Epstein-Barr virus (EBV) open reading frame BILF1encodes a seven trans-membrane (TM) G protein-coupled receptor that signals with high constitutive activity through Ga i Paulsen et al., 2005). In this paper, the transforming potential of BILF1 is investigated in vitro in a foci formation assay using retrovirally transduced NIH3T3 cells, as well as in vivo by using nude mice. BILF1 revealed a substantial transforming potential that was dependent on constitutive signaling, as a signaling-deficient mutant completely lost its ability to transform cells in vitro, and an intermediately active triple-mutated receptor possessed an intermediate transforming potential. Furthermore, BILF1 expression induced vascular endothelial growth factor secretion in a constitutively active manner. In nude mice, BILF1 promoted tumor formation in 90% of cases, ORF74 (from Kaposi's sarcoma-associated herpes virus) in 100% of cases, whereas the signaling-deficient receptor resulted in tumor establishment in 40% of cases. These data suggest that BILF1, when expressed during EBV infection, could indeed be involved in the pathogenesis of EBV-associated diseases and malignancies. Furthermore, the correlation between receptor activity and the ability to mediate cell transformation in vitro and tumor formation in vivo supports the idea that inverse agonists for BILF1 could inhibit cell transformation and be relevant therapeutic candidates.
Abstract-We present a novel numerically robust and computationally efficient extended Kalman filter for state estimation in nonlinear continuous-discrete stochastic systems. The resulting differential equations for the mean-covariance evolution of the nonlinear stochastic continuous-discrete time systems are solved efficiently using an ESDIRK integrator with sensitivity analysis capabilities. This ESDIRK integrator for the meancovariance evolution is implemented as part of an extended Kalman filter and tested on a PDE system. For moderate to large sized systems, the ESDIRK based extended Kalman filter for nonlinear stochastic continuous-discrete time systems is more than two orders of magnitude faster than a conventional implementation. This is of significance in nonlinear model predictive control applications, statistical process monitoring as well as grey-box modelling of systems described by stochastic differential equations.
We describe our research-its approach, results and products-on Danish emergency medical service (EMS) field or "pre-hospital" work in minor and major incidents. We discuss how commitments to participatory design and attention to the qualitative differences between minor and major incidents address challenges identified by disaster sociologists when designing for major incidents. Through qualitative research and participatory design, we have examined the features of EMS work and technology use in different emergency situations from the perspective of multiple actors. We conceptualize victims in incidents-and particularly in major incidents, where on-site medical assessments is highly incomplete-as boundary objects over which the complex and imperfect work of coordination is done. As an outcome of our participatory design approach, we describe a set of designs in support of future EMS work.
We propose the use of implicit one-step Explicit Singly Diagonal Implicit Runge-Kutta (ESDIRK) methods for integration of the stiff kinetics in reactive, compositional and thermal processes that are solved using operator-splitting type approaches. To facilitate the algorithmic development we construct a virtual kinetic cell model. The model serves both as a tool for the development and testing of tailored solvers as well as a testbed for studying the interactions between chemical kinetics and phase behavior. As case study, two chemical kinetics models with 6 and 14 components, respectively, are implemented for in situ combustion, a thermal oil recovery process. Through benchmark studies using the 14 component reaction model the new ESDIRK solvers are shown to improve computational speed when compared to the widely used multi-step BDF methods DASSL and LSODE. Phase changes are known to cause convergence problems for the integration method. We propose 384 M. R. Kristensen et al. an algorithm for detection and location of phase changes based on discrete event system theory. Experiments show that the algorithm improves the robustness of the integration process near phase boundaries by lowering the number convergence and error test failures by more than 50% compared to direct integration without the new algorithm.
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