(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.

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.

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.

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.

The dynamic nature of Vibrio parahaemolyticus epidemiology has presented a unique challenge for disease intervention strategies. Despite the continued rise of disease incidence and outbreaks of vibriosis, as well as the global emergence of pandemic clones and serovariants with enhanced virulence, there is a paucity of molecular methods for the serotyping of V. parahaemolyticus strains to improve disease surveillance and outbreak investigations. We describe the development of a multiplex ligation reaction based on probe melting curve analysis (MLMA) for the simultaneous identification of 11 clinically most common V. parahaemolyticus serotypes spanning a 10-year period. Through extensive sequence analyses using 418 genomes, specific primers and probes were designed for a total of 22 antigen gene targets for the O- and K- serogroups. Additionally, the toxR gene was incorporated into the assay for the confirmation of V. parahaemolyticus. All gene targets were detected by the assay and gave expected Tm values, without any cross reactions between the 11 clinically common serotypes or with 38 other serotypes. The limit of identification for all gene targets ranged from 0.1 to 1 ng/μL. The intra- and inter-assay standard deviations and the coefficients of variation were no more than 1°C and <1% respectively, indicating a highly reproducible assay. A multicenter double-blind clinical study was conducted using the traditional V. parahaemolyticus identification workflow and the MLMA assay workflow in parallel. From consecutive diarrheal stool specimens (n = 6118) collected over a year at 10 sentinel hospitals, a total of 153 V. parahaemolyticus isolates (2.5%) were identified by both workflows. A total agreement (kappa = 1.0) between the serotypes identified by the MLMA assay and conventional serological method was demonstrated. This is the first molecular assay to simultaneously identify multiple clinically important V. parahaemolyticus serotypes, which satisfies the acute need for a practical, rapid and robust identification of V. parahaemolyticus serotypes to facilitate the timely detection of vibriosis outbreaks and surveillance.

Background SARS-CoV-2 is a newly emerged coronavirus, causing the coronavirus disease 2019 (COVID-19) outbreak in December, 2019. As drugs and vaccines of COVID-19 remain in development, accurate virus detection plays a crucial role in the current public health crisis. Quantitative real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) kits have been reliably used for detection of SARS-CoV-2 RNA since the beginning of the COVID-19 outbreak, whereas isothermal nucleic acid amplification-based point-of-care automated kits have also been considered as a simpler and rapid alternative. However, as these kits have only been developed and applied clinically within a short timeframe, their clinical performance has not been adequately evaluated to date. We describe a comparative study between a newly developed cross-priming isothermal amplification (CPA) kit (Kit A) and five RT-qPCR kits (Kits B–F) to evaluate their sensitivity, specificity, predictive values and accuracy. Methods Fifty-two clinical samples were used including throat swabs (n = 30), nasal swabs (n = 7), nasopharyngeal swabs (n = 7) and sputum specimens (n = 8), comprising confirmed (n = 26) and negative cases (n = 26). SARS-CoV-2 detection was simultaneously performed on each sample using six nucleic acid amplification kits. The sensitivity, specificity, positive/negative predictive values (PPV/NPV) and the accuracy for each kit were assessed using clinical manifestation and molecular diagnoses as the reference standard. Reproducibility for RT-qPCR kits was evaluated in triplicate by three different operators using a SARS-CoV-2 RNA-positive sample. On the basis of the six kits’ evaluation results, CPA kit (Kit A) and two RT-qPCR Kits (Kit B and F) were applied to the SARS-CoV-2 detection in close-contacts of COVID-19 patients. Results For Kit A, the sensitivity, specificity, PPV/NPV and accuracy were 100%. Among the five RT-qPCR kits, Kits B, C and F had good agreement with the clinical diagnostic reports (Kappa ≥ 0.75); Kits D and E were less congruent (0.4 ≤ Kappa < 0.75). Differences between all kits were statistically significant (P < 0.001). The reproducibility of RT-qPCR kits was determined using a coefficients of variation (CV) between 0.95% and 2.57%, indicating good reproducibility. Conclusions This is the first comparative study to evaluate CPA and RT-qPCR kits’ specificity and sensitivity for SARS-CoV-2 detection, and could serve as a reference for clinical laboratories, thus informing testing protocols amid the rapidly progressing COVID-19 pandemic.

Compressive strength is an important mechanical property of high-strength concrete (HSC), but testing methods are usually uneconomical, time-consuming, and labor-intensive. To this end, in this paper, a long short-term memory (LSTM) model was proposed to predict the HSC compressive strength using 324 data sets with five input independent variables, namely water, cement, fine aggregate, coarse aggregate, and superplasticizer. The prediction results were compared with those of the conventional support vector regression (SVR) model using four metrics, root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and correlation coefficient (R2). The results showed that the prediction accuracy and reliability of LSTM were higher with R2 = 0.997, RMSE = 0.508, MAE = 0.08, and MAPE = 0.653 compared to the evaluation metrics R2 = 0.973, RMSE = 1.595, MAE = 0.312, MAPE = 2.469 of the SVR model. The LSTM model is recommended for the pre-estimation of HSC compressive strength under a given mix ratio before the laboratory compression test. Additionally, the Shapley additive explanations (SHAP)-based approach was performed to analyze the relative importance and contribution of the input variables to the output compressive strength.