Trends in Analytical Chemistry最新文献_第2页

Advances in detection of heteroatom-containing reactive species in advanced oxidation processes 高级氧化过程中含杂原子反应物质的检测研究进展

IF 12 1区化学

Trends in Analytical Chemistry Pub Date : 2026-04-01 Epub Date: 2026-01-30 DOI: 10.1016/j.trac.2026.118689

Xi Chen , Huajie Zhong , Tao Zhan , Zeyu Gong , Yuan Tao , Jiaxing Yu , Yu Hou , Qi Fu , Junhui Wang , Gangfeng Ouyang

{"title":"Advances in detection of heteroatom-containing reactive species in advanced oxidation processes","authors":"Xi Chen , Huajie Zhong , Tao Zhan , Zeyu Gong , Yuan Tao , Jiaxing Yu , Yu Hou , Qi Fu , Junhui Wang , Gangfeng Ouyang","doi":"10.1016/j.trac.2026.118689","DOIUrl":"10.1016/j.trac.2026.118689","url":null,"abstract":"<div><div>Reactive heteroatom-containing radicals (HCRSs), such as sulfate radicals (SO<sub>4</sub>·<sup>-</sup>), reactive nitrogen species (RNS), reactive halogen species (RHS), and carbonate radicals (CO<sub>3</sub>·<sup>-</sup>) could efficiently degrade organic pollutants in advanced oxidation processes (AOPs). However, their transient nature and complex reactivity pose significant challenges for precise detection. This review comprehensively examines the generation mechanisms and reactivity of these radicals, focusing on the comparison of detection techniques including electron spin resonance (ESR/EPR), time-resolved spectroscopy, chemical probes, fluorescence, and chemiluminescence. Current methods face limitations in real-time monitoring within complex aqueous matrices due to short radical lifetimes and interference from coexisting species. Future development should focus on novel detection strategies integrated with material engineering and real-time monitoring technologies. Optimizing radical generation pathways and reaction conditions is essential to balance degradation efficiency and byproduct control, thereby enabling the translation of AOPs from fundamental research to full-scale environmental applications.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"197 ","pages":"Article 118689"},"PeriodicalIF":12.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Smart sensors and nanoenabled systems: Pioneering technologies for monitoring emerging organic contaminants in environmental matrices 智能传感器和纳米系统：用于监测环境矩阵中新兴有机污染物的开创性技术

IF 12 1区化学

Trends in Analytical Chemistry Pub Date : 2026-04-01 Epub Date: 2026-02-06 DOI: 10.1016/j.trac.2026.118732

S. Thanigaivel , V. Sundaram , Infant Shofia Saghya , S. Anbalagan , K. Anbarasu , B. Bhavani Sowndharya

{"title":"Smart sensors and nanoenabled systems: Pioneering technologies for monitoring emerging organic contaminants in environmental matrices","authors":"S. Thanigaivel , V. Sundaram , Infant Shofia Saghya , S. Anbalagan , K. Anbarasu , B. Bhavani Sowndharya","doi":"10.1016/j.trac.2026.118732","DOIUrl":"10.1016/j.trac.2026.118732","url":null,"abstract":"<div><div>Emerging organic contaminants (EOCs) like pharmaceuticals, personal care products, and endocrine-disrupting compounds are found increasingly at trace levels in environmental media, posing risks in ecosystem as well as human health. Conventional surveillance methods typically lack speed and sensitivity, so new, higher-order methods are required. Recent developments in smart sensors and nanoenabled devices have enhanced environmental monitoring drastically by offering real-time, extremely sensitive, and selective detection of EOCs. Nanomaterials such as graphene, carbon nanotubes, and metal nanoparticles offer enhanced signal transduction and in situ detection at sub-ng/L concentration. Graphene-based electrochemical sensors, for example, detected bisphenol in as low as 0.1 ng/L concentration, while quantum dot-based optical sensors are exceptionally selective towards contaminants like triclosan in complex media. Sensor integration with IoT platforms offers real-time, automated tracking, while AI-based data analysis offers predictive contamination pattern modeling. In this review, design principles, detection mechanisms, and field deployments of nanoenabled sensors in a host of environments like industrial effluent, potable waters, and crop runoff are outlined. Challenges like materials sustainability, standardization of regulatory norms, and scale up are also addressed, underscoring that effective interdisciplinary collaborations among toxicology, data science, and regulatory regimes are imperative. Future prospects like biodegradable materials in sensors and multiservice sensing platforms are also addressed. The convergence of nanotechnology, sensing, and digital data analytics holds much promise in revolutionizing environmental surveillance by offering cost-effective, portable, and high-performing tools to ensure protection of public health and ecosystem.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"197 ","pages":"Article 118732"},"PeriodicalIF":12.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Single-molecule microscopy for precision medicine and diagnostics 用于精准医疗和诊断的单分子显微镜

