HBHA-Induced Polycytotoxic CD4+ T Lymphocytes Are Associated with the Control of <i>Mycobacterium tuberculosis</i> Infection in Humans
Bibliographic record
Abstract
Abstract Heparin-binding hemagglutinin (HBHA), a surface protein of Mycobacterium tuberculosis, is an attractive vaccine candidate and marker of protective immunity against tuberculosis, although the mechanisms underlying this protective immunity are not fully understood. Comparisons of the immune responses of latently M. tuberculosis–infected (LTBI) subjects to those of patients with active tuberculosis (aTB) may help to identify surrogate markers of protection, as LTBI subjects are most often lifelong protected against the disease. HBHA was shown to induce strong Th1 responses and cytotoxic CD8+ responses in LTBI subjects, but additional mechanisms of control of M. tuberculosis infection remain to be identified. In this study, using HBHA-induced blast formation as a readout of specific T lymphocyte activation, we report the presence in M. tuberculosis–infected subjects of HBHA-induced CD4+ T cell blasts that degranulate, as measured by surface capture of CD107a. This suggests the induction by HBHA of a CD4+ T cell subset with cytolytic function, and as nearly half of these cells also contained IFN-γ, they had both Th1 and cytotoxic characteristics. We further identified a CD4+ T lymphocyte subset producing IFN-γ together with a combination of mediators of cytotoxicity, i.e., perforin, granzymes, and granulysin, and we called them polycytotoxic CD4+ T lymphocytes. Interestingly, whereas purified protein derivative induced such cells in both LTBI subjects and patients with aTB, HBHA-specific polycytotoxic CD4+ T lymphocytes were detected in LTBI subjects and not in patients with pulmonary aTB. To our knowledge, we thus identified a new HBHA-induced CD4+ T cell subset that may contribute to the control of M. tuberculosis infection.
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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".