Multiplex bead arrays with 17 different analytes, including cytokines, chemokines, and a growth factor, were performed using sera and QFT-IT plasma samples using BD FACSVerse™ (BD Biosciences, San Jose, CA, USA). The analytes included IL-1β, IL-2, IL-4, IL-5, IL-6, IL-9, IL-10, IL-12p70, IL-13, IL-17A, IL-22, IFN-γ, TNF-α, IFN-α, sCD40L, CXCL10 (IP-10), and vascular endothelial growth factor A (VEGF-A). The manufacturer’s protocol (eBioscience, San Diego, CA, USA) was followed for the multiplex bead arrays. The concentration of each analyte was calculated using selleck chemical FlowCytomix Pro software

(eBioscience), and values out of standard curve ranges were adjusted by setting minimum and maximum values. Values of 17 analytes in QFT-IT plasma were corrected for background levels by subtracting negative control values (nil tubes). In order to abate false positive responses, responders were defined as those who showed higher values than twice the limits of detection in standard curves: 5.5 pg/mL for IL-9, 27 pg/mL for IL-17A, 34.5 pg/mL for CXCL10, 55 pg/mL for IL-1β, IL-2, IL-4, IL-5, IL-6, IL-10, IL-12p70,

IL-13, IFN-γ, TNF-α, IFN-α, VEGF-A, 110 pg/mL for sCD40L, and 220 pg/mL for IL-22. Concentration differences of the 17 analytes from sera and QFT-IT plasma samples from active TB patients, TB contacts with LTBI, and normal healthy controls were analysed by Kruskal–Wallis tests and Dunn’s multiple comparison tests. Mann Whitney tests were used to analyse concentration differences of 17 analytes between active TB and NTM diseases. Concentrations of the 17 analytes between pre- and post-treatment Natural Product Library datasheet in TB patients were analysed by Wilcoxon signed rank tests. P values were adjusted using Bonferroni correction to account for multiple comparisons. Diagnostic values of 17 analytes in sera and QFT-IT plasma were examined Rebamipide by analysis of the area under the receiver operating characteristic (ROC) curves (AUC). Median concentrations of serum IL-22,

CXCL10, and VEGF-A were significantly higher in 58 TB patients than in 55 controls (P < 0.05) while only VEGF-A concentration differed between active TB and LTBI groups (P < 0.01) ( Fig. 2A). Analysis of the AUC indicated that serum VEGF-A could be a good biomarker for discriminating active TB from LTBI (AUC = 0.7576, P < 0.001; Supplementary Fig. 1). Concentrations of the 17 analytes in the sera from 38 TB patients (Table 1), before treatment, were compared with those from 42 NTM patients at diagnosis. TB patients had significantly higher concentrations of Th1 and Th2 cytokines, as well as IL-17, than did the NTM patients. Five out of the 17 analytes (IL-2, IL-9, IL-13, IL-17 and TNF-α) were detected at statistically significant higher levels in TB patients than in NTM patients (Fig. 2B). On the other hand, TB patients showed significantly lower concentrations of sCD40L (P < 0.01) than did the NTM patients.