Evaluation of chemiluminescence immunoassays kits for detection of influenza A virus

目的考核甲型流感化学发光检测试剂的灵敏度和特异性。方法分别利用病毒分离培养液和入境人群的鼻咽拭子标本考查甲型流感试剂盒的检测灵敏度和特异性。结果化学发光法对H1、H3、H5、H7、H9等亚型的甲型流感病毒株均有很好的检出率,灵敏度明显优于flu A-dOT和dIrECTIgEn Ez flu A;对102份入境人群鼻咽拭子标本的检测灵敏度为97.62%。结论甲型流感化学发光检测试剂具有很好的灵敏度和特异性,适用于口岸现场的甲型流感快速筛查。Objective To evaluate the sensitivity and specificity of chemiluminescence immunoassays kit for detection of influenza A virus.Methods To analyze the sensitivity and specificity of three different assay kits for detection of influenza A virus by using the viral culture liquid and nasopharyngeal swabs from entry-exit travelers.Results The chemiluminescence immunoassays kit had a good detection rate when it was tested against a panel of influenza A virus strains(H1/H3/H5/H7/H9),and its sensitivity was much better than Flu A-DOT kit`s and Directigen EZ Flu A kit' chemiluminescence immunoassays kit used for the detection of 102 nasopharyngeal swabs from entryexit travelers had a detection sensitivity of 97.62%.Conclusion Chemiluminescence immunoassays kit had good sensitivity and specificity, which was fit for the rapid detection of influenza A virus at frontier ports.国家质检总局科技计划项目(2014IK045); 厦门市科技惠民项目(3502Z20144083

多倍体银鲫nanos2等位多态性、共线性和表达模式分析

为研究生殖干细胞(Germline stem cells, GSCs)的标记基因nanos2的功能,在银鲫(Carassius gibelio)中克隆了两个nanos2的同源基因(Homologs),将其命名为Cgnanos2a和Cgnanos2b,等位、系统进化树和共线性分析表明,在银鲫进化历程中发生了额外的两轮多倍化事件,是一个异源六倍体。qPCR分析表明Cgnanos2a和Cgnanos2b在5月龄银鲫精巢中的表达水平最高,其次是卵巢;对在孵化后25-190d的卵巢中的表达动态分析表明,孵化后25d的卵巢中的Cgnanos2a和Cgnanos2b转录水平最高,随后表达水平急剧下降;并且Cgnanos2a和Cgnanos2b呈现出偏向表达的特征。切片RNA原位杂交实验结果表明, Cgnanos2a和Cgnanos2b均特异地在银鲫卵巢邻近生殖上皮的胞囊(Cyst)中一类直径小于20 μm的细胞中表达, Cgnanos2a在精巢精小囊边缘一类单个或两个紧紧相邻的细胞中高表达,推测是银鲫的GSCs。此外,还可在精原细胞和初级精母细胞中检测到Cgnanos2a和Cgnanos2b的转录本。研究通过对nanos2阳性细胞的追踪描绘了银鲫卵巢早期胞囊的发育过程,为后续分离银鲫GSCs奠定了基础;同时对银鲫nanos2两个歧化的部分同源基因的序列特征、进化及表达特征分析,为研究鱼类多次多倍化事件后重复基因的进化提供了一个典型例子

多倍体银鲫nanos2等位多态性、共线性和表达模式分析

为研究生殖干细胞(Germline stem cells, GSCs)的标记基因nanos2的功能,在银鲫(Carassius gibelio)中克隆了两个nanos2的同源基因(Homologs),将其命名为Cgnanos2a和Cgnanos2b,等位、系统进化树和共线性分析表明,在银鲫进化历程中发生了额外的两轮多倍化事件,是一个异源六倍体。qPCR分析表明Cgnanos2a和Cgnanos2b在5月龄银鲫精巢中的表达水平最高,其次是卵巢;对在孵化后25-190d的卵巢中的表达动态分析表明,孵化后25d的卵巢中的Cgnanos2a和Cgnanos2b转录水平最高,随后表达水平急剧下降;并且Cgnanos2a和Cgnanos2b呈现出偏向表达的特征。切片RNA原位杂交实验结果表明, Cgnanos2a和Cgnanos2b均特异地在银鲫卵巢邻近生殖上皮的胞囊(Cyst)中一类直径小于20 μm的细胞中表达, Cgnanos2a在精巢精小囊边缘一类单个或两个紧紧相邻的细胞中高表达,推测是银鲫的GSCs。此外,还可在精原细胞和初级精母细胞中检测到Cgnanos2a和Cgnanos2b的转录本。研究通过对nanos2阳性细胞的追踪描绘了银鲫卵巢早期胞囊的发育过程,为后续分离银鲫GSCs奠定了基础;同时对银鲫nanos2两个歧化的部分同源基因的序列特征、进化及表达特征分析,为研究鱼类多次多倍化事件后重复基因的进化提供了一个典型例子

智能传感器主动协同的变电站机器人智能巡检系统及方法

本发明提供了一种智能传感器主动协同的变电站机器人智能巡检系统及方法，本发明巡检系统包括：智能机器人协同巡检层、自主协同层和变电站智能传感层形成三层智能巡检架构。本发明巡检系统中，巡检机器人进行自主路径规划完成图像数据采集，智能传感器感知被检测设备的状态并进行数据预处理和分析，巡检机器人和智能传感器通过近场通信机制和智能执行器进行主动协同，协同服务器基于巡检机器人感知数据进行复杂场景识别，以及对巡检机器人感知数据和智能传感器感知数据进行多源数据融合分析。显著的提升了巡视的及时性，避免操作过程的人员安全风险.减少巡检时的人工干预，保证变电巡视任务顺利进行

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies

Prediction of Energy Resolution in the JUNO Experiment

International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors