Pulmonary mucosal dendritic cells in T-cell activation: implications for TB therapy
Bibliographic record
Abstract
Mycobacterium tuberculosis, the causative agent of pulmonary TB, causes chronic intracellular infection of lung-resident antigen-presenting cells, including macrophages and dendritic cells (DCs). Life-long bacterial control requires robust T-cell immune responses. Lung DCs are critical for initiating and co-ordinating adaptive immune responses against TB. The recent description of previously uncharacterized DC subsets has prompted the re-examination of lung DCs and their role in priming antimycobacterial T-cell responses. While there is some data on these new DCs in their naive state, very little is known about how these DCs respond to pulmonary mycobacterial infection. In this article, we attempt to identify the major antigen-presenting cell subsets that may be critical to lymph node homing, T-cell priming and controlling mycobacterial infection. We further examine the areas of DC heterogeneity that may relate to differential susceptibility between mouse strains. Furthermore, we discuss how DCs may be manipulated and exploited as a cell-based prophylactic TB vaccine and the prospect of using this strategy for post-M. tuberculosis exposure settings.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".