Here, we introduce the 3D Genome Browser, http://3dgenome.org, which allows users to conveniently explore both their own and over 300 publicly available chromatin interaction data of different types. We design a new binary data format for Hi-C data that reduces the file size by at least a magnitude and allows users to visualize chromatin interactions over millions of base pairs within seconds. Our browser provides multiple methods linking distal cis-regulatory elements with their potential target genes. Users can seamlessly integrate thousands of other omics data to gain a comprehensive view of both regulatory landscape and 3D genome structure.Electronic supplementary materialThe online version of this article (10.1186/s13059-018-1519-9) contains supplementary material, which is available to authorized users.

SummaryBackground and objectives Measurement of C-reactive protein (CRP) levels remains uncommon in North America, although it is now routine in many countries. Using Dialysis Outcomes and Practice Patterns Study data, our primary aim was to evaluate the value of CRP for predicting mortality when measured along with other common inflammatory biomarkers.Design, setting, participants, & measurements We studied 5061 prevalent hemodialysis patients from 2005 to 2008 in 140 facilities routinely measuring CRP in 10 countries. The association of CRP with mortality was evaluated using Cox regression. Prediction of 1-year mortality was assessed in logistic regression models with differing adjustment variables.Results Median baseline CRP was lower in Japan (1.0 mg/L) than other countries (6.0 mg/L). CRP was positively, monotonically associated with mortality. No threshold below which mortality rate leveled off was identified. In prediction models, CRP performance was comparable with albumin and exceeded ferritin and white blood cell (WBC) count based on measures of model discrimination (c-statistics, net reclassification improvement [NRI]) and global model fit (generalized R 2 ). The primary analysis included age, gender, diabetes, catheter use, and the four inflammatory markers (omitting one at a time). Specifying NRI Ն5% as appropriate reclassification of predicted mortality risk, NRI for CRP was 12.8% compared with 10.3% for albumin, 0.8% for ferritin, and Ͻ0.1% for WBC. ConclusionsThese findings demonstrate the value of measuring CRP in addition to standard inflammatory biomarkers to improve mortality prediction in hemodialysis patients. Future studies are indicated to identify interventions that lower CRP and to identify whether they improve clinical outcomes.

The transition of the Munc18-1/syntaxin-1 complex to the SNARE complex, a key step involved in exocytosis, is regulated by Munc13-1, SNAP-25 and synaptobrevin-2, but the underlying mechanism remains elusive. Here, we identify an interaction between Munc13-1 and the membrane-proximal linker region of synaptobrevin-2, and reveal its essential role in transition and exocytosis. Upon this interaction, Munc13-1 not only recruits synaptobrevin-2-embedded vesicles to the target membrane but also renders the synaptobrevin-2 SNARE motif more accessible to the Munc18-1/syntaxin-1 complex. Afterward, the entry of SNAP-25 leads to a half-zippered SNARE assembly, which eventually dissociates the Munc18-1/syntaxin-1 complex to complete SNARE complex formation. Our data suggest that Munc18-1 and Munc13-1 together serve as a functional template to orchestrate SNARE complex assembly.

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Big Earth data are produced from satellite observations, Internet-of-Things, model simulations, and other sources. The data embed unprecedented insights and spatiotemporal stamps of relevant Earth phenomena for improving our understanding, responding, and addressing challenges of Earth sciences and applications. In the past years, new technologies (such as cloud computing, big data and artificial intelligence) have gained momentum in addressing the challenges of using big Earth data for scientific studies and geospatial applications historically intractable. This paper reviews the big Earth data analytics from several aspects to capture the latest advancements in this fast-growing domain. We first introduce the concepts of big Earth data. The architecture, various functionalities, and supporting modules are then reviewed from a generic methodology aspect. Analytical methods supporting the functionalities are surveyed and analyzed in the context of different tools. The driven questions are exemplified through cutting-edge Earth science researches and applications. A list of challenges and opportunities are proposed for different stakeholders to collaboratively advance big Earth data analytics in the near future.