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Vaccines and therapeutics are urgently needed for the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here, we screen human monoclonal antibodies (mAb) targeting the receptor binding domain (RBD) of the viral spike protein via antibody library constructed from peripheral blood mononuclear cells of a convalescent patient. The CT-P59 mAb potently neutralizes SARS-CoV-2 isolates including the D614G variant without antibody-dependent enhancement effect. Complex crystal structure of CT-P59 Fab/RBD shows that CT-P59 blocks interaction regions of RBD for angiotensin converting enzyme 2 (ACE2) receptor with an orientation that is notably different from previously reported RBD-targeting mAbs. Furthermore, therapeutic effects of CT-P59 are evaluated in three animal models (ferret, hamster, and rhesus monkey), demonstrating a substantial reduction in viral titer along with alleviation of clinical symptoms. Therefore, CT-P59 may be a promising therapeutic candidate for COVID-19.

Purpose Deep sedation for endoscopic retrograde cholangiopancreatography (ERCP) can be challenging in elderly patients in the prone position. This study investigated the effect of a high flow nasal oxygen (HFNO) delivery system on oxygenation in this procedure compared with that of conventional nasal cannula oxygen administration. Methods A prospective randomized trial was conducted using HFNO and conventional nasal cannula in patients undergoing ERCP in the prone position. For each patient, the lowest oxygen saturation (SpO 2 ), the incidence of hypoxemia defined as an SpO 2 below 90%, and This manuscript is accompanied by an editorial. Please see Can J Anesth 2020; this issue.

Using a reliable primate model is critical for developing therapeutic advances to treat humans infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Here, we exposed macaques to high titres of SARS-CoV-2 via combined transmission routes. We observed acute interstitial pneumonia with endotheliitis in the lungs of all infected macaques. All macaques had a significant loss of total lymphocytes during infection, which were restored over time. These data show that SARS-CoV-2 causes a coronavirus disease 2019 (COVID-19)-like disease in macaques. This new model could investigate the interaction between SARS-CoV-2 and the immune system to test therapeutic strategies.

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The unprecedented and rapid spread of SARS-CoV-2 (severe acute respiratory syndrome-coronavirus-2) has motivated the need for a rapidly producible and scalable vaccine. Here, we developed a synthetic soluble SARS-CoV-2 spike (S) DNA-based vaccine candidate, GX-19. In mice, immunization with GX-19 elicited not only S-specific systemic and pulmonary antibody responses but also Th1-biased T cell responses in a dose-dependent manner. GX-19-vaccinated nonhuman primates seroconverted rapidly and exhibited a detectable neutralizing antibody response as well as multifunctional CD4+ and CD8+ T cell responses. Notably, when the immunized nonhuman primates were challenged at 10 weeks after the last vaccination with GX-19, they had reduced viral loads in contrast to non-vaccinated primates as a control. These findings indicate that GX-19 vaccination provides a durable protective immune response and also support further development of GX-19 as a vaccine candidate for SARS-CoV-2.

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The aim of this study was to validate an artificial neural network model at Youngin, Janghung, and Boeun, Korea, using the geographic information system (GIS). The factors that influence landslide occurrence, such as the slope, aspect, curvature, and geomorphology of topography, the type, material, drainage, and effective thickness of soil, the type, diameter, age, and density of forest, distance from lineament, and land cover were either calculated or extracted from the spatial database and Landsat TM satellite images. Landslide susceptibility was analyzed using the landslide occurrence factors provided by the artificial neural network model. The landslide susceptibility analysis results were validated and cross-validated using the landslide locations as study areas. For this purpose, weights for each study area were calculated by the artificial neural network model. Among the nine cases, the best accuracy (81.36%) was obtained in the case of the Boeun-based Janghung weight, whereas the Janghungbased Youngin weight showed the worst accuracy (71.72%).