Interferon-γ and Interleukin-17 production from PPD-stimulated PBMCss of patients with pulmonary tuberculosis
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to evaluate Interferon (IFN)-γ and Interleukin(IL)-17 profiles in patients with different clinical presentations of pulmonary tuberculosis (TB) and to compare them with those of tuberculin-negative and tuberculin-reactive healthy controls METHODS: Peripheral blood mononuclear cells (PBMCss), isolated from patients (n=52) and controls (n=30), were stimulated ex vivo with purified protein derivative (PPD) and IFN-γ and IL-17 levels in the supernatant were measured. RESULTS: At baseline, PBMCss from patients with TB released a significantly lower amount of IL-17 (p=0.043) than PBMCss from healthy controls, whereas IFN-γ levels were similar in the two groups. After PPD stimulation, a significant rise in IL-17 levels was found only among healthy controls (p=0.02). This rise in IL-17 levels was similar between tuberculin-reactive and tuberculin-negative subjects. After PPD stimulation, patients with infiltrative TB secreted higher levels of IL-17 and IFN-γ than those affected with chronic, miliary and cavitary TB (p < 0.01). IFN-γ production from patients with infiltrative TB was even higher than for healthy controls (p < 0.01). PBMCss from tuberculin-reactive patients released higher levels of IFN-γ than tuberculin-negative subjects after PPD stimulation (p < 0.01). CONCLUSION: Ex vivo PPD stimulation of PBMCs from patients with pulmonary TB does not significantly stimulate IL-17 release; however, higher IL-17 and IFN-γ levels are found in patients with infiltrative disease, in comparison with those affected with miliary, cavitary and chronic 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 | 0.000 | 0.001 |
| 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".