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Highly Sensitive Poly-N-isopropylacrylamide Microgel-based Electrochemical Biosensor for the Detection of SARS-COV-2 Spike Protein

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Biomedical and Environmental Sciences 2023年第3期36卷 269-278页

作者： CHEN Hao HOU Zhi Yuan CHEN Die LI Ting WANG Yi Ming DE LIMA Marcelo Andrade YANG Ying GUO Zhen Zhong Department of Anaesthesiology Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030HubeiChina Hubei Province Key Laboratory of Occupational Hazard Identification and Control Wuhan University of Science and TechnologyWuhan 430065HubeiChina Department of Pharmacy Medical CollegeWuhan University of Science and Technology Wuhan 430065HubeiChina School of Public Health Medical CollegeWuhan University of Science and Technology Wuhan 430065HubeiChina School of Life Sciences Keele UniversityStaffordshire ST55BGUK School of Pharmacy and Bioengineering Keele UniversityStaffordshire ST47QBUK

Objective Late 2019 witnessed the outbreak and widespread transmission of coronavirus disease 2019(COVID-19),a new,highly contagious disease caused by novel severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Consequently,considerable attention has been paid to the development of new diagnostic tools for the early Detection of SARS-CoV-2.Methods In this study,a new poly-N-isopropylacrylamide microgel-based electrochemical sensor was explored to detect the SARS-CoV-2 spike protein(S protein)in human saliva.The microgel was composed of a copolymer of N-isopropylacrylamide and acrylic acid,and gold nanoparticles were encapsulated within the microgel through facile and economical fabrication.The electrochemical performance of the sensor was evaluated through differential pulse voltammetry.Results Under optimal experimental conditions,the linear range of the sensor was 10-13-10-9 mg/m L,whereas the Detection limit was 9.55 fg/mL.Furthermore,the S protein was instilled in artificial saliva as the infected human saliva model,and the sensing platform showed satisfactory Detection capability.Conclusion The sensing platform exhibited excellent specificity and sensitivity in detecting spike protein,indicating its potential application for the time-saving and inexpensive Detection of SARS-CoV-2.

关键词： Microgel SARS-CoV-2 Spike protein Detection

Towards resilient average consensus in multi-agent systems:a Detection and compensation approach

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Frontiers of Information Technology & Electronic Engineering 2024年第2期25卷 182-196页

作者： Chongrong FANG Wenzhe ZHENG Zhiyu HE Jianping HE Chengcheng ZHAO Jingpei WANG Department of Automation Shanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhou310027China Technology and Engineering Center for Space Utilization Chinese Academy of SciencesBeijing100094China

Consensus is one of the fundamental distributed control technologies for collaboration in multi-agent systems such as collaborative handling in intelligent manufacturing.In this paper,we study the problem of resilient average consensus for multi-agent systems with misbehaving nodes.To protect consensus value from being influenced by misbehaving nodes,we address this problem by detecting misbehaviors,mitigating the corresponding adverse impact,and achieving the resilient average consensus.General types of misbehaviors are considered,including attacks,accidental faults,and link failures.We characterize the adverse impact of misbehaving nodes in a distributed manner via two-hop communication information and develop a deterministic Detection compensation based consensus(D-DCC)algorithm with a decaying fault-tolerant error bound.Considering scenarios wherein information sets are intermittently available due to link failures,a stochastic extension named stochastic Detection compensation based consensus(S-DCC)algorithm is proposed.We prove that D-DCC and S-DCC allow nodes to asymptotically achieve resilient accurate average consensus and unbiased resilient average consensus in a statistical sense,respectively.Then,the Wasserstein distance is introduced to analyze the accuracy of S-DCC.Finally,extensive simulations are conducted to verify the effectiveness of the proposed algorithms.

关键词： Resilient consensus Multi-agent systems Malicious attacks Detection Compensation

The characteristics of liver injury induced by Amanita and clinical value of α-amanitin Detection

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Hepatobiliary & Pancreatic Diseases International 2022年第3期21卷 257-266页

作者： Li-Ying Lin Ya-Ling Tong Yuan-Qiang Lu Department of Emergency Medicine the First Affiliated HospitalZhejiang University School of MedicineHangzhou 310003China The Key Laboratory for Diagnosis and Treatment of Aging and Physic-chemical Injury Diseases of Zhejiang Province Hangzhou 310003China

