BiOSS: A system for biomedical ontology selection

In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing biomedical ontologies, choosing the ones to be used in a semantic annotation problem or to design a specific application is a difficult task. As a consequence, the design of approaches and tools addressed to facilitate the selection of biomedical ontologies is becoming a priority. In this paper we present BiOSS, a novel system for the selection of biomedical ontologies. BiOSS evaluates the adequacy of an ontology to a given domain according to three different criteria: (1) the extent to which the ontology covers the domain; (2) the semantic richness of the ontology in the domain; (3) the popularity of the ontology in the biomedical community. BiOSS has been applied to 5 representative problems of ontology selection. It also has been compared to existing methods and tools. Results are promising and show the usefulness of BiOSS to solve real-world ontology selection problems. BiOSS is openly available both as a web tool and a web service.Instituto de Salud Carlos III; FIS-PI10/02180Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2012/217Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2011/034Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2012/211Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo; ref. 209RT036

Ofiuroideos del Cretácico Inferior de Patagonia: primer registro fósil articulado para el Mesozoico de América del Sur

The first articulated remains of ophiuroids for the Mesozoic of South America are described from the Lower Cretaceous of Neuquén Basin, Argentina. The taxonomic analysis allows the assignment of the material described herein to the extinct genus Ophiopetra. The specimens belong to a new species, but considering the poor preservation, a new name is not introduced, as it would be based on an incomplete diagnosis. Certain characteristics (e.g., the diameter of the disc, the width/height ratio of the vertebrae) suggest that these ophiuroids are paedomorphic specimens. In light of the latest classification of the Ophiuroidea, and new insights on the spine articulation microstructure of Ophiopetra lithographica presented herein, a transfer of Ophiopetra to the family Ophionereididae within the order Amphilepidida is proposed. This material expands the palaeogeographic record of this genus, since it represents the first remains of Ophiopetra described in the Southern Hemisphere. It is also the first Cretaceous record of the genus worldwide.Fil: Fernández, Diana Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; Argentina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias Geológicas; ArgentinaFil: Giachetti, Luciana María. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias Geológicas; ArgentinaFil: Stöhr, Sabine. Swedish Museum of Natural History; SueciaFil: Thuy, Ben. Natural History Museum Luxembourg; LuxemburgoFil: Perez, Damián. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales “Bernardino Rivadavia”; ArgentinaFil: Comerio, Marcos. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Centro de Tecnología de Recursos Minerales y Cerámica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Tecnología de Recursos Minerales y Cerámica; ArgentinaFil: Pazos, Pablo Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Estudios Andinos "Don Pablo Groeber". Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Estudios Andinos "Don Pablo Groeber"; Argentin

The iOSC3 system: using ontologies and SWRL rules for intelligent supervision and care of patients with acute cardiac disorders

[Abstract] Physicians in the Intensive Care Unit (ICU) are specially trained to deal constantly with very large and complex quantities of clinical data and make quick decisions as they face complications. However, the amount of information generated and the way the data are presented may overload the cognitive skills of even experienced professionals and lead to inaccurate or erroneous actions that put patients’ lives at risk. In this paper, we present the design, development, and validation of iOSC3, an ontology-based system for intelligent supervision and treatment of critical patients with acute cardiac disorders. The system analyzes the patient’s condition and provides a recommendation about the treatment that should be administered to achieve the fastest possible recovery. If the recommendation is accepted by the doctor, the system automatically modifies the quantity of drugs that are being delivered to the patient. The knowledge base is constituted by an OWL ontology and a set of SWRL rules that represent the expert’s knowledge. iOSC3 has been developed in collaboration with experts from the Cardiac Intensive Care Unit (CICU) of the Meixoeiro Hospital, one of the most significant hospitals in the northwest region of Spain.Instituto de Salud Carlos III; FIS-PI10/02180Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo; 209RT0366Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2012/217Xunta. Consellería de Cultura, Educación e Ordenación Universitaria; CN2011/034Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2012/21

NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation

[Abstract] Background. Ontologies and controlled terminologies have become increasingly important in biomedical research. Researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability across disparate datasets. However, the number, variety and complexity of current biomedical ontologies make it cumbersome for researchers to determine which ones to reuse for their specific needs. To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms. Methods. We developed a new version of the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a novel recommendation approach that evaluates the relevance of an ontology to biomedical text data according to four different criteria: (1) the extent to which the ontology covers the input data; (2) the acceptance of the ontology in the biomedical community; (3) the level of detail of the ontology classes that cover the input data; and (4) the specialization of the ontology to the domain of the input data. Results. Our evaluation shows that the enhanced recommender provides higher quality suggestions than the original approach, providing better coverage of the input data, more detailed information about their concepts, increased specialization for the domain of the input data, and greater acceptance and use in the community. In addition, it provides users with more explanatory information, along with suggestions of not only individual ontologies but also groups of ontologies to use together. It also can be customized to fit the needs of different ontology recommendation scenarios. Conclusions. Ontology Recommender 2.0 suggests relevant ontologies for annotating biomedical text data. It combines the strengths of its predecessor with a range of adjustments and new features that improve its reliability and usefulness. Ontology Recommender 2.0 recommends over 500 biomedical ontologies from the NCBO BioPortal platform, where it is openly available (both via the user interface at http://bioportal.bioontology.org/recommender, and via a Web service API).National Institutes of Health (United States); U54 HG004028Center for Expanded Data Annotationand Retrieval (CEDAR); U54 AI11792Agence nationale de la recherche (France); NR-12-JS02-0100

Developing a system for advanced monitoring and intelligent drug administration in critical care units using ontologies

Selected paper of the 16th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, 2012 September 10-12, San Sebastian, Spain[Abstract] When a patient enters an intensive care unit (ICU), either after surgery or due to a serious clinical condition, his vital signs are continually changing, forcing the medical experts to make rapid and complex decisions, which frequently imply modifications on the dosage of drugs being administered. Life of patients at critical units depends largely on the wisdom of such decisions. However, the human factor is sometimes a source of mistakes that lead to incorrect or inaccurate actions. This work presents an expert system based on a domain ontology that acquires the vital parameters from the patient monitor, analyzes them and provides the expert with a recommendation regarding the treatment that should be administered. If the expert agrees, the system modifies the drug infusion rates being supplied at the infusion pumps in order to improve the patient's physiological status. The system is being developed at the IMEDIR Center (A Coruña, Spain) and it is being tested at the cardiac intensive care unit (CICU) of the Meixoeiro Hospital (Vigo, Spain), which is a specific type of ICU exclusively aimed to treat patients who have underwent heart surgery or that are affected by a serious coronary disorder.Instituto de Salud Carlos III; FIS-PI10/02180Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo; ref. 209RT0366Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2012/217Galicia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2011/034Galcia. Consellería de Cultura, Educación e Ordenación Universitaria; CN2012/21

Texture analysis in gel electrophoresis images using an integrative kernel-based approach

[Abstract] Texture information could be used in proteomics to improve the quality of the image analysis of proteins separated on a gel. In order to evaluate the best technique to identify relevant textures, we use several different kernel-based machine learning techniques to classify proteins in 2-DE images into spot and noise. We evaluate the classification accuracy of each of these techniques with proteins extracted from ten 2-DE images of different types of tissues and different experimental conditions. We found that the best classification model was FSMKL, a data integration method using multiple kernel learning, which achieved AUROC values above 95% while using a reduced number of features. This technique allows us to increment the interpretability of the complex combinations of textures and to weight the importance of each particular feature in the final model. In particular the Inverse Difference Moment exhibited the highest discriminating power. A higher value can be associated with an homogeneous structure as this feature describes the homogeneity; the larger the value, the more symmetric. The final model is performed by the combination of different groups of textural features. Here we demonstrated the feasibility of combining different groups of textures in 2-DE image analysis for spot detection.Instituto de Salud Carlos III; PI13/00280United Kingdom. Medical Research Council; G10000427, MC_UU_12013/8Galicia. Consellería de Economía e Industria; 10SIN105004P

