Epidemiological and genetic characterization of porcine epidemic diarrhea virus in the Mekong Delta, Vietnam, from 2015 to 2017.

Porcine epidemic diarrhea (PED) virus (PEDV) is a highly contagious virus. PED was first identified in 2008 and has greatly affected the Vietnamese pig production economy. The aim of this study was to investigate the epidemiological and genetic characteristics of PEDV in piglet herds in the Mekong Delta, Vietnam. Diarrheal stool and intestinal samples from 2262 piglets from 191 herds in five provinces were collected to test for the presence of PEDV. Ten PEDV strains were randomly selected for sequencing, and four genes encoding PEDV structural proteins were analyzed. The rates of herds and samples positive for PEDV were 27.23% and 27.72%, respectively. In positive herds, the morbidity and mortality of PEDV-positive piglets were 97.97% and 79.06%, respectively, with most of the infected piglets under 7 days of age. Phylogenetic analysis showed that the 10 PEDV strains from this study clustered with genotype G2 strains from Vietnam and neighboring countries. Many amino acid substitutions were identified in important antigenic regions in the spike protein of the 10 strains when compared to four PEDV vaccine strains. This study provides novel insights into the epidemiology and genetic diversity of circulating PEDV strains, which could facilitate the development of an appropriate and proactive strategy for controlling PED.

Predicting the severity of COVID-19 patients using the CD24-CSF1R index in whole blood samples.

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has become one of the most serious public health crises worldwide. Most infected people are asymptomatic but are still able to spread the virus. People with mild or moderate illnesses are likely to recover without hospitalization, while critically ill patients face a higher risk of organ injury or even death. In this study, we aimed to identify a novel biomarker that can predict the severity of COVID-19 patients. Clinical information and RNA-seq data of leukocytes from whole blood samples with and without a COVID-19 diagnosis (n = 100 and 26, respectively) were retrieved from the National Center for Biotechnology Information Gene Expression Omnibus database. Raw data were processed using the Transcripts Per Million (TPM) method and then transformed using log2 (TPM+1) for normalization. The CD24-CSF1R index was established. Violin plots, Kaplan-Meier curves, ROC curves, and multivariate Cox proportional hazards regression analyses were performed to evaluate the prognostic value of the established index. The CD24-CSF1R index was significantly associated with ICU admission (n = 50 ICU, 50 non-ICU) and ventilatory status (n = 42 ventilation, 58 non-ventilation) with p = 4.186e-11 and p = 1.278e-07, respectively. The ROC curve produced a relatively accurate prediction of ICU admission with an AUC of 0.8524. Additionally, patients with a high index had significantly fewer mechanical ventilation-free days than patients with a low index (p = 6.07e-07). Furthermore, the established index showed a strong prognostic ability for the risk of using a ventilator in the multivariate Cox regression model (p < 0.001). The CD24-CSF1R index was significantly associated with COVID-19 severity. The established index could have potential implications for prognosis, disease severity stratification, and clinical management.

Binding of inhibitors to the monomeric and dimeric SARS-CoV-2 Mpro† † Electronic supplementary information (ESI) available: The binding pose of ligands to SARS-CoV-2 Mpro, pulling forces and works over 8 independent trajectories of SMD simulations, interaction diagram between inhibitors and SARS-CoV-2 Mpro, the binding pose of other inhibitors to SARS-CoV-2 Mpro, the pulling force and pulling work of other inhibitors to SARS-CoV-2 Mpro. See DOI: 10.1039/d0ra09858b

SARS-CoV-2 rapidly infects millions of people worldwide since December 2019. There is still no effective treatment for the virus, resulting in the death of more than one million patients. Inhibiting the activity of SARS-CoV-2 main protease (Mpro), 3C-like protease (3CLP), is able to block the viral replication and proliferation. In this context, our study has revealed that in silico screening for inhibitors of SARS-CoV-2 Mpro can be reliably done using the monomeric structure of the Mpro instead of the dimeric one. Docking and fast pulling of ligand (FPL) simulations for both monomeric and dimeric forms correlate well with the corresponding experimental binding affinity data of 24 compounds. The obtained results were also confirmed via binding pose and noncovalent contact analyses. Our study results show that it is possible to speed up computer-aided drug design for SARS-CoV-2 Mpro by focusing on the monomeric form instead of the larger dimeric one. Binding of inhibitors to the monomeric SARS-CoV-2 Mpro is similar to the dimeric one.