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      Potential diagnostic value of pleural fluid cytokines levels for tuberculous pleural effusion

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          Abstract

          Patients with tuberculous pleural effusion (TPE) or malignant pleural effusions (MPE) frequently have similar pleural fluid profiles. New biomarkers for the differential diagnosis of TPE are required. We determined whether cytokine profiles in the PE of patients could aid the differential diagnosis of TPE. 30 patients with TPE, 30 patients with MPE, 14 patients with empyema (EMP) and 14 patients with parapneumonic effusion (PPE) were enrolled between Dec 2018 and 2019. The levels of interleukin (IL)-6, IL-18, IL-27, CXCL8, CCL-1 and IP-10 were determined in PE by ELISA along with measurements of adenosine deaminase (ADA). The best predictors of TPE were combined ADA.IL-27 [optimal cut-off value = 42.68 (10 3 U ng/l 2), sensitivity 100%, specificity 98.28%], ADA [cut off value 27.5 (IU/l), sensitivity 90%, specificity 96.5%] and IL-27 [cut-off value = 2363 (pg/ml), sensitivity 96.7%, specificity 98.3%, p ≤ 0.0001]. A high level of IL-6 [cut-off value = 3260 (pg/ml), sensitivity 100%, specificity 67.2%], CXCL8 [cut-off value = 144.5 (pg/ml), sensitivity 93.3%, specificity 58.6%], CCL1 [cut-off value = 54 (pg/ml), sensitivity 100%, specificity 70.7%] and IP-10 [cut-off value = 891.9 (pg/ml), sensitivity 83.3%, specificity 48.3%] were also predictive of TPE. High ADA.IL-27, ADA and IL-27 levels differentiate between TPE and non-TPE with improved specificity and diagnostic accuracy and may be useful clinically.

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          Occurrence of the potent mutagens 2- nitrobenzanthrone and 3-nitrobenzanthrone in fine airborne particles

          Polycyclic aromatic compounds (PACs) are known due to their mutagenic activity. Among them, 2-nitrobenzanthrone (2-NBA) and 3-nitrobenzanthrone (3-NBA) are considered as two of the most potent mutagens found in atmospheric particles. In the present study 2-NBA, 3-NBA and selected PAHs and Nitro-PAHs were determined in fine particle samples (PM 2.5) collected in a bus station and an outdoor site. The fuel used by buses was a diesel-biodiesel (96:4) blend and light-duty vehicles run with any ethanol-to-gasoline proportion. The concentrations of 2-NBA and 3-NBA were, on average, under 14.8 µg g−1 and 4.39 µg g−1, respectively. In order to access the main sources and formation routes of these compounds, we performed ternary correlations and multivariate statistical analyses. The main sources for the studied compounds in the bus station were diesel/biodiesel exhaust followed by floor resuspension. In the coastal site, vehicular emission, photochemical formation and wood combustion were the main sources for 2-NBA and 3-NBA as well as the other PACs. Incremental lifetime cancer risk (ILCR) were calculated for both places, which presented low values, showing low cancer risk incidence although the ILCR values for the bus station were around 2.5 times higher than the ILCR from the coastal site.
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            IL-27, a heterodimeric cytokine composed of EBI3 and p28 protein, induces proliferation of naive CD4+ T cells.

            An efficient Th1-driven adaptive immune response requires activation of the T cell receptor and secretion of the T cell stimulatory cytokine IL-12 by activated antigen-presenting cells. IL-12 triggers Th1 polarization of naive CD4(+) T cells and secretion of IFN-gamma. We describe a new heterodimeric cytokine termed IL-27 that consists of EBI3, an IL-12p40-related protein, and p28, a newly discovered IL-12p35-related polypeptide. IL-27 is an early product of activated antigen-presenting cells and drives rapid clonal expansion of naive but not memory CD4(+) T cells. It also strongly synergizes with IL-12 to trigger IFN-gamma production of naive CD4(+) T cells. IL-27 mediates its biologic effects through the orphan cytokine receptor WSX-1/TCCR.
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              Heterogeneity in tuberculosis

              Infection with Mycobacterium tuberculosis , the causative agent of tuberculosis (TB), results in a range of clinical presentations in humans. Most infections manifest as a clinically asymptomatic, contained state that is termed latent TB infection (LTBI); a smaller subset of infected individuals present with symptomatic, active TB. Within these two seemingly binary states, there is a spectrum of host outcomes that have varying symptoms, microbiologies, immune responses and pathologies. Recently, it has become apparent that there is diversity of infection even within a single individual. A good understanding of the heterogeneity that is intrinsic to TB — at both the population level and the individual level — is crucial to inform the development of intervention strategies that account for and target the unique, complex and independent nature of the local host–pathogen interactions that occur in this infection. In this Review, we draw on model systems and human data to discuss multiple facets of TB biology and their relationship to the overall heterogeneity observed in the human disease.
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                Author and article information

                Contributors
                emortaz@gmail.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                12 January 2021
                12 January 2021
                2021
                : 11
                : 660
                Affiliations
                [1 ]GRID grid.411600.2, Department of Immunology, Faculty of Medicine, , Shahid Beheshti University of Medical Sciences, ; Tehran, Iran
                [2 ]GRID grid.411600.2, Clinical Tuberculosis and Epidemiology Research Center, , National Research Institute of Tuberculosis and Lung Diseases, Shahid Beheshti University of Medical Sciences, ; Tehran, Iran
                [3 ]GRID grid.411600.2, Mycobacteriology Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, ; Tehran, Iran
                [4 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, National Heart and Lung Institute, Imperial College, ; London, UK
                [5 ]GRID grid.266842.c, ISNI 0000 0000 8831 109X, Priority Research Centre for Asthma and Respiratory Disease, , Hunter Medical Research Institute, University of Newcastle, ; Newcastle, NSW Australia
                [6 ]Department of Immunology, School of Medicine, Dezful University of Medical Sciences, Dezful, Iran
                Article
                79685
                10.1038/s41598-020-79685-1
                7803752
                33436672
                650108d9-f61f-41dc-a10a-69338f83eeac
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 2 September 2020
                : 8 December 2020
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                © The Author(s) 2021

                Uncategorized
                immunology,biomarkers,diseases,medical research
                Uncategorized
                immunology, biomarkers, diseases, medical research

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