Background/objectives To evaluate the prevalence of malnutrition and its related factors in elderly patients with COVID-19 in Wuhan, China. Subjects/methods In a cross-sectional study, we evaluated the nutritional status of elderly inpatients with COVID-19 using the Mini Nutritional Assessment (MNA). Based on MNA scores, patients were divided into non-malnutrition group (MNA ≥ 24), the group with risk of malnutrition (MNA 17-23.5) and malnutrition group (MNA score < 17). Regression analysis was conducted to screen for risk factors for malnutrition. Results A total of 182 patients were included in the study, of which 27.5% were in the group with malnutrition risk and 52.7% were in the malnutrition group. There were statistical differences in the incidence of comorbid diabetes mellitus, body mass index (BMI), calf circumference,albumin, hemoglobin, and lymphocyte counts among the three groups. Further regression analysis suggested that combined diabetes, low calf circumference, and low albumin were independent risk factors for malnutrition. Conclusions The prevalence of malnutrition in elderly patients with COVID-19 was high, and nutritional support should be strengthened during treatment, especially for those with diabetes mellitus, low calf circumference, or low albumin.

The creation of novel enzymes capable of catalyzing any desired chemical reaction is a grand challenge for computational protein design. Here we describe two new algorithms for enzyme design that employ hashing techniques to allow searching through large numbers of protein scaffolds for optimal catalytic site placement. We also describe an in silico benchmark, based on the recapitulation of the active sites of native enzymes, that allows rapid evaluation and testing of enzyme design methodologies. In the benchmark test, which consists of designing sites for each of 10 different chemical reactions in backbone scaffolds derived from 10 enzymes catalyzing the reactions, the new methods succeed in identifying the native site in the native scaffold and ranking it within the top five designs for six of the 10 reactions. The new methods can be directly applied to the design of new enzymes, and the benchmark provides a powerful in silico test for guiding improvements in computational enzyme design.Keywords: enzyme design; protein design; active site recapitulation; protein-ligand interactions; geometric hashing Enzymes are among the most efficient, specific, and selective catalysts known. The ability to design efficient enzymes for a broad class of different reactions would be of tremendous practical interest for both science and the industry. Furthermore, the rational design of enzymes is a stringent test of our understanding of biological catalysis.There has been exciting progress in enzyme design. On the experimental side, catalytic antibodies, elicited by immunization with transition state analogs, have been shown to possess catalytic activity (Lerner et al. 1991;Hilvert 2000). More recently, several successful enzyme designs have been reported. Kaplan and DeGrado (2004) The computational methods used in enzyme site design to date, such as ORBIT from the Mayo group (Dahiyat and Mayo 1996) and Dezymer from the Hellinga group (Hellinga and Richards 1991), have primarily been used to search for catalytic site placement in one or a small number of scaffolds. In contrast, computational methods for searching for functional sites that employ geometric hashing (Russell 1998) In general, how to evaluate and optimize computational design methods for the creation of new molecules is a nontrivial problem. For robust conclusions, it is desirable to compare alternative methods and parameter choices by comparing results on a representative set of test systems. In the ''protein design cycle'' approach described by Dahiyat and Mayo (1997), alternative choices in a design method are tested by producing designs and experimentally characterizing them, and the choice is selected that produces designs with the desired properties. While this is a very powerful approach, experimentally characterizing a large number of designs for a number of different methods is slow and expensive, and therefore, it is desirable to have a faster and cheaper test. A purely in silico test for monomeric protein design developed in our group based on...

SummaryZika virus (ZIKV) remained obscure until the recent explosive outbreaks in French Polynesia (2013-2014) and South America (2015-2016). Phylogenetic studies reveal that ZIKV has evolved into African and Asian lineages. The Asian lineage of ZIKV is responsible for the recent epidemics in the Americas. However, the underlying mechanisms through which ZIKV rapidly and explosively spread from Asia to the Americas are limited. We have recently shown that nonstructural protein 1 (NS1) facilitates flavivirus acquisition by mosquitoes from an infected mammalian host and subsequently enhances viral prevalence in mosquitoes. Here, we report that the antigenemia of NS1 determines ZIKV infectivity in its mosquito vector Aedes aegypti, which acquires ZIKV via a blood meal. Clinical isolates from the most recent outbreak in the Americas were much more infectious in mosquitoes than the FSS13025 strain, which was isolated in Cambodia in 2010. Further analyses showed that these epidemic strains have more robust NS1 antigenemia than the FSS13025 strain because of an alanine-to-valine amino acid substitution at the 188th residue in NS1. ZIKV infectivity was enhanced by this residue substitution in the ZIKV FSS13025 strain in mosquitoes that acquired ZIKV from a viremic Type I and II interferon receptor-deficient (ifnagr-/-) C57BL/6 (AG6) mouse. Our results reveal that ZIKV evolved to acquire a spontaneous mutation in its NS1 protein, resulting in increased antigenemia of the protein. Enhancement of NS1 antigenemia in infected hosts promotes ZIKV infectivity and prevalence in mosquitoes, which potentially facilitates transmission during the recent ZIKV epidemics.