IF 12 1区化学

Trends in Analytical Chemistry Pub Date : 2026-04-01 Epub Date: 2026-02-06 DOI: 10.1016/j.trac.2026.118723

Yachen Ying , Yijun Liu , Songlin Liu , Li Li , Bochen Ma , Liang Yuan , Xilin Dou , Qin Shentu , Rui Ai , Jiao Lei , Lubin Qi , Yifei Jiang , Xiaohong Fang

{"title":"Single-molecule microscopy for precision medicine and diagnostics","authors":"Yachen Ying , Yijun Liu , Songlin Liu , Li Li , Bochen Ma , Liang Yuan , Xilin Dou , Qin Shentu , Rui Ai , Jiao Lei , Lubin Qi , Yifei Jiang , Xiaohong Fang","doi":"10.1016/j.trac.2026.118723","DOIUrl":"10.1016/j.trac.2026.118723","url":null,"abstract":"<div><div>The advent of precision medicine has created an urgent need for detecting disease at its molecular origins. Conventional bioanalytical methods, including immunoassays and mass spectrometry, rely on ensemble averaging and often obscure rare events, molecular heterogeneity, and dynamic processes that are critical to disease initiation and progression. Recent advances in fluorescence-based single-molecule microscopy address these limitations by enabling ultrasensitive, molecule-resolved analysis in complex biological environments. This review provides a conceptual overview of fluorescence-based single-molecule detection strategies and their emerging applications in precision diagnostics. We outline the basic principles of single-molecule fluorescence detection, introduce recent advances in key methodological classes, including single-molecule counting for absolute quantification, single-molecule localization microscopy for nanoscale spatial mapping, and single-molecule dynamic tracing approaches for probing interactions and conformational states, as well as their potential applications in disease diagnosis. Finally, we discuss current challenges and future opportunities for integrating single-molecule microscopy into clinically workflows.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"197 ","pages":"Article 118723"},"PeriodicalIF":12.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Digital PCR in noninvasive prenatal testing: Analytical principles, clinical utilities, and future integration 数字PCR在无创产前检测：分析原则，临床应用，和未来的整合

IF 12 1区化学

Trends in Analytical Chemistry Pub Date : 2026-04-01 Epub Date: 2026-01-23 DOI: 10.1016/j.trac.2026.118695

Wen Zeng , Wenbo Luo , Junwei Zhou , Bohang Wang , Hao Qin , Yang He , Imrich Gablech , Marie Korabečná , Pavel Neužil

{"title":"Digital PCR in noninvasive prenatal testing: Analytical principles, clinical utilities, and future integration","authors":"Wen Zeng , Wenbo Luo , Junwei Zhou , Bohang Wang , Hao Qin , Yang He , Imrich Gablech , Marie Korabečná , Pavel Neužil","doi":"10.1016/j.trac.2026.118695","DOIUrl":"10.1016/j.trac.2026.118695","url":null,"abstract":"<div><div>Digital PCR (dPCR) enables absolute nucleic acid quantification through partition-based amplification and has emerged as a robust analytical platform for non-invasive prenatal testing (NIPT). Direct molecular counting, independent of calibration curves and amplification efficiency, enables precise detection of chromosomal aneuploidies, rare paternal or de novo variants, and microdeletions at very low fetal DNA fractions where sequencing-based screening loses statistical power. High partition numbers, strong reproducibility, and minimal computational requirements distinguish dPCR from qPCR and next-generation sequencing (NGS), positioning it as a reliable confirmatory method for sequencing-derived findings. Analytical advances, including improved extraction efficiency, enhanced partition stability, expanded multiplexing strategies, and duplex ratio assays, further improve performance in complex plasma samples. Hybrid workflows integrating NGS-based genome-wide discovery with dPCR-based quantitative validation reduce false positives and enhance diagnostic confidence. Digital PCR thus complements sequencing and supports a precise and scalable framework for next-generation prenatal diagnostics.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"197 ","pages":"Article 118695"},"PeriodicalIF":12.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Exploiting the penetration depth of XRF and NIR radiation: from 2D to 3D spectral imaging 利用XRF和近红外辐射的穿透深度：从2D到3D光谱成像

