Mechanisms of Mucosal and Parenteral Tuberculosis Vaccinations: Adenoviral-Based Mucosal Immunization Preferentially Elicits Sustained Accumulation of Immune Protective CD4 and CD8 T Cells within the Airway Lumen
Bibliographic record
Abstract
The mechanisms underlying better immune protection by mucosal vaccination have remained poorly understood. In our current study we have investigated the mechanisms by which respiratory virus-mediated mucosal vaccination provides remarkably better immune protection against pulmonary tuberculosis than parenteral vaccination. A recombinant adenovirus-based tuberculosis (TB) vaccine expressing Mycobacterium tuberculosis Ag85A (AdAg85A) was administered either intranasally (i.n.) or i.m. to mice, and Ag-specific CD4 and CD8 T cell responses, including frequency, IFN-gamma production, and CTL, were examined in the spleen, lung interstitium, and airway lumen. Although i.m. immunization with AdAg85A led to activation of T cells, particularly CD8 T cells, in the spleen and, to a lesser extent, in the lung interstitium, it failed to elicit any T cell response in the airway lumen. In contrast, although i.n. immunization failed to effectively activate T cells in the spleen, it uniquely elicited higher numbers of Ag-specific CD4 and CD8 T cells in the airway lumen that were capable of IFN-gamma production and cytolytic activities, as assessed by an intratracheal in vivo CTL assay. These airway luminal T cells of i.n. immunized mice or splenic T cells of i.m. immunized mice, upon transfer locally to the lungs of naive SCID mice, conferred immune protection against M. tuberculosis challenge. Our study has demonstrated that the airway luminal T cell population plays an important role in immune protection against pulmonary TB, thus providing mechanistic insights into the superior immune protection conferred by respiratory mucosal TB vaccination.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".