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      Glucocorticosteroids trigger reactivation of human cytomegalovirus from latently infected myeloid cells and increase the risk for HCMV infection in D+R+ liver transplant patients

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          Abstract

          Graft rejection in transplant patients is managed clinically by suppressing T-cell function with immunosuppressive drugs such as prednisolone and methylprednisolone. In such immunocompromised hosts, human cytomegalovirus (HCMV) is an important opportunistic pathogen and can cause severe morbidity and mortality. Currently, the effect of glucocorticosteroids (GCSs) on the HCMV life cycle remains unclear. Previous reports showed enhanced lytic replication of HCMV in vitro in the presence of GCSs. In the present study, we explored the implications of steroid exposure on latency and reactivation. We observed a direct effect of several GCSs used in the clinic on the activation of a quiescent viral major immediate-early promoter in stably transfected THP-1 monocytic cells. This activation was prevented by the glucocorticoid receptor (GR) antagonist Ru486 and by shRNA-mediated knockdown of the GR. Consistent with this observation, prednisolone treatment of latently infected primary monocytes resulted in HCMV reactivation. Analysis of the phenotype of these cells showed that treatment with GCSs was correlated with differentiation to an anti-inflammatory macrophage-like cell type. On the basis that these observations may be pertinent to HCMV reactivation in post-transplant settings, we retrospectively evaluated the incidence, viral kinetics and viral load of HCMV in liver transplant patients in the presence or absence of GCS treatment. We observed that combination therapy of baseline prednisolone and augmented methylprednisolone, upon organ rejection, significantly increased the incidence of HCMV infection in the intermediate risk group where donor and recipient are both HCMV seropositive (D+R+) to levels comparable with the high risk D+R− group.

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          A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays.

          The ability to identify active compounds (³hits²) from large chemical libraries accurately and rapidly has been the ultimate goal in developing high-throughput screening (HTS) assays. The ability to identify hits from a particular HTS assay depends largely on the suitability or quality of the assay used in the screening. The criteria or parameters for evaluating the ³suitability² of an HTS assay for hit identification are not well defined and hence it still remains difficult to compare the quality of assays directly. In this report, a screening window coefficient, called ³Z-factor,² is defined. This coefficient is reflective of both the assay signal dynamic range and the data variation associated with the signal measurements, and therefore is suitable for assay quality assessment. The Z-factor is a dimensionless, simple statistical characteristic for each HTS assay. The Z-factor provides a useful tool for comparison and evaluation of the quality of assays, and can be utilized in assay optimization and validation.
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            Recognition of double-stranded RNA and activation of NF-kappaB by Toll-like receptor 3.

            Toll-like receptors (TLRs) are a family of innate immune-recognition receptors that recognize molecular patterns associated with microbial pathogens, and induce antimicrobial immune responses. Double-stranded RNA (dsRNA) is a molecular pattern associated with viral infection, because it is produced by most viruses at some point during their replication. Here we show that mammalian TLR3 recognizes dsRNA, and that activation of the receptor induces the activation of NF-kappaB and the production of type I interferons (IFNs). TLR3-deficient (TLR3-/-) mice showed reduced responses to polyinosine-polycytidylic acid (poly(I:C)), resistance to the lethal effect of poly(I:C) when sensitized with d-galactosamine (d-GalN), and reduced production of inflammatory cytokines. MyD88 is an adaptor protein that is shared by all the known TLRs. When activated by poly(I:C), TLR3 induces cytokine production through a signalling pathway dependent on MyD88. Moreover, poly(I:C) can induce activation of NF-kappaB and mitogen-activated protein (MAP) kinases independently of MyD88, and cause dendritic cells to mature.
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              SAS for Mixed Models

              The indispensable, up-to-date guide to mixed models using SAS®. Discover the latest capabilities available for a variety of applications featuring the MIXED, GLIMMIX, and NLMIXED procedures in this valuable edition of the comprehensive mixed models guide for data analysis, completely revised and updated for SAS®9. The theory underlying the models, the forms of the models for various applications, and a wealth of examples from different fields of study are integrated in the discussions of these models: random effect only and random coefficients models split-plot, multilocation, and repeated measures models hierarchical models with nested random effects analysis of covariance models spatial correlation models generalized linear mixed models nonlinear mixed models Professionals and students with a background in two-way ANOVA and regression and a basic knowledge of linear models and matrix algebra will benefit from the topics covered. Includes a free CD-ROM with example SAS code!
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                Author and article information

                Journal
                J Gen Virol
                J. Gen. Virol
                JGV
                vir
                The Journal of General Virology
                Society for General Microbiology
                0022-1317
                1465-2099
                January 2015
                January 2015
                : 96
                : Pt 1
                : 131-143
                Affiliations
                [1 ]Janssen Infectious Diseases BVBA, Turnhoutseweg 30, 2340 Beerse, Belgium
                [2 ]Department of Medicine, University of Cambridge, Level 5, Addenbrooke’s Hospital, Hills Road, Cambridge CB2 0QQ, UK
                [3 ]Division of Infection and Immunity (Royal Free Campus), University College London, Rowland Hill Street, Hampstead, London NW3 2QG, UK
                [4 ]Sheila Sherlock Liver Centre, Royal Free NHS Trust, Hampstead, London NW3 2QG, UK
                [5 ]Department of Microbial and Cellular Sciences, University of Surrey, Guildford, Surrey GU2 7XH, UK
                Author notes
                Correspondence Marnix Van Loock mvloock@ 123456its.jnj.com
                [†]

                Deceased.

                Article
                069872
                10.1099/vir.0.069872-0
                4268819
                25312585
                9999a084-37d5-43ad-bdb0-00b5d5985c64
                © 2015 The Authors

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 08 July 2014
                : 08 October 2014
                Funding
                Funded by: UK Medical Research Council
                Award ID: G:0701279
                Funded by: NIHR UK Biomedical Research Centre
                Funded by: Wellcome Trust
                Award ID: 078332
                Funded by: UCL Medical Research Council Centre for Molecular Virology
                Categories
                Standard
                Animal
                DNA viruses
                Custom metadata
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                Microbiology & Virology
                Microbiology & Virology

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