Intranasal Immunization with Nontypeable Haemophilus influenzae Outer Membrane Vesicles Induces Cross-Protective Immunity in Mice
Bibliographic record
Abstract
Haemophilus influenzae is a Gram-negative human-restricted bacterium that can act as a commensal and a pathogen of the respiratory tract. Especially nontypeable H. influenzae (NTHi) is a major threat to public health and is responsible for several infectious diseases in humans, such as pneumonia, sinusitis, and otitis media. Additionally, NTHi strains are highly associated with exacerbations in patients suffering from chronic obstructive pulmonary disease. Currently, there is no licensed vaccine against NTHi commercially available. Thus, this study investigated the utilization of outer membrane vesicles (OMVs) as a potential vaccine candidate against NTHi infections. We analyzed the immunogenic and protective properties of OMVs derived from various NTHi strains by means of nasopharyngeal immunization and colonization studies with BALB/c mice. The results presented herein demonstrate that an intranasal immunization with NTHi OMVs results in a robust and complex humoral and mucosal immune response. Immunoprecipitation revealed the most important immunogenic proteins, such as the heme utilization protein, protective surface antigen D15, heme binding protein A, and the outer membrane proteins P1, P2, P5 and P6. The induced immune response conferred not only protection against colonization with a homologous NTHi strain, which served as an OMV donor for the immunization mixtures, but also against a heterologous NTHi strain, whose OMVs were not part of the immunization mixtures. These findings indicate that OMVs derived from NTHi strains have a high potential to act as a vaccine against NTHi infections.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".