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Comprehensive characterization and detection of nut allergens in bakery foods using Q-TOF mass spectrometry and bioinformatics

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food Quality and safety 2024年第1期8卷 145-157页

作者： Daokun Xu Haolun Huang Zhen Liu YumeiWang Qinan Liu Xing Jiang JunYang Rui Ling Nanjing Institute for food and Drug Control NanjingChina State key laboratory of food Science and technology School of Food Science and TechnologyJiangnan UniversityWuxiChina Demonstration Collaborative laboratory of Analysis and detection technology for food and Drug safety Nanjing Institute for Food and Drug Control and Agilent Technologies(China)NanjingChina Collaborative laboratory for food safety Nanjing Institute for Food and Drug Control and SCIEX(China)NanjingChina

food allergy is a growing health issue worldwide and the demand for sensitive,robust and high-throughput analytical methods is *** recent years,mass spectrometry-based methods have been established for multiple food allergen *** the present study,a novel method was developed for the simultaneous detection of almond,cashew,peanut,and walnut allergens in bakery foods using liquid chromatography–mass *** unique to these four ingredients were extracted,followed by trypsin digestion,quadrupole time-of-flight(Q-TOF)mass spectrometry and bioinformatics *** raw data were processed by de-novo sequencing module plus PEAKS DB(database search)module of the PEAKS software to screen peptides specific to each nut *** thermal stability and uniqueness of these candidate peptides were further verified using triple quadrupole mass spectrometry(QQQ-MS)in multiple reaction monitoring(MRM)*** nut species was represented by four peptides,all of which were validated for label-free quantification(LFQ).Calibration curves were constructed with good linearity and correlation coefficient(r 2)greater than *** limits of detection(LODs)were determined to range from 0.11 to 0.31 mg/kg,and were compared with the reference doses proposed by Voluntary Incidental Trace Allergen Labelling(VITAL).The recoveries of the developed method in incurred bakery food matrices ranged from 72.5%to 92.1%with relative standard deviations(RSD)ofdetection of undeclared allergens in commercial bakery food samples confirmed the presence of these *** conclusion,this method provides insight into the qualitative and quantitative detection of trace levels of nut allergens in bakery foods.

关键词： Nut allergen Q-TOF mass spectrometry peptides label-free quantitation bakery foods.

Observer design and interval estimation of time-delay discrete-time linear systems with external disturbance and measurement noise

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Control Theory and technology 2024年第1期22卷 69-80页

作者： Junqi Yang Jianhao Xie Feiyang Liu School of Electrical Engineering and Automation Henan Key Laboratory of Intelligent Detection and Control of Coal Mine EquipmentHenan Polytechnic UniversityJiaozuo454003HenanChina

For a class of time-delay discrete-time linear systems with external disturbance and measurement noise, the interval estimation problems of state and measurement noise are investigated in this paper. First, the system state together with the time-delay term and measurement noise is augmented as a new state, and a singular system is then constructed. Subsequently, a kind of decoupling technique is employed to eliminate the effect of external disturbance, and an observer is designed to simultaneously estimate the system state and measurement noise. based on the estimated state and measurement noise, the interval estimations of system state and measurement noise are obtained by reachability analysis technique. Finally, the effectiveness of the proposed method is verified by a four-tank liquid level system.

关键词： Interval estimation Time-delay system Observer design Reachability analysis

Utilization of hydralazine as a reactive matrix for enhanced detection and on-MALDI-target derivatization of saccharides

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Chinese Chemical Letters 2024年第5期35卷 386-391页

作者： Dan Ouyang Huan Huang Yanting He Jiajing Chen Jiali Lin Zhuling Chen Zongwei Cai Zian Lin Ministry of Education key laboratory of Analytical Science for food safety and Biology Fujian Provincial Key Laboratory of Analysis and Detection Technology for Food SafetyCollege of ChemistryFuzhou UniversityFuzhou 350108China School of Pharmacy Bengbu Medical UniversityBengbu 233000China Partner State key laboratory of Environmental and Biological Analysis Department of ChemistryHong Kong Baptist UniversityHong KongChina