Variabilidad glucémica y envejecimiento: Estudio de la monitorización continua de glucemia intersticial en Diabetes Mellitus tipo 2

La variabilidad glucémica (VG) se define como la magnitud de las oscilaciones de glucosa en sangre por encima y por debajo del rango de normalidad. Este concepto ha adquirido gran importancia en los últimos años, no solo por ser un factor limitante del tratamiento de la diabetes (por riesgo de hipoglucemias), sino por su relación con la aparición de complicaciones micro/macrovasculares. Las herramientas utilizadas en la clínica habitual para el control de la diabetes mellitus son la hemoglobina glicosilada (HbA1c) y la glucemia capilar (GC). Sin embargo, ni la HbA1c ni la GC aportan una información completa de las oscilaciones glucémicas. La HbA1c es un reflejo de la exposición glucémica global, y la GC nos proporciona el resultado de glucosa en un momento determinado. La monitorización continua de glucemia (MCG) es un sistema que mide la glucosa intersticial de forma continua a lo largo de las 24 horas del día, proporcionando mayor densidad de datos para la estimación de la VG y la detección de la hipoglucemias que la HbA1c y la GC. Sin embargo el uso de la MCG en el control del paciente con diabetes mellitus tipo 2 (DM2) es escaso (especialmente en paciente con DM2 en edad avanzada). El objetivo de este trabajo fue investigar qué nos aporta la monitorización continua de glucemia intersticial en el control de los pacientes con diabetes mellitus tipo 2 estables a tratamiento con insulina con respecto a las herramientas de control habituales (HbA1c y GC)

Redesign and performance of an automatic segmentation method

[Resumen] La información más relevante de las angiografías coronarias se extrae empleando técnicas de segmentación, que pueden ser automáticas, semiautomáticas o manuales. Existen numerosos algoritmos de segmentación vascular, obteniendo mejores resultados, por normal general, aquellos que emplean múltiples técnicas e imágenes a diferentes escalas para proporcionar los resultados requeridos. Se presenta un nuevo método de segmentación automatizado basado en el método manual de Hamarneh incluyendo un estudio estadístico que demuestra su idoneidad para el problema

GesEPOC 2021 and GOLD 2021: perfect is the enemy of good

Carta científic

Reversible Control of DNA Binding with Cucurbit[8]uril-Induced Supramolecular 4,4′-Bipyridinium–Peptide Dimers

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUGThe Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.bioconjchem.1c00063[Abstract] Many cellular processes in living organisms are regulated by complex regulatory networks, built from noncovalent interactions between relatively few proteins that perform their functions by switching between homo- and heterooligomeric assemblies or mono- and bivalent states. Herein, we demonstrate that the conjugation of a 4,4′-bipyridinium scaffold to the basic region of the GCN₄ bZip transcription factor can be exploited to control the dimerization of the conjugate by formation of a supramolecular complex with cucurbit[8]uril. Importantly, this supramolecular complex is able to specifically recognize its target dsDNA, and this binding can be reversibly switched by the application of external stimuli.We are thankful for the funding received from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 851179), the Ministerio de Economía y Competitividad and Fondo Europeo de Desarrollo Regional (FEDER) (CTQ2016-75629-P), the Agencia Estatal de Investigación and FEDER (CTQ2017-89166-R and PID2019-105272GB-I00) and the Consellería de Educación, Universidade e Formación Profesional, Xunta de Galicia (ED431C 2018/39). P.N thanks the Ministerio de Ciencia, Innovación y Universidades for her PhD fellowship (FPU17/04357). E.P. thanks the UDC-Inditex InTalent Programme for her research contract and funding and the Xunta de Galicia for the Oportunius ProgrammeXunta de Galicia; ED431C 2018/39https://pubs.acs.org/doi/suppl/10.1021/acs.bioconjchem.1c00063/suppl_file/bc1c00063_si_001.pd