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Amsterdam-Zuidoost, Netherlands

Fagoe N.D.,Institute of the Royal Academy of Arts and science | Eggers R.,Institute of the Royal Academy of Arts and science | Verhaagen J.,Institute of the Royal Academy of Arts and science | Verhaagen J.,Vrije Universtiteit Amsterdam | Mason M.R.J.,Institute of the Royal Academy of Arts and science
Gene Therapy | Year: 2014

Adeno-associated viral (AAV) vectors based on serotype 5 are an efficient means to target dorsal root ganglia (DRG) to study gene function in the primary sensory neurons of the peripheral nervous system. In this study, we have developed a compact AAV dual promoter vector composed of the cytomegalovirus (CMV) and chicken beta-actin (CAG) promoters in a back-to-back configuration with a shared enhancer, and show efficient expression of two proteins simultaneously in DRG neurons. We demonstrate how this is useful for experiments on axonal regeneration, by co-expressing a gene of interest and an axonal marker. Using a farnesylated form of eGFP, which is actively transported along axons, we show superior long-distance labelling of axons of DRG neurons compared with normal eGFP. Additionally, we have efficiently transduced lumbar DRG neurons by injecting the AAV dual promoter vector into the dorsal intrathecal space, which is a less invasive delivery method. In summary, we have developed an AAV dual promoter vector designed for simultaneous expression of a gene of interest and a fluorescent protein to label long-distance axonal projections, which allows specific quantification of axons from transduced neurons after injury. © 2014 Macmillan Publishers Limited.

Tagni G.,Vrije Universtiteit Amsterdam | Schlobach S.,Vrije Universtiteit Amsterdam | Ten Teije A.,Vrije Universtiteit Amsterdam | Van Harmelen F.,Vrije Universtiteit Amsterdam | Karafotias G.,Vrije Universtiteit Amsterdam
Frontiers in Artificial Intelligence and Applications | Year: 2010

Reasoning is computationally expensive. This is especially true for reasoning on the Web, where data sets are very large and often described by complex terminologies. One way to reduce this complexity is through the use of approximate reasoning methods which trade one computational property (eg. quality of answers) for others, such as time and memory. Previous research into approximation on the Semantic Web has been rather ad-hoc, and we propose a framework for systematically studying such methods. We developed a workbench which allows the structured combination of different algorithms for approximation, reasoning and measuring in one single framework. As a case-study we investigate an incremental method for instance retrieval through ontology approximation, and we use our workbench to study the computational behaviour of several approximation strategies. © 2011 The authors and IOS Press. All rights reserved.

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