In this paper we present a mathematical model for the dynamics of

In this paper we present a mathematical model for the dynamics of an immune response to a viral infection

and autoimmunity, which takes into account T cells with different activation thresholds. We show how the infection can be cleared by the immune system, as well as how it can lead to a chronic infection or recurrent infection with relapses and remissions. Numerical simulations of the model are performed to illustrate various dynamical regimes, as well as to analyse the potential impact of treatment of autoimmune disease in the chronic and recurrent states. The results provide good qualitative agreement with available data on immune responses to viral infections and progression Linsitinib of autoimmune diseases. (C) 2012 Elsevier Ltd. All rights reserved.”

human coronavirus, called the Middle East respiratory syndrome coronavirus (MERS-CoV), was first identified in September 2012 in samples obtained from a Saudi Arabian businessman who died from acute respiratory failure. Since then, 49 cases of infections caused by MERS-CoV (previously called a novel coronavirus) with 26 deaths have been reported to date. In this report, we describe a family case cluster of MERS-CoV infection, including the clinical presentation, treatment outcomes, and household relationships of three young men who became ill with MERS-CoV infection after the hospitalization of an elderly male JIB04 cost relative, who died of HDAC inhibitor the disease. Twenty-four other family members living in the same household and 124 attending staff members at the hospitals did not become ill. MERS-CoV infection may cause a spectrum of clinical illness. Although an animal reservoir is suspected, none has been discovered. Meanwhile, global concern rests on the ability of MERS-CoV to cause major illness in close contacts of patients.”
“The impact that flows of air and water have on organisms moving through these environments

has received a great deal of attention in theoretical and empirical studies. There are many behavioral strategies that animals can adopt to interact with these flows, and by assuming one of these strategies a researcher can quantify the instantaneous assistance an animal derives from a particular flow. Calculating flow-assistance in this way can provide an elegant simplification of a multivariate problem to a univariate one and has many potential uses; however, the resultant flow-assistance values are inseparably linked to the specific behavioral strategy assumed. We expect that flow-assistance may differ considerably depending on the behavioral strategy assumed and the accuracy of the assumptions associated with that strategy. Further, we expect that the magnitude of these differences may depend on the specific flow conditions.

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