Saccharides are a sort of ubiquitous and vital molecules within the whole ***,the application of saccharides analysis with matrix-assisted laser desorption/ionization mass spectrometry(MALDI-MS)is restricted by their low ionization efficiency and the instability of the sialic acid *** strategy based on nonreductive amination provides a good solution,however,this is often time consuming and may result in sample loss due to removal of excessive derivatization ***,hydralazine(HZN)was utilized as a reactive matrix for labeling reducing saccharides directly on MALDI target which eliminated tedious sample preparation and avoided sample *** optimization,effective and reproducible on-MALDI-target derivatization of neutral and acidic saccharides was achieved in both positive and negative *** with 2,5-dihydroxybenzoic acid(DHB)and 9-aminoacridine(9-AA),HZN improved the detection sensitivity of reducing saccharides and provided more abundant fragment ions in MS/MS ***,26 kinds of neutral glycans and 5 kinds of sialic glycans were identified from ovalbumin(OVA)and bovine fetuin,*** with the statistical models,this strategy could be used to distinguish and predict samples of 6 brands of beer,and discriminate 2 kinds of beer fermentation *** addition,HZN was applied for quantitative analysis of glucose in urine samples,and the obtained urine glucose concentrations of diabetic patients were consistent with the clinical test results,showing the potential of qualitative and quantitative analysis of reducing saccharides in complex samples.

关键词： Hydralazine Reactive matrix On-MALDI-target derivatization Saccharides

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Lightweight Steganography detection Method based on Multiple Residual Structures and Transformer

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Chinese Journal of Electronics 2024年第4期33卷 965-978页

作者： Hao LI Yi ZHANG Jinwei WANG Weiming ZHANG Xiangyang LUO key laboratory of Cyberspace Situation Awareness of henan province Nanjing University of Information Science & technology University of Science and technology of China

Existing deep learning-based steganography detection methods utilize convolution to automatically capture and learn steganographic features, yielding higher detection efficiency compared to manually designed steganography detection methods. detection methods based on convolutional neural network frameworks can extract global features by increasing the network's depth and width. These frameworks are not highly sensitive to global features and can lead to significant resource consumption. This manuscript proposes a lightweight steganography detection method based on multiple residual structures and Transformer(Res Former). A multi-residuals block based on channel rearrangement is designed in the preprocessing layer. Multiple residuals are used to enrich the residual features and channel shuffle is used to enhance the feature representation capability. A lightweight convolutional and Transformer feature extraction backbone is constructed, which reduces the computational and parameter complexity of the network by employing depth-wise separable convolutions. This backbone integrates local and global image features through the fusion of convolutional layers and Transformer, enhancing the network's ability to learn global features and effectively enriching feature diversity. An effective weighted loss function is introduced for learning both local and global features, Bias Loss loss function is used to give full play to the role of feature diversity in classification, and cross-entropy loss function and contrast loss function are organically combined to enhance the expression ability of features. based on Boss Base-1.01, BOWS2 and ALASKA#2, extensive experiments are conducted on the stego images generated by spatial and JPEG domain adaptive steganographic algorithms, employing both classical and state-of-theart steganalysis techniques. The experimental results demonstrate that compared to the SRM, SRNet, Sia Steg Net,CSANet, LWENet, and Sia IRNet methods, the proposed Res

关键词： Q-factor Steganography Accuracy Convolution Computational modeling Transform coding Transformers

IP-Pealing: A Robust Network Flow Watermarking Method based on IP Packet Sequence

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Chinese Journal of Electronics 2024年第3期33卷 694-707页

作者： Wangxin FENG Xiangyang LUO Tengyao LI Chunfang YANG State key laboratory of Mathematical Engineering and Advanced Computing key laboratory of Cyberspace Situation Awareness of henan province

