Genetic analysis of chikungunya viruses imported to mainland China in 2008

<p>Abstract</p> <p>Background</p> <p>Chikungunya virus (CHIKV) has caused large outbreaks worldwide in recent years, especially on the islands of the Indian Ocean and India. The virus is transmitted by mosquitoes (<it>Aedes aegypti</it>), which are widespread in China, with an especially high population density in southern China. Analyses of full-length viral sequences revealed the acquisition of a single adaptive mutation providing a selective advantage for the transmission of CHIKV by this species. No outbreaks due to the local transmission of CHIKV have been reported in China, and no cases of importation were detected on mainland China before 2008. We followed the spread of imported CHIKV in southern China and analyzed the genetic character of the detected viruses to evaluate their potential for evolution.</p> <p>Results</p> <p>The importation of CHIKV to mainland China was first detected in 2008. The genomic sequences of four of the imported viruses were identified, and phylogenetic analysis demonstrated that the sequences were clustered in the Indian Ocean group; however, seven amino acid changes were detected in the nonstructural protein-coding region, and five amino acid changes were noted in the structural protein-coding regions. In particular, a novel substitution in E2 was detected (K252Q), which may impact the neurovirulence of CHIKV. The adaptive mutation A226V in E1 was observed in two imported cases of chikungunya disease.</p> <p>Conclusions</p> <p>Laboratory-confirmed CHIKV infections among travelers visiting China in 2008 were presented, new mutations in the viral nucleic acids and proteins may represent adaptive mutations for human or mosquito hosts.</p

The Prognostic Significance of NEK2 in Hepatocellular Carcinoma: Evidence from a Meta-Analysis and Retrospective Cohort Study

Background/Aims: Numerous studies have shown that NIMA-related kinase 2 (NEK2) expression in hepatocellular carcinoma (HCC) tissue is associated with survival and clinicopathological features; however, the evidence remains inconclusive. Thus, we aimed to further explore the prognostic and clinicopathological significance of NEK2 expression in HCC using a two-part study consisting of a retrospective cohort study and a meta-analysis. Methods: In the cohort study, NEK2 expression in 206 HCC samples and adjacent normal liver tissues was detected by immunohistochemistry (IHC). Patients were divided into a high NEK2 expression group and a low NEK2 expression group by the median value of the immunohistochemical scores. The Kaplan–Meier method with the log-rank test was used to analyze survival outcomes in the two groups, and multivariate analysis based on Cox proportional hazard regression models was applied to identify independent prognostic factors. In the meta-analysis, eligible studies were searched in PubMed, EMBASE, Web of Science, and CNKI databases. STATA version 12.0 (Stata Corporation, College Station, TX) was used for statistical analyses. Results: The IHC results of our cohort study showed higher NEK2 expression in HCC tissues compared with adjacent normal liver tissues. Multivariate analysis revealed that high NEK2 expression was an independent risk factor for poor overall survival (OS) [hazard ratio (HR) = 1.763; 95% CI, 1.060–2.935; P = 0.029] and disease-free survival (DFS) [hazard ratio (HR) = 1.687; 95% CI, 1.102–2.584; P = 0.016] in HCC patients. A total of 11 studies with 1,698 patients were enrolled in the meta-analysis, consisting of 10 studies from the database search and our cohort study. The pooled results revealed that high NEK2 expression correlated closely with poor OS among HCC patients (HR = 1.47; 95% CI, 1.21–1.80; P &#x3c; 0.01), and DFS/recurrence-free survival (RFS) (HR = 1.92; 95% CI, 1.41–2.63; P &#x3c; 0.01). Additionally, our meta-analysis also showed that the proportion of HCC patients with high NEK2 expression was greater in the group with larger tumors (&#x3e; 5 cm) than in the group with smaller tumors (≤ 5 cm) [odds ratio (OR) = 2.02; 95% CI, 1.13–3.64; P &#x3c; 0.01). Conclusion: Our study demonstrated that high NEK2 expression is a risk factor for poor survival in HCC patients. More prospective, homogeneous, and multiethnic studies are required to validate our findings

