The infection of a novel coronavirus found in Wuhan of China (SARS-CoV-2) is rapidly spreading, and the incidence rate is increasing worldwide. Due to the lack of effective treatment options for SARS-CoV-2, various strategies are being tested in China, including drug repurposing. In this study, we used our pre-trained deep learning-based drug-target interaction model called Molecule Transformer-Drug Target Interaction (MT-DTI) to identify commercially available drugs that could act on viral proteins of SARS-CoV-2. The result showed that atazanavir, an antiretroviral medication used to treat and prevent the human immunodeficiency virus (HIV), is the best chemical compound, showing an inhibitory potency with Kd of 94.94 nM against the SARS-CoV-2 3C-like proteinase, followed by remdesivir (113.13 nM), efavirenz (199.17 nM), ritonavir (204.05 nM), and dolutegravir (336.91 nM). Interestingly, lopinavir, ritonavir, and darunavir are all designed to target viral proteinases. However, in our prediction, they may also bind to the replication complex components of SARS-CoV-2 with an inhibitory potency with Kd < 1,000 nM. In addition, we also found that several antiviral agents, such as Kaletra (lopinavir/ritonavir), could be used for the treatment of SARS-CoV-2. Overall, we suggest that the list of antiviral drugs identified by the MT-DTI model should be considered, when establishing effective treatment strategies for SARS-CoV-2.

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Porous carbon nitride (CN) spheres with partially crystalline frameworks have been successfully synthesized via a nanocasting approach by using spherical mesoporous cellular silica foams (MCFs) as a hard template, and ethylenediamine and carbon tetrachloride as precursors. The resulting spherical CN materials have uniform diameters of ca. 4 μm, hierarchical three-dimensional (3-D) mesostructures with small and large mesopores with pore diameters centered at ca. 4.0 and 43 nm, respectively, a relatively high BET surface area of ~550 m 2 /g, and a pore volume of 0.90 cm 3 /g. High-resolution transmission electron microscope (HRTEM) images, wide-angle X-ray diffraction (XRD) patterns, and Raman spectra demonstrate that the porous CN material has a partly graphitized structure. In addition, elemental analyses, X-ray photoelectron spectra (XPS), Fourier transform infrared spectra (FT-IR), and CO 2 temperature-programmed desorption (CO 2 -TPD) show that the material has a high nitrogen content (17.8 wt%) with nitrogen-containing groups and abundant basic sites. The hierarchical porous CN spheres have excellent CO 2 capture properties with a capacity of 2.90 mmol/g at 25 °C and 0.97 mmol/g at 75 °C , superior to those of the pure carbon materials with analogous mesostructures. This can be mainly attributed to the abundant nitrogen-containing basic groups, hierarchical mesostructure, relatively high BET surface area and stable framework. Furthermore, the presence of a large number of micropores and small mesopores also enhance the CO 2 capture performance, owing to the capillary condensation effect.

The use of robotic systems is assumed to provide a technically superior operative environment for minimally invasive surgery. However, our analysis of perioperative surgical outcomes indicated that robotic gastrectomy is not superior to laparoscopic gastrectomy. Clinical trials identification: NCT01309256.

SUMMARY Central arterial wall stiffening driven by a chronic inflammatory milieu accompanies arterial diseases, the leading cause of cardiovascular (CV) morbidity and mortality in Western society. Increase in central arterial wall stiffening, measured as an increase in aortic pulse wave velocity (PWV), is a major risk factor for clinical CV disease events. However, no specific therapies to reduce PWV are presently available. In rhesus monkeys, a two-year diet high in fat and sucrose (HFS) increases not only body weight and cholesterol, but also induces prominent central arterial wall stiffening and increases PWV and inflammation. The observed loss of endothelial cell integrity, lipid and macrophage infiltration, and calcification of the arterial wall were driven by genomic and proteomic signatures of oxidative stress and inflammation. Resveratrol prevented the HFS-induced arterial wall inflammation and the accompanying increase in PWV. Dietary resveratrol may hold promise as a novel therapy to ameliorate increases in PWV.

Massively parallel sequencing technologies have identified a broad spectrum of human genome diversity. Here we deep sequenced and correlated 18 genomes and 17 transcriptomes of unrelated Korean individuals. This has allowed us to construct a genome-wide map of common and rare variants and also identify variants formed during DNA-RNA transcription. We identified 9.56 million genomic variants, 23.2% of which appear to be previously unidentified. From transcriptome sequencing, we discovered 4,414 transcripts not previously annotated. Finally, we revealed 1,809 sites of transcriptional base modification, where the transcriptional landscape is different from the corresponding genomic sequences, and 580 sites of allele-specific expression. Our findings suggest that a considerable number of unexplored genomic variants still remain to be identified in the human genome, and that the integrated analysis of genome and transcriptome sequencing is powerful for understanding the diversity and functional aspects of human genomic variants.

In view of their high energy densities, absence of memory effects, and high round-trip energy efficiencies, conventional lithium-ion batteries (LIBs) are widely used on scales ranging from compact electronic devices to grid systems [8,9] but are currently reaching their maximal capacity, as their specific/volumetric energy densities are limited by the use of heavy metal-based active host materials. [10,11] The use of Li as a high-energy active anode material is a possible solution to this problem, as this metal exhibits a high theoretical capacity of ≈3860 mAh g −1 and a low redox potential (−3.040 V vs the standard hydrogen electrode). [12,13] However, the Li-metal anode (LMA) has some fatal drawbacks originating from highaspect-ratio metal growth, e.g., continuous electrolyte consumption, Coulombic efficiency (CE) reduction, elevated cell polarization due to side reactions producing dead Li, and safety issues caused by electrode short-circuiting. [14,15] Recently, these drawbacks have been addressed by several approaches such as electrode design and electrolyte engineering. [16-21] Metal growth can be described by a first-order linear equation as Although the lithium-metal anode (LMA) can deliver a high theoretical capacity of ≈3860 mAh g −1 at a low redox potential of −3.040 V (vs the standard hydrogen electrode), its application in rechargeable batteries is hindered by the poor Coulombic efficiency and safety issues caused by dendritic metal growth. Consequently, careful electrode design, electrolyte engineering, solid-electrolyte interface control, protective layer introduction, and other strategies are suggested as possible solutions. In particular, one should note the great potential of 3D-structured electrode materials, which feature high active specific surface areas and stereoscopic structures with multitudinous lithiophilic sites and can therefore facilitate rapid Li-ion flux and metal nucleation as well as mitigate Li dendrite formation through the kinetic control of metal deposition even at high local current densities. This progress report reviews the design of 3D-structured electrode materials for LMA according to their categories, namely 1) metal-based materials, 2) carbon-based materials, and 3) their hybrids, and allows the results obtained under different experimental conditions to be seen at a single glance, thus being helpful for researchers working in related fields.

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