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Search Results: 1 - 10 of 12614 matches for " Frank Weber "
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Genetic Background May Confer Susceptibility to PTC in Benign Multinodular Thyroid Disease  [PDF]
Sivatharsiny Thavarajah, Frank Weber
Journal of Cancer Therapy (JCT) , 2012, DOI: 10.4236/jct.2012.36128
Abstract: Purpose: The incidence of hyperplastic thyroid nodular disease has been consistently rising over the last decades. In addition, unsuspected papillary thyroid carcinoma (PTC) can be found in up to 34% of patients operated for benign thyroid lesions. PTC tends to occur multi-focally and is commonly of polyclonal origin. We set out to test the hypothesis that in benign thyroid disease, a unique genetic signature can already be identified in the benign pathology, which is associated with a susceptibility of the thyroid tissue to neoplastic transformation in the context of additional growth promoting stimuli. Patients and Methods: We obtained a set of 23 samples from patients with multinodular goiter (MNG), 12 of whom also harbored an unsuspected PTC. We used global gene expression analysis to evaluate for dissimilarities in the gene expression patterns between these two groups. We also compared these patterns to the profiles of 3 normal thyroid and 7 PTC samples. Results: We were able to accurately distinguish between hyperplastic nodules of patients with multinodular goiter and those that were associated with a PTC. One of the strongest differentially expressed genes, CDC42, has been implicated to respond to environmental factors such as UVB radiation and might point to novel factors contributing to PTC genesis in the setting of pre-existing benign proliferative disease. Conclusion: While the comparison between histologically identical samples cannot distinguish the two groups of goiters, unsupervised or supervised approaches allowed us to identify a molecular signature associated with PTC susceptibility in multinodular goiter.
Personalized medicine: caught between hope, hype and the real world
Dammann, Marc;Weber, Frank;
Clinics , 2012, DOI: 10.6061/clinics/2012(Sup01)16
Abstract: genomic and personalized medicine have become buzz phrases that pervade all fields of medicine. rapid advances in "-omics" fields of research (chief of which are genomics, proteinomics, and epigenomics) over the last few years have allowed us to dissect the molecular signatures and functional pathways that underlie disease initiation and progression and to identify molecular profiles that help the classification of tumor subtypes and determine their natural course, prognosis, and responsiveness to therapies. genomic medicine implements the use of traditional genetic information, as well as modern pangenomic information, with the aim of individualizing risk assessment, prevention, diagnosis, and treatment of cancers and other diseases. it is of note that personalizing medical treatment based on genetic information is not the revolution of the 21st century. indeed, the use of genetic information, such as human leukocyte antigen-matching for solid organ transplantation or blood transfusion based on abo blood group antigens, has been standard of care for several decades. however, in recent years rapid technical advances have allowed us to perform high-throughput, high-density molecular analyses to depict the genomic, proteinomic, and epigenomic make-up of an individual at a reasonable cost. hence, the so-called genomic revolution is more or less the logical evolution from years of bench-based research and bench-to-bedside translational medicine.
Frank Eissmann,Uwe Kafurke,Edwin Weber
Acta Crystallographica Section E , 2010, DOI: 10.1107/s1600536810024529
Abstract: The molecular structure of the title compound, C12H14O2, features a nearly coplanar arrangement including the aromatic ring, the C[triple-bond]C—C group and the ether O atom. The maximum deviation from the least-squares plane of these ten atoms is 0.0787 (8) for the ether O atom. In the crystal, molecules are connected via O—H...O hydrogen bonds (involving the hydroxy O atom both as hydrogen-bond donor and acceptor) and weaker (aryl)C—H...π(aryl) contacts, leading to the formation of strands running parallel to the b axis. Further stabilization results from weaker (methyl)C—H...π(acetylene) interactions between different strands.