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Residual Recurrent Neural Networks for Learning Sequential Representations

Recurrent neural networks (RNN) are efficient in modeling sequences for generation and classification, but their training is obstructed by the vanishing and exploding gradient issues. In this paper, we reformulate the RNN unit to learn the residual functions with reference to the hidden state instead of conventional gated mechanisms such as long short-term memory (LSTM) and the gated recurrent unit (GRU). The residual structure has two main highlights: firstly, it solves the gradient vanishing and exploding issues for large time-distributed scales; secondly, the residual structure promotes the optimizations for backward updates. In the experiments, we apply language modeling, emotion classification and polyphonic modeling to evaluate our layer compared with LSTM and GRU layers. The results show that our layer gives state-of-the-art performance, outperforms LSTM and GRU layers in terms of speed, and supports an accuracy competitive with that of the other methods

The impact of educational digitalization on the creativity of students with special needs: the role of study crafting and creative self-efficacy

Abstract Special needs are of paramount importance in international equitable education. The focus on students with special needs has become the basis of current special education and education reform. The world is currently undergoing a pivotal phase of digital transformation, with educational digitalization gradually developing. However, only a few studies have focused on the effect of educational digitalization on the creativity of students with special needs, and most of them have ignored its internal mechanism. This study therefore aims to explore the manner in which and the circumstances under which educational digitalization affects the creativity of students with special needs. Building upon information theory, this study proposes a mediated moderating framework to examine the effects of educational digitalization on the creativity of students with special needs, considering the mediating role of studying crafting and the moderating effect of creative self-efficacy. A survey methodology was employed to collect empirical data on the interrelationships among educational digitalization, study crafting, creative self-efficacy, and the creativity of students with special needs. The results demonstrated a significant positive relationship between educational digitalization and the creativity of students with special needs through study crafting. Furthermore, creative self-efficacy was found to play a moderating role in this process. The findings provide educators and policymakers with practical guidance on how to optimize the implementation of digital technologies in educational environments in order to promote education equity

Hierarchical Matching Algorithm for Relay Selection in MEC-Aided Ultra-Dense UAV Networks

With the rapid development of communication technology, unmanned aerial vehicle–mobile edge computing (UAV-MEC) networks have emerged with powerful capabilities. However, existing research studies have neglected the issues involving user grouping and relay selection structures under UAV cluster-assisted communication. Therefore, in this article, we present a comprehensive communication–computing resource allocation for UAV-MEC networks. In particular, ground users make stable user groups first, and then multiple UAVs act as relays in order to assist these user groups in simultaneously uploading their tasks to the terrestrial base station at the edge server. Moreover, in order to maximize the system’s overall throughput, a more flexible and hierarchical matching relay selection algorithm is proposed in terms of matching the ground user groups and corresponding UAVs. For vulnerable users, we also propose a weighted relay selection algorithm to maximize the system performance. Furthermore, simulation results show that the proposed relay selection algorithm achieves a significant gain in comparison with the other benchmarks, and the stability of the proposed algorithms could be verified

Enhanced thermal properties and lab-scale thermal performance of polyethylene glycol/modified halloysite nanotube form-stable phase change material cement panel

Phase change material (PCM) with large thermal storage capacity and constant phase change temperature is one of the most promising materials for building energy saving. However, its leakage problem and poor thermal conductivity have largely hindered its large-scale application. This study, therefore, utilizes acid-modified halloysite to encapsulate PCM for preparing form-stable PCM with enhanced thermal storage capacity and systematically investigates the thermal conductivity enhancement on the thermal performance of FSPCM cement panel by a lab-scale test chamber. The study results indicated that the maximum PCM loading for the acidmodified halloysite-based FSPCM was 55 wt%, 10 wt% higher than that of the original one and the associated mechanism of acid-modification was in-depth discussed. The as-prepared FSPCM had comparatively high thermal storage capacity and appropriate phase change temperature. Although the addition of FSPCM may decrease the mechanical properties of cement panels, the prepared sample can still meet the standard for building application. More importantly, the thermal conductivity enhancement of the FSPCM cement panel had a different impact on its thermal performance for various models and the reasons for this difference were systematically investigated. The study results can provide insights into the preparation and building application of FSPCM

