Intranasal Mucosal Boosting with an Adenovirus-Vectored Vaccine Markedly Enhances the Protection of BCG-Primed Guinea Pigs against Pulmonary Tuberculosis
Bibliographic record
Abstract
BACKGROUND: Recombinant adenovirus-vectored (Ad) tuberculosis (TB) vaccine platform has demonstrated great potential to be used either as a stand-alone or a boost vaccine in murine models. However, Ad TB vaccine remains to be evaluated in a more relevant and sensitive guinea pig model of pulmonary TB. Many vaccine candidates shown to be effective in murine models have subsequently failed to pass the test in guinea pig models. METHODS AND FINDINGS: Specific pathogen-free guinea pigs were immunized with BCG, AdAg85A intranasally (i.n), AdAg85A intramuscularly (i.m), BCG boosted with AdAg85A i.n, BCG boosted with AdAg85A i.m, or treated only with saline. The animals were then infected by a low-dose aerosol of M. tuberculosis (M.tb). At the specified times, the animals were sacrificed and the levels of infection in the lung and spleen were assessed. In separate studies, the long-term disease outcome of infected animals was monitored until the termination of this study. Immunization with Ad vaccine alone had minimal beneficial effects. Immunization with BCG alone and BCG prime-Ad vaccine boost regimens significantly reduced the level of M.tb infection in the tissues to a similar extent. However, while BCG alone prolonged the survival of infected guinea pigs, the majority of BCG-immunized animals succumbed by 53 weeks post-M.tb challenge. In contrast, intranasal or intramuscular Ad vaccine boosting of BCG-primed animals markedly improved the survival rate with 60% of BCG/Ad i.n- and 40% of BCG/Ad i.m-immunized guinea pigs still surviving by 74 weeks post-aerosol challenge. CONCLUSIONS: Boosting, particularly via the intranasal mucosal route, with AdAg85A vaccine is able to significantly enhance the long-term survival of BCG-primed guinea pigs following pulmonary M.tb challenge. Our results thus support further evaluation of this viral-vectored TB vaccine in clinical trials.
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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 | 0.000 | 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 | 0.000 | 0.001 |
| 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".