Wirkung von Adenosin auf reizinduzierte Aktivität im Hippocampus der Ratte unter nicht-epileptiformen und epileptiformen Bedingungen (in vitro)

Gegenstand der vorliegenden Arbeit war die Analyse der Wirkung von Adenosin auf reizinduzierte Aktivität im Hippocampus der Ratte unter nicht-epileptiformen und epileptiformen Bedingungen. Dazu wurden die synaptischen Eingänge der CA1-Region bei Stimulation der Schafferkollateralen untersucht. Zur Erfassung räumlich-zeitlicher Aktivitätsmuster diente ein spannungsempfindlicher Farbstoff und ein schnelles optisches Ableitverfahren. Die Erzeugung epileptiformer Potentiale erfolgte durch das 0 Mg2+-Epilepsie-Modell. Applikation von Adenosin führte in nahezu allen Versuchen zu einer Reduktion der Signalamplitude. Das Ausmaß der Reduktion war abhängig von der applizierten Adenosinkonzentration und Reizstärke. Eine signifikante Reduktion der Erregung war vor allem unter epileptiformen Versuchsbedingungen zu beobachten. Folglich übt Adenosin seine inhibitorische Wirkung in Abhängigkeit vom vorherrschenden neuronalen Aktivitätsniveau aus und kann als neuro-modulatorisch klassifiziert werden

Two Phase Description Logic Reasoning for Efficient Information Retrieval

Description Logics are used more and more frequently for knowledge representation, creating an increasing demand for efficient automated DL reasoning. However, the existing implementations are inefficient in the presence of large amounts of data. This paper summarizes the results in transforming DL axioms to a set of function-free clauses of first-order logic which can be used for efficient, query oriented data reasoning. The described method has been implemented in a module of the DLog reasoner openly available on SourceForge to download

A Semantic Model for Enhancing Network Services Management and Auditing

The road toward ubiquity, heterogeneity and virtualization of network services and resources urges for a formal and systematic approach to network management tasks. In particular, the semantic characterization and modeling of services provided to users assume an essential role in fostering autonomic service management, service negotiation and auditing. This paper is centered on the definition of an ontology for multiservice IP networks which intends to address multiple service management goals, namely: (i) to foster client and service provider interoperability; (ii) to manage network service contracts, facilitating the dynamic negotiation between clients and ISPs; (iii) to access and query SLA/SLSs data on an individual or aggregated basis to assist service provisioning in the network; and (iv) to sustain service monitoring and auditing. In order to take full advantage of the proposed semantic model, a service model API is provided to allow service management platforms to access the ontological contents. This ontological development also takes advantage of SWRL to discover new knowledge, enriching the possibilities of systems described using this support

How Can Reasoner Performance of ABox Intensive Ontologies Be Predicted?

Reasoner performance prediction of ontologies in OWL 2 language has been studied so far from different dimensions. One key aspect of these studies has been the prediction of how much time a particular task for a given ontology will consume. Several approaches have adopted different machine learning techniques to predict time consumption of ontologies already. However, these studies focused on capturing general aspects of the ontologies (i.e., mainly the complexity of their TBoxes), while paying little attention to ABox intensive ontologies. To address this issue, in this paper, we propose to improve the representativeness of ontology metrics by developing new metrics which focus on the ABox features of ontologies. Our experiments show that the proposed metrics contribute to overall prediction accuracy for all ontologies in general without causing side-effects

Answering SPARQL queries over databases under OWL 2 QL entailment regime

We present an extension of the ontology-based data access platform Ontop that supports answering SPARQL queries under the OWL 2 QL direct semantics entailment regime for data instances stored in relational databases. On the theoretical side, we show how any input SPARQL query, OWL 2 QL ontology and R2RML mappings can be rewritten to an equivalent SQL query solely over the data. On the practical side, we present initial experimental results demonstrating that by applying the Ontop technologies—the tree-witness query rewriting, T-mappings compiling R2RML mappings with ontology hierarchies, and T-mapping optimisations using SQL expressivity and database integrity constraints—the system produces scalable SQL queries

Correlation of gene expression with magnetic resonance imaging features of retinoblastoma: a multi-center radiogenomics validation study.

To validate associations between MRI features and gene expression profiles in retinoblastoma, thereby evaluating the repeatability of radiogenomics in retinoblastoma. In this retrospective multicenter cohort study, retinoblastoma patients with gene expression data and MRI were included. MRI features (scored blinded for clinical data) and matched genome-wide gene expression data were used to perform radiogenomic analysis. Expression data from each center were first separately processed and analyzed. The end product normalized expression values from different sites were subsequently merged by their Z-score to permit cross-sites validation analysis. The MRI features were non-parametrically correlated with expression of photoreceptorness (radiogenomic analysis), a gene expression signature informing on disease progression. Outcomes were compared to outcomes in a previous described cohort. Thirty-six retinoblastoma patients were included, 15 were female (42%), and mean age was 24 (SD 18) months. Similar to the prior evaluation, this validation study showed that low photoreceptorness gene expression was associated with advanced stage imaging features. Validated imaging features associated with low photoreceptorness were multifocality, a tumor encompassing the entire retina or entire globe, and a diffuse growth pattern (all p < 0.05). There were a number of radiogenomic associations that were also not validated. A part of the radiogenomic associations could not be validated, underlining the importance of validation studies. Nevertheless, cross-center validation of imaging features associated with photoreceptorness gene expression highlighted the capability radiogenomics to non-invasively inform on molecular subtypes in retinoblastoma. Radiogenomics may serve as a surrogate for molecular subtyping based on histopathology material in an era of eye-sparing retinoblastoma treatment strategies. • Since retinoblastoma is increasingly treated using eye-sparing methods, MRI features informing on molecular subtypes that do not rely on histopathology material are important. • A part of the associations between retinoblastoma MRI features and gene expression profiles (radiogenomics) were validated. • Radiogenomics could be a non-invasive technique providing information on the molecular make-up of retinoblastoma

Steinert's syndrome presenting as anal incontinence: a case report

<p>Abstract</p> <p>Introduction</p> <p>Myotonic dystrophy (MD) or Steinert's syndrome is a rare cause of chronic diarrhea and anal incontinence. In the presence of chronic diarrhea and fecal incontinence with muscle weakness, neuromuscular disorders such as myotonic dystrophy should be considered in the differential diagnosis.</p> <p>Case Presentation</p> <p>We present the case of a 45-year-old Turkish man with Steinert's syndrome, who was not diagnosed until the age of 45.</p> <p>Conclusions</p> <p>In clinical practice, the persistence of diarrhea and fecal incontinence with muscle weakness should suggest that the physician perform an anal manometric study and electromyography. Neuromuscular disorders such as myotonic dystrophy should be considered in the differential diagnosis.</p

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results