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Designer SARS-CoV-2 RBD vaccine produces dramatically improved antibody response in preclinical trials The importance of computational modeling in the prediction of the course of the ongoing coronavirus disease 2019 (COVID-19) pandemic, as well as evaluating multiple potential drug leads, has never been more clear. Now, a new study describes a set of designer vaccine antigens that may improve vaccine stability as well as enhance the neutralizing antibody response. The virus causing this pandemic is the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes an asympto...

Computational Modeling in Medicine In the past few decades, information technology has revolutionized the medical industry. The accuracy with which biological systems and interactions can be simulated and data can be gathered have improved exponentially. Computational modeling has provided ever-more sophisticated data for the field of medical research. This article will discuss this subject. Image Credit: ShustrikS/Shutterstock.com What is computational modeling? Computational modeling is used to simulate and study complex systems using computer science, physics, and mathematics. Numerous var...

Evidence that elevated blood glucose is a significant risk factor for severe COVID-19 Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus responsible for the outbreak of the COVID-19 disease. The virus emerged in China in late 2019, with viral transmission reaching pandemic proportions in early 2020. The average mortality rate of COVID-19 is under 2%, as this virus also causes asymptomatic infections in a large proportion of the population. However, in a small percentage of infected individuals, the virus causes symptomatic infections, leading to severe disease...

Cleaning frequency key to limiting SARS-CoV-2 spread at theme parks As vaccine rollout begins to reach clinically effective levels in many countries, the question of reopening public entertainment facilities has become a burning one. However, this step must include considered policies on how to safeguard public health as well as open up public spaces. A new preprint research paper provides some insights into how this may be done using computational modeling. The study, which appeared on the medRxiv* server, deals with the mitigation strategies that must be implemented in order to contain the...

The task of multi-label image recognition is to predict a set of object labels that present in an image. As objects normally co-occur in an image, it is desirable to model label dependencies to improve recognition performance. To capture and explore such important information, we propose Graph Convolutional Networks based models for multi-label recognition, where directed graphs are constructed over classes and information is propagated between classes to learn inter-dependent class-level representations. Following this idea, we design two particular models that approach multi-label classifica...