Mucosal immunity and novel tuberculosis vaccine strategies: route of immunisation-determined T-cell homing to restricted lung mucosal compartments
Bibliographic record
Abstract
Despite the use of bacille Calmette-Guérin (BCG) for almost a century, pulmonary tuberculosis (TB) continues to be a serious global health concern. Therefore, there has been a pressing need for the development of new booster vaccines to enhance existing BCG-induced immunity. Protection following mucosal intranasal immunisation with AdHu5Ag85A is associated with the localisation of antigen-specific T-cells to the lung airway. However, parenteral intramuscular immunisation is unable to provide protection despite the apparent presence of antigen-specific T-cells in the lung interstitium. Recent advances in intravascular staining have allowed us to reassess the previously established T-cell distribution profile and its relationship with the observed differential protection. Respiratory mucosal immunisation empowers T-cells to home to both the lung interstitium and the airway lumen, whereas intramuscular immunisation-activated T-cells are largely trapped within the pulmonary vasculature, unable to populate the lung interstitium and airway. Given the mounting evidence supporting the safety and enhanced efficacy of respiratory mucosal immunisation over the traditional parenteral immunisation route, a greater effort should be made to clinically develop respiratory mucosal-deliverable TB vaccines.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".