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Clinical application of SARS-CoV-2 antibody detection and monoclonal antibody therapies against COVID-19

World Journal of Clinical Cases 2023年第10期11卷 2168-2180页

作者： Jin Sun Zhen-Dong Yang Xiong Xie Li Li Hua-Song Zeng Bo Gong Jian-Qiang Xu Ji-Hong Wu Bei-Bei Qu Guo-Wei Song Medical Innovation Research Office Sinopharm Gezhouba Central HospitalThird Clinical Medical College of Three Gorges UniversityYichang 443002Hubei ProvinceChina Department of Respiratory Beijing Jindu Children HospitalBeijing 102208China Innovative Medicine Working Committee of the Chinese Society of Water Resources and Electric Power Medical Science and Technology Beijing 100053China Department of Pediatrics Sinopharm Gezhouba Central HospitalThird Clinical Medical College of Three Gorges UniversityYichang 443002Hubei ProvinceChina Department of Intensive Care First Clinical Medical College of Three Gorges UniversityYichang 443000Hubei ProvinceChina Department of Allergy Immunology and Rheumatology Guangzhou Children's HospitalWomen's and Children's Medical Center Affiliated with Guangzhou Medical UniversityGuangzhou 510000Guangdong ProvinceChina Central Laboratory Shanghai Changning District Maternal and Child HealthMaternal and Child Health Hospital Affiliated with Shanghai East China Normal UniversityShanghai 210000China Department of Respiratory and Critical Care Medicine Sinopharm Gezhouba Central HospitalThird Clinical Medical College of Three Gorges UniversityYichang 443002Hubei ProvinceChina School of Clinical Medicine Beijing Tsinghua Chang Gung Hospital Affiliated to Tsinghua UniversityBeijing 102218China Department of Emergency Children's Hospital Affiliated with Beijing Capital Institute of PediatricsBeijing 100020China

The purpose of this study was to investigate the clinical application of severe acute respiratory distress syndrome coronavirus-2(SARS-CoV-2)specific antibody detection and anti-SARS-CoV-2 specific monoclonal antibodies(mAbs)in the treatment of coronavirus infectious disease 2019(COVID-19).The dynamic changes of SARS-CoV-2 specific antibodies during COVID-19 were studied.Immunoglobulin M(IgM)appeared earlier and lasted for a short time,while immunoglobulin G(IgG)appeared later and lasted longer.IgM tests can be used for early diagnosis of COVID-19,and IgG tests can be used for late diagnosis of COVID-19 and identification of asymptomatic infected persons.The combination of antibody testing and nucleic acid testing,which complement each other,can improve the diagnosis rate of COVID-19.Monoclonal anti-SARS-CoV-2 specific antibodies can be used to treat hospitalized severe and critically ill patients and non-hospitalized mild to moderate COVID-19 patients.COVID-19 convalescent plasma,highly concentrated immunoglobulin,and anti-SARS-CoV-2 specific mAbs are examples of anti-SARS-CoV-2 antibody products.Due to the continuous emergence of mutated strains of the novel coronavirus,especially omicron,its immune escape ability and infectivity are enhanced,making the effects of authorized products reduced or invalid.Therefore,the optimal application of anti-SARS-CoV-2 antibody products(especially anti-SARS-CoV-2 specific mAbs)is more effective in the treatment of COVID-19 and more conducive to patient recovery.

关键词： SARS-CoV-2 antibody detection COVID-19 Monoclonal antibody Clinical application

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A systematic review of real-time detection and classification of power quality disturbances

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Protection and Control of Modern Power Systems 2023年第1期8卷 30-66页

作者： Joaquín E.Caicedo Daniel Agudelo-Martínez Edwin Rivas-Trujillo Jan Meyer Faculty of Engineering Universidad Distrital Francisco Joséde CaldasBogotáColombia Institute of Electrical Power Systems and High Voltage Engineering Technische Universität DresdenDresdenGermany Bogotá Colombia

This paper offers a systematic literature review of real-time detection and classification of Power Quality Disturbances(PQDs).A particular focus is given to voltage sags and notches,as voltage sags cause huge economic losses while research on voltage notches is still very incipient.A systematic method based on scientometrics,text similarity and the analytic hierarchy process is proposed to structure the review and select the most relevant literature.A biblio-metric analysis is then performed on the bibliographic data of the literature to identify relevant statistics such as the evolution of publications over time,top publishing countries,and the distribution by relevant topics.A set of articles is subsequently selected to be critically analyzed.The critical review is structured in steps for real-time detection and classification of PQDs,namely,input data preparation,preprocessing,transformation,feature extraction,feature selec-tion,detection,classification,and characterization.Aspects associated with the type of disturbance(s)addressed in the literature are also explored throughout the review,including the perspectives of those studies aimed at multiple PQDs,or specifically focused on voltage sags or voltage notches.The real-time performance of the reviewed tools is also examined.Finally,unsolved issues are discussed,and prospects are highlighted.

