Use of Real- time RT-PCR Analysis for mRNA Expression of Tobacco Ferritin Gene (NtFer1)

To understand the use of real-time reverse transcription-polymerase chain reaction （real-time RT-PCR） for detecting the relative abundance of mRNA, the expression of a tobacco ferrltin gene （NtFer1） was detected by Northern blot and real-time RT-PCR. The results indicated that both of the two methods were able to detect mRNA expression of NtFer1 cleady and similady, namely NtFer1 expression was responsive to iron-ovedoad, and the abundance of NtFer1 mRNA was greatly increased after iron loaded for 6 h. To compare the effect and sensitivity of two methods, results revealed that Northern blot need 30 μg of total RNA and at least 3 days for the total protocol performance, whereas real-time RT-PCR only need 2 μg of total RNA and 1.5 h. The real-time RT-PCR is rather sensitive and effective than Northern blot. Real-time RT-PCR analysis can be used to rapidly detect the relative abundance of mRNA expression instead of Northern blot analysis.

4种植物源性成分多重real-time PCR检测方法的建立及其在食用淀粉中的应用

建立一种可同时快速检测红薯、木薯、马铃薯、玉米源性成分的多重实时聚合酶链式反应(real-time polymerase chain reaction,real-time PCR)方法。分别以红薯g3pdh基因、木薯g3pdh基因、马铃薯UGPase基因、玉米zSSIIb基因为靶基因设计特异性引物和TaqMan探针,以18S rRNA基因为内参基因,建立多重real-time PCR方法,开展方法学验证,并对不同掺入比例模拟样品和实际淀粉样品进行检测。结果显示,该方法具有高通量、特异性强、灵敏度高等优点。与15种非目标源性均无交叉反应;对目标DNA的检测灵敏度可达到3×10^(-3) ng/μL,且具有良好的线性关系和扩增效率;对淀粉样品的检出限可达0.1%,对50份实际样品进行检测,结果与参比方法一致,说明建立的多重real-time PCR法可用于食用淀粉种类掺假鉴别检测。

Real- Time Color Enhancement Method Used for Intelligent Mobile Terminals

In certain environments and under some conditions, the video images taken by the intelligent mobile video phones seem dark, and the colors are not bright or saturated enough.This paper presents an adaptive method to enhance the video image brightness visualization and the color performance depending on the certain hardware property and function parameters. The experimental results prove that this method can enhance the colors and the contrast of the video images, based on the estimated quality feature values of each frame, without using the extra Digital Signal Processor (DSP).

基于病菌孢子捕捉和real-time PCR技术的田间空气中小麦白粉病菌孢子动态监测及病情估计模型研究

利用Burkard定容式孢子捕捉器结合real-time PCR定量技术,分别对种植高抗、中感和高感白粉病小麦品种的田间空气中白粉病菌分生孢子浓度进行监测,结果表明,real-time PCR定量与传统的显微观察计数两种方法测得的孢子浓度呈显著正相关(P≤0.01),且两种病菌孢子计数方法在同一抗性品种上监测到的孢子浓度动态相近。此外,两种方法测得的孢子浓度与各气象因子的相关性分析结果一致,空气中的白粉病菌孢子浓度主要与空气相对湿度显著正相关。在此基础上,利用两种方法测定的田间空气中白粉病菌孢子浓度分别建立了基于累积孢子浓度的田间病情估计模型。分析发现,基于两种孢子浓度测定方法建立的病情估计模型间无显著性差异,表明real-time PCR定量技术测定的孢子浓度在构建白粉病病情估计模型上具有一定可行性。该结果为real-time PCR定量技术与病菌孢子捕捉技术相结合用于小麦白粉病的监测和预测提供理论依据。

马乳酒样乳杆菌马乳酒样亚种real-time PCR检测方法的建立与应用

本研究建立了一种特异性实时聚合酶链式反应(real-time polymerase chain reaction,real-time PCR)检测方法,根据模式菌株马乳酒样乳杆菌马乳酒样亚种ZW3的16S rDNA序列和全基因组序列设计筛选特异性引物,采用SYBR Green I荧光染料建立real-time PCR方法,并对方法的特异性、灵敏度、重复性和混合体系等进行检测。结果表明,本研究所建立的方法特异性强、灵敏度高、重复性好,建立real-time PCR的标准曲线,其决定系数R2为0.965,具有良好的线性关系,且在马乳酒样乳杆菌马乳酒样亚种及混合体系中可以特异性检出。综上,本研究建立的real-time PCR法可以快速、准确地检测马乳酒样乳杆菌马乳酒样亚种,为马乳酒样乳杆菌的特异性定性定量检测提供了一种新的方法。

