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Objective: Current commercially available immunological tests cannot be used for discriminating active tuberculosis (TB) from latent TB infection. To evaluate the value of biomarker candidates in the diagnosis of active TB, this study aimed to identify differentially expressed genes in peripheral blood mononuclear cells (PBMCs) between patients with active TB and individuals with latent TB infection by transcriptome sequencing. Methods: The differentially expressed genes in unstimulated PBMCs and in Mycobacterium tuberculosis (Mtb)antigen-stimulated PBMCs from patients with active TB and individuals with latent TB infection were identified by transcriptome sequencing. Selected candidate genes were evaluated in cohorts consisting of 110 patients with TB, 30 individuals with latent TB infections, and 50 healthy controls by quantitative real-time RT-PCR. Receiver operating characteristic (ROC) curve analysis was performed to calculate the diagnostic value of the biomarker candidates. Results: Among the differentially expressed genes in PBMCs without Mtbantigen stimulation, interferon-induced protein with tetratricopeptide repeats 3 (IFIT3) had the highest area under curve (AUC) value (0.918, 95% CI: 0.852–0.984, P<0.0001) in discriminating patients with active TB from individuals with latent TB infection, with a sensitivity of 91.86% and a specificity of 84.00%. In Mtbantigen-stimulated PBMCs, orosomucoid 1 (ORM1) had a high AUC value (0.833, 95% CI: 0.752–0.915, P<0.0001), with a sensitivity of 81.94% and a specificity of 70.00%. Conclusion: IFIT3 and ORM1 might be potential biomarkers for discriminating active TB from latent TB infection.

Objective: Mycobacterium tuberculosis(Mtb), the causative agent of tuberculosis (TB), causes an estimated 1.6 million human deaths annually, but the pathogenesis of TB remains unclear. Immunity plays a critical role in the onset and outcome of TB. This study aimed to uncover the roles of innate and adaptive immunity in TB. Methods: The gene expression profiles generated by RNA sequencing from human peripheral blood mononuclear cells (PBMCs) stimulated with or without Mtbstrain H37Rv antigens were analyzed. A total of 973 differentially expressed mRNAs were identified. Results: The differentially expressed genes were enriched in innate immunity signaling functions. The mesenchymal-epithelial transition factor (MET) gene was significantly upregulated in CD14+monocytes. A MET inhibitor improved the uptake of the BCG strain by monocytes and macrophages as well as inhibited the expression of indoleamine 2,3-dioxygenase (IDO). The expression of IDO was increased in PBMCs stimulated with Mtbantigens, and the IDO inhibitor promoted the expression of CD40, CD83, and CD86. Conclusion: Our results might provide clues regarding the immunomodulatory mechanisms used by Mtbto evade the host defense system.

Understanding the interface effect in dielectric nanocomposites is crucial to the enhancement of their performance. In this work, a data-driven interface design strategy based on high-throughput phase-field simulations is developed to study the interface effect and then optimize the permittivity and breakdown strength of nanocomposites. Here, we use two microscopic features that are closely related to the macroscopic dielectric properties, the thickness and permittivity of the interface phases, to evaluate the role of interfaces in experimental configuration, and thus provide quantitative design schemes for the interfacial phases. Taking the polyvinyl difluoride (PVDF)BaTiO3nanocomposite as an example, the calculation results demonstrate that the interfacial polarization could account for up to 83.6% of the increase in the experimentally measured effective permittivity of the nanocomposite. Based on the interface optimized strategy, a maximum enhancement of ∼156% in the energy density could be achieved by introducing an interface phase with d/r = 0.55 and εinterface/εfiller=0.036, compared to the pristine nanocomposite. Overall, the present work not only provides fundamental understanding of the interface effect in dielectric nanocomposites, but also establishes a powerful data-driven interface design framework for such materials that could also be easily generalized and applied to study interface issues in other functional nanocomposites, such as solid electrolytes and thermoelectrics.