IF 12 1区化学

Trends in Analytical Chemistry Pub Date : 2026-04-01 Epub Date: 2026-01-23 DOI: 10.1016/j.trac.2026.118693

Zelan Li , Carolina Scagliarini , Alberto Mazzoleni , Sara Gariglio , Emilio Catelli , Cristina Malegori , Silvia Prati , Eugenio Alladio , Giorgia Sciutto , Paolo Oliveri

{"title":"Exploiting the penetration depth of XRF and NIR radiation: from 2D to 3D spectral imaging","authors":"Zelan Li , Carolina Scagliarini , Alberto Mazzoleni , Sara Gariglio , Emilio Catelli , Cristina Malegori , Silvia Prati , Eugenio Alladio , Giorgia Sciutto , Paolo Oliveri","doi":"10.1016/j.trac.2026.118693","DOIUrl":"10.1016/j.trac.2026.118693","url":null,"abstract":"<div><div>The present review examines the fundamental mechanisms governing the penetration of X-ray and near-infrared (NIR) radiation under sample surface – a feature that is often disregarded in analytical applications, especially in the spectral imaging implementations, which are usually considered as surface analytical techniques. The impact of material composition and geometry, scattering effects, as well as instrumental factors are thoroughly described and critically discussed. A particular focus is placed on data processing techniques, from first-principle equations to data-driven multivariate models, implemented to estimate/assess the extent of penetration. Applications in several areas, including food, forensic, material and cultural heritage sciences, are comprehensively reviewed. The potential for exploiting penetration of electromagnetic radiation is highlighted, paving the way for the development of 3D-resolved X-ray fluorescence (XRF) and NIR imaging approaches able to characterize multilayer samples in a non-invasive way.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"197 ","pages":"Article 118693"},"PeriodicalIF":12.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Multiplex biosensors for comprehensive health monitoring: Non-invasive, minimally invasive, and invasive platforms 用于全面健康监测的多重生物传感器：非侵入性、微创性和侵入性平台

IF 12 1区化学

Trends in Analytical Chemistry Pub Date : 2026-04-01 Epub Date: 2026-01-24 DOI: 10.1016/j.trac.2026.118698

Sudenur Ozbey , Tugba Akkas , Temmuz Ege Kaplan , Ilker Polatoglu , Mustafa Sen , Sevinc Kurbanoglu

{"title":"Multiplex biosensors for comprehensive health monitoring: Non-invasive, minimally invasive, and invasive platforms","authors":"Sudenur Ozbey , Tugba Akkas , Temmuz Ege Kaplan , Ilker Polatoglu , Mustafa Sen , Sevinc Kurbanoglu","doi":"10.1016/j.trac.2026.118698","DOIUrl":"10.1016/j.trac.2026.118698","url":null,"abstract":"<div><div>Multiplex biosensors are distinguished as cutting-edge strategies that offer a more holistic analysis by simultaneous, instantaneous monitoring of multiple biomarkers. The system's strength lies in its ability to support the care of complex pathologies, providing the necessary multi-indicator monitoring required for precise diagnostic assessment and personalized therapeutic optimization. Recent technological developments, including the integration of artificial intelligence, point-of-care, lab-on-a-chip systems, and wearable biosensors, have significantly improved the accessibility and usability of multiplex sensing platforms. Multiplex biosensors will play a critical role in enabling early detection, real-time health tracking, and individualized therapeutic interventions, ultimately yielding superior patient results and reducing the burden on healthcare systems. This review sheds light on new investigations by highlighting technological advances such as multiplexing, sensitivity, miniaturization, and integration for non-invasive, minimally invasive, and invasive platforms. It explores promising multi-analyte biosensors, a comprehensive understanding of the mechanisms, types, and challenges of state-of-the-art multi-analyte biosensors, and current challenges and future research areas.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"197 ","pages":"Article 118698"},"PeriodicalIF":12.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146049001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Synthetic urinary biomarker probes for disease detection and monitoring 用于疾病检测和监测的合成尿液生物标志物探针

