LinkEHR-Ed: A multi-reference model archetype editor based on formal semantics

Purpose To develop a powerful archetype editing framework capable of handling multiple reference models and oriented towards the semantic description and standardization of legacy data. Methods The main prerequisite for implementing tools providing enhanced support for archetypes is the clear specification of archetype semantics. We propose a formalization of the definition section of archetypes based on types over tree-structured data. It covers the specialization of archetypes, the relationship between reference models and archetypes and conformance of data instances to archetypes. Results LinkEHR-Ed, a visual archetype editor based on the former formalization with advanced processing capabilities that supports multiple reference models, the editing and semantic validation of archetypes, the specification of mappings to data sources, and the automatic generation of data transformation scripts, is developed. Conclusions LinkEHR-Ed is a useful tool for building, processing and validating archetypes based on any reference model.This work was supported in part by the Spanish Ministry of Education and Science under grant TS12007-66S7S-C02; by the Generalitat Valenciana under grant APOSTD/2007/055 and by the program PAID-06-07 de la Universidad Politecnica de Valencia.Maldonado Segura, JA.; Moner Cano, D.; Boscá Tomás, D.; Fernandez Breis, JT.; Angulo Fernández, C.; Robles Viejo, M. (2009). LinkEHR-Ed: A multi-reference model archetype editor based on formal semantics. International Journal of Medical Informatics. 78(8):559-570. https://doi.org/10.1016/j.ijmedinf.2009.03.006S55957078

Non-invasive lightweight integration engine for building EHR from autonomous distributed systems

[EN] In this paper we describe Pangea-LE, a message-oriented lightweight data integration engine that allows homogeneous and concurrent access to clinical information from disperse and heterogeneous data sources. The engine extracts the information and passes it to the requesting client applications in a flexible XML format. The XML response message can be formatted on demand by appropriate Extensible Stylesheet Language (XSL) transformations in order to meet the needs of client applications. We also present a real deployment in a hospital where Pangea-LE collects and generates an XML view of all the available patient clinical information. The information is presented to healthcare professionals in an Electronic Health Record (EHR) viewer Web application with patient search and EHR browsing capabilities. Implantation in a real setting has been a success due to the non-invasive nature of Pangea-LE which respects the existing information systems.This work was partially funded by the Spanish Ministry of Science and Technology (MEC-TSI2004-06475-102-01) and the Spanish Ministry of Health (PI052245)Angulo Fernández, C.; Crespo Molina, PM.; Maldonado Segura, JA.; Moner Cano, D.; Perez Cuesta, D.; Abad, I.; Mandingorra Gimenez, J.... (2007). Non-invasive lightweight integration engine for building EHR from autonomous distributed systems. International Journal of Medical Informatics. 76(Supplement 3):417-424. https://doi.org/10.1016/j.ijmedinf.2007.05.002S41742476Supplement

Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE) Conceptual Design Report Volume 2: The Physics Program for DUNE at LBNF

The Physics Program for the Deep Underground Neutrino Experiment (DUNE) at the Fermilab Long-Baseline Neutrino Facility (LBNF) is described

Remote Data Retrieval for Bioinformatics Applications: An Agent Migration Approach

Some of the approaches have been developed to retrieve data automatically from one or multiple remote biological data sources. However, most of them require researchers to remain online and wait for returned results. The latter not only requires highly available network connection, but also may cause the network overload. Moreover, so far none of the existing approaches has been designed to address the following problems when retrieving the remote data in a mobile network environment: (1) the resources of mobile devices are limited; (2) network connection is relatively of low quality; and (3) mobile users are not always online. To address the aforementioned problems, we integrate an agent migration approach with a multi-agent system to overcome the high latency or limited bandwidth problem by moving their computations to the required resources or services. More importantly, the approach is fit for the mobile computing environments. Presented in this paper are also the system architecture, the migration strategy, as well as the security authentication of agent migration. As a demonstration, the remote data retrieval from GenBank was used to illustrate the feasibility of the proposed approach

COMPASS identifies T-cell subsets correlated with clinical outcomes.

Advances in flow cytometry and other single-cell technologies have enabled high-dimensional, high-throughput measurements of individual cells as well as the interrogation of cell population heterogeneity. However, in many instances, computational tools to analyze the wealth of data generated by these technologies are lacking. Here, we present a computational framework for unbiased combinatorial polyfunctionality analysis of antigen-specific T-cell subsets (COMPASS). COMPASS uses a Bayesian hierarchical framework to model all observed cell subsets and select those most likely to have antigen-specific responses. Cell-subset responses are quantified by posterior probabilities, and human subject-level responses are quantified by two summary statistics that describe the quality of an individual's polyfunctional response and can be correlated directly with clinical outcome. Using three clinical data sets of cytokine production, we demonstrate how COMPASS improves characterization of antigen-specific T cells and reveals cellular 'correlates of protection/immunity' in the RV144 HIV vaccine efficacy trial that are missed by other methods. COMPASS is available as open-source software