A broad-spectrum pneumococcal vaccine induces mucosal immunity and protects against lethal <i>Streptococcus pneumoniae</i> challenge
Bibliographic record
Abstract
Pneumococcal disease is a major threat to public health globally, impacting individuals across all age groups, particularly infants and elderly individuals.The use of current vaccines has led to unintended consequences, including serotype replacement, leading to a need for a new approach to combat pneumococcal disease.A promising solution is the development of a broad-spectrum pneumococcal vaccine.In this study, we present the development of a broadspectrum protein-based pneumococcal vaccine that contains three pneumococcal virulence factors: rlipo-PsaA (lipidated form), rPspAC (truncated form), and rPspCC (truncated form).Intranasal immunization with rlipo-PsaA, rPspAC, and rPspCC (LAAC) resulted in significantly higher IgG titres than those induced by administration of nonlipidated rPsaA, rPspAC, and rPspCC (AAC).Furthermore, LAAC immunization induced the production of higher IgA titres in vaginal washes, feces, and sera in mice, indicating that LAAC can induce systemic mucosal immunity.In addition, administration of LAAC also induced Th1/Th17-biased immune responses and promoted opsonic phagocytosis of Streptococcus pneumoniae strains of various serotypes, implying that the immunogenicity of LAAC immunization provides a protective effect against pneumococcal infection.Importantly, challenge data showed that the LAACimmunized mice had a reduced bacterial load not only for several serotypes of the 13-valent conjugate pneumococcal vaccine (PCV13) but also for selected non-PCV13 serotypes.Consistently, LAAC immunization increased the survival rate of mice after bacterial challenge with both PCV13 and non-PCV13 serotypes.In conclusion, our protein-based pneumococcal vaccine provides protective effects against a broad spectrum of Streptococcus pneumoniae serotypes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".