DeepCancerMap: A versatile deep learning platform for target- and cell-based anticancer drug discovery.

Discovering new anticancer drugs has been widely concerned and remains an open challenge. Target- and phenotypic-based experimental screening represent two mainstream anticancer drug discovery methods, which suffer from time-consuming, labor-intensive, and high experimental costs. In this study, we collected 485,900 compounds involving in 3,919,974 bioactivity records against 426 anticancer targets and 346 cancer cell lines from academic literature, as well as 60 tumor cell lines from NCI-60 panel. A total of 832 classification models (426 target- and 406 cell-based predictive models) were then constructed to predict the inhibitory activity of compounds against targets and tumor cell lines using FP-GNN deep learning method. Compared to the classical machine learning and deep learning methods, the FP-GNN models achieve considerable overall predictive performance, with the highest AUC values of 0.91, 0.88, 0.91 for the test sets of targets, academia-sourced and NCI-60 cancer cell lines, respectively. A user-friendly webserver called DeepCancerMap and its local version were developed based on these high-quality models, enabling users to perform anticancer drug discovery-related tasks including large-scale virtual screening, profiling prediction of anticancer agents, target fishing, and drug repositioning. We anticipate this platform to accelerate the discovery of anticancer drugs in the field. DeepCancerMap is freely available at https://deepcancermap.idruglab.cn.

Monitoring graphene oxide's efficiency for removing Re(VII) and Cr(VI) with fluorescent silica hydrogels.

Supported carbon quantum dots (CQDs), used as fluorescent sensors for the detection of metal ions, have rarely been used to remove heavy metals from water. Nitrogen-doped CQDs immobilized in hydrophilic silica hydrogels exhibited a more superior sensitivity and selectivity for the detection of Re(VII) and Cr(VI) than other metal ions, including Fe(III), Fe(II), Zn(II), Cu(II) and Mn(II). For the first time, low limits of detection (LOD) of 2.3 µM for Re(VII) detection and 65 nM for Cr(VI) detection were reported by a facile method. Based on the high selectivity of fluorescent silica hydrogels for Re(VII) and Cr(VI) detection, the removal of Re(VII) and Cr(VI) by graphene oxide (GO) in water was monitored with the hydrogels used as a turn-off fluorescent sensing platform. The consistent results of the sorption isotherms of each metal on GO, which were obtained from the fluorescence spectra and by UV absorption, further verified the possibility of monitoring metal removal by fluorescence detection. Remarkably, GO removed 1186 mg/g of Re(VII) but only 178 mg/g of Cr(VI). The density functional theory (DFT) calculations indicated that both Re(VII) and Cr(VI) formed stable bonds with silica hydrogels, confirming that the interactions between the metal ions and the substrate would promote the fluorescence quenching of the supported CQDs. On the other hand, Re(VII) interacted more strongly with the carboxyl groups of GO than Cr(VI). In addition, a real-time detection system was designed to alarm the service life of a GO filter used for Re(VII) removal.

[Bibliometric analysis and quality assessment of clinical evidence on Xiaotong Tiegao].

Many clinical studies on Cheezheng Xiaotong Tiegao have been accumulated since it was launched in 1993,but they have not been comprehensively analyzed and evaluated. This study systematically retrieved relevant studies in six databases at home and abroad as of December 2017. This study analyzed the statistics of the included studies in several aspects,including publication time,region,fund,disease category and type of study. In this study,various tools were used to evaluate the methodological quality of included studies,such as the Cochrane collaboration's tool for assessing the risk of bias in randomized trials,MINORS,IHE,AMSTAR2.The results showed that the literatures were mainly published from 2010 to 2011,and a total of 28 projects were financially supported.The most involved disease was arthropathy. The randomized controlled trials were the majority in the included studies,but the quality was low,and most of the literatures didn't report the allocation concealment and blinding. This study comprehensively reflected the current situations and shortcomings of the clinical studies of Cheezheng Xiaotong Tiegao,and put forward several suggestions,in the expectation of providing a reference for the future clinical research direction of Cheezheng Xiaotong Tiegao.