Background:Amanita poisoning as a foodborne disease has raised concerning mortality issues.Reducing the interval between mushroom ingestion and medical intervention could greatly influence the outcomes of Amanita poisoning patients,while treatment is highly dependent on a confirmed diagnosis.To this end,we developed an early Detection-guided intervention strategy by optimizing diagnostic process with performingα-amanitin Detection,and further explored whether this strategy influenced the progression of Amanita poisoning.Methods:This study was a retrospective analysis of 25 Amanita poisoning patients.Thirteen patients in the Detection group were diagnosed mainly based onα-amanitin Detection,and 12 patients were diagnosed essentially on the basis of mushroom consumption history,typical clinical patterns and mushroom identification(conventional group).Amanita poisoning patients received uniform therapy,in which plasmapheresis was executed once confirming the diagnosis of Amanita poisoning.We compared the demographic baseline,clinical and laboratory data,treatment and outcomes between the two groups,and further explored the predictive value ofα-amanitin concentration in serum.Results:Liver injury induced by Amanita appeared worst at the fourth day and alanine aminotransferase(ALT)rose higher than aspartate aminotransferase(AST).The mortality rate was 7.7%(1/13)in the Detection group and 50.0%(6/12)in the conventional group(P=0.030),since patients in the Detection group arrived hospital much earlier and received plasmapheresis at the early stage of disease.The early Detection-guided intervention helped alleviate liver impairment caused by Amanita and decreased the peak AST as well as ALT.However,the predictive value ofα-amanitin concentration in serum was still considered limited.Conclusions:In the management of mushroom poisoning,consideration should be given to the rapid Detection ofα-amanitin in suspected Amanita poisoning patients and the immediate initiation of medical treatment upon a positive toxin screening re

关键词： Mushroom poisoning α-amanitin Detection Acute liver failure Early diagnosis and intervention

A lightweight DDoS Detection scheme under SDN context

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Cybersecurity 2023年第1期6卷 75-89页

作者： Kun Jia Chaoge Liu Qixu Liu Junnan Wang Jiazhi Liu Feng Liu State Key Laboratory of Information Security Institute of Information EngineeringBeijingChina School of Cyber Security University of Chinese Acad emy of SciencesBeijing 100049China The Sixth Research Offce Institute of Information EngineeringChinese Academy of SciencesBeijing 100093China

Software-defined networking(SDN),a novel network paradigm,separates the control plane and data plane into dif-ferent network equipment to realize the flexible control of network traffic.Its excellent programmability and global view present many new opportunities.DDoS Detection under the SDN context is an important and challenging research field.Some previous works attempted to collect and analyze statistics related to flows,usually recorded in switches,to address DDoS threats.In contrast,other works applied machine learning-based solutions to identify DDos and achieved promising results.Generally,most previous works need to periodically request flow rules or packets to obtain flow statistics or features to detect stealthy exceptions.Nevertheless,the request for flow rules is very time-consuming and CPU-consuming;moreover may congest the communication channel between the controller and the switches.Therefore,we present FORT,a lightweight DDoS Detection scheme,which spreads the rule-based Detection algorithm at edge switches and determines whether to start it by periodically retrieving the ports state.A time-series algorithm,ARIMA,is utilized to determine the port statistics adaptively,and an SVM algorithm is applied to detect whether a DDoS attack does occur.Representative experiments demonstrate that FORT can significantly reduce the controller load and provide a reliable Detection accuracy.Referring to the false alarm rate of 1.24%in the comparison scheme,the false alarm rate of this scheme is only 0.039%,which significantly reduces the probability of false alarm.Besides,by introducing the alarm mechanism,this scheme can reduce the load of the southbound chan-nel by more than 60%in the normal state.

关键词： DDoS Port monitoring Flow rule Software defined network MiniNet RYU controller Detection

Detection and classification of breast lesions using multiple information on contrast-enhanced mammography by a multiprocess deep-learning system: A multicenter study

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中国癌症研究:英文版 2023年第4期35卷 408-423页

作者： Yuqian Chen Zhen Hua Fan Lin Tiantian Zheng Heng Zhou Shijie Zhang Jing Gao Zhongyi Wang Huafei Shao Wenjuan Li Fengjie Liu Simin Wang Yan Zhang Feng Zhao Hao Liu Haizhu Xie Heng Ma Haicheng Zhang Ning Mao School of Information and Electronic Engineering Shandong Technology and Business UniversityYantai 264005China Department of Radiology Yantai Yuhuangding HospitalAffiliated Hospital of Qingdao UniversityYantai 264000China School of Medical Imaging Binzhou Medical UniversityYantai 264003China Department of Radiology Fudan University Cancer CenterShanghai 200433China Department of Radiology Guangdong Maternal and Child Health HospitalGuangzhou 510010China School of Computer Science and Technology Shandong Technology and Business UniversityYantai 264005China Yizhun Medical AI Co.Ltd. Beijing 100080China Big Data and Artificial Intelligence Laboratory Yantai Yuhuangding HospitalAffiliated Hospital of Qingdao UniversityYantai 264000China

