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Steinau an der Strasse, Germany

Danker T.,NMI TT GmbH | Moller C.,Albstadt-Sigmaringen University of Applied Sciences
Frontiers in Pharmacology | Year: 2014

Blockade of the cardiac ion channel coded by hERG can lead to cardiac arrhythmia, which has become a major concern in drug discovery and development. Automated electrophysiological patch clamp allows assessment of hERG channel effects early in drug development to aid medicinal chemistry programs and has become routine in pharmaceutical companies. However, a number of potential sources of errors in setting up hERG channel assays by automated patch clamp can lead to misinterpretation of data or false effects being reported. This article describes protocols for automated electrophysiology screening of compound effects on the hERG channel current. Protocol details and the translation of criteria known from manual patch clamp experiments to automated patch clamp experiments to achieve good quality data are emphasized. Typical pitfalls and artifacts that may lead to misinterpretation of data are discussed. While this article focuses on hERG channel recordings using the QPatch (Sophion A/S, Copenhagen, Denmark) technology, many of the assay and protocol details given in this article can be transferred for setting up different ion channel assays by automated patch clamp and are similar on other planar patch clamp platforms. © 2014 Danker and Möller.

Jekerle V.,European Medicines Agency | Schroder C.,Albstadt-Sigmaringen University of Applied Sciences | Pedone E.,European Medicines Agency
Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz | Year: 2010

Advanced therapy medicinal products consist of gene therapy, somatic cell therapy and tissue engineered products. Due to their specific manufacturing process and mode of action these products require specially tailored legislation. With Regulation (EC) No. 1394/2007, these needs have been met. Definitions of gene therapy, somatic cell therapy and tissue engineered products were laid down. A new committee, the Committee for Advanced Therapies, was founded, special procedures such as the certification procedure for small- and medium-sized enterprises were established and the technical requirements for Marketing Authorisation Applications (quality, non-clinical and clinical) were revised. © 2009 Springer Medizin Verlag.

Palm G.,University of Ulm | Knoblauch A.,Honda Corporation | Knoblauch A.,Albstadt-Sigmaringen University of Applied Sciences | Hauser F.,University of Ulm | Schuz A.,MPI for Biological Cybernetics
Biological Cybernetics | Year: 2014

Donald Hebb’s concept of cell assemblies is a physiology-based idea for a distributed neural representation of behaviorally relevant objects, concepts, or constellations. In the late 70s Valentino Braitenberg started the endeavor to spell out the hypothesis that the cerebral cortex is the structure where cell assemblies are formed, maintained and used, in terms of neuroanatomy (which was his main concern) and also neurophysiology. This endeavor has been carried on over the last 30 years corroborating most of his findings and interpretations. This paper summarizes the present state of cell assembly theory, realized in a network of associative memories, and of the anatomical evidence for its location in the cerebral cortex. © 2014, Springer-Verlag Berlin Heidelberg.

Knoblauch A.,Albstadt-Sigmaringen University of Applied Sciences | Knoblauch A.,Honda Research Institute Europe | Korner E.,Honda Research Institute Europe | Korner U.,Honda Research Institute Europe | Sommer F.T.,University of California at Berkeley
PLoS ONE | Year: 2014

Although already William James and, more explicitly, Donald Hebb's theory of cell assemblies have suggested that activity dependent rewiring of neuronal networks is the substrate of learning and memory, over the last six decades most theoretical work on memory has focused on plasticity of existing synapses in prewired networks. Research in the last decade has emphasized that structural modification of synaptic connectivity is common in the adult brain and tightly correlated with learning and memory. Here we present a parsimonious computational model for learning by structural plasticity. The basic modeling units are "potential synapses" defined as locations in the network where synapses can potentially grow to connect two neurons. This model generalizes well-known previous models for associative learning based on weight plasticity. Therefore, existing theory can be applied to analyze how many memories and how much information structural plasticity can store in a synapse. Surprisingly, we find that structural plasticity largely outperforms weight plasticity and can achieve a much higher storage capacity per synapse. The effect of structural plasticity on the structure of sparsely connected networks is quite intuitive: Structural plasticity increases the "effectual network connectivity", that is, the network wiring that specifically supports storage and recall of the memories. Further, this model of structural plasticity produces gradients of effectual connectivity in the course of learning, thereby explaining various cognitive phenomena including graded amnesia, catastrophic forgetting, and the spacing effect. © 2014 Knoblauch et al.

Mayer T.,Daimler AG | Kreyenberg D.,Daimler AG | Wind J.,Daimler AG | Braun F.,Albstadt-Sigmaringen University of Applied Sciences
International Journal of Hydrogen Energy | Year: 2012

Vehicles with electric drive trains are currently the subject of intense discussion by society. The cost trends of the individual components in the electric drive train are a central aspect of the future market success of the different vehicle drive systems. An innovative two-factor experience curve approach was developed to facilitate the generation of the most meaningful cost forecasts for these components. This enables the creation of a flexible cost forecast model that supplements the two-factor experience curve approach by an analogous technology component. The performance of the model was demonstrated using alternative drive components, namely the proton exchange membrane (PEM) fuel cell stack, a high energy lithium-ion battery and a high power lithium-ion battery. A comparison of the forecast values calculated using this model with the industry targets determined by McKinsey in the study "A portfolio of power-trains for Europe" [1] shows that the realization of these targets for the fuel cell stack is possible if the product volume increases rapidly enough. For the high energy and high power lithium-ion battery targets, the product volume and research and development activity, measured here in terms of patent growth, need to grow compared to the trend of the last years. © 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

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