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Bonn, Germany

The University of Bonn is a public research university located in Bonn, Germany. Founded in its present form in 1818, as the linear successor of earlier academic institutions, the University of Bonn is today one of the leading universities in Germany. The University of Bonn offers a large number of undergraduate and graduate programs in a range of subjects. Its library holds more than two million volumes. The University of Bonn has 525 professors and 31,000 students. Among its notable alumni and faculty are seven Nobel Laureates, two Fields Medalists, twelve Gottfried Wilhelm Leibniz Prize winners, Prince Albert, Pope Benedict XVI, Frederick III, Karl Marx, Heinrich Heine, Friedrich Nietzsche, Konrad Adenauer, and Joseph Schumpeter. In the years 2010, 2011 and 2013, the Times Higher Education ranked the University of Bonn as one of the 200 best universities in the world. The University of Bonn is ranked 94th worldwide according to the ARWU University ranking. Wikipedia.

Staub F.,University of Bonn
Computer Physics Communications | Year: 2014

We present the new version of the Mathematica package SARAH which provides the same features for a non-supersymmetric model as previous versions for supersymmetric models. This includes an easy and straightforward definition of the model, the calculation of all vertices, mass matrices, tadpole equations, and self-energies. Also the two-loop renormalization group equations for a general gauge theory are now included and have been validated with the independent Python code PyR@TE. Model files for FeynArts, CalcHep/CompHep, WHIZARD and in the UFO format can be written, and source code for SPheno for the calculation of the mass spectrum, a set of precision observables, and the decay widths and branching ratios of all states can be generated. Furthermore, the new version includes routines to output model files for Vevacious for both, supersymmetric and non-supersymmetric, models. Global symmetries are also supported with this version and by linking Susyno the handling of Lie groups has been improved and extended. Program summary Program title: SARAH Catalogue identifier: AEIB-v3-0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ AEIB-v3-0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 271 795 No. of bytes in distributed program, including test data, etc.: 2 612 867 Distribution format: tar.gz Programming language: Mathematica. Computer: All for which Mathematica is available. Operating system: All for which Mathematica is available. Classification: 11.1, 11.6. Catalogue identifier of previous version: AEIB-v2-1 Journal reference of previous version: Comput. Phys. Commun. 184 (2013) 2604 Does the new version supersede the previous version?: Yes, the new version includes all known features of the previous versions but also provides the new features mentioned below. Nature of problem: A supersymmetric model is usually characterized by the particle content, the gauge sector and the superpotential. It is a time consuming process to obtain all necessary information for phenomenological studies from these basic ingredients. Solution method: Non-supersymmetric models are supported by the new possibility to define not only chiral superfields but also component fields. The renormalization group equations (RGEs) for a non-supersymmetric models are calculated by using the generic formulae for a general quantum field theory. Reasons for new version: New features in the definition of models and a full support of non-supersymmetric models. New output for Vevacious. Summary of revisions: Support of non-supersymmetric models; calculation of renormalization group equations for a general gauge theory; link to Susyno for handling of non-SU(N) gauge groups; support of global symmetries; output of model files for Vevacious; support of aligned VEVs; calculation of gauge dependent parts of RGEs for VEVs in running of supersymmetric and non-supersymmetric models. Restrictions: Only renormalizable terms in the Lagrangian are supported. No support of fields with spin 2 or 3/2. Unusual features: Calculation of non-supersymmetric RGEs includes effects of kinetic mixing as well as gauge dependence of running vacuum expectation values. SARAH is the first tool which can automatically create model files for Vevacious. Fully automatized derivation of all terms in the Lagrangian which are fixed by gauge invariance. Running time: Loading the Standard Model: 1.6 s; calculation of all vertices: 11.8 s; calculation of all RGEs: 130.2 s; output for Vevacious model files: 0.1 s; output of model files in UFO format: 0.8 s; output of model files for FeynArts: 0.1 s; output of model files for CalcHep: 0.8 s; output of model files for WHIZARD: 3.5 s; writing of source code for SPheno: 34.5 s. All times measured on Lenovo X220 with Intel(R) Core(TM) i7-2620M CPU @ 2.70 GHz. © 2014 Elsevier B.V. All rights reserved.

Klockgether T.,University of Bonn
The Lancet Neurology | Year: 2010

In most patients with adult-onset progressive ataxia, the condition manifests without an obvious familial background. The classification and correct diagnosis of such patients remain a challenge, because almost the entire spectrum of non-genetic and genetic causes of ataxia has to be considered. A wide range of potential causes of acquired ataxia exist, including chronic alcohol use, various other toxic agents, immune-mediated inflammation, vitamin deficiency, chronic leptomeningeal deposition of iron leading to superficial siderosis, and chronic CNS infection. Mutations in single genes can also underlie sporadic ataxia in adults. Finally, patients might have a sporadic degenerative disease, such as multiple system atrophy of cerebellar type or sporadic adult-onset ataxia of unknown aetiology. The definition of clinical criteria and delineation of characteristic MRI features have greatly facilitated the early and correct recognition of sporadic ataxias. In addition, specific serological and genetic markers are available that allow a definite diagnosis in many cases. © 2010 Elsevier Ltd. All rights reserved.

