XMLTK: An XML Toolkit for Scalable XML Stream Processing

We describe a toolkit for highly scalable XML data processing, consisting of two components. The first is a collection of stand-alone XML tools, s.a. sort- ing, aggregation, nesting, and unnesting, that can be chained to express more complex restructurings. The second is a highly scalable XPath processor for XML streams that can be used to develop scalable solutions for XML stream applications. In this paper we dis- cuss the tools, and some of the techniques we used to achieve high scalability. The toolkit is freely available as an open-source project

Spanish guide for neonatal stabilization and resuscitation 2021: Analysis, adaptation and consensus on international recommendations

Reanimación; Estabilización; Recién nacidoReanimació; Estabilització; NounatResuscitation; Stabilization; NewbornAfter the publication of the recommendations, agreed by all the scientific societies through the ILCOR, at the end of 2020, the GRN-SENeo began a process of analysis and review of the main changes since the last guidelines, to which a specific consensus positioning on controversial issues, trying to avoid ambiguities and trying to adapt the evidence to our environment. This text summarizes the main conclusions of this work and reflects the positioning of that group.Tras la publicación de las recomendaciones, consensuadas por todas las sociedades científicas a través del ILCOR, a finales del año 2020, el GRN-SENeo inició un proceso de análisis y revisión de los principales cambios desde las últimas guías, a los que se añadió un posicionamiento específico de consenso en temas controvertidos, tratando de evitar ambigüedades, y procurando adaptar la evidencia a nuestro medio. El presente texto, resume las principales conclusiones de este trabajo y refleja el posicionamiento de dicho grupo

Derivation of genetic interaction networks from quantitative phenotype data

We have generalized the derivation of genetic-interaction networks from quantitative phenotype data. Familiar and unfamiliar modes of genetic interaction were identified and defined. A network was derived from agar-invasion phenotypes of mutant yeast. Mutations showed specific modes of genetic interaction with specific biological processes. Mutations formed cliques of significant mutual information in their large-scale patterns of genetic interaction. These local and global interaction patterns reflect the effects of gene perturbations on biological processes and pathways

Mapping the genetic architecture of gene expression in human liver

Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process. © 2008 Schadt et al

Spanish guide for neonatal stabilization and resuscitation 2021: analysis, adaptation and consensus on international recommendations

Reanimación; Estabilización; Recién nacidoResuscitation; Stabilization; NewbornReanimació; Estabilització; NounatTras la publicación de las recomendaciones, consensuadas por todas las sociedades científicas a través del ILCOR, a finales del año 2020, el GRN-SENeo inició un proceso de análisis y revisión de los principales cambios desde las últimas guías, a los que se añadió un posicionamiento específico de consenso en temas controvertidos, tratando de evitar ambigüedades, y procurando adaptar la evidencia a nuestro medio. El presente texto, resume las principales conclusiones de este trabajo y refleja el posicionamiento de dicho grupo.After the publication of the recommendations, agreed by all the scientific societies through the ILCOR, at the end of 2020, the GRN-SENeo began a process of analysis and review of the main changes since the last guidelines, to which a specific consensus positioning on controversial issues, trying to avoid ambiguities and trying to adapt the evidence to our environment. This text summarizes the main conclusions of this work and reflects the positioning of that group

Flexible network reconstruction from relational databases with Cytoscape and CytoSQL

<p>Abstract</p> <p>Background</p> <p>Molecular interaction networks can be efficiently studied using network visualization software such as Cytoscape. The relevant nodes, edges and their attributes can be imported in Cytoscape in various file formats, or directly from external databases through specialized third party plugins. However, molecular data are often stored in relational databases with their own specific structure, for which dedicated plugins do not exist. Therefore, a more generic solution is presented.</p> <p>Results</p> <p>A new Cytoscape plugin 'CytoSQL' is developed to connect Cytoscape to any relational database. It allows to launch SQL ('Structured Query Language') queries from within Cytoscape, with the option to inject node or edge features of an existing network as SQL arguments, and to convert the retrieved data to Cytoscape network components. Supported by a set of case studies we demonstrate the flexibility and the power of the CytoSQL plugin in converting specific data subsets into meaningful network representations.</p> <p>Conclusions</p> <p>CytoSQL offers a unified approach to let Cytoscape interact with relational databases. Thanks to the power of the SQL syntax, this tool can rapidly generate and enrich networks according to very complex criteria. The plugin is available at <url>http://www.ptools.ua.ac.be/CytoSQL</url>.</p