SAP Speaks PDDL: Exploiting a Software-Engineering Model for Planning in Business Process Management
Joerg Hoffman,Ingo Weber,Frank Michael Kraft
Computer Science , 2014, DOI: 10.1613/jair.3636
Abstract: Planning is concerned with the automated solution of action sequencing problems described in declarative languages giving the action preconditions and effects. One important application area for such technology is the creation of new processes in Business Process Management (BPM), which is essential in an ever more dynamic business environment. A major obstacle for the application of Planning in this area lies in the modeling. Obtaining a suitable model to plan with -- ideally a description in PDDL, the most commonly used planning language -- is often prohibitively complicated and/or costly. Our core observation in this work is that this problem can be ameliorated by leveraging synergies with model-based software development. Our application at SAP, one of the leading vendors of enterprise software, demonstrates that even one-to-one model re-use is possible. The model in question is called Status and Action Management (SAM). It describes the behavior of Business Objects (BO), i.e., large-scale data structures, at a level of abstraction corresponding to the language of business experts. SAM covers more than 400 kinds of BOs, each of which is described in terms of a set of status variables and how their values are required for, and affected by, processing steps (actions) that are atomic from a business perspective. SAM was developed by SAP as part of a major model-based software engineering effort. We show herein that one can use this same model for planning, thus obtaining a BPM planning application that incurs no modeling overhead at all. We compile SAM into a variant of PDDL, and adapt an off-the-shelf planner to solve this kind of problem. Thanks to the resulting technology, business experts may create new processes simply by specifying the desired behavior in terms of status variable value changes: effectively, by describing the process in their own language.
Nuclear Receptor Variants in Liver Disease
Roman Müllenbach,Susanne N. Weber,Frank Lammert
Journal of Lipids , 2012, DOI: 10.1155/2012/934707
Abstract: This review aims to provide a snapshot of the actual state of knowledge on genetic variants of nuclear receptors (NR) involved in regulating important aspects of liver metabolism. It recapitulates recent evidence for the application of NR in genetic diagnosis of monogenic (“Mendelian”) liver disease and their use in clinical diagnosis. Genetic analysis of multifactorial liver diseases such as viral hepatitis or fatty liver disease identifies key players in disease predisposition and progression. Evidence from these analyses points towards a role of NR polymorphisms in common diseases, linking regulatory networks to complex and variable phenotypes. The new insights into NR variants also offer perspectives and cautionary advice for their use as handles towards diagnosis and treatment. 1. Introduction Systematically, genetic analysis with regard to disease onset and progression can be separated into pre- and post-hoc examination of monogenic or polygenic diseases. Monogenic (“Mendelian”) diseases are caused by a single gene defect and follow relatively straightforward inheritance patterns. The most prominent of these disorders are rather rare, often severe, and characterized by early onset. Genetic testing for monogenic liver disease in symptomatic patients is based on known disease-associated gene variants, thereby confirming the genetic etiology and sometimes allowing prediction of disease progression [1]. In contrast, polygenic diseases such as fatty liver disease and gallstones result from combinations of multiple gene variants and environmental factors, all of which play a role in disease initiation and progression [2]. The assessment of predisposition towards polygenic disease is based on sequence analysis of known contributory genes and construction of “polygenic risk scores” from variants of these genes [1]. Still in its infancy, personal genome information might eventually be able to predict a variety of risks associated with an individual’s lifestyle such as fatty food and alcohol consumption, as well as susceptibility to infectious diseases such as infection with hepatitis B or C virus. 2. Nuclear Receptors Nuclear receptors (NRs) are a subclass of regulatory molecules that orchestrate gene transcription in response to the presence or absence of specific ligands. Due to these functional requirements, they are characterized by the presence of a ligand-binding and a DNA-binding domain. NRs represent a central point of interaction between environment and gene regulation. They are the “hinge” connecting endogenous and environmental stimuli, that is,
Sebastian Förster,Frank Eissmann,Wilhelm Seichter,Edwin Weber
Acta Crystallographica Section E , 2011, DOI: 10.1107/s1600536811017569
Abstract: There are two molecules in the asymmetric unit of the title compound, C14H6F6O2, in which the azulene systems possess an almost planar geometry with maximum deviations of 0.0438 (15) and 0.0396 (14) . Besides intra- and intermolecular C—H...O and C—H...F interactions, the structure displays three F...F contacts [2.793 (2), 2.8820 (17) and 2.9181 (16) ]. Furthermore, a characteristic azulene π-stacking is observed with an alternating sequence of electron-rich five-membered rings and electron-deficient seven-membered rings [centroid–centroid distances = 3.5413 (12), 3.6847 (12), 3.5790 (12) and 3.7718 (12) ].