Bilkei-Gorzo A.,University of Bonn
Pharmacology and Therapeutics | Year: 2014

Progression of brain ageing is influenced by a complex interaction of genetic and environmental factors. Analysis of genetically modified animals with uniform genetic backgrounds in a standardised, controlled environment enables the dissection of critical determinants of brain ageing on a molecular level. Human and animal studies suggest that increased load of damaged macromolecules, efficacy of DNA maintenance, mitochondrial activity, and cellular stress defences are critical determinants of brain ageing. Surprisingly, mouse lines with genetic impairment of anti-oxidative capacity generally did not show enhanced cognitive ageing but rather an increased sensitivity to oxidative challenge. Mouse lines with impaired mitochondrial activity had critically short life spans or severe and rapidly progressing neurodegeneration. Strains with impaired clearance in damaged macromolecules or defects in the regulation of cellular stress defences showed alterations in the onset and progression of cognitive decline. Importantly, reduced insulin/insulin-like growth factor signalling generally increased life span but impaired cognitive functions revealing a complex interaction between ageing of the brain and of the body. Brain ageing is accompanied by an increased risk of developing Alzheimer's disease. Transgenic mouse models expressing high levels of mutant human amyloid precursor protein showed a number of symptoms and pathophysiological processes typical for early phase of Alzheimer's disease. Generally, therapeutic strategies effective against Alzheimer's disease in humans were also active in the Tg2576, APP23, APP/PS1 and 5xFAD lines, but a large number of false positive findings were also reported. The 3xtg AD model likely has the highest face and construct validity but further studies are needed. © 2013 Elsevier Inc.

Voos W.,University of Bonn
Biochimica et Biophysica Acta - Molecular Cell Research | Year: 2013

As essential organelles, mitochondria are intimately integrated into the metabolism of a eukaryotic cell. The maintenance of the functional integrity of the mitochondrial proteome, also termed protein homeostasis, is facing many challenges both under normal and pathological conditions. First, since mitochondria are derived from bacterial ancestor cells, the proteins in this endosymbiotic organelle have a mixed origin. Only a few proteins are encoded on the mitochondrial genome, most genes for mitochondrial proteins reside in the nuclear genome of the host cell. This distribution requires a complex biogenesis of mitochondrial proteins, which are mostly synthesized in the cytosol and need to be imported into the organelle. Mitochondrial protein biogenesis usually therefore comprises complex folding and assembly processes to reach an enzymatically active state. In addition, specific protein quality control (PQC) processes avoid an accumulation of damaged or surplus polypeptides. Mitochondrial protein homeostasis is based on endogenous enzymatic components comprising a diverse set of chaperones and proteases that form an interconnected functional network. This review describes the different types of mitochondrial proteins with chaperone functions and covers the current knowledge of their roles in protein biogenesis, folding, proteolytic removal and prevention of aggregation, the principal reactions of protein homeostasis. This article is part of a Special Issue entitled: Protein Import and Quality Control in Mitochondria and Plastids. © 2012 Elsevier B.V.

The Janus kinase (JAK)-inhibitor ruxolitinib decreases constitutional symptoms and spleen size of myelofibrosis (MF) patients by mechanisms distinct from its anticlonal activity. Here we investigated whether ruxolitinib affects dendritic cell (DC) biology. The in vitro development of monocyte-derived DCs was almost completely blocked when the compound was added throughout the differentiation period. Furthermore, when applied solely during the final lipopolysaccharide-induced maturation step, ruxolitinib reduced DC activation as demonstrated by decreased interleukin-12 production and attenuated expression of activation markers. Ruxolitinib also impaired both in vitro and in vivo DC migration. Dysfunction of ruxolitinib-exposed DCs was further underlined by their impaired induction of allogeneic and antigen-specific T-cell responses. Ruxolitinib-treated mice immunized with ovalbumin (OVA)/CpG induced markedly reduced in vivo activation and proliferation of OVA-specific CD8+ T cells compared with vehicle-treated controls. Finally, using an adenoviral infection model, we show that ruxolitinib-exposed mice exhibit delayed adenoviral clearance. Our results demonstrate that ruxolitinib significantly affects DC differentiation and function leading to impaired T-cell activation. DC dysfunction may result in increased infection rates in ruxolitinib-treated patients. However, our findings may also explain the outstanding anti-inflammatory and immunomodulating activity of JAK inhibitors currently used in the treatment of MF and autoimmune diseases.

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