Objective: Accurate Detection and classification of breast lesions in early stage is crucial to timely formulate effective treatments for patients. We aim to develop a fully automatic system to detect and classify breast lesions using multiple contrast-enhanced mammography(CEM) images.Methods: In this study, a total of 1,903 females who underwent CEM examination from three hospitals were enrolled as the training set, internal testing set, pooled external testing set and prospective testing set. Here we developed a CEM-based multiprocess Detection and classification system(MDCS) to perform the task of Detection and classification of breast lesions. In this system, we introduced an innovative auxiliary feature fusion(AFF)algorithm that could intelligently incorporates multiple types of information from CEM images. The average freeresponse receiver operating characteristic score(AFROC-Score) was presented to validate system’s Detection performance, and the performance of classification was evaluated by area under the receiver operating characteristic curve(AUC). Furthermore, we assessed the diagnostic value of MDCS through visual analysis of disputed cases,comparing its performance and efficiency with that of radiologists and exploring whether it could augment radiologists’ performance.Results: On the pooled external and prospective testing sets, MDCS always maintained a high standalone performance, with AFROC-Scores of 0.953 and 0.963 for Detection task, and AUCs for classification were 0.909[95% confidence interval(95% CI): 0.822-0.996] and 0.912(95% CI: 0.840-0.985), respectively. It also achieved higher sensitivity than all senior radiologists and higher specificity than all junior radiologists on pooled external and prospective testing sets. Moreover, MDCS performed superior diagnostic efficiency with an average reading time of 5 seconds, compared to the radiologists’ average reading time of 3.2 min. The average performance of all radiologists was also improved to varying degrees with MDCS assistance.Conclusion

关键词： Deep learning contrast-enhanced mammography breast lesions Detection classification

Nanostructure enabled extracellular vesicles separation and Detection

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Nanotechnology and Precision Engineering 2023年第4期6卷 98-120页

作者： Xinyuan He Wei Wei Xuexin Duan State Key Laboratory of Precision Measuring Technology and Instruments Tianjin UniversityTianjin 300072China Department of Chemistry School of ScienceTianjin UniversityTianjin 300072China

Extracellular vesicles(EVs)have recently attracted significant research attention owing to their important biological functions,including cell-to-cell communication.EVs are a type of membrane vesicles that are secreted into the extracellular space by most types of cells.Several biological biomolecules found in EVs,such as proteins,microRNA,and DNA,are closely related to the pathogenesis of human malignancies,making EVs valuable biomarkers for disease diagnosis,treatment,and prognosis.Therefore,EV separation and Detection are prerequisites for providing important information for clinical research.Conventional separation methods suffer from low levels of purity,as well as the need for cumbersome and prolonged operations.Moreover,Detection methods require trained operators and present challenges such as high operational expenses and low sensitivity and specificity.In the past decade,platforms for EV separation and Detection based on nanostructures have emerged.This article reviews recent advances in nanostructure-based EV separation and Detection techniques.First,nanostructures based on membranes,nanowires,nanoscale deterministic lateral displacement,and surface modification are presented.Second,high-throughput separation of EVs based on nanostructures combined with acoustic and electric fields is described.Third,techniques combining nanostructures with immunofluorescence,surface plasmon resonance,surface-enhanced Raman scattering,electrochemical Detection,or piezoelectric sensors for high-precision EV analysis are summarized.Finally,the potential of nanostructures to detect individual EVs is explored,with the aim of providing insights into the further development of nanostructure-based EV separation and Detection techniques.

关键词： Nanostructure Extracellular vesicle Separation Detection Individual

Efficacy of ctDNA methylation combined with traditional Detection modality to detect liver cancer among high-risk patients:A multicenter diagnostic trial

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Chinese Journal of Cancer Research 2023年第1期35卷 58-65页

作者： Maomao Cao Jufang Shi Changfa Xia He Li Wei Cai Xianyun Qi Chunyun Dai Wanqing Chen Office of Cancer Screening National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China Department of Prevention and Control of Chronic Noncommunicable Diseases Binhai County Center for Disease Control and PreventionBinhai 224521China Chronic Noncommunicable Diseases Prevention and Treatment Department Yingdong District Center for Disease Control and PreventionFuyang 236142China Department for Chronic Noncommunicable Diseases Control Sheyang Center for Disease Control and PreventionSheyang 224300China

