Anhui University

About: Anhui University is a education organization based out in Hefei, Anhui, China. It is known for research contribution in the topics: Computer science & Catalysis. The organization has 17286 authors who have published 16777 publications receiving 210550 citations. The organization is also known as: ānhuī dàxué.

A human neutralizing antibody targets the receptor-binding site of SARS-CoV-2.

Abstract: An outbreak of coronavirus disease 2019 (COVID-19)1-3, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)4, has spread globally. Countermeasures are needed to treat and prevent further dissemination of the virus. Here we report the isolation of two specific human monoclonal antibodies (termed CA1 and CB6) from a patient convalescing from COVID-19. CA1 and CB6 demonstrated potent SARS-CoV-2-specific neutralization activity in vitro. In addition, CB6 inhibited infection with SARS-CoV-2 in rhesus monkeys in both prophylactic and treatment settings. We also performed structural studies, which revealed that CB6 recognizes an epitope that overlaps with angiotensin-converting enzyme 2 (ACE2)-binding sites in the SARS-CoV-2 receptor-binding domain, and thereby interferes with virus-receptor interactions by both steric hindrance and direct competition for interface residues. Our results suggest that CB6 deserves further study as a candidate for translation to the clinic.

PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum]

Abstract: Over the last three decades, a large number of evolutionary algorithms have been developed for solving multi-objective optimization problems. However, there lacks an upto-date and comprehensive software platform for researchers to properly benchmark existing algorithms and for practitioners to apply selected algorithms to solve their real-world problems. The demand of such a common tool becomes even more urgent, when the source code of many proposed algorithms has not been made publicly available. To address these issues, we have developed a MATLAB platform for evolutionary multi-objective optimization in this paper, called PlatEMO, which includes more than 50 multiobjective evolutionary algorithms and more than 100 multi-objective test problems, along with several widely used performance indicators. With a user-friendly graphical user interface, PlatEMO enables users to easily compare several evolutionary algorithms at one time and collect statistical results in Excel or LaTeX files. More importantly, PlatEMO is completely open source, such that users are able to develop new algorithms on the basis of it. This paper introduces the main features of PlatEMO and illustrates how to use it for performing comparative experiments, embedding new algorithms, creating new test problems, and developing performance indicators. Source code of PlatEMO is now available at: http://bimk.ahu.edu.cn/index.php?s=/Index/Software/index.html.