Adjuvant-dependent impacts on vaccine-induced humoral responses and protection in preclinical models of nasal and genital colonization by pathogenic Neisseria
Bibliographic record
Abstract
Neisseria gonorrhoeae, which causes the sexually transmitted infection gonorrhea and N. meningitidis, a leading cause of bacterial meningitis and septicemia, are closely related human-restricted pathogens that inhabit distinct primary mucosal niches. While successful vaccines against invasive meningococcal disease have been available for decades, the rapid rise in antibiotic resistance has led to an urgent need to develop an effective gonococcal vaccine. Several surface antigens are shared among these two pathogens, making cross-species protection an exciting prospect. However, the type of vaccine-mediated immune response required to achieve protection against respiratory versus genital infection remains ill defined. In this study, we utilize well established mouse models of female lower genital tract colonization by N. gonorrhoeae and upper respiratory tract colonization by N. meningitidis to examine the performance of transferrin binding protein B (TbpB) vaccines formulated with immunologically distinct vaccine adjuvants. We demonstrate that vaccine-mediated protection is influenced by the choice of adjuvant, with Th1/2-balanced adjuvants performing optimally against N. gonorrhoeae, and both Th1/2-balanced and Th2-skewing adjuvants leading to a significant reduction in N. meningitidis burden. We further establish a lack of correlation between protection status and the humoral response or bactericidal titre. Combined, this work provides supports the feasibility for a single vaccine formulation to achieve pan-neisserial coverage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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".