(2020): Viral RNA level, serum antibody responses, and transmission risk in recovered COVID-19 patients with recurrent positive SARS-CoV-2 RNA test results: a population-based observational cohort study, Emerging Microbes & Infections,
Capsule-forming extracellular polysaccharides are crucial for bacterial host colonization, invasion, immune evasion, and ultimately pathogenicity. Due to warming ocean waters and human encroachment of coastal ecosystems, Vibrio parahaemolyticus has emerged as a globally important foodborne enteropathogen implicated in acute gastroenteritis, wound infections, and septic shock. Conventionally, the antigenic properties of lipopolysaccharide (LPS, O antigen) and capsular polysaccharide (CPS, K antigen) have provided a basis for serotyping V. parahaemolyticus, whereas disclosure of genetic elements encoding 13 O-serogroups have allowed molecular serotyping methods to be developed. However, the genetic structure of CPS loci for 71 K-serogroups has remained unidentified, limiting progress in understanding its roles in V. parahaemolyticus pathophysiology. In this study, we identified and characterized the genetic structure and their evolutionary relationship of CPS loci of 40 K-serogroups through whole genome sequencing of 443 V. parahaemolyticus strains. We found a distinct pattern of CPS gene cluster across different K-serogroups and expanded its new 3′-border by identifying glpX as a key gene conserved across all K-serogroups. A total of 217 genes involved in CPS biosynthesis were annotated. Functional contents and genetic structure of the 40 K-serogroups were analyzed. Based on inferences from species trees and gene trees, we proposed an evolution model of the CPS gene clusters of 40 K-serogroups. Horizontal gene transfer by recombination from other Vibrio species, gene duplication is likely to play instrumental roles in the evolution of CPS in V. parahaemolyticus. This is the first time, to the best of our knowledge, that a large scale of CPS gene clusters of different K-serogroups in V. parahaemolyticus have been identified and characterized in evolutionary contexts. This work should help advance understanding on the variation of CPS in V. parahaemolyticus and provide a framework for developing diagnostically relevant serotyping methods.
Abstract-In this paper, a cross-slot-coupled dual-band circularly polarized (CP) hybrid dielectric resonator antenna (DRA) is presented. The design concept is based on using a cross-slot as both a feeding structure of the DRA and an effective radiator. Full wave simulation is used to verify the proposed design concept in this paper. A prototype antenna is designed, fabricated, and measured. Good agreement is obtained between the simulated and measured results.
Controlling foodborne diseases requires robust outbreak detection and a comprehensive understanding of outbreak dynamics. Here, by integrating large-scale phylogenomic analysis of 3,642 isolates and epidemiological data, we performed "data-driven" outbreak detection and described the long-term outbreak dynamics of the leading seafood-associated bacterial pathogen, Vibrio parahaemolyticus, in a high-prevalence city, Shenzhen, China, over a 17-year period. Different from the widely accepted notion that sporadic patients and independent point-source outbreaks dominated foodborne infections, we found that 71% of isolates from patients grouped into within-1-month clusters that differed by ≤6 SNPs, indicating putative outbreaks; 56% of these clusters contained isolates exclusively from previously de ned "sporadic" patients, representing unrecognized cryptic outbreaks. Furthermore, we showed that despite the long time spans between clusters, 70% of them were genomically closely related and were inferred to arise from a small number of common sources, which provides evidence that hidden persistent reservoirs generated most of the outbreaks, rather than independent pointsources. Phylogeographical analysis further revealed the geographical heterogeneity of outbreaks and identi ed a coastal district as the potential hotspot of outbreaks and as the hub and major source of cross-district spread events. Our ndings provide a comprehensive picture of the long-term spatiotemporal dynamics of foodborne outbreaks for the rst time and present a novel perspective on the major source of foodborne infections, which will inform the design of future foodborne disease control strategies.
Purpose: Build a multi-objective Flexible Job-shop Scheduling Problem(FJSP) optimization model, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered, then Design a Modified Non-dominated Sorting Genetic Algorithm (NSGA-II) based on blood variation for above scheduling model. Design/methodology/approach: A multi-objective optimization theory based on Pareto optimal method is used in carrying out the optimization model. NSGA-II is used to solve the model. Findings: By analyzing the research status and insufficiency of multi-objective FJSP, Find that the difference in scheduling will also have an effect on energy consumption in machining process and environmental emissions. Therefore, job-shop scheduling requires not only guaranteeing the processing quality, time and cost, but also optimizing operation plan of machines and minimizing energy consumption. Originality/value: A multi-objective FJSP optimization model is put forward, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered. According to above model, Blood-Variation-based NSGA-II (BVNSGA-II) is designed. In which, the chromosome mutation rate is determined after calculating the blood relationship between two cross chromosomes, crossover and mutation strategy of NSGA-II is-589-Journal of Industrial Engineering and Management-http://dx.doi.org/10.3926/jiem.1075 optimized and the prematurity of population is overcome. Finally, the performance of the proposed model and algorithm is evaluated through a case study, and the results proved the efficiency and feasibility of the proposed model and algorithm.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.