Network flow watermarking(NFW) is usually used for flow *** actively modulating some features of the carrier traffic,NFW can establish the correspondence between different network *** the face of strict demands of network traffic tracing,current watermarking methods cannot work efficiently due to the dependence on specific protocols,demand for large quantities of packets,weakness on resisting network channel interferences and so *** this end,we propose a robust network flow watermarking method based on IP packet sequence,called as *** is designed to utilize the packet sequence as watermark carrier with IP identification field which is insensitive to time jitter and suitable for all IP based *** enhance the robustness against packet loss and packet reordering,the detection sequence set is constructed in terms of the variation range of packet sequence,correcting the possible errors caused by the network *** improve the detection accuracy,the long watermark information is divided into several short sequences to embed in turn and assembled during *** a large number of experiments on the Internet,the overall detection rate and accuracy of IP-Pealing reach 99.91% and 99.42%*** comparison with the classical network flow watermarking methods,such as PROFW,IBW,ICBW,WBIPD and SBTT,the accuracy of IP-Pealing is increased by 13.70% to 54.00%.

关键词： Protocols Packet loss Watermarking Telecommunication traffic Jitter Robustness Internet

A core-satellite self-assembled SERS aptasensor containing a“biological-silent region”Raman tag for the accurate and ultrasensitive detection of histamine

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food Science and Human Wellness 2024年第2期13卷 1029-1039页

作者： Chen Chen Yingfang Zhang Ximo Wang Xuguang Qiao Geoffrey I.N.Waterhouse Zhixiang Xu key laboratory of food Processing technology and Quality Control in Shandong province College of Food Science and EngineeringShandong Agricultural UniversityTai’an 271018China School of Chemical Sciences The University of AucklandAuckland 1142New Zealand

Herein,a novel interference-free surface-enhanced Raman spectroscopy(SERS)strategy based on magnetic nanoparticles(MNPs)and aptamer-driven assemblies was proposed for the ultrasensitive detection of histamine.A core-satellite SERS aptasensor was constructed by combining aptamer-decorated Fe_(3)O_(4)@Au MNPs(as the recognize probe for histamine)and complementary DNA-modified silver nanoparticles carrying 4-mercaptobenzonitrile(4-MBN)(Ag@4-MBN@Ag-c-DNA)as the SERS signal probe for the indirect detection of *** an applied magnetic field in the absence of histamine,the assembly gave an intense Raman signal at“Raman biological-silent”region due to *** the presence of histamine,the Ag@4-MBN@Ag-c-DNA SERS-tag was released from the Fe_(3)O_(4)@Au MNPs,thus decreasing the SERS *** optimal conditions,an ultra-low limit of detection of 0.65×10^(-3)ng/mL and a linear range 10^(-2)-10^5 ng/mL on the SERS aptasensor were *** histamine content in four food samples were analyzed using the SERS aptasensor,with the results consistent with those determined by high performance liquid *** present work highlights the merits of indirect strategies for the ultrasensitive and highly selective SERS detection of small biological molecules in complex matrices.

关键词： Surface-enhanced Raman spectroscopy Raman biological-silent region Aptamer Histamine detection Universal SERS-tag

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A multi-colloidal gold immunochromatography assay for rapid and simultaneous detection of 13 herbicides

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Nano Research 2024年第9期17卷 8368-8376页

作者： Qianqian Lu Xinxin Xu Aihua Qu Liqiang Liu Yuzhe Li Maozhong Sun Chuanlai Xu Hua Kuang International Joint Research laboratory for Biointerface and Biodetection and School of Food Science and TechnologyJiangnan UniversityWuxi 214122China China National Center for food safety Risk Assessment Beijing 100021China

Herbicide residues in agricultural products can have adverse effects on the environment and human health,therefore,there is an urgent need to establish a sensitive,rapid,and wide-ranging detection *** this study,haptens of phenylurea herbicides(PUs)and sulfonylurea herbicides(SUs)were analyzed and designed based on computational simulation techniques,and two high-performance broad-spectrum monoclonal antibodies against PUs and SUs were *** this basis,a multi-colloidal gold immunochromatography assay(multi-CGIA)was developed to simultaneously detect 13 herbicides in *** visual limit of detection(vLOD)for PUs including diuron,chlortoluron,neburon,chlorbromuron,and linuron was 1-2μg/*** vLOD for SUs including metsulfuron methyl,ethametsulfuron-methyl,sulfometuron-methyl,tribenuron methyl,cinosulfuron,triasulfuron,chlorimuron-ethyl,and chlorsulfuron was 2-10μg/*** results of real sample determination indicated that the multi-CGIA is accurate,stable,and reliable,and adaptable to on-site preliminary screening of actual samples.