关键词： Bibliometric analysis Classification detection Power quality(PQ) Real-time Systematic review Voltage sag Voltage notch

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Comparative analysis of breast cancer detection using machine learning and biosensors

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Intelligent Medicine 2022年第2期2卷 69-81页

作者： Yash Amethiya Prince Pipariya Shlok Patel Manan Shah Dharmsinh Desai University NadiadGujaratIndia Department of Chemical Engineering School of Technology Pandit Deendayal Energy UniversityGandhinagarGujaratIndia

Breast cancer is a widely occurring cancer in women worldwide and is related to high mortality.The objective of this review was to present several approaches to investigate the application of multiple algorithms based on machine learning(ML)approach and biosensors for early breast cancer detection.Automation is needed because biosensors and ML are needed to identify cancers based on microscopic images.ML aims to facilitate self-learning in computers.Rather than relying on explicit pre-programmed rules and models,it is based on identifying patterns in observed data and building models to predict outcomes.We have compared and analysed various types of algorithms such as fuzzy extreme learning machine-radial basis function(ELM-RBF),support vector machine(SVM),support vector regression(SVR),relevance vector machine(RVM),naive bayes,k-nearest neighbours algorithm(K-NN),decision tree(DT),artificial neural network(ANN),back-propagation neural network(BPNN),and random forest across different databases including images digitized from fine needle aspirations of breast masses,scanned film mammography,breast infrared images,MR images,data collected by using blood analyses,and histopathology image samples.The results were compared on performance metric elements like accuracy,precision,and recall.Further,we used biosensors to determine the presence of a specific biological analyte by transforming the cellular constituents of proteins,DNA,or RNA into electrical signals that can be detected and analysed.Here,we have compared the detection of different types of analytes such as HER2,miRNA 21,miRNA 155,MCF-7 cells,DNA,BRCA1,BRCA2,human tears,and saliva by using different types of biosensors including FET,electrochemical,and sandwich electrochemical,among others.Several biosensors use a different type of specification which is also discussed.The result of which is analysed on the basis of detection limit,linear ranges,and response time.Different studies and related articles were reviewed and analysed systematically,and those publis

关键词： Breast cancer detection Machine learning Biosensors

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Grey Hole Attack detection and Prevention Methods in Wireless Sensor Networks

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Computer Systems Science & Engineering 2022年第7期42卷 373-386页

作者： Gowdham Chinnaraju S.Nithyanandam Department of Computer Science and Engineering PRIST Deemed to be University613403India

Wireless Sensor Networks(WSNs)gained wide attention in the past decade,thanks to its attractive features likeﬂexibility,monitoring capability,and scalability.It overcomes the crucial problems experienced in network man-agement and facilitates the development of diverse network architectures.The existence of dynamic and adaptive routing features facilitate the quick formation of such networks.Butﬂexible architecture also makes it highly vulnerable to dif-ferent sorts of attacks,for instance,Denial of Service(DoS).Grey Hole Attack(GHA)is the most crucial attack types since it creates a heavy impact upon the components of WSN and eventually degrades the performance of network.In cur-rent study,a simple attack detection,prevention and reduction approach is pro-posed.This is to secure the WSN from GHA and other such attacks by warning and blocking the malicious suspensions and by examining the storage table.Instead of blocking the entire host,the presented approach speciﬁcally elim-inates the malicious nodes.Further,in case of no malicious trafﬁc detection,the host gets unblocked.In current study,the researchers simulated the model under MATLAB environment and the outcomes showed an enhanced performance and increased utilization of Central Processing Unit(CPU)and packet delivery ratio.

关键词： Grey-Hole Attack WSN detection prevention reduction network performance

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Oxygen-vacancy-rich phenanthroline/TiO_(2) nanocomposites: An integrated adsorption, detection and photocatalytic material for complex pollutants remediation

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Chinese Chemical Letters 2022年第2期33卷 907-911页

作者： Pinghua Chen Huitao Zheng Hualin Jiang Jun Liu Xinman Tu Weibo Zhang Bailey Phillips Lei Fang Jian-Ping Zou Key Laboratory of Jiangxi Province for Persistent Pollutants Control and Resources Recycle Nanchang Hangkong UniversityNanchang 330063China Department of Applied Chemistry College of Environmental and Chemical EngineeringNanchang Hangkong UniversityNanchang 330063China Department of Chemistry Texas A&M UniversityCollege StationTexas 77843United States School of Resources Environmental and Chemical EngineeringNanchang UniversityNanchang 330031China

