Exploitation of Neisseria meningitidis Group B OMV Vaccines Against N. gonorrhoeae to Inform the Development and Deployment of Effective Gonorrhea Vaccines
Bibliographic record
Abstract
Have potential clues to an effective gonorrhea vaccine been lurking in international disease surveillance data for decades? While no clinically effective vaccines against gonorrhea have been developed we present direct and indirect evidence that a vaccine is not only possible, but may already exist. Experience from Cuba, New Zealand, and Canada suggest that vaccines containing Group B Neisseria meningitides outer membrane vesicles developed to control type-specific meningococcal disease may also prevent a significant proportion of gonorrhea. The mechanisms for this phenomenon have not yet been elucidated but we present some strategies for unravelling potential cross protective antigens and effector immune responses by exploiting stored sera from clinical trials and individuals primed with a meningococcal group B outer membrane vesicle vaccine (MeNZB). Elucidating these will contribute to the ongoing development of high efficacy vaccine options for gonorrhea. While the vaccine used in New Zealand, where the strongest empirical evidence has been gathered, is no longer available, the outer membrane vesicle has been included in the multi component recombinant meningococcal vaccine 4CMenB (Bexsero) which is now licenced and in used in numerous countries. Several lines of evidence suggest it has the potential to affect gonorrhea prevalence. A vaccine to control gonorrhea does not need to be perfect and modelling supports that even a moderately efficacious vaccine could make a significant impact in disease prevalence. How might we use an off the shelf vaccine to reduce the burden of gonorrhea? What are the some of the potential societal barriers in a world where vaccine hesitancy is growing? We summarise the evidence and consider some of the remaining questions.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".