Single Mucosal, but Not Parenteral, Immunization with Recombinant Adenoviral-Based Vaccine Provides Potent Protection from Pulmonary Tuberculosis
Bibliographic record
Abstract
Bacillus Calmette-Guerin (BCG) vaccine has failed to control the global tuberculosis (TB) epidemic, and there is a lack of safe and effective mucosal vaccines capable of potent protection against pulmonary TB. A recombinant replication-deficient adenoviral-based vaccine expressing an immunogenic Mycobacterium tuberculosis Ag Ag85A (AdAg85A) was engineered and evaluated for its potential to be used as a respiratory mucosal TB vaccine in a murine model of pulmonary TB. A single intranasal, but not i.m., immunization with AdAg85A provided potent protection against airway Mycobacterium tuberculosis challenge at an improved level over that by cutaneous BCG vaccination. Systemic priming with an Ag85A DNA vaccine and mucosal boosting with AdAg85A conferred a further enhanced immune protection which was remarkably better than BCG vaccination. Such superior protection triggered by AdAg85 mucosal immunization was correlated with much greater retention of Ag-specific T cells, particularly CD4 T cells, in the lung and was shown to be mediated by both CD4 and CD8 T cells. Thus, adenoviral TB vaccine represents a promising novel vaccine platform capable of potent mucosal immune protection against TB. Our study also lends strong evidence that respiratory mucosal vaccination is critically advantageous over systemic routes of vaccination against TB.
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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) | 0.000 | 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 | 0.000 |
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".