CAN3: BASELINE COST OF ILLNESS OF PARKINSON'S DISEASE IN A LARGE HEALTHCARE PLAN

We present a mixed finite element formulation for the spatial discretization in dynamic analysis of non-isothermal variably saturated porous media using different order of approximating functions for solid displacements and fluid pressures/temperature. It is known in fact that there are limitations on the approximating functions N-u and N-p for displacements and pressures if the BabuskaBrezzi convergence conditions or their equivalent [5] are to be satisfied. Although this formulation complicates the numerical implementation compared to equal order interpolation, it provides competitive advantages e.g. in speed of computation, accuracy and convergence

The role of cell lysis and matrix deposition in tumor growth modeling

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02/10/1995 - Hightlights Of The Week Ahead.pdf

Previous results indicate that fibers in ribbons are sometimes affected by systematic birefringence superimposed on the random one, their relative weights depending on fiber position in the ribbon. We report new theoretical and experimental results on stress distribution in ribbons, which is shown to depend on thermal and mechanical properties of the common coating. Numerical simulations are based on the theory of elasticity and the finite-element method (FEM). Polarization dispersion measurements vs. temperature match very well with numerical results, and indicate that central fibers in the ribbon exhibit significantly larger birefringence than lateral ones

Elucidating the role of matrix porosity and rigidity in glioblastoma type IV progression

The highly infiltrating nature of glioma cells is the major cause for the poor prognosis of brain malignancies. Motility, proliferation, and gene expression of cells in natural and synthetic gels have been analyzed by several authors, yet quantitative studies elucidating the role of matrix porosity and rigidity in the development of whole malignant masses are missing. Here, an experimental\u2010computational framework is introduced to analyze the behavior of U87\u2010MG cells and spheroids in compact hyaluronic acid gels (HA), replicating the brain parenchyma; and fibrous collagen gels (COL), resembling the organized structures of the brain. Experimentally it was observed that individual U87\u2010MG cells in COL assumed an elongated morphology within a few hours post inclusion (p.i.) and travelled longer distances than in HA. As spheroids, U87\u2010MG cells rapidly dispersed into COL resulting in infiltrating regions as large as tumor cores ( 48600 \u3bcm, at 8 days p.i.). Conversely, cells in HA originated smaller and denser infiltrating regions ( 48300 \u3bcm, at 8 days p.i.). Notably, COL tumor core size was only 20% larger than in HA, at longer time points. Computationally, by introducing for the first time the effects of matrix heterogeneity in our numerical simulations, the results confirmed that matrix porosity and its spatial organization are key factors in priming the infiltrating potential of these malignant cells. The experimental\u2010numerical synergy can be used to predict the behavior of neoplastic masses under diverse conditions and the efficacy of combination therapies simultaneously aiming at killing cancer cells and modulating the tumor microenvironment

A parametric study of a multiphase porous media model for tumor spheroids and environment interactions

Computational models for tumor growth provide an effective in silico tool to investigate the different stages of cancer growth. Recently, a series of computational models based on porous media theory has been proposed to predict tumor evolution and its interactions with the host tissue. In addition, a specialization of the original models, adapted for tumor spheroids, has been proposed and validated experimentally. However, due to the complexity of the modeling framework, a systematic understanding of the role of the parameters governing the equations is still lacking. In this work, we perform a parametric analysis on a set of fundamental parameters appearing in the model equations. We investigate the effects of a variation of these coefficients on the spheroid growth curves and, in particular, on the final radii reached by the cell aggregates in the growth saturation stage. Finally, we provide a discussion of the results and give a brief summary of our findings