To address the challenge of treating complex pollutants containing heavy metals and organic compounds,a phenanthroline/TiO_(2)nanocomposite with rich oxygen vacancy defects was synthesized to integrate the functions of pollutant detection, adsorption, and photocatalytic degradation. The results showed that the nanocomposite could adsorb Cr^(3+)and the process could be transduced into a colorimetric signal for qualitative and quantitative detection. The adsorbed heavy metal also exhibited a synergistically enhanced photocatalytic degradation of a model organic pollutant under visible light. The simultaneous adsorption, detection, and photocatalysis could reduce the multifarious operations and high cost of traditional environmental remediation methods, indicating a strong application potential for the nanocomposite.

关键词： Heavy metals Organic contaminants Adsorption detection Photocatalytic degradation Oxygen vacancy

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Mesoporous magnetic nanoparticles conjugated aptamers for exosomes capture and detection of Alzheimer’s disease

Engineered Regeneration

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Engineered Regeneration 2023年第4期4卷 349-356页

作者： Guidan Wang Zhenshan Pan Xiaorui Zhu Ruyue Yang Rong Yang Tingting Yang Dong Hu Aihua Jing Gaofeng Liang School of Medical Technology and Engineering Henan University of Science&TechnologyLuoyang 471023China Department of Psychiatry the fifth people’s hospital of Luoyangthe Fifth Affiliated Hospital of Henan University of Science and TechnologyLuoyang 471027China Collaboration Innovative Center of Henan Province for Energy-Saving Building Materials Xinyang Normal UniversityXinyang 464000China School of Basic Medicine and Forensic Medicine Henan University of Science&TechnologyLuoyang 471023China

Exosomes are nanoscale membrane-enclosed extracellular vesicles secreted by various cells,which have enormous potential as disease biomarkers for clinical application.However,the isolation and detection of exosomes remain enormous challenges,which limits their further application.Herein,inspired by immunomagnetic beads,a magnetic nanoparticle conjugated aptamer was repurposed for the effective capture and detection of exosomes.The magnetic nanoparticles,composed of Fe 3 O 4 synthesized by the hydrothermal method as the core and coupled with gold nanoparticles(Fe 3 O 4@Au),provide a large specific surface area,making the resulting composite material an effective platform for exosome capture.Furthermore,the elution of captured exosomes with 1.0 M NaCl made downstream analysis of exosomes possible.The preliminary clinical application value of the composite in exosome analyses of serum from healthy individuals and patients with Alzheimer’s disease(AD)has also been verified,which could provide a promising platform for biomedical and clinical diagnosis.

关键词： Exosomes Capture detection Alzheimer’s disease(AD)

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Analysis of trends in patent development for coronavirus detection,prevention,and treatment technologies in key countries

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Journal of Biosafety and Biosecurity 2022年第1期4卷 23-32页

作者： Feng Wei Hong Zhou Guoqing Gao Qibin Zheng Wuhan Library Chinese Academy of SciencesWuhan430071 Department of Library Information and Archives ManagementChinese Academy of SciencesBeijing100191

Coronavirus causes significant damage to human health and the global economy.In this paper,we undertake patent analysis and data mining to systematically analyze the trend in patent applications for coronavirus detection,prevention,and treatment technologies.Our goals are to determine the correlation between typical coronavirus outbreaks and changes in patent technology applications,and to compare the research and development(R&D)progress,patent layout,and characteristics of major institutions in various countries experiencing coronavirus outbreaks.We find that the United States commenced coronavirus detection and vaccine technology R&D earlier than other countries,as it attached importance to the R&D for treatment technologies from the time of the SARS outbreak and initiated the trend of multi-party R&D,with full technology chain coverage by the government,enterprises,universities,and research institutions.China’s patent applications have grown rapidly in recent years,mainly based on the R&D of research institutions and universities,although it has formed full technology chain coverage.However,the patent quality and technology global layout still need to be improved.This paper reviews the patent development trends of important coronavirus technologies,and proposes that policymakers should establish a long-term mechanism for R&D,pay attention to intellectual property protection,and deepen international technical cooperation to provide a reference for the development and application of coronavirus detection technology,vaccine technology,and treatment technology.

关键词： Coronavirus Patent analysis detection Vaccine Treatment

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Highly sensitive detection of daminozide using terahertz metamaterial sensors

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International Journal of Agricultural and Biological Engineering 2022年第6期15卷 180-188页

作者： Hanping Mao Xiaoxue Du Yuting Yan Xiaodong Zhang Guoxin Ma Yafei Wang Yong Liu Bin Wang Xiaoyue Yang Qiang Shi Key Laboratory of Modern Agricultural Equipment and Technology Ministry of EducationJiangsu UniversityZhenjiang 212013JiangsuChina School of Agricultural Engineering Zhenjiang 212013JiangsuChina Department of Obstetrics and Gynecology Affiliated Hospital of Jiangsu UniversityZhenjiang 212013JiangsuChina

In order to solve the problems of low sensitivity and complex sample pretreatment in traditional detection,a method was proposed in this study to detect daminozide using terahertz combined with a metamaterial sensor,which enables real-time and label-free molecular detection with high sensitivity.The correlation between the transmission frequency shift and absorbance of daminozide solution at different concentrations was analyzed.The simulation and experimental results showed that this metamaterial sensor could achieve highly sensitive sensing of daminozide solutions at 0.05 mg/L.The maximum quality factor(Q_(max))of the two peaks could reach 5.78 and 13.05,and the maximum figure of merit(FOM)of the two peaks can reach 0.82 and 1.72.The maximum sensitivity of two resonance peaks reached 38.148 GHz/(mg·L)and 133.516 GHz/(mg·L)when the concentration of daminozide in the solution was 2000 mg/L.There was an obvious positive correlation between the transmission and transmission,frequency shift and frequency shift,and absorbance and absorbance of the resonance peak of daminozide solutions.Therefore,this platform not only opens up new possibilities for the microanalysis of the chemical composition of substances in solutions but also provides a valuable reference for the design of other metamaterial-based sensors in the field of food safety.

关键词： Terahertz time-domain spectroscopy plant growth regulator detection metamaterial

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Eye detection-Based Deep Belief Neural Networks and Speeded-Up Robust Feature Algorithm

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Computer Systems Science & Engineering 2023年第6期45卷 3195-3213页

作者： Zahraa Tarek Samaa M.Shohieb Abdelghafar M.Elhady El-Sayed M.El-kenawy Mahmoud Y.Shams Faculty of Computers and Information Mansoura UniversityMansoura35516Egypt Deanship of Scientific Research Umm Al-Qura UniversityMakkah21955KSA Delta Higher Institute of Engineering and Technology Mansoura35111Egypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

The ability to detect and localize the human eye is critical for use in security applications and human identification and verification systems.This is because eye recognition algorithms have multiple challenges,such as multi-pose variations,ocular parts,and illumination.Moreover,the modern security applica-tions fail to detect facial expressions from eye images.In this paper,a Speeded-Up Roust Feature(SURF)Algorithm was utilized to localize the face images of the enrolled subjects.We highlighted on eye and pupil parts to be detected based on SURF,Hough Circle Transform(HCT),and Local Binary Pattern(LBP).Afterward,Deep Belief Neural Networks(DBNN)were used to classify the input features results from the SURF algorithm.We further determined the correctly and wrongly classified subjects using a confusion matrix with two class labels to classify people whose eye images are correctly detected.We apply Stochastic Gradient Descent(SGD)optimizer to address the overfitting problem,and the hyper-parameters arefine-tuned based on the applied DBNN.The accuracy of the proposed system is determined based on SURF,LBP,and DBNN classifier achieved 95.54%for the ORL dataset,94.07%for the BioID,and 96.20%for the CASIA-V5 dataset.The proposed approach is more reliable and more advanced when compared with state-of-the-art algorithms.

关键词： Eye localization classification DBNN detection feature extraction LBP feature extraction SURF

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Airborne GNSS-Receiver Threat detection in No-Fading Environments

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Journal of Beijing Institute of Technology 2022年第6期31卷 613-620页

作者： Omid Sharifi-Tehrani Department of Electrical and Communication Engineering Imam Hussein Comprehensive UniversityTehranIran.

Jamming and spoofing detection of global navigation satellite systems(GNSS)is of great importance.Civil and military aerial platforms use GNSS as main navigation systems and these systems are main target of threat attacks.In this paper a simple method based on different empirical probability density functions of successive received signal powers and goodness of fit tech-nique is proposed for airborne platforms such as unmanned aerial vehicle(UAV),in no fading envi-ronment.The two different paths between UAV-satellite and UAV-threat,experience different empirical probability density functions which can be used to distinguish between authentic and threat signals.Simulation results including detection and false alarm probabilities show good perfor-mance of proposed method as well as low computational burden.

关键词： detection global navigation satellite systems(GNSS) jamming spoofing unmanned aerial vehicle

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