Objective:Circulating tumor DNA(ctDNA)and alpha-fetoprotein(AFP)plus ultrasound(US)have been considered to have high diagnostic accuracy for cancer Detection,however,the efficacy of ctDNA methylation combined with the traditional Detection modality of liver cancer has not been tested in a Chinese independent cohort.Methods:The high-risk individuals aged between 35 and 70 years who were diagnosed with liver cirrhosis or had moderate and severe fatty liver were eligible for inclusion.All participants were invited to receive a traditional examination[referring to AFP plus US],and ctDNA methylation,respectively.The sensitivity and specificity of different diagnostic tools were calculated.The logistic regression model was applied to estimate the area under the curve(AUC),which was further validated by 10-fold internal cross-validation.Results:A total of 1,205 individuals were recruited in our study,and 39 participants were diagnosed with liver cancer.The sensitivity of AFP,US,US plus AFP,and the combination of US,AFP,and ctDNA methylation was33.33%,56.41%,66.67%,and 87.18%,respectively.The corresponding specificity of AFP,US,US plus AFP,and the combination of all modalities was 98.20%,99.31%,97.68%,and 97.68%,respectively.The AUCs of AFP,US,US plus AFP,and the combination of AFP,US,and ctDNA methylation were 65.77%,77.86%,82.18%,and92.43%,respectively.The internally validated AUCs of AFP,US,US plus AFP,and the combination of AFP,US,and ctDNA methylation were 67.57%,83.26%,86.54%,and 93.35%,respectively.Conclusions:The ctDNA methylation is a good complementary to AFP and US for the Detection of liver cancer.

关键词： Liver cancer Detection ctDNA methylation diagnostic performance

Application of three Ln(Ⅲ)-coordination polymers in fields of luminescence,antibacteria and Detection of Fe^(3+) and 4-nitrophenol

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稀土学报:英文版 2023年第9期41卷 1392-1397,I0005页

作者： Lun Zhao Yue Han Guanlin Guo Helong Bai Zhexin Wang Hongwei Jing Guanying Song Ziyun Wang Jiayu Li Jia Li College of Chemistry Changchun Normal UniversityChangchun 130032China

Three lanthanide-based coordination polymers(Ln-CPs) with layered structure,{[La_(2)(L)_(3)(DMF)(H_(2)O)_(3)]·H_(2)O}_n(1),{[Eu_(2)(L)_(3)(DMF)_(2)(H_(2)O)]·(H_(2)O)}_n(2){Tb_(2)(L)_(3)(DMF)_(2)(H_(2)O)]·H_(2)O}n(3) were successfully synthesized from H_(2)L(N,N'-bis(4-carbozylbenzyl)aniline).Remarkably,compound 3 has extremely high sensitivity to 4-nitrophenol.When the concentration of 4-nitrophenol reaches 5.98 × 10^(-3) mmol/L,the fluorescence intensity of compound 3 is quenched by 59%.The calculated K_(SV) is 7.56 × 10~4 and limit of Detection(LOD) is 4.73 μg/L.3 exhibits a highly sensitive Detection towards Fe^(3+) and compound 2 shows outstanding antibacterial effects on Staphylococcus aureus,re spectively.The white light emission was also investigated by changing the mixing ratio of LaNO_(3),EuNO_(3) and TbNO_(3) during the preparation of coordination polymers.

关键词： Coordination polymers Lanthanide-based Detection Luminescence Antibacterial Rare earths

Jointly beam stealing attackers Detection and localization without training:an image processing viewpoint

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Frontiers of Computer Science 2023年第3期17卷 145-160页

作者： Yaoqi YANG Xianglin WEI Renhui XU Weizheng WANG Laixian PENG Yangang WANG College of Communication Engineer Army Engineering University of PLANanjing 210000China The 63rd Research Institute National University of Defense TechnologyNanjing 210007China Department of Computer Science City University of Hong KongHong Kong 999077China

Recently revealed beam stealing attacks could greatly threaten the security and privacy of IEEE 802.11ad communications.The premise to restore normal network service is detecting and locating beam stealing attackers without their cooperation.Current consistency-based methods are only valid for one single attacker and are parametersensitive.From the viewpoint of image processing,this paper proposes an algorithm to jointly detect and locate multiple beam stealing attackers based on RSSI(Received Signal Strength Indicator)map without the training process involved in deep learning-based solutions.Firstly,an RSSI map is constructed based on interpolating the raw RSSI data for enabling high-resolution localization while reducing monitoring cost.Secondly,three image processing steps,including edge Detection and segmentation,are conducted on the constructed RSSI map to detect and locate multiple attackers without any prior knowledge about the attackers.To evaluate our proposal’s performance,a series of experiments are conducted based on the collected data.Experimental results have shown that in typical parameter settings,our algorithm’s positioning error does not exceed 0.41 m with a Detection rate no less than 91%.

关键词： beam-stealing attacks Detection localization image processing