Regulation of TB Vaccine-Induced Airway Luminal T Cells by Respiratory Exposure to Endotoxin
Bibliographic record
Abstract
Tuberculosis (TB) vaccine-induced airway luminal T cells (ALT) have recently been shown to be critical to host defense against pulmonary TB. However, the mechanisms that maintain memory ALT remain poorly understood. In particular, whether respiratory mucosal exposure to environmental agents such as endotoxin may regulate the size of vaccine-induced ALT population is still unclear. Using a murine model of respiratory genetic TB vaccination and respiratory LPS exposure, we have addressed this issue in the current study. We have found that single or repeated LPS exposure increases the number of antigen-specific ALT which are capable of robust secondary responses to pulmonary mycobacterial challenge. To investigate the potential mechanisms by which LPS exposure modulates the ALT population, we have examined the role of ALT proliferation and peripheral T cell recruitment. We have found that LPS exposure-increased ALT is not dependent on increased ALT proliferation as respiratory LPS exposure does not significantly increase the rate of proliferation of ALT. But rather, we find it to be dependent upon the recruitment of peripheral T cells into the airway lumen as blockade of peripheral T cell supplies markedly reduces the initially increased ALT. Thus, our data suggest that environmental exposure to airborne agents such as endotoxin has a profound modulatory effect on TB vaccine-elicited T cells within the respiratory tract. Our study provides a new, M.tb antigen-independent mechanism by which the respiratory mucosal anti-TB memory T cells may be maintained.
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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".