Validação do questionário Childhood Asthma Control Test (c-ACT) para o Brasil

Introdução: Atualmente a percepção e os relatos da própria criança sobre seu diagnóstico de asma tem se demonstrado confiável e relevante para o manejo da doença.Objetivo: Validar a versão Português para o Brasil do Childhood Asthma Control Test em jovens com idade entre 4 a 11 anos.Métodos: O estudo foi dividido em duas etapas: a primeira o processo de tradução, adaptação linguística do instrumento. A segunda etapa foi realizada a análise das propriedades psicométricas validade e a confiabilidade.Resultados: Foram incluídas 105 participantes, com idades entre 4 a 11 anos. Validade: todas as correlações entre o escore total e os itens do questionário foram significativas e com valores r = > 0,3. Não houve correlações entre o escore total do questionário e a função pulmonar. O grupo com asma controlada apresenta valores significativamente superiores no c-ACT ao compararmos com o grupo com asma não controlada (controlada 22±2,9 VS não controlada 16,3±5,3 p 0. 3. There was no correlation between the total score of the questionnaire and lung function. The controlled asthma group showed significantly higher c-ACT scores than those of the uncontrolled asthma group (controlled 22±2. 9 VS uncontrolled 16. 3±5. 3 p <0. 001). Reliability: The Alfa de Cronbach coefficient for the total c-ACT score was 0. 677 (CI95% 0. 573-0763). In the assessment of sensitivity to change, the effect size was 0. 8 and the intraclass correlation coefficient was 0. 598. No floor or ceiling effects were observed in the sample studied.Completed: The Brazilian version of the Childhood Asthma Control Test proved to be valid and reliable

Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time

This paper investigates how to utilize different forms of human interaction to safely train autonomous systems in real-time by learning from both human demonstrations and interventions. We implement two components of the Cycle-of-Learning for Autonomous Systems, which is our framework for combining multiple modalities of human interaction. The current effort employs human demonstrations to teach a desired behavior via imitation learning, then leverages intervention data to correct for undesired behaviors produced by the imitation learner to teach novel tasks to an autonomous agent safely, after only minutes of training. We demonstrate this method in an autonomous perching task using a quadrotor with continuous roll, pitch, yaw, and throttle commands and imagery captured from a downward-facing camera in a high-fidelity simulated environment. Our method improves task completion performance for the same amount of human interaction when compared to learning from demonstrations alone, while also requiring on average 32% less data to achieve that performance. This provides evidence that combining multiple modes of human interaction can increase both the training speed and overall performance of policies for autonomous systems.Comment: 9 pages, 6 figure

Web-based visual analysis for high-throughput genomics

BACKGROUND: Visualization plays an essential role in genomics research by making it possible to observe correlations and trends in large datasets as well as communicate findings to others. Visual analysis, which combines visualization with analysis tools to enable seamless use of both approaches for scientific investigation, offers a powerful method for performing complex genomic analyses. However, there are numerous challenges that arise when creating rich, interactive Web-based visualizations/visual analysis applications for high-throughput genomics. These challenges include managing data flow from Web server to Web browser, integrating analysis tools and visualizations, and sharing visualizations with colleagues. RESULTS: We have created a platform simplifies the creation of Web-based visualization/visual analysis applications for high-throughput genomics. This platform provides components that make it simple to efficiently query very large datasets, draw common representations of genomic data, integrate with analysis tools, and share or publish fully interactive visualizations. Using this platform, we have created a Circos-style genome-wide viewer, a generic scatter plot for correlation analysis, an interactive phylogenetic tree, a scalable genome browser for next-generation sequencing data, and an application for systematically exploring tool parameter spaces to find good parameter values. All visualizations are interactive and fully customizable. The platform is integrated with the Galaxy (http://galaxyproject.org) genomics workbench, making it easy to integrate new visual applications into Galaxy. CONCLUSIONS: Visualization and visual analysis play an important role in high-throughput genomics experiments, and approaches are needed to make it easier to create applications for these activities. Our framework provides a foundation for creating Web-based visualizations and integrating them into Galaxy. Finally, the visualizations we have created using the framework are useful tools for high-throughput genomics experiments

Promoting Physical Activity in Local Communities: Understanding Health, Nutrition, and Physical Activity Needs in Winooski, VT

Introduction: Since the Winooski YMCA opened in March 2008, enrollment has been much lower than expected, with only 200 members enrolled by September 2008. One goal of the YMCA is to promote the health of the community by increasing involvement in physical activity in Winooski. Regular exercise is associated with enhanced health and decreased risk of diabetes, cardiovascular disease, as well as many cancers. In order to promote physical activity in the Winooski community, the YMCA set a goal to increase their enrollment to 500 members by December 2008.https://scholarworks.uvm.edu/comphp_gallery/1005/thumbnail.jp

Proteomics to go: Proteomatic enables the user-friendly creation of versatile MS/MS data evaluation workflows

We present Proteomatic, an operating system independent and user-friendly platform that enables the construction and execution of MS/MS data evaluation pipelines using free and commercial software. Required external programs such as for peptide identification are downloaded automatically in the case of free software. Due to a strict separation of functionality and presentation, and support for multiple scripting languages, new processing steps can be added easily

Resistance gene enrichment sequencing (RenSeq) enables reannotation of the NB-LRR gene family from sequenced plant genomes and rapid mapping of resistance loci in segregating populations

RenSeq is a NB-LRR (nucleotide binding-site leucine-rich repeat) gene-targeted, Resistance gene enrichment and sequencing method that enables discovery and annotation of pathogen resistance gene family members in plant genome sequences. We successfully applied RenSeq to the sequenced potato Solanum tuberosum clone DM, and increased the number of identified NB-LRRs from 438 to 755. The majority of these identified R gene loci reside in poorly or previously unannotated regions of the genome. Sequence and positional details on the 12 chromosomes have been established for 704 NB-LRRs and can be accessed through a genome browser that we provide. We compared these NB-LRR genes and the corresponding oligonucleotide baits with the highest sequence similarity and demonstrated that ~80% sequence identity is sufficient for enrichment. Analysis of the sequenced tomato S. lycopersicum ‘Heinz 1706’ extended the NB-LRR complement to 394 loci. We further describe a methodology that applies RenSeq to rapidly identify molecular markers that co-segregate with a pathogen resistance trait of interest. In two independent segregating populations involving the wild Solanum species S. berthaultii (Rpi-ber2) and S. ruiz-ceballosii (Rpi-rzc1), we were able to apply RenSeq successfully to identify markers that co-segregate with resistance towards the late blight pathogen Phytophthora infestans. These SNP identification workflows were designed as easy-to-adapt Galaxy pipelines

The Bioinformatics Open Source Conference (BOSC) 2013

Contact: [email protected]

Developing and applying heterogeneous phylogenetic models with XRate

Modeling sequence evolution on phylogenetic trees is a useful technique in computational biology. Especially powerful are models which take account of the heterogeneous nature of sequence evolution according to the "grammar" of the encoded gene features. However, beyond a modest level of model complexity, manual coding of models becomes prohibitively labor-intensive. We demonstrate, via a set of case studies, the new built-in model-prototyping capabilities of XRate (macros and Scheme extensions). These features allow rapid implementation of phylogenetic models which would have previously been far more labor-intensive. XRate's new capabilities for lineage-specific models, ancestral sequence reconstruction, and improved annotation output are also discussed. XRate's flexible model-specification capabilities and computational efficiency make it well-suited to developing and prototyping phylogenetic grammar models. XRate is available as part of the DART software package: http://biowiki.org/DART .Comment: 34 pages, 3 figures, glossary of XRate model terminolog