Effects of different plyometric training frequencies on physical performance in youth male volleyball players: a randomized trial

This study aimed to analyze the effect of plyometric training (PT) at different frequencies on jump performance, running sprint speed, and service speed in youth male volleyball players. The participants were randomly assigned to one PT session per week (Experimental Group 1, EG1, n = 15), two PT sessions per week (Experimental Group 2, EG2, n = 14), and a control group (CG, n = 13). The total weekly jumping ranged between 98 and 196 jumps (equalized between, EG1 and, EG2). The assessments performed were squat jump (SJ), countermovement jump (CMJ), CMJ-arms, drop jump (DJ), 5-m sprint, 10-m sprint, and service speed. The intragroup comparisons showed that, EG1 significantly (p &lt; 0.001) improved SJ (Δ = 12.74%; d = 1.30), CMJ (Δ = 11.94%; d = 1.71), CMJ-arms (Δ = 12.02%; d = 1.47), DJ (Δ = 10.93%; d = 1.30), 5-m sprint (Δ = −4.61%; d = 0.29), 10-m sprint (Δ = −3.95%; d = 0.40) and service speed (Δ = 8.17%; d = 1.53). Similarly, EG2 significantly (p˂ 0.001) improved SJ (Δ = 11.52%; d = 1.25), CMJ (Δ = 11.29%; d = 1.38), CMJ-arms (Δ = 11.42%; d = 1.26), DJ (Δ = 13.90%; d = 2.17), 5-m sprint (Δ = −3.85%; d = 0.25), 10-m sprint (Δ = −2.73%; d = 0.25) and service speed (Δ = 6.77%; d = 1.44). The CG significantly (p &lt; 0.05) improved SJ (Δ = 2.68; d = 0.28), CMJ-arms (Δ = 2.30; d = 0.35), 5-m sprint (Δ = −1.27; d = 0.10) and service speed (Δ = 1.42; d = 0.30). Intergroup comparisons revealed significantly greater improvements in all variables (p &lt; 0.001) in, EG1 and, EG2 concerning to CG. However, no significant differences were found between, EG1 and, EG2. A moderate weekly PT volume, distributed in one or two sessions per week, seems equally effective

Construction of gene regulatory networks using biclustering and bayesian networks

<p>Abstract</p> <p>Background</p> <p>Understanding gene interactions in complex living systems can be seen as the ultimate goal of the systems biology revolution. Hence, to elucidate disease ontology fully and to reduce the cost of drug development, gene regulatory networks (GRNs) have to be constructed. During the last decade, many GRN inference algorithms based on genome-wide data have been developed to unravel the complexity of gene regulation. Time series transcriptomic data measured by genome-wide DNA microarrays are traditionally used for GRN modelling. One of the major problems with microarrays is that a dataset consists of relatively few time points with respect to the large number of genes. Dimensionality is one of the interesting problems in GRN modelling.</p> <p>Results</p> <p>In this paper, we develop a biclustering function enrichment analysis toolbox (BicAT-plus) to study the effect of biclustering in reducing data dimensions. The network generated from our system was validated via available interaction databases and was compared with previous methods. The results revealed the performance of our proposed method.</p> <p>Conclusions</p> <p>Because of the sparse nature of GRNs, the results of biclustering techniques differ significantly from those of previous methods.</p

DASMI: exchanging, annotating and assessing molecular interaction data

Motivation: Ever increasing amounts of biological interaction data are being accumulated worldwide, but they are currently not readily accessible to the biologist at a single site. New techniques are required for retrieving, sharing and presenting data spread over the Internet