ABSTRACT
Comprehensive analyses of viral genomes can provide a global picture on SARS-CoV-2 transmission and help to predict the oncoming trends of pandemic. This molecular tracing is mainly conducted through extensive phylogenetic network analyses. However, the rapid accumulation of SARS-CoV-2 genomes presents an unprecedented data size and complexity that has exceeded the capacity of existing methods in constructing evolution network through virus genotyping. Here we report a Viral genome Evolution Network Analysis System (VENAS), which uses Hamming distances adjusted by the minor allele frequency to construct viral genome evolution network. The resulting network was topologically clustered and divided using community detection algorithm, and potential evolution paths were further inferred with a network disassortativity trimming algorithm. We also employed parallel computing technology to achieve rapid processing and interactive visualization of >10,000 viral genomes, enabling accurate detection and subtyping of the viral mutations through different stages of Covid-19 pandemic. In particular, several core viral mutations can be independently identified and linked to early transmission events in Covid-19 pandemic. As a general platform for comprehensive viral genome analysis, VENAS serves as a useful computational tool in the current and future pandemics.
ABSTRACT
Objective To investigate the clinical features of patients with multiple sclerosis (MS) and restless legs syndrome (RLS) and to further examine relevant factors that may contribute to the co-occurrence of MS and RLS.Methods Seventy MS patients were recruited in the present study.The RLS screen was further performed in MS patients based on the diagnostic criteria for RLS.MS patients with RLS were designated as the case group and MS patients without RLS served as the control group.The clinical data including age of MS onset,MS duration and clinical disability by the expanded disability status scale (EDSS) were analyzed.Results There were 12 MS patients with RLS in total 70 MS patients and the incidence rate was 17.1％.The average age of MS onset in the RLS group was (47.6 ± 10.0) years,and (40.1 ± 10.4 ) years in the control group.The difference of average age of MS onset was found to be significant (t =2.29,P =0.030).The average history of MS in the RLS group was ( 12.6 ± 6.8 ) years,and ( 8.2 ± 6.6) years in the control group ( t =2.10,P =0.039).The average EDSS of the RLS group was 4.5 ±2.5,and 2.5 ±2.0 in the control group (t =3.02,P =0.004).There was no significant association between RLSRS and EDSS in MS patients with RLS (P =0.15).Conclusion The incidence rate of RLS in MS patients was high.Among patients with MS,RLS was associated with older age,longer MS duration,and more severe disability.