A multiphase model for three-dimensional tumor growth

Several mathematical formulations have analyzed the time-dependent behaviour of a tumor mass. However, most of these propose simplifications that compromise the physical soundness of the model. Here, multiphase porous media mechanics is extended to model tumor evolution, using governing equations obtained via the Thermodynamically Constrained Averaging Theory (TCAT). A tumor mass is treated as a multiphase medium composed of an extracellular matrix (ECM); tumor cells (TC), which may become necrotic depending on the nutrient concentration and tumor phase pressure; healthy cells (HC); and an interstitial fluid (IF) for the transport of nutrients. The equations are solved by a Finite Element method to predict the growth rate of the tumor mass as a function of the initial tumor-to-healthy cell density ratio, nutrient concentration, mechanical strain, cell adhesion and geometry. Results are shown for three cases of practical biological interest such as multicellular tumor spheroids (MTS) and tumor cords. First, the model is validated by experimental data for time-dependent growth of an MTS in a culture medium. The tumor growth pattern follows a biphasic behaviour: initially, the rapidly growing tumor cells tend to saturate the volume available without any significant increase in overall tumor size; then, a classical Gompertzian pattern is observed for the MTS radius variation with time. A core with necrotic cells appears for tumor sizes larger than 150 μm, surrounded by a shell of viable tumor cells whose thickness stays almost constant with time. A formula to estimate the size of the necrotic core is proposed. In the second case, the MTS is confined within a healthy tissue. The growth rate is reduced, as compared to the first case – mostly due to the relative adhesion of the tumor and healthy cells to the ECM, and the less favourable transport of nutrients. In particular, for tumor cells adhering less avidly to the ECM, the healthy tissue is progressively displaced as the malignant mass grows, whereas tumor cell infiltration is predicted for the opposite condition. Interestingly, the infiltration potential of the tumor mass is mostly driven by the relative cell adhesion to the ECM. In the third case, a tumor cord model is analyzed where the malignant cells grow around microvessels in a 3D geometry. It is shown that tumor cells tend to migrate among adjacent vessels seeking new oxygen and nutrient. This model can predict and optimize the efficacy of anticancer therapeutic strategies. It can be further developed to answer questions on tumor biophysics, related to the effects of ECM stiffness and cell adhesion on tumor cell proliferation

The role of rock joint frictional strength in the containment of fracture propagation

The fracturing phenomenon within the reservoir environment is a complex process that is controlled by several factors and may occur either naturally or by artificial drivers. Even when deliberately induced, the fracturing behaviour is greatly influenced by the subsurface architecture and existing features. The presence of discontinuities such as joints, artificial and naturally occurring faults and interfaces between rock layers and microfractures plays an important role in the fracturing process and has been known to significantly alter the course of fracture growth. In this paper, an important property (joint friction) that governs the shear behaviour of discontinuities is considered. The applied numerical procedure entails the implementation of the discrete element method to enable a more dynamic monitoring of the fracturing process, where the joint frictional property is considered in isolation. Whereas fracture propagation is constrained by joints of low frictional resistance, in non-frictional joints, the unrestricted sliding of the joint plane increases the tendency for reinitiation and proliferation of fractures at other locations. The ability of a frictional joint to suppress fracture growth decreases as the frictional resistance increases; however, this phenomenon exacerbates the influence of other factors including in situ stresses and overburden conditions. The effect of the joint frictional property is not limited to the strength of rock formations; it also impacts on fracturing processes, which could be particularly evident in jointed rock masses or formations with prominent faults and/or discontinuities

Systematizing Policy Learning: From Monolith to Dimensions

notes: The authors wish to express their gratitude to the Norwegian Political Science Association Annual Conference, 6 January 2010, University of Agder, Kristiansand, participants of the ‘Establishing Causality in Policy Learning’ panel at the American Political Science Association (APSA) annual meeting,2–5 September 2010,Washington DC, and the European Consortium of Political Research (ECPR) Joint Sessions, St Gallen, 12–17 April 2011, workshop 2. Dunlop and Radaelli gratefully acknowledge the support of the European Research Council, grant on Analysis of Learning in Regulatory Governance, ALREG, http://centres.exeter.ac.uk/ceg/research/ALREG/index.php.publication-status: AcceptedThe definitive version is available at www.blackwell-synergy.com and also from DOI: 10.1111/j.1467-9248.2012.00982.xThe field of policy learning is characterised by concept stretching and lack of systematic findings. To systematize them, we combine the classic Sartorian approach to classification with the more recent insights on explanatory typologies. At the outset, we classify per genus et differentiam – distinguishing between the genus and the different species within it. By drawing on the technique of explanatory typologies to introduce a basic model of policy learning, we identify four major genera in the literature. We then generate variation within each cell by using rigorous concepts drawn from adult education research. Specifically, we conceptualize learning as control over the contents and goals of knowledge. By looking at learning through the lenses of knowledge utilization, we show that the basic model can be expanded to reveal sixteen different species. These types are all conceptually possible, but are not all empirically established in the literature. Up until now the scope conditions and connections among types have not been clarified. Our reconstruction of the field sheds light on mechanisms and relations associated with alternatives operationalizations of learning and the role of actors in the process of knowledge construction and utilization. By providing a comprehensive typology, we mitigate concept stretching problems and aim to lay the foundations for the systematic comparison across and within cases of policy learning.European Research Council, grant no 230267 on Analysis of Learning in Regulatory Governance, ALREG