New Players in Immunity to Tuberculosis: The Host Microbiome, Lung Epithelium, and Innate Immune Cells
Bibliographic record
Abstract
Tuberculosis (TB) is a highly contagious infection and devastating chronic disease, causing 10.4 million new infections and 1.8 million deaths every year globally. Efforts to control and eradicate TB are hampered by the rapid emergence of drug resistance and limited efficacy of the only available vaccine, BCG. Immunological events in the airways and lungs are of major importance in determining whether exposure to Mycobacterium tuberculosis (Mtb) results in successful infection or protective immunity. Several studies have demonstrated that the host microbiota is in constant contact with the immune system, and thus continually directs the nature of immune responses occurring during new infections. However, little is known about its role in the eventual outcome of the mycobacterial infection. In this review, we highlight the changes in microbial composition in the respiratory tract and gut that have been linked to the alteration of immune responses, and to the risk, prevention and treatment of TB. Additionally, we summarize our current understanding of alveolar epithelial cells and the innate immune system, and their interaction with Mtb during early infection. Extensive studies are warranted to fully understand the all-inclusive role of the lung microbiota, its interaction with epithelium and innate immune responses and resulting adaptive immune responses, and in the pathogenesis and/or protection from Mtb infection. Novel interventions aimed at influencing the microbiota, the alveolar immune system and innate immunity will shape future strategies of prevention and treatment for 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".