Mathematical Model of HIV superinfection dynamics and R5 to X4 switch

During the HIV infection several quasispecies of the virus arise, which are able to use different coreceptors, in particular the CCR5 and CXCR4 coreceptors (R5 and X4 phenotypes, respectively). The switch in coreceptor usage has been correlated with a faster progression of the disease to the AIDS phase. As several pharmaceutical companies are starting large phase III trials for R5 and X4 drugs, models are needed to predict the co-evolutionary and competitive dynamics of virus strains. We present a model of HIV early infection which describes the dynamics of R5 quasispecies and a model of HIV late infection which describes the R5 to X4 switch. We report the following findings: after superinfection or coinfection, quasispecies dynamics has time scales of several months and becomes even slower at low number of CD4+ T cells. The curve of CD4+ T cells decreases, during AIDS late stage, and can be described taking into account the X4 related Tumor Necrosis Factor dynamics. Phylogenetic inference of chemokine receptors suggests that viral mutational pathway may generate R5 variants able to interact with chemokine receptors different from CXCR4. This may explain the massive signaling disruptions in the immune system observed during AIDS late stages and may have relevance for vaccination and therapy.Comment: 21 pages, 14 figure

Modeling HIV quasispecies evolutionary dynamics

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background During the HIV infection several quasispecies of the virus arise, which are able to use different coreceptors, in particular the CCR5 and CXCR4 coreceptors (R5 and X4 phenotypes, respectively). The switch in coreceptor usage has been correlated with a faster progression of the disease to the AIDS phase. As several pharmaceutical companies are starting large phase III trials for R5 and X4 drugs, models are needed to predict the co-evolutionary and competitive dynamics of virus strains. Results We present a model of HIV early infection which describes the dynamics of R5 quasispecies and a model of HIV late infection which describes the R5 to X4 switch. We report the following findings: after superinfection (multiple infections at different times) or coinfection (simultaneous infection by different strains), quasispecies dynamics has time scales of several months and becomes even slower at low number of CD4+ T cells. Phylogenetic inference of chemokine receptors suggests that viral mutational pathway may generate a large variety of R5 variants able to interact with chemokine receptors different from CXCR4. The decrease of CD4+ T cells, during AIDS late stage, can be described taking into account the X4-related Tumor Necrosis Factor dynamics. Conclusion The results of this study bridge the gap between the within-patient and the inter-patients (i.e. world-wide) evolutionary processes during HIV infection and may represent a framework relevant for modeling vaccination and therapy

Multibody analysis of solar array deployment using flexible bodies

The solar panels represent the main device for collecting and converting solar energy into electrical energy and they are widely used in space missions supplying the energy necessary for both spacecrafts and payloads. To optimize the sun exposed surface the panels are usually organized in wings configurations, that, stored during the launch, deploy in the space at the beginning of the operative phase of the satellite. This work of thesis focus on this deployment phase and on the associated dynamic loads. The need of this investigation is connected to the strict requirements on the deployment. Since we want to be sure of the complete deployment in every condition with high margin of safety, the energy stored in the deployment mechanism is quite oversized. This leads to the dynamic loads that we want to estimate. The key topic of the thesis consists in the generation of a flexible multi-body model for solar arrays deployment studies and analysis. The main aim of this model is the verification and validation of a usually pre-existing rigid model used for the conceptual studies of the deployment. In this rigid model, generated directly in ADAMS environment, all the structural stiffness is condensed in a small number of DOF (rotational springs located on the hinge lines). It’s clear that this way of modelling does not cover higher frequency or side dynamics effects. By the introduction of a flexible model we want to investigate these effects and check the right working of the mechanism also in presence of deformation. Optionally, using the flexible model, we can also have a first estimation of stresses and strains due to the dynamics of the deployment. The two main requirements for a flexible model are to be easy to generate and to be compatible with the related rigid model. These two aspects are important to avoid significant impact on the project budget. The flexible bodies are generated using the user friendly interface of PATRAN (avoiding or minimizing manual inputs in NASTRAN) and then importing this flexible bodies in an ADAMS adapted rigid model (avoiding to re-built the flexible model from the beginning). The first chapter of the thesis will show the theoretical background of the NASTRANADAMS interface for the generation of flexible bodies. This theoretical part, even if not strictly necessary for the final-user, is anyway important for the full comprehension of some of the choices that will be adopted. The second chapter will introduce and explain the main characteristics of a solar array rigid model using BEPI COLOMBO MPO solar array and AMOS 3 solar array as examples. The third chapter will focus on the generation of the flexible model using the same two formers examples. In chapter four the results of the two models will be compared and in the fifth chapter the consequent conclusions will be drawn. In last chapter six will be shown other possible fields of application of the flexible body modelling with ADAMS