关键词： phenylurea herbicides sulfonylurea herbicides monoclonal antibody immunochromatographic assay wheat

Fake News detection based on Cross-Modal Message Aggregation and Gated Fusion Network

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Computers, Materials & Continua 2024年第7期80卷 1521-1542页

作者： Fangfang Shan Mengyao Liu Menghan Zhang Zhenyu Wang College of Computer Zhongyuan University of TechnologyZhengzhou450007China henan key laboratory of Cyberspace Situation Awareness Zhengzhou450001China

Social media has become increasingly significant in modern society,but it has also turned into a breeding ground for the propagation of misleading information,potentially causing a detrimental impact on public opinion and daily *** to pure text content,multmodal content significantly increases the visibility and share ability of *** has made the search for efficient modality representations and cross-modal information interaction methods a key focus in the field of multimodal fake news *** effectively address the critical challenge of accurately detecting fake news on social media,this paper proposes a fake news detection model based on crossmodal message aggregation and a gated fusion network(MAGF).MAGF first uses BERT to extract cumulative textual feature representations and word-level features,applies Faster Region-based ConvolutionalNeuralNetwork(Faster R-CNN)to obtain image objects,and leverages ResNet-50 and Visual Geometry Group-19(VGG-19)to obtain image region features and global *** image region features and word-level text features are then projected into a low-dimensional space to calculate a text-image affinity matrix for cross-modal message *** gated fusion network combines text and image region features to obtain adaptively aggregated *** interaction matrix is derived through an attention mechanism and further integrated with global image features using a co-attention mechanism to producemultimodal ***,these fused features are fed into a classifier for news *** were conducted on two public datasets,Twitter and *** show that the proposed model achieves accuracy rates of 91.8%and 88.7%on the two datasets,respectively,significantly outperforming traditional unimodal and existing multimodal models.

关键词： Fake news detection cross-modalmessage aggregation gate fusion network co-attention mechanism multi-modal representation

Multimodal Social Media Fake News detection based on Similarity Inference and Adversarial Networks

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Computers, Materials & Continua 2024年第4期79卷 581-605页

作者： Fangfang Shan Huifang Sun Mengyi Wang College of Computer Zhongyuan University of TechnologyZhengzhou450007China henan key laboratory of Cyberspace Situation Awareness Zhengzhou 450001China

As social networks become increasingly complex, contemporary fake news often includes textual descriptionsof events accompanied by corresponding images or videos. Fake news in multiple modalities is more likely tocreate a misleading perception among users. While early research primarily focused on text-based features forfake news detection mechanisms, there has been relatively limited exploration of learning shared representationsin multimodal (text and visual) contexts. To address these limitations, this paper introduces a multimodal modelfor detecting fake news, which relies on similarity reasoning and adversarial networks. The model employsBidirectional Encoder Representation from Transformers (BERT) and Text Convolutional Neural Network (Text-CNN) for extracting textual features while utilizing the pre-trained Visual Geometry Group 19-layer (VGG-19) toextract visual features. Subsequently, the model establishes similarity representations between the textual featuresextracted by Text-CNN and visual features through similarity learning and reasoning. Finally, these features arefused to enhance the accuracy of fake news detection, and adversarial networks have been employed to investigatethe relationship between fake news and events. This paper validates the proposed model using publicly availablemultimodal datasets from Weibo and Twitter. Experimental results demonstrate that our proposed approachachieves superior performance on Twitter, with an accuracy of 86%, surpassing traditional unimodalmodalmodelsand existing multimodal models. In contrast, the overall better performance of our model on the Weibo datasetsurpasses the benchmark models across multiple metrics. The application of similarity reasoning and adversarialnetworks in multimodal fake news detection significantly enhances detection effectiveness in this paper. However,current research is limited to the fusion of only text and image modalities. Future research directions should aimto further integrate f

关键词： Fake news detection attention mechanism image-text similarity multimodal feature fusion