The phenotypic distribution and functional profile of tuberculin‐specific CD4 T‐cells characterizes different stages of TB infection
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Recent publications have suggested that altered proportions of functional CD4 T-cell subsets correlate with active pulmonary TB. Also, CD27-expression on tuberculin-activated IFN-γ(+) CD4 T-cells is known to differ significantly between patients with active pulmonary TB and healthy TB-unexposed BCG vaccinees. Here, we explore links between CD4 T-cell phenotype, multiple functional subsets, and control of TB. METHODS: We examined ex-vivo overnight tuberculin activated CD4 T-cells in regards to CD27-expression and the activation markers, CD154 upregulation, IFN-γ, TNF-α, IL-2, and degranulation in 44 individuals, including cases of clinically active pulmonary TB, and hospital staff with prolonged TB exposure, some of whom had latent TB. RESULTS: Active pulmonary TB generally showed an excess of TNF-α(+) subsets over IFN-γ(+) subsets, paralleled by decreased CD27 expression on activated IFN-γ(+) or CD154(+) CD4 T-cells. The single subset distinguishing best between active pulmonary TB and high TB exposure was CD154(+) /TNF-α(+) / IFN-γ(-) /IL-2(-) /degranulation(-) (AUROC 0.90). The ratio between the frequencies of TNF-α(+) /IFN-γ(+) CD4 T-cells was an effective alternative parameter (AUROC 0.87). CONCLUSIONS: Functional subsets and phenotype of tuberculin induced CD4 T-cells differ between stages of TB infection. Predominance of TNF-α(+) CD4 T-cells in active infection suggests an increased effort of the immune system to contain disease.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it