The Tayler instability at low magnetic Prandtl numbers: between chiral symmetry breaking and helicity oscillations
Norbert Weber,Vladimir Galindo,Frank Stefani,Tom Weier
Physics , 2015,
Abstract: The Tayler instability is a kink-type, current driven instability that plays an important role in plasma physics but might also be relevant in liquid metal applications with high electrical currents. In the framework of the Tayler-Spruit dynamo model of stellar magnetic field generation, the question of spontaneous helical (chiral) symmetry breaking during the saturation of the Tayler instability has received considerable interest. Focusing on fluids with low magnetic Prandtl numbers, for which the quasistatic approximation can be applied, we utilize an integro-differential equation approach in order to investigate the saturation mechanism of the Tayler instability. Both the exponential growth phase and the saturated phase are analyzed in terms of the action of the alpha and beta effects of mean-field magnetohydrodynamics. In the exponential growth phase we always find a spontaneous chiral symmetry breaking which, however, disappears in the saturated phase. For higher degrees of supercriticality, we observe helicity oscillations in the saturated regime. For Lundquist numbers in the order of one we also obtain chiral symmetry breaking of the saturated magnetic field.
Numerical simulation of the Tayler instability in liquid metals
Norbert Weber,Vladimir Galindo,Frank Stefani,Tom Weier,Thomas Wondrak
Physics , 2012, DOI: 10.1088/1367-2630/15/4/043034
Abstract: The electrical current through an incompressible, viscous and resistive liquid conductor produces an azimuthal magnetic field that becomes unstable when the corresponding Hartmann number exceeds a critical value in the order of 20. This Tayler instability, which is not only discussed as a key ingredient of a non-linear stellar dynamo model (Tayler-Spruit dynamo), but also as a limiting factor for the maximum size of large liquid metal batteries, was recently observed experimentally in a column of a liquid metal (Seilmayer et al., Phys. Rev. Lett. 108, 244501, 2012}. On the basis of an integro-differential equation approach, we have developed a fully three-dimensional numerical code, and have utilized it for the simulation of the Tayler instability at typical viscosities and resistivities of liquid metals. The resulting growth rates are in good agreement with the experimental data. We illustrate the capabilities of the code for the detailed simulation of liquid metal battery problems in realistic geometries.
Current-driven flow instabilities in large-scale liquid metal batteries, and how to tame them
Norbert Weber,Vladimir Galindo,Frank Stefani,Tom Weier
Physics , 2013,
Abstract: The use of liquid metal batteries is considered as one promising option for electric grid stabilisation. While large versions of such batteries are preferred in view of the economies of scale, they are susceptible to various magnetohydrodynamic instabilities which imply a risk of short-circuiting the battery due to the triggered fluid flow. Here we focus on the current driven Tayler instability and give critical electrical currents for its onset as well as numerical estimates for the appearing flow structures and speeds. Scaling laws for different materials, battery sizes and geometries are found. We further discuss and compare various means for preventing the instability.
Algorithms for Kullback-Leibler Approximation of Probability Measures in Infinite Dimensions
Frank J. Pinski,Gideon Simpson,Andrew M. Stuart,Hendrik Weber
Mathematics , 2014,
Abstract: In this paper we study algorithms to find a Gaussian approximation to a target measure defined on a Hilbert space of functions; the target measure itself is defined via its density with respect to a reference Gaussian measure. We employ the Kullback-Leibler divergence as a distance and find the best Gaussian approximation by minimizing this distance. It then follows that the approximate Gaussian must be equivalent to the Gaussian reference measure, defining a natural function space setting for the underlying calculus of variations problem. We introduce a computational algorithm which is well-adapted to the required minimization, seeking to find the mean as a function, and parameterizing the covariance in two different ways: through low rank perturbations of the reference covariance; and through Schr\"odinger potential perturbations of the inverse reference covariance. Two applications are shown: to a nonlinear inverse problem in elliptic PDEs, and to a conditioned diffusion process. We also show how the Gaussian approximations we obtain may be used to produce improved pCN-MCMC methods which are not only well-adapted to the high-dimensional setting, but also behave well with respect to small observational noise (resp. small temperatures) in the inverse problem (resp. conditioned diffusion).
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