been approved for use in people older than age 2 months in Europe, Australia, and Canada. Preapproval clinical efficacy studies are not feasible for invasive meningococcal disease because its incidence is low/very low, and the serum bactericidal antibody (SBA) titer (or the human SBA [hSBA] titer when human complement is used in the assay) has been used as a surrogate marker of protection. However, the hSBA assay cannot be used on a large scale, and therefore, a meningococcal antigen typing system (MATS) was developed. MATS combines conventional PorA genotyping with an enzyme-linked immunosorbent assay (ELISA) that quantifies both the expression and the cross-reactivity of antigenic variants. The assay has been used to evaluate the potential of the 4CMenB meningococcal group B vaccine to cover group B strains in several countries. Some recent data suggest that MATS is a conservative predictor of strain coverage. We used pooled sera from adolescents and infants to test by the hSBA assay 10 meningococcal group B strains isolated in Spain that were negative for the 3 antigens (n = 9) or that had very low levels of the 3 antigens (n = 1) by MATS. We found that all strains were killed by sera from adolescents and that 5 of the 10 strains were also killed, although at a low titer, by sera from infants. Our data confirm that MATS underestimates vaccine coverage.
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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) | 0.001 | 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".