基于Real-time PCR法检测乳粉中牛源性成分定量研究

基于Real-timePCR建立了乳粉中牛源性成分相对定量检测方法,并对牛的特异性引物与探针进行了特异性、灵敏度和稳定性测试。通过模拟不同浓度牛乳粉与马乳粉混合样本,根据其△Ct值的函数关系进行线性拟合进而绘制标准曲线,建立乳粉中牛源性成分的相对定量检测。结果显示,该方法的最低检测限为0.00001 mg/mL,回收率为91.11%~119.2%,组间变异系数≤0.58%、组内变异系数≤1.44%。说明该方法在特异性与稳定性上适用于乳粉中牛源性成分及含量的掺假检测。

一种基于real-time PCR技术的TTV检测方法的建立及应用

目的:本研究旨在开发一种具有更高灵敏度和特异性的TTV检测技术,为揭示TTV在多种疾病过程中的作用提供重要的技术支持。方法:为了更精确、灵敏的检测TTV,本研究分析了目前公布的所有亚型的TTV基因序列,在此基础上建立了一种基于UTR区域的real-time PCR检测方法,并与文献报道应用较为广泛的PCR检测方法进行了对比。结果:本研究建立的方法在1×10^(7)~1×10^(1) copies/μL标准品浓度范围内具有良好的线性关系,相关系数为1.000,斜率为-3.446,检测下限为1×10^(1) copies/μL。重复性试验结果显示,组内变异系数为7.22%,表明本方法重复性、稳定性较强。针对30份临床样本,使用本研究建立的real-time PCR检测方法及目前被多个研究所使用的4套引物进行对比。结果表明,本研究所建立的方法灵敏度显著高于文献中报道的4种方法(P<0.01);Sanger测序结果表明,本方法检测出的30份阳性样本均为TTV,检测特异性为100%。结论:本研究采用基于TaqMan探针的real-time PCR检测方法,检测灵敏性高、覆盖基因型范围广,尤其对于TTV病毒载量较低的情况下能够进行定量检测,对于TTV病毒的致病性及作为免疫标志物的应用提供重要的技术支持。

Real-time Rescue Target Detection Based on UAV Imagery for Flood Emergency Response

Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including high-resolution imagery and exceptional mobility,making them well suited for monitoring flood extent and identifying rescue targets during floods.However,there are some challenges in interpreting rescue information in real time from flood images captured by UAVs,such as the complexity of the scenarios of UAV images,the lack of flood rescue target detection datasets and the limited real-time processing capabilities of the airborne on-board platform.Thus,we propose a real-time rescue target detection method for UAVs that is capable of efficiently delineating flood extent and identifying rescue targets(i.e.,pedestrians and vehicles trapped by floods).The proposed method achieves real-time rescue information extraction for UAV platforms by lightweight processing and fusion of flood extent extraction model and target detection model.The flood inundation range is extracted by the proposed method in real time and detects targets such as people and vehicles to be rescued based on this layer.Our experimental results demonstrate that the Intersection over Union(IoU)for flood water extraction reaches an impressive 80%,and the IoU for real-time flood water extraction stands at a commendable 76.4%.The information on flood stricken targets extracted by this method in real time can be used for flood emergency rescue.

Prevalence and Antibiotic Resistance of Urinary Tract Pathogens, with Molecular Identification of Klebsiella pneumoniae, Klebsiella oxytoca, and Acinetobacter spp., Using Multiplex Real-Time PCR

