The first nickel(0)-catalyzed linear-selective hydroarylation of unactivated alkenes and styrenes with organoboronic acids are achieved under redox-neutral conditions.

The conventional oxidative Heck reaction between aryl boronic acids and alkenes typically involved the PdII/Pd0/PdII catalytic cycle incorporating an external oxidant and often suffered C=C bond isomerization for internal alkyl-substituted alkenes via chain-walking. Herein, we demonstrate that the regioselectivity (γ-selectivity vs. δ-selectivity) and pathway selectivity (hydroarylation vs. oxidative Heck coupling) of a directed Ni-catalyzed alkene arylation can be controlled by judicious tuning of the coordination environment around the nickel catalyst via optimization of an appropriate phosphine ligand and directing group. In this way, the Ni(0)-catalyzed oxidative Heck arylation that relies on transfer hydrogenation of an acceptor olefin is developed with excellent E/Z selectivity and regioselectivity. Mechanistic investigations suggest that the addition of the acceptor is crucial for lowering the energy for carbometalation and for enabling catalytic turnover.

A combination of computational tools will be useful in mining candidate genes for periodontitis. These theoretical results provide new clues for experimental biologists to plan targeted experiments.

DNA methylation, the most intensively studied epigenetic modification, plays an important role in understanding the molecular basis of diseases. Furthermore, epigenome-wide association study (EWAS) provides a systematic approach to identify epigenetic variants underlying common diseases/phenotypes. However, there is no comprehensive database to archive the results of EWASs. To fill this gap, we developed the EWASdb, which is a part of 'The EWAS Project', to store the epigenetic association results of DNA methylation from EWASs. In its current version (v 1.0, up to July 2018), the EWASdb has curated 1319 EWASs associated with 302 diseases/phenotypes. There are three types of EWAS results curated in this database: (i) EWAS for single marker; (ii) EWAS for KEGG pathway and (iii) EWAS for GO (Gene Ontology) category. As the first comprehensive EWAS database, EWASdb has been searched or downloaded by researchers from 43 countries to date. We believe that EWASdb will become a valuable resource and significantly contribute to the epigenetic research of diseases/phenotypes and have potential clinical applications. EWASdb is freely available at http://www.ewas.org.cn/ewasdb or http://www.bioapp.org/ewasdb.

The human disease network (HDN) has become a powerful tool for revealing disease-disease associations. Some studies have shown that genes that share similar or same disease phenotypes tend to encode proteins that interact with each other. Therefore, protein-protein interactions (PPIs) may help us to further understand the relationships between diseases with overlapping clinical phenotypes. In this study, we constructed the expanded HDN (eHDN) by combining disease gene information with PPI information, and analyzed its topological features and functional properties. We found that the network is hierarchical and, most diseases are connected to only a few diseases, whereas a small part of diseases are linked to many different diseases. Diseases in a specific disease class tend to cluster together, and genes associated with the same disease are functionally related. Comparing the eHDN with the original HDN (oHDN, constructed using disease gene information) revealed high consistency over all topological and functional properties. This, to some extent, indicates that our eHDN is reliable. In the eHDN, we found some new associations among diseases resulting from the shared genes interacting with disease genes. The new eHDN will provide a valuable reference for clinicians and medical researchers.