<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Shimizu, Chisato</style></author><author><style face="normal" font="default" size="100%">Kim, Jihoon</style></author><author><style face="normal" font="default" size="100%">Stepanowsky, Petra</style></author><author><style face="normal" font="default" size="100%">Trinh, Christine</style></author><author><style face="normal" font="default" size="100%">Lau, Hubert D</style></author><author><style face="normal" font="default" size="100%">Akers, Johnny C</style></author><author><style face="normal" font="default" size="100%">Chen, Clark</style></author><author><style face="normal" font="default" size="100%">Kanegaye, John T</style></author><author><style face="normal" font="default" size="100%">Tremoulet, Adriana</style></author><author><style face="normal" font="default" size="100%">Ohno-Machado, Lucila</style></author><author><style face="normal" font="default" size="100%">Burns, Jane C</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Differential expression of miR-145 in children with Kawasaki disease.</style></title><secondary-title><style face="normal" font="default" size="100%">PLoS One</style></secondary-title><alt-title><style face="normal" font="default" size="100%">PLoS ONE</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">e58159</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: Kawasaki disease is an acute, self-limited vasculitis of childhood that can result in structural damage to the coronary arteries. Previous studies have implicated the TGF-β pathway in disease pathogenesis and generation of myofibroblasts in the arterial wall. microRNAs are small non-coding RNAs that modulate gene expression at the post-transcriptional level and can be transported between cells in extracellular vesicles. To understand the role that microRNAs play in modifying gene expression in Kawasaki disease, we studied microRNAs from whole blood during the acute and convalescent stages of the illness.

METHODOLOGY/PRINCIPAL FINDINGS: RNA isolated from the matched whole blood of 12 patients with acute and convalescent Kawasaki disease were analyzed by sequencing of small RNA. This analysis revealed six microRNAs (miRs-143, -199b-5p, -618, -223, -145 and -145* (complementary strand)) whose levels were significantly elevated during the acute phase of Kawasaki disease. The result was validated using targeted qRT-PCR using an independent cohort (n = 16). miR-145, which plays a critical role in the differentiation of neutrophils and vascular smooth muscle cells, was expressed at high levels in blood samples from acute Kawasaki disease but not adenovirus-infected control patients (p = 0.005). miR-145 was also detected in small extracellular vesicles isolated from acute Kawasaki disease plasma samples. Pathway analysis of the predicted targets of the 6 differentially expressed microRNAs identified the TGF-β pathway as the top pathway regulated by microRNAs in Kawasaki disease.

CONCLUSION: Sequencing of small RNA species allowed discovery of microRNAs that may participate in Kawasaki disease pathogenesis. miR-145 may participate, along with other differentially expressed microRNAs, in regulating expression of genes in the TGF-β pathway during the acute illness. If the predicted target genes are confirmed, our findings suggest a model of Kawasaki disease pathogenesis whereby miR-145 modulates TGF-β signaling in the arterial wall.</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Pu, Minya</style></author><author><style face="normal" font="default" size="100%">Hayashi, Tomoko</style></author><author><style face="normal" font="default" size="100%">Cottam, Howard</style></author><author><style face="normal" font="default" size="100%">Mulvaney, Joseph</style></author><author><style face="normal" font="default" size="100%">Arkin, Michelle</style></author><author><style face="normal" font="default" size="100%">Corr, Maripat</style></author><author><style face="normal" font="default" size="100%">Carson, Dennis</style></author><author><style face="normal" font="default" size="100%">Messer, Karen</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Analysis of high-throughput screening assays using cluster enrichment.</style></title><secondary-title><style face="normal" font="default" size="100%">Stat Med</style></secondary-title><alt-title><style face="normal" font="default" size="100%">Stat Med</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012 Dec 30</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">31</style></volume><pages><style face="normal" font="default" size="100%">4175-89</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper, we describe the implementation and evaluation of a cluster-based enrichment strategy to call hits from a high-throughput screen using a typical cell-based assay of 160,000 chemical compounds. Our focus is on statistical properties of the prospective design choices throughout the analysis, including how to choose the number of clusters for optimal power, the choice of test statistic, the significance thresholds for clusters and the activity threshold for candidate hits, how to rank selected hits for carry-forward to the confirmation screen, and how to identify confirmed hits in a data-driven manner. Whereas previously the literature has focused on choice of test statistic or chemical descriptors, our studies suggest that cluster size is the more important design choice. We recommend clusters to be ranked by enrichment odds ratio, not by p-value. Our conceptually simple test statistic is seen to identify the same set of hits as more complex scoring methods proposed in the literature do. We prospectively confirm that such a cluster-based approach can outperform the naive top X approach and estimate that we improved confirmation rates by about 31.5% from 813 using the top X approach to 1187 using our cluster-based method.</style></abstract><issue><style face="normal" font="default" size="100%">30</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Grando, MA</style></author><author><style face="normal" font="default" size="100%">Schwab, R</style></author><author><style face="normal" font="default" size="100%">Boxwala, A</style></author><author><style face="normal" font="default" size="100%">Alipanah, N</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Ontological approach for the management of informed consent permissions</style></title><secondary-title><style face="normal" font="default" size="100%">2nd IEEE Conference on Healthcare informatics, Imaging, and Systems Biology</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ohno-Machado, Lucila</style></author><author><style face="normal" font="default" size="100%">Bafna, Vineet</style></author><author><style face="normal" font="default" size="100%">Boxwala, Aziz A</style></author><author><style face="normal" font="default" size="100%">Chapman, Brian E</style></author><author><style face="normal" font="default" size="100%">Chapman, Wendy W</style></author><author><style face="normal" font="default" size="100%">Chaudhuri, Kamalika</style></author><author><style face="normal" font="default" size="100%">Day, Michele E</style></author><author><style face="normal" font="default" size="100%">Farcas, Claudiu</style></author><author><style face="normal" font="default" size="100%">Heintzman, Nathaniel D</style></author><author><style face="normal" font="default" size="100%">Jiang, Xiaoqian</style></author><author><style face="normal" font="default" size="100%">Kim, Hyeoneui</style></author><author><style face="normal" font="default" size="100%">Kim, Jihoon</style></author><author><style face="normal" font="default" size="100%">Matheny, Michael E</style></author><author><style face="normal" font="default" size="100%">Resnic, Frederic S</style></author><author><style face="normal" font="default" size="100%">Vinterbo, Staal A</style></author></authors><translated-authors><author><style face="normal" font="default" size="100%">and the iDASH team</style></author></translated-authors></contributors><titles><title><style face="normal" font="default" size="100%">iDASH: integrating data for analysis, anonymization, and sharing.</style></title><secondary-title><style face="normal" font="default" size="100%">J Am Med Inform Assoc</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Am Med Inform Assoc</style></alt-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011 Nov 10</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">iDASH (integrating data for analysis, anonymization, and sharing) is the newest National Center for Biomedical Computing funded by the NIH. It focuses on algorithms and tools for sharing data in a privacy-preserving manner. Foundational privacy technology research performed within iDASH is coupled with innovative engineering for collaborative tool development and data-sharing capabilities in a private Health Insurance Portability and Accountability Act (HIPAA)-certified cloud. Driving Biological Projects, which span different biological levels (from molecules to individuals to populations) and focus on various health conditions, help guide research and development within this Center. Furthermore, training and dissemination efforts connect the Center with its stakeholders and educate data owners and data consumers on how to share and use clinical and biological data. Through these various mechanisms, iDASH implements its goal of providing biomedical and behavioral researchers with access to data, software, and a high-performance computing environment, thus enabling them to generate and test new hypotheses.</style></abstract></record></records></xml>