Prevention of Pneumococcal Disease in Mice Immunized with Conserved Surface-Accessible Proteins
Bibliographic record
Abstract
The development of a vaccine against Streptococcus pneumoniae has been complicated by the existence of at least 90 antigenically distinct capsular serotypes. Common protein-based vaccines could represent the best strategy to prevent pneumococcal infections, regardless of serotype. In the present study, the immunoscreening of an S. pneumoniae genomic library allowed the identification of a novel immune protein target, BVH-3. We demonstrate that immunization of mice with BVH-3 elicits protective immunity against experimental sepsis and pneumonia. Sequence analysis revealed that the bvh-3 gene is highly conserved within the species. Since the BVH-3 protein shows homology at its amino-terminal end with other pneumococcal proteins, it was of interest to determine if protection was due to the homologous or to the protein-specific regions. Immunoprotection studies using recombinant BVH-3 and BVH-3-related protein fragments as antigens allowed the localization of surface-exposed and protective epitopes at the protein-specific carboxyl termini, thus establishing that BVH-3 is distinct from other previously reported protective protein antigens. Immunization with a chimeric protein comprising the carboxyl-terminal regions of BVH-3 and of a BVH-3-related protein improved the protection by targeting two surface pneumococcal components. Thus, BVH-3 and the chimeric protein hold strong promise as vaccine components to control pneumococcal disease.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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".