3 resultados para Multiple Covariates and Biomarker Interactions

em ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha


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This thesis presents new methods to simulate systems with hydrodynamic and electrostatic interactions. Part 1 is devoted to computer simulations of Brownian particles with hydrodynamic interactions. The main influence of the solvent on the dynamics of Brownian particles is that it mediates hydrodynamic interactions. In the method, this is simulated by numerical solution of the Navier--Stokes equation on a lattice. To this end, the Lattice--Boltzmann method is used, namely its D3Q19 version. This model is capable to simulate compressible flow. It gives us the advantage to treat dense systems, in particular away from thermal equilibrium. The Lattice--Boltzmann equation is coupled to the particles via a friction force. In addition to this force, acting on {it point} particles, we construct another coupling force, which comes from the pressure tensor. The coupling is purely local, i.~e. the algorithm scales linearly with the total number of particles. In order to be able to map the physical properties of the Lattice--Boltzmann fluid onto a Molecular Dynamics (MD) fluid, the case of an almost incompressible flow is considered. The Fluctuation--Dissipation theorem for the hybrid coupling is analyzed, and a geometric interpretation of the friction coefficient in terms of a Stokes radius is given. Part 2 is devoted to the simulation of charged particles. We present a novel method for obtaining Coulomb interactions as the potential of mean force between charges which are dynamically coupled to a local electromagnetic field. This algorithm scales linearly, too. We focus on the Molecular Dynamics version of the method and show that it is intimately related to the Car--Parrinello approach, while being equivalent to solving Maxwell's equations with freely adjustable speed of light. The Lagrangian formulation of the coupled particles--fields system is derived. The quasi--Hamiltonian dynamics of the system is studied in great detail. For implementation on the computer, the equations of motion are discretized with respect to both space and time. The discretization of the electromagnetic fields on a lattice, as well as the interpolation of the particle charges on the lattice is given. The algorithm is as local as possible: Only nearest neighbors sites of the lattice are interacting with a charged particle. Unphysical self--energies arise as a result of the lattice interpolation of charges, and are corrected by a subtraction scheme based on the exact lattice Green's function. The method allows easy parallelization using standard domain decomposition. Some benchmarking results of the algorithm are presented and discussed.

