Mycobacterium tuberculosis resisters despite HIV exhibit activated T cells and macrophages in their pulmonary alveoli
Bibliographic record
Abstract
Abstract To understand natural resistance to Mycobacterium tuberculosis (Mtb) infection, we studied people living with HIV (PLWH) in an area of high Mtb transmission. Given that alveolar leukocytes may contribute to this resistance, we performed single cell RNA-sequencing of bronchoalveolar lavage cells, unstimulated or ex vivo stimulated with Mtb. We obtained high quality cells for 7 participants who were TST & IGRA positive (called LTBI) and 6 who were persistently TST & IGRA negative (called resisters). Alveolar macrophages (AM) from resisters displayed more of an M1 phenotype relative to LTBI AM at baseline. Alveolar lymphocytosis (10%-60%) was exhibited by 5/6 resisters, resulting in higher numbers of CD4+ and CD8+ IFNG-expressing cells at baseline and upon Mtb challenge than LTBI samples. Mycobactericidal granulysin was expressed almost exclusively by a cluster of CD8+ T cells that co-expressed granzyme B, perforin and NK cell receptors. For resisters, these poly-cytotoxic T cells over-represented activating NK cell receptors and were present at 15-fold higher numbers in alveoli compared to LTBI. Altogether, our results showed that alveolar lymphocytosis, with increased numbers of alveolar IFNG-expressing cells and CD8+ poly-cytotoxic T cells, as well as activated AM were strongly associated with protection from persistent Mtb infection in PLWH.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".