IF 12 1区化学

Trends in Analytical Chemistry Pub Date : 2026-04-01 Epub Date: 2026-02-01 DOI: 10.1016/j.trac.2026.118725

Xumin Pan , Ping Xie , Yanhong Lu, Lan Liu, Xia Chu

{"title":"Synthetic urinary biomarker probes for disease detection and monitoring","authors":"Xumin Pan , Ping Xie , Yanhong Lu, Lan Liu, Xia Chu","doi":"10.1016/j.trac.2026.118725","DOIUrl":"10.1016/j.trac.2026.118725","url":null,"abstract":"<div><div>Owing to their noninvasive nature and convenient accessibility, urine-based detection methods hold great promise for enabling early diagnosis, which is essential for precision clinical intervention and improving therapeutic outcomes. However, conventional urine biomarker analysis faces critical challenges, including low abundance, short half-life, and interference from background signals, which limit sensitivity and reliability. To address these limitations, Synthetic Urinary Biomarker Probes (SUBPs) have emerged to interact with disease biomarkers as an active diagnostic strategy. Through programmable molecular designs, SUBPs amplify weak signals originating from specific biomarkers <em>in vivo</em> and convert them into stable reporter molecules excreted in urine, thereby providing a novel and sensitive platform for noninvasive disease detection. In this Review, we first outline the fundamental concepts of SUBPs and highlight their advantages over traditional endogenous urinary biomarkers. We then systematically discuss their modular design principles, including disease-responsive modules, programmable reporter units, and scaffolds. Finally, we provide a detailed overview of representative applications spanning multiple diseases, followed by a discussion of the opportunities and challenges associated with their clinical translation.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"197 ","pages":"Article 118725"},"PeriodicalIF":12.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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AI-enhanced CRISPR diagnostics: From gRNA design to Cas protein engineering and signal analytics 人工智能增强的CRISPR诊断：从gRNA设计到Cas蛋白工程和信号分析

IF 12 1区化学

Trends in Analytical Chemistry Pub Date : 2026-04-01 Epub Date: 2026-01-31 DOI: 10.1016/j.trac.2026.118704

Qiong Li, Xiaodong Lin

{"title":"AI-enhanced CRISPR diagnostics: From gRNA design to Cas protein engineering and signal analytics","authors":"Qiong Li, Xiaodong Lin","doi":"10.1016/j.trac.2026.118704","DOIUrl":"10.1016/j.trac.2026.118704","url":null,"abstract":"<div><div>CRISPR-based diagnostics have expanded molecular sensing through programmable target recognition and diverse signal transduction modes, yet their analytical performance remains limited by guide RNA (gRNA) design constraints, effector variability, and heterogeneous readout formats. Advances in artificial intelligence (AI) offer powerful solutions. Deep learning enables data-driven optimization of gRNA specificity, target interactions, and Cas protein engineering, while machine-learning models enhance automated, quantitative, and noise-tolerant interpretation of CRISPR-derived signals. Emerging methods in uncertainty estimation and explainable AI further support reliable and clinically aligned deployment. This review outlines how AI contributes across the CRISPR diagnostic workflow, accelerating Cas effector discovery and engineering, refining gRNA design and off-target assessment, and improving extraction, correction, and classification of heterogeneous output signals. Together, these developments define an emerging CRISPR-AI framework that integrates protein optimization, guide design, and signal analytics, enabling more sensitive, robust, and scalable next-generation diagnostic platforms.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"197 ","pages":"Article 118704"},"PeriodicalIF":12.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Roadmap to highest-throughput Raman flow cytometry for biological applications 生物应用最高通量拉曼流式细胞术的路线图

IF 12 1区化学

Trends in Analytical Chemistry Pub Date : 2026-04-01 Epub Date: 2026-01-24 DOI: 10.1016/j.trac.2026.118699

Ranran Zhou , Pan Wang , Yang Yu , Jian Ye , Chang Chen , Jian Xu , Bo Ma , Jing Wang , Yuling Wang , Yuntong Wang , Bei Li , Youzhi Feng , Jianlong Zhao , Haoye Tang , Jing Lu , Songlin Zhuang , Shilun Feng , Dawei Zhang