Urinary tract infections (UTIs) caused by uropathogens are a significant public health problem, and their treatment primarily relies on antibiotic therapy. However, the increasing global development of antibiotic resistance necessitates updating diagnostic techniques to ensure higher sensitivity and specificity, especially with advancements in science and medicine. This study aimed to evaluate the prevalence of UTIs and antibiotic resistance profiles through urine culture, as well as to identify Klebsiella pneumoniae, Klebsiella oxytoca, and Acinetobacter spp. in urine samples using a molecular approach with multiplex real-time PCR. From May 3 to July 25, 2023, at the Pietro Annigoni Biomolecular Research Center (CERBA) and Saint Camille Hospital of Ouagadougou (HOSCO), 209 urine samples collected from patients with suspected UTIs were analyzed using both urine culture and multiplex real-time PCR. Among the 209 patients, 52.15% were male and 47.85% female, with an average age of 46.87 ± 21.33 years. Urine cultures revealed an overall UTI prevalence of 23.44%, with a prevalence of 8.13% in men versus 15.31% in women (P = 0.023). The bacterial prevalence rates were as follows: Escherichia coli (12.92%), Klebsiella spp. (7.18%), Enterobacter cloacae (1.44%), Staphylococcus aureus (0.96%), and other bacteria. Klebsiella spp. demonstrated 100% resistance to Amoxicillin and Amoxicillin/Clavulanic Acid, while Escherichia coli showed 96.2% and 65.4% resistance to Amoxicillin and Amoxicillin/Clavulanic Acid, respectively. PCR analysis of the target bacteria revealed mono-infection prevalence rates of Klebsiella pneumoniae (10.39%), Klebsiella oxytoca (7.79%), and Acinetobacter spp. (7.79%), along with a co-infection prevalence rate of Klebsiella pneumoniae/Acinetobacter spp. (1.30%). This study demonstrated that PCR, with its high sensitivity and specificity, could effectively distinguish Klebsiella pneumoniae from Klebsiella oxytoca and detect Acinetobacter spp. in less than 24 hours—something urine culture alone could not achieve. The relative ease of automating urine PCR testing, combined with its diagnostic accuracy and rapid turnaround time, makes it a valuable addition to modern medical practice for the laboratory diagnosis of UTIs.

24重荧光real-time PCR技术在食物中毒快速检测中的应用

目的:应用24重荧光real-time PCR检测技术快速筛检食物中毒病原菌,结合国家标准中的培养法探讨24重荧光real-time PCR检测技术符合性和应用价值。方法:采用高灵敏度、高特异性的24重荧光real-time PCR检测技术作为中毒病原菌的初筛方法,国标方法进行细菌分离培养,并对分离出的病原菌进行生化鉴定。结果:5份食物中毒患者肛拭子在增菌前检出4份霍乱弧菌核酸(非O1/非O139群,24重荧光real-time PCR),9份患者肛拭子在增菌后检出5株霍乱弧菌(非O1/非O139群,国标培养法),其中包含4份PCR技术初筛阳性样品,两个方法的符合率为80%。所有样本均未检出沙门氏菌、志贺菌、副溶血性弧菌、致泻性大肠埃希菌以及金黄色葡萄球菌。结论:应用24重荧光real-time PCR检测技术同时检测24种常见致病病原菌,能高效锁定中毒病原菌。将其与国标培养法相结合,对临床治疗和食物中毒快速处置能起到积极作用,值得应用和推广。

Real-Time Monitoring of Meteorological Data at In-Situ GCW Remediation Sites

To optimize the self-organization network, self-adaptation, real-time monitoring, remote management capability, and equipment reuse level of the meteorological station supporting the portable groundwater circulation wells, and to provide real-time and effective technical services and environmental data support for groundwater remediation, a real-time monitoring system design of the meteorological station supporting the portable groundwater circulation wells based on the existing equipment is proposed. A variety of environmental element information is collected and transmitted to the embedded web server by the intelligent weather transmitter, and then processed by the algorithm and stored internally, displayed locally, and published on the web. The system monitoring algorithm and user interface are designed in the CNWSCADA development environment to realize real-time processing and analysis of environmental data and monitoring, control, management, and maintenance of the system status. The PLC-controlled photovoltaic power generating panels and lithium battery packs are in line with the concept of energy saving and emission reduction, and at the same time, as an emergency power supply to guarantee the safety of equipment and data when the utility power fails to meet the requirements. The experiment proves that the system has the characteristics of remote control, real-time interaction, simple station deployment, reliable operation, convenient maintenance, and green environment protection, which is conducive to improving the comprehensive utilization efficiency of various types of environmental information and providing reliable data support, theoretical basis and guidance suggestions for the research of groundwater remediation technology and its disciplines, and the research and development of the movable groundwater cycling well monitoring system.

