ABSTRACT
Fritillaria ussuriensis Bulbus, a genuine medicinal material of Northeast China, is the dry bulb of Fritillaria ussuriensis Maxim. It contains various active ingredients, such as alkaloids, alkaloids glycosides, adenosines, polysaccharides, and trace elements . It has antitussive, eliminating phlegm, antiasthmatic, antiulcer, antiplatelet aggregation, and anti-inflammatory. The qualitative and quantitative analysis of alkaloids, polysaccharides, nucleosides, and trace elements in Fritillaria ussuriensis Bulbus were reviewed, which is helpful for its cultivation and accurate application, and would provide a new choice for the treatment of coronavirus disease 2019 (COVID-19). © 2022
ABSTRACT
Background. As the COVID-19 pandemic continues, growing attention has been placed on whether patients previously infected with SARS-CoV-2 have an increased risk of developing and/or exacerbating medical complications. Our study aimed to determine whether individuals with previous evidence of SARS-CoV-2 infection prior to their current emergency department (ED) visit were more likely to present with specific clinical sign/symptoms, laboratory markers, and/or clinical complications. Methods. A COVID-19 seroprevalence study was conducted at Johns Hopkins Hospital ED (JHH ED) from March 16 to May 31, 2020. Evidence of ever having SARSCoV-2 infection (PCR positive or IgG Ab positive) was found in 268 ED patients at this time (i.e. infected and/or previously infected). These patients were matched 1:2 to controls, by date, to other patients who attended the JHHED. Clinical signs/symptoms, laboratory markers, and/or clinical complications associated with ED visits and/ or hospitalizations at JHH within 6 months after their initial ED visit was ed through chart review for these 804 patients. Cox proportional hazards regression analyses were performed. Results. Among 804 ED patients analyzed, 50% were female, 56% Black race, and 15% Hispanic with a mean age of 47 years. 323 (40%) patients had at least 1 subsequent ED visit and additional 70 (9%) had been admitted to JHH. After controlling for race and ethnicity, patients with evidence of current or prior COVID-19 infection were more likely to require supplemental oxygen [hazards ratio (HR) =2.53;p=0.005] and have a cardiovascular complication [HR =2.13;p=0.008] during the subsequent ED visit than the non-infected patients. Conclusion. Our findings demonstrate that those previously infected with SARSCoV-2 have an increased frequency of cardiovascular complications and need for supplemental oxygen in ED visits in the months after their initial SARS-CoV-2 infection was detected. EDs could serve as a critical surveillance site for monitoring post-acute COVID-19 syndrome complications.
ABSTRACT
The topological distance is to measure the structural difference between two graphs in a metric space. Graphs are ubiquitous, and topological measurements over graphs arise in diverse areas, including, e.g. COVID-19 structural analysis, DNA/RNA alignment, discovering the Isomers, checking the code plagiarism. Unfortunately, popular distance scores used in these applications, that scale over large graphs, are not metrics, and the computation usually becomes NP-hard. While, fuzzy measurement is an uncertain representation to apply for a polynomial-time solution for undirected multigraph isomorphism. But the graph isomorphism problem is to determine two finite graphs that are isomorphic, which is not known with a polynomial-time solution. This paper solves the undirected multigraph isomorphism problem with an algorithmic approach as NP=P and proposes a polynomial-time solution to check if two undirected multigraphs are isomorphic or not. Based on the solution, we define a new fuzzy measurement based on graph isomorphism for topological distance/structural similarity between two graphs. Thus, this paper proposed a fuzzy measure of the topological distance between two undirected multigraphs. If two graphs are isomorphic, the topological distance is 0;if not, we will calculate the Euclidean distance among eight extracted features and provide the fuzzy distance. The fuzzy measurement executes more efficiently and accurately than the current methods.