{"title":"Roadmap to highest-throughput Raman flow cytometry for biological applications","authors":"Ranran Zhou , Pan Wang , Yang Yu , Jian Ye , Chang Chen , Jian Xu , Bo Ma , Jing Wang , Yuling Wang , Yuntong Wang , Bei Li , Youzhi Feng , Jianlong Zhao , Haoye Tang , Jing Lu , Songlin Zhuang , Shilun Feng , Dawei Zhang","doi":"10.1016/j.trac.2026.118699","DOIUrl":"10.1016/j.trac.2026.118699","url":null,"abstract":"<div><div>The interrogation of single cells is revolutionizing biology by revealing heterogeneity that is masked in bulk analyses. Flow cytometry (FCM) enables high-throughput single-cell analysis but typically depends on exogenous fluorescent labels, which are time-intensive to prepare and may perturb native cellular states. In contrast, Raman scattering provides a label-free alternative with intrinsic molecular specificity. Raman flow cytometry (RFC) combines Raman scattering with FCM, merging high-throughput sample processing with detailed molecular characterization. However, the inherently weak intensity of spontaneous Raman scattering necessitates long integration times, and precise cell positioning in the laser focal volume limits linear flow velocity, resulting in lower throughput compared to conventional fluorescence-based flow cytometry (FFC). Overcoming these limitations demands a multidisciplinary approach. Recent progress in nanofabrication have facilitated the development of microfluidic chips that help address this bottleneck through precise multiphysics-based cell focusing techniques, as well as scalability achieved through parallel channel arrays or droplet systems. This review examines three principal strategies for enhancing the throughput of RFC from the perspective of modern microfluidic frameworks: (ⅰ) advanced cell focusing methods, (ⅱ) Raman signal amplification techniques, and (ⅲ) artificial intelligence (AI)-assisted spectral analysis. By synthesizing recent advances in these areas, we highlight the potential of RFC to advance high-throughput, label-free single-cell analysis in biomedical research.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"197 ","pages":"Article 118699"},"PeriodicalIF":12.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146076715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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Immunoassay-based approaches for multiplex detection: A review of pesticide residues in food and water matrices 基于免疫分析的多重检测方法：食品和水基质中农药残留的综述

IF 12 1区化学

Trends in Analytical Chemistry Pub Date : 2026-04-01 Epub Date: 2026-02-03 DOI: 10.1016/j.trac.2026.118727

Fei Yu , Fanting Wang , Eunice Y. Kwon , Xiaofan Ruan , Yuehe Lin , Dan Du , Bernard J. Van Wie

{"title":"Immunoassay-based approaches for multiplex detection: A review of pesticide residues in food and water matrices","authors":"Fei Yu , Fanting Wang , Eunice Y. Kwon , Xiaofan Ruan , Yuehe Lin , Dan Du , Bernard J. Van Wie","doi":"10.1016/j.trac.2026.118727","DOIUrl":"10.1016/j.trac.2026.118727","url":null,"abstract":"<div><div>The use of pesticides is integral to modern agriculture for managing pests, mitigating diseases, and securing harvest output. As multiple pesticides and their residues can coexist in plant-based products, they may pose synergistic health risks to humans. Thus, the simultaneous detection of such compounds provides a more efficient strategy than single-component analysis for monitoring pesticide residues in food, thereby helping to ensure compliance with food quality and safety regulations. Immunoassay technology is widely employed for pesticide detection owing to its high specificity, sensitivity, portability, and cost-effectiveness. This review systematically covers major multiplex immunoassay strategies, including microarray immunoassays, immunochromatographic assays, flow injection immunoassays, and multi-label immunoassays. It focuses on their application for the simultaneous analysis of pesticide residues in various matrices, such as water and diverse food products including fruits, vegetables, grain, and the processed derivatives. Furthermore, the current challenges and future research trajectories for developing automated, portable, highly sensitive, and high-throughput multiplex detection platforms are discussed.</div></div>","PeriodicalId":439,"journal":{"name":"Trends in Analytical Chemistry","volume":"197 ","pages":"Article 118727"},"PeriodicalIF":12.0,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146185718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0