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Glioblastoma multiforme (GBM) is the most common and most aggressive astrocytic tumor of the central nervous system (CNS) in adults. The standard treatment consisting of surgery, followed by a combinatorial radio- and chemotherapy, is only palliative and prolongs patient median survival to 12 to 15 months. The tumor subpopulation of stem cell-like glioma-initiating cells (GICs) shows resistance against radiation as well as chemotherapy, and has been suggested to be responsible for relapses of more aggressive tumors after therapy. The efficacy of immunotherapies, which exploit the immune system to specifically recognize and eliminate malignant cells, is limited due to strong immunosuppressive activities of the GICs and the generation of a specialized protective microenvironment. The molecular mechanisms underlying the therapy resistance of GICs are largely unknown. rnThe first aim of this study was to identify immune evasion mechanisms in GICs triggered by radiation. A model was used in which patient-derived GICs were treated in vitro with fractionated ionizing radiation (2.5 Gy in 7 consecutive passages) to select for a more radio-resistant phenotype. In the model cell line 1080, this selection process resulted in increased proliferative but diminished migratory capacities in comparison to untreated control GICs. Furthermore, radio-selected GICs downregulated various proteins involved in antigen processing and presentation, resulting in decreased expression of MHC class I molecules on the cellular surface and diminished recognition potential by cytotoxic CD8+ T cells. Thus, sub-lethal fractionated radiation can promote immune evasion and hamper the success of adjuvant immunotherapy. Among several immune-associated proteins, interferon-induced transmembrane protein 3 (IFITM3) was found to be upregulated in radio-selected GICs. While high expression of IFITM3 was associated with a worse overall survival of GBM patients (TCGA database) and increased proliferation and migration of differentiated glioma cell lines, a strong contribution of IFITM3 to proliferation in vitro as well as tumor growth and invasiveness in a xenograft model could not be observed. rnMultiple sclerosis (MS) is the most common autoimmune disease of the CNS in young adults of the Western World, which leads to progressive disability in genetically susceptible individuals, possibly triggered by environmental factors. It is assumed that self-reactive, myelin-specific T helper cell 1 (Th1) and Th17 cells, which have escaped the control mechanisms of the immune system, are critical in the pathogenesis of the human disease and its animal model experimental autoimmune encephalomyelitis (EAE). It was observed that in vitro differentiated interleukin 17 (IL-17) producing Th17 cells co-expressed the Th1-phenotypic cytokine Interferon-gamma (IFN-γ) in combination with the two respective lineage-associated transcription factors RORγt and T-bet after re-isolation from the CNS of diseased mice. Pathogenic molecular mechanisms that render a CD4+ T cell encephalitogenic have scarcely been investigated up to date. rnIn the second part of the thesis, whole transcriptional changes occurring in in vitro differentiated Th17 cells in the course of EAE were analyzed. Evaluation of signaling networks revealed an overrepresentation of genes involved in communication between the innate and adaptive immune system and metabolic alterations including cholesterol biosynthesis. The transcription factors Cebpa, Fos, Klf4, Nfatc1 and Spi1, associated with thymocyte development and naïve T cells were upregulated in encephalitogenic CNS-isolated CD4+ T cells, proposing a contribution to T cell plasticity. Correlation of the murine T-cell gene expression dataset to putative MS risk genes, which were selected based on their proximity (± 500 kb; ensembl database, release 75) to the MS risk single nucleotide polymorphisms (SNPs) proposed by the most recent multiple sclerosis GWAS in 2011, revealed that 67.3% of the MS risk genes were differentially expressed in EAE. Expression patterns of Bach2, Il2ra, Irf8, Mertk, Odf3b, Plek, Rgs1, Slc30a7, and Thada were confirmed in independent experiments, suggesting a contribution to T cell pathogenicity. Functional analysis of Nfatc1 revealed that Nfatc1-deficient CD4+ T cells were restrained in their ability to induce clinical signs of EAE. Nfatc1-deficiency allowed proper T cell activation, but diminished their potential to fully differentiate into Th17 cells and to express high amounts of lineage cytokines. As the inducible Nfatc1/αA transcript is distinct from the other family members, it could represent an interesting target for therapeutic intervention in MS.rn

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In this thesis different approaches for the modeling and simulation of the blood protein fibrinogen are presented. The approaches are meant to systematically connect the multiple time and length scales involved in the dynamics of fibrinogen in solution and at inorganic surfaces. The first part of the thesis will cover simulations of fibrinogen on an all atom level. Simulations of the fibrinogen protomer and dimer are performed in explicit solvent to characterize the dynamics of fibrinogen in solution. These simulations reveal an unexpectedly large and fast bending motion that is facilitated by molecular hinges located in the coiled-coil region of fibrinogen. This behavior is characterized by a bending and a dihedral angle and the distribution of these angles is measured. As a consequence of the atomistic detail of the simulations it is possible to illuminate small scale behavior in the binding pockets of fibrinogen that hints at a previously unknown allosteric effect. In a second step atomistic simulations of the fibrinogen protomer are performed at graphite and mica surfaces to investigate initial adsorption stages. These simulations highlight the different adsorption mechanisms at the hydrophobic graphite surface and the charged, hydrophilic mica surface. It is found that the initial adsorption happens in a preferred orientation on mica. Many effects of practical interest involve aggregates of many fibrinogen molecules. To investigate such systems, time and length scales need to be simulated that are not attainable in atomistic simulations. It is therefore necessary to develop lower resolution models of fibrinogen. This is done in the second part of the thesis. First a systematically coarse grained model is derived and parametrized based on the atomistic simulations of the first part. In this model the fibrinogen molecule is represented by 45 beads instead of nearly 31,000 atoms. The intra-molecular interactions of the beads are modeled as a heterogeneous elastic network while inter-molecular interactions are assumed to be a combination of electrostatic and van der Waals interaction. A method is presented that determines the charges assigned to beads by matching the electrostatic potential in the atomistic simulation. Lastly a phenomenological model is developed that represents fibrinogen by five beads connected by rigid rods with two hinges. This model only captures the large scale dynamics in the atomistic simulations but can shed light on experimental observations of fibrinogen conformations at inorganic surfaces.