470 research outputs found

    Get my pizza right: Repairing missing is-a relations in ALC ontologies (extended version)

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    With the increased use of ontologies in semantically-enabled applications, the issue of debugging defects in ontologies has become increasingly important. These defects can lead to wrong or incomplete results for the applications. Debugging consists of the phases of detection and repairing. In this paper we focus on the repairing phase of a particular kind of defects, i.e. the missing relations in the is-a hierarchy. Previous work has dealt with the case of taxonomies. In this work we extend the scope to deal with ALC ontologies that can be represented using acyclic terminologies. We present algorithms and discuss a system

    OWL-POLAR : semantic policies for agent reasoning

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    The original publication is available at www.springerlink.comPostprin

    The limits of social class in explaining ethnic gaps in educational attainment

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    This paper reports an analysis of the educational attainment and progress between age 11 and age 14 of over 14,500 students from the nationally representative Longitudinal Study of Young People in England (LSYPE). The mean attainment gap in national tests at age 14 between White British and several ethnic minority groups were large, more than three times the size of the gender gap, but at the same time only about one-third of the size of the social class gap. Socio-economic variables could account for the attainment gaps for Black African, Pakistani and Bangladeshi students, but not for Black Caribbean students. Further controls for parental and student attitudes, expectations and behaviours indicated minority ethnic groups were on average more advantaged on these measures than White British students, but this was not reflected proportionately in their levels of attainment. Black Caribbean students were distinctive as the only group making less progress than White British students between age 11 and 14 and this could not be accounted for by any of the measured contextual variables. Possible explanations for the White British-Black Caribbean gap are considered

    Collagen matricryptin promotes cardiac function by mediating scar formation

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    This is an open access article under the CC BY-NC-ND license.Aims A peptide mimetic of a collagen-derived matricryptin (p1159) was shown to reduce left ventricular (LV) dilation and fibrosis after 7 days delivery in a mouse model of myocardial infarction (MI). This suggested p1159 long-term treatment post-MI could have beneficial effects and reduce/prevent adverse LV remodeling. This study aimed to test the potential of p1159 to reduce adverse cardiac remodeling in a chronic MI model and to elucidate p1159 mode-of-action. Materials and methods Using a permanent occlusion MI rodent model, animals received p1159 or vehicle solution up to 28 days. We assessed peptide treatment effects on scar composition and structure and on systolic function. To assess peptide effects on scar vascularization, a cohort of mice were injected with Griffonia simplicifolia isolectin-B4. To investigate p1159 mode-of-action, LV fibroblasts from naïve animals were treated with increasing doses of p1159. Key findings Matricryptin p1159 significantly improved systolic function post-MI (2-fold greater EF compared to controls) by reducing left ventricular dilation and inducing the formation of a compliant and organized infarct scar, which promoted LV contractility and preserved the structural integrity of the heart. Specifically, infarcted scars from p1159-treated animals displayed collagen fibers aligned parallel to the epicardium, to resist circumferential stretching, with reduced levels of cross-linking, and improved tissue perfusion. In addition, we found that p1159 increases cardiac fibroblast migration by activating RhoA pathways via the membrane receptor integrin α4. Significance Our data indicate p1159 treatment reduced adverse LV remodeling post-MI by modulating the deposition, arrangement, and perfusion of the fibrotic scar.ECU Open Access Publishing Support Fun

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

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    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

    Analytic Metaphysics versus Naturalized Metaphysics: The Relevance of Applied Ontology

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    The relevance of analytic metaphysics has come under criticism: Ladyman & Ross, for instance, have suggested do discontinue the field. French & McKenzie have argued in defense of analytic metaphysics that it develops tools that could turn out to be useful for philosophy of physics. In this article, we show first that this heuristic defense of metaphysics can be extended to the scientific field of applied ontology, which uses constructs from analytic metaphysics. Second, we elaborate on a parallel by French & McKenzie between mathematics and metaphysics to show that the whole field of analytic metaphysics, being useful not only for philosophy but also for science, should continue to exist as a largely autonomous field

    Annotations for Rule-Based Models

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    The chapter reviews the syntax to store machine-readable annotations and describes the mapping between rule-based modelling entities (e.g., agents and rules) and these annotations. In particular, we review an annotation framework and the associated guidelines for annotating rule-based models of molecular interactions, encoded in the commonly used Kappa and BioNetGen languages, and present prototypes that can be used to extract and query the annotations. An ontology is used to annotate models and facilitate their description

    RDFScape: Semantic Web meets Systems Biology

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    <p>Abstract</p> <p>Background</p> <p>The recent availability of high-throughput data in molecular biology has increased the need for a formal representation of this knowledge domain. New ontologies are being developed to formalize knowledge, e.g. about the functions of proteins. As the Semantic Web is being introduced into the Life Sciences, the basis for a distributed knowledge-base that can foster biological data analysis is laid. However, there still is a dichotomy, in tools and methodologies, between the use of ontologies in biological investigation, that is, in relation to experimental observations, and their use as a knowledge-base.</p> <p>Results</p> <p>RDFScape is a plugin that has been developed to extend a software oriented to biological analysis with support for reasoning on ontologies in the semantic web framework. We show with this plugin how the use of ontological knowledge in biological analysis can be extended through the use of inference. In particular, we present two examples relative to ontologies representing biological pathways: we demonstrate how these can be abstracted and visualized as interaction networks, and how reasoning on causal dependencies within elements of pathways can be implemented.</p> <p>Conclusions</p> <p>The use of ontologies for the interpretation of high-throughput biological data can be improved through the use of inference. This allows the use of ontologies not only as annotations, but as a knowledge-base from which new information relevant for specific analysis can be derived.</p

    SOWL QL: Querying Spatio - Temporal Ontologies in OWL

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    We introduce SOWL QL, a query language for spatio-temporal information in ontologies. Buildingupon SOWL (Spatio-Temporal OWL), an ontology for handling spatio-temporal information in OWL, SOWL QL supports querying over qualitative spatio-temporal information (expressed using natural language expressions such as “before”, “after”, “north of”, “south of”) rather than merely quantitative information (exact dates, times, locations). SOWL QL extends SPARQL with a powerful set of temporal and spatial operators, including temporal Allen topological, spatial directional and topological operations or combinations of the above. SOWL QL maintains simplicity of expression and also, upward and downward compatibility with SPARQL. Query translation in SOWL QL yields SPARQL queries implying that, querying spatio-temporal ontologies using SPARQL is still feasible but suffers from several drawbacks the most important of them being that, queries in SPARQL become particularly complicated and users must be familiar with the underlying spatio-temporal representation (the “N-ary relations” or the “4D-fluents” approach in this work). Finally, querying in SOWL QL is supported by the SOWL reasoner which is not part of the standard SPARQL translation. The run-time performance of SOWL QL has been assessed experimentally in a real data setting. A critical analysis of its performance is also presented

    Ambient-aware continuous care through semantic context dissemination

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    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
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