Research on Wide-Temperature Rechargeable Sodium-Sulfur Batteries: Features, Challenges and Solutions

Sodium-sulfur (Na-S) batteries hold great promise for cutting-edge fields due to their high specific capacity, high energy density and high efficiency of charge and discharge. However, Na-S batteries operating at different temperatures possess a particular reaction mechanism; scrutinizing the optimized working conditions toward enhanced intrinsic activity is highly desirable while facing daunting challenges. This review will conduct a dialectical comparative analysis of Na-S batteries. Due to its performance, there are challenges in the aspects of expenditure, potential safety hazards, environmental issues, service life and shuttle effect; thus, we seek solutions in the electrolyte system, catalysts, anode and cathode materials at intermediate and low temperatures (T < 300 °C) as well as high temperatures (300 °C < T < 350 °C). Nevertheless, we also analyze the latest research progress of these two situations in connection with the concept of sustainable development. Finally, the development prospects of this field are summarized and discussed to look forward to the future of Na-S batteries

ECO : An Integrated Gene Expression Omnibus for Mouse Endothelial Cells In Vivo

Endothelial cell (EC) plays critical roles in vascular physiological and pathological processes. With the development of high-throughput technologies, transcriptomics analysis of EC has increased dramatically and a large amount of informative data have been generated. The dynamic patterns of gene expression in ECs under various conditions were revealed. Unfortunately, due to the lack of bioinformatics infrastructures, reuse of these large-scale datasets is challenging for many scientists. Here, by systematic re-analyzing, integrating, and standardizing of 203 RNA sequencing samples from freshly isolated mouse ECs under 71 conditions, we constructed an integrated mouse EC gene expression omnibus (ECO). The ECO database enables one-click retrieval of endothelial expression profiles from different organs under different conditions including disease models, genetic modifications, and clinically relevant treatments in vivo. The EC expression profiles are visualized with user-friendly bar-plots. It also provides a convenient search tool for co-expressed genes. ECO facilitates endothelial research with an integrated tool and resource for transcriptome analysis. The ECO database is freely available at https://heomics. shinyapps.io/ecodb/

Outcomes and prognosis of non-small cell lung cancer patients who underwent curable surgery: a protocol for a real-world, retrospective, population-based and nationwide Chinese National Lung Cancer Cohort (CNLCC) study

Introduction Surgery is one of the main approaches for the comprehensive treatment of early and locally advanced non-small cell lung cancer (NSCLC). This study conducts a nationwide multicentre study to explore factors that could influence the outcomes of patients with I–IIIA NSCLC who underwent curable surgery in real-world scenarios.Methods and analysis All patients diagnosed with NSCLC between January 2013 and December 2020 will be identified from 30 large public medical services centres in mainland China. The algorithm of natural language processing and artificial intelligence techniques were used to extract data from electronic health records of enrolled patients who fulfil the inclusion criteria. Six categories of parameters are collected and stored from the electronic records, then the parameters will be structured as a high-quality structured case report form. The code book will be compiled and each parameter will be classified and designated a code. In addition, the study retrieves the survival status and causes of death of patients from the Chinese Centre for Disease Control and Prevention. The primary endpoints are overall survival and the secondary endpoint is disease-free survival. Finally, an online platform is formed for data queries and the original records will be stored as secure electronic documents.Ethics and dissemination The study has been approved by the Ethical Committee of the Chinese Academy of Medical Sciences. Study findings will be disseminated via presentations at conferences and publications in open-access journals. This study has been registered in the Chinese Trial Register (ChiCTR2100052773) on 11 May 2021, http://www.chictr.org.cn/showproj.aspx?proj=136659.Trial registration number ChiCTR2100052773