垂体后叶粉中3种动物源性成分多重real-time PCR检测方法的建立及应用

目的基于三重实时聚合酶链式反应(real-time polymerase chain reaction,real-time PCR)技术同时快速检测垂体后叶粉中的猪、牛、羊性动物源性成分。方法采用CTAB法提取样品及对照品DNA,以线粒体基因为靶基因设计并合成三重real-time PCR的引物探针,并对建立方法进行验证,用于检测垂体后叶粉样品是否与标识一致。结果猪、牛、羊源性成分的最低检测浓度为10 pg/μL,采用建立的方法检测3批垂体后叶粉样品,均只检测出猪源性成分。结论建立的方法可用于同时检测垂体后叶粉中的猪、牛、羊源性成分,可为相关工作提供技术支持。

A real-time performance improvement method for composite time scale

The composite time scale(CTS)provides a stable,accurate,and reliable time scale for modern society.The improvement of CTS’s real-time performance will improve its stability,which strengths related applications’performance.Aiming at this goal,a method achieved by determining the optimal calculation interval and accelerating adjustment stage is proposed in this paper.The determinants of the CTS’s calculation interval(characteristics of the clock ensemble,the measurement noise,the time and frequency synchronization system’s noise and the auxiliary output generator noise floor)are studied and the optimal calculation interval is obtained.We also investigate the effect of ensemble algorithm’s initial parameters on the CTS’s adjustment stage.A strategy to get the reasonable initial parameters of ensemble algorithm is designed.The results show that the adjustment stage can be finished rapidly or even can be shorten to zero with reasonable initial parameters.On this basis,we experimentally generate a distributed CTS with a calculation interval of 500 s and its stability outperforms those of the member clocks when the averaging time is longer than1700 s.The experimental result proves that the CTS’s real-time performance is significantly improved.

A CNN-Based Single-Stage Occlusion Real-Time Target Detection Method

Aiming at the problem of low accuracy of traditional target detection methods for target detection in endoscopes in substation environments, a CNN-based real-time detection method for masked targets is proposed. The method adopts the overall design of backbone network, detection network and algorithmic parameter optimisation method, completes the model training on the self-constructed occlusion target dataset, and adopts the multi-scale perception method for target detection. The HNM algorithm is used to screen positive and negative samples during the training process, and the NMS algorithm is used to post-process the prediction results during the detection process to improve the detection efficiency. After experimental validation, the obtained model has the multi-class average predicted value (mAP) of the dataset. It has general advantages over traditional target detection methods. The detection time of a single target on FDDB dataset is 39 ms, which can meet the need of real-time target detection. In addition, the project team has successfully deployed the method into substations and put it into use in many places in Beijing, which is important for achieving the anomaly of occlusion target detection.

A step to the decentralized real-time timekeeping network

The composite time scale(CTS) provides an accurate and stable time-frequency reference for modern science and technology. Conventional CTS always features a centralized network topology, which means that the CTS is accompanied by a local master clock. This largely restricts the stability and reliability of the CTS. We simulate the restriction and analyze the influence of the master clock on the CTS. It proves that the CTS's long-term stability is also positively related to that of the master clock, until the region dominated by the frequency drift of the H-maser(averaging time longer than ~10~5s).Aiming at this restriction, a real-time clock network is utilized. Based on the network, a real-time CTS referenced by a stable remote master clock is achieved. The experiment comparing two real-time CTSs referenced by a local and a remote master clock respectively reveals that under open-loop steering, the stability of the CTS is improved by referencing to a remote and more stable master clock instead of a local and less stable master clock. In this way, with the help of the proposed scheme, the CTS can be referenced to the most stable master clock within the network in real time, no matter whether it is local or remote, making democratic polycentric timekeeping possible.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

Effects of data smoothing and recurrent neural network(RNN)algorithms for real-time forecasting of tunnel boring machine(TBM)performance

Tunnel boring machines(TBMs)have been widely utilised in tunnel construction due to their high efficiency and reliability.Accurately predicting TBM performance can improve project time management,cost control,and risk management.This study aims to use deep learning to develop real-time models for predicting the penetration rate(PR).The models are built using data from the Changsha metro project,and their performances are evaluated using unseen data from the Zhengzhou Metro project.In one-step forecast,the predicted penetration rate follows the trend of the measured penetration rate in both training and testing.The autoregressive integrated moving average(ARIMA)model is compared with the recurrent neural network(RNN)model.The results show that univariate models,which only consider historical penetration rate itself,perform better than multivariate models that take into account multiple geological and operational parameters(GEO and OP).Next,an RNN variant combining time series of penetration rate with the last-step geological and operational parameters is developed,and it performs better than other models.A sensitivity analysis shows that the penetration rate is the most important parameter,while other parameters have a smaller impact on time series forecasting.It is also found that smoothed data are easier to predict with high accuracy.Nevertheless,over-simplified data can lose real characteristics in time series.In conclusion,the RNN variant can accurately predict the next-step penetration rate,and data smoothing is crucial in time series forecasting.This study provides practical guidance for TBM performance forecasting in practical engineering.

4种动物源性成分多重real-time PCR检测方法的建立及其在驴肉制品检测中的应用

建立一种同时快速检测驴、马、猪及鸭源性成分的四重实时聚合酶链式反应(real-time polymerase chain reaction,real-time PCR)方法。分别以4种源性成分的Nad5、ATpase6、ATP8、cytb基因为靶基因设计特异性引物和TaqMan探针,以18S rRNA基因为内参基因,建立多重real-time PCR方法,并对该方法进行方法学验证,同时对不同掺入比例模拟样品、不同加工工艺模拟样品和实际驴肉样品进行检测。结果显示,该方法具有高通量、特异性强、灵敏度高等优点。当Ct值≤35.0时,方法对16种非目标源性具有良好特异性;灵敏度可检测到质量浓度为2×10^(-4)ng/μL的模板DNA;对生肉的检出限为肉含量的0.001%,对熟肉制品的检出限为肉含量的0.01%;对100份实际样品进行检测,结果与标准方法一致,说明建立的多重real-time PCR法可用于肉及肉制品中常见掺假源性成分的检测。

肉中猪源性成分Real-time PCR定量检测技术

【目的】建立一种快速、准确的肉中猪源性成分定量检测方法。【方法】首先从GenBank数据库中筛选猪特异性的微卫星DNA,根据微卫星DNA核酸序列设计引物,对常见10种动物基因组DNA进行PCR扩增,通过有无扩增产物判断筛选的微卫星DNA对猪源性成分的特异性。然后根据微卫星DNA核酸序列,设计特异性引物和探针,建立猪源性成分Real-time PCR检测方法,采用双标准曲线分别对猪源性成分和总动物源性成分进行定量,计算猪源性成分的百分含量。【结果】筛选到猪特异性微卫星DNA(Accession EF172428),根据其序列设计的引物SEQ-sus2-F/R只能从猪基因组DNA中扩增出目的条带,其他动物的基因组均无目的条带扩增。建立的Real-time PCR检测方法灵敏度为0.02 ng/25μL反应体系。该方法能够准确检测出混合DNA样品中猪源性成分和混合肉样品中猪源性成分,百分误差分别约为1.32%和1.06%-7.12%。【结论】本研究利用Real-time PCR技术建立的定量猪源性成分的检测方法可以用来检测猪源性成分在混合样品中的百分含量。

猪NLRP3基因Real-time PCR检测方法的建立及应用

根据NCBI NLRP3 cds(NM-001256770)序列设计1对特异性引物,构建标准品质粒pMD18T-NLRP3-189。通过反应条件优化、稳定性、敏感性等试验,成功建立了NLRP3的SYBR GreenⅠreal-time PCR检测方法,用该方法定量检测猪肺炎支原体(Mycoplasma hyopneumoniae,Mhp)感染后的猪肺组织中NLRP3表达水平。最佳引物浓度为0.15μmol/L,建立的标准曲线方程为y=-3.5196x+36.968,E值为0.96,最低检测量为84个拷贝,熔解曲线有单一峰,批内变异系数CV为0.067%~0.184%,批间变异系数为0.221%~0.594%,重复性好。该方法检测仔猪在感染Mhp后肺组织中的NLRP3 mRNA表达水平,感染组与健康组相比差异显著(P<0.01),NLRP3表达水平明显增高,在感染后14 d可达到高峰,平均mRNA拷贝数达18000左右,可持续42 d。表明该检测方法稳定性良好,精确度高,特异性强,为进一步研究猪炎症小体NLRP3的激活及其相关炎症反应机制提供了技术支持。