Microchemical Journal最新文献_第8页

Recent advances in MOF synthesis and their applications in mixed-matrix membranes for water treatment: A critical review MOF合成及其在水处理混合基质膜中的应用研究进展

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-19 DOI: 10.1016/j.microc.2026.116982

Aitezaz Alam , Jamil Ahmad , Mansoor Ul Hassan Shah , Asmatullah , Hayat Khan , Wajid Ali

Global water scarcity demands innovative treatment technologies, yet conventional membranes face persistent challenges including fouling, the permeability-selectivity trade-off, and limited contaminant removal efficiency. Although mixed matrix membranes (MMMs) offer promising results, critical gaps remain in understanding how metal-organic framework (MOF) integration can simultaneously overcome these fundamental limitations. This review uniquely synthesizes recent breakthrough developments in MOF-based MMMs, focusing on innovative solutions that address multiple performance challenges. The objectives of this review are to evaluate sustainable MOF synthesis methods reducing environmental impact, analyze advanced fabrication techniques achieving superior filler-matrix integration, and assess performance breakthroughs in removing diverse contaminants. The key innovations highlighted include photocatalytic self-cleaning membranes, dual cross-linking strategies overcoming permeability-selectivity trade-offs, multi-functional systems with simultaneous contaminant removal capabilities, and bio-MOF integration. These advances have significantly enhanced membrane stability, reusability, antifouling capability, and filler-matrix compatibility, achieving remarkable removal efficiencies for heavy metal ions (>99%), dyes (>95%), salts (>99%), and emerging contaminants. Despite these achievements, critical challenges persist, including aqueous stability limitations, filler aggregation, performance degradation over operational cycles, and scalability barriers. To address these limitations, the review proposes scalable green synthesis methods, predictive modeling for lifespan optimization, and comprehensive stability assessments under realistic industrial conditions. This analysis provides a roadmap for advancing MOF-based MMMs to commercially viable water treatment solutions.

全球水资源短缺需要创新的处理技术，但传统的膜面临着持续的挑战，包括污染、渗透性和选择性权衡以及有限的污染物去除效率。尽管混合基质膜（MMMs）提供了有希望的结果，但在理解金属-有机框架（MOF）集成如何同时克服这些基本限制方面仍然存在关键空白。本综述独特地综合了基于mof的mmmm的最新突破性发展，重点介绍了解决多种性能挑战的创新解决方案。本综述的目的是评估减少环境影响的可持续MOF合成方法，分析实现优越填料-基质集成的先进制造技术，并评估去除各种污染物的性能突破。重点创新包括光催化自清洁膜，克服渗透性和选择性权衡的双交联策略，具有同时去除污染物能力的多功能系统，以及生物mof集成。这些进步显著提高了膜的稳定性、可重复使用性、防污能力和填料-基质相容性，对重金属离子（>99%）、染料（>95%）、盐（>99%）和新出现的污染物实现了显著的去除效率。尽管取得了这些成就，但关键的挑战仍然存在，包括水性稳定性限制、填料聚集、操作周期中的性能下降以及可扩展性障碍。为了解决这些局限性，本文提出了可扩展的绿色合成方法、寿命优化的预测建模以及现实工业条件下的综合稳定性评估。该分析为将mof基MMMs推进到商业上可行的水处理解决方案提供了路线图。

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引用次数: 0

Multi-scale synergistic analysis on microscopic mechanism of cyclohexanone /cyclohexanol extractive separation by hydrogen-bond dominated HDES 氢键主导HDES萃取分离环己酮/环己醇微观机理的多尺度协同分析

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-19 DOI: 10.1016/j.microc.2026.117044

Ruitong Guo, Xiaohong Wang, Chen Li, Weibin Zhang, Ying Zhao

To address industrial wastewater containing cyclohexanone (CHN) and To address industrial wastewater containing CHN and cyclohexanol (CHL) generated during Ketone-Alcohol (KA) oil and nylon production, this study employed simulated aqueous systems of CHN and CHL. Nine green hydrophobic deep eutectic solvents (HDESs) were synthesized using three terpenoids, two fatty alcohols, and tributyl phosphate as extractants for liquid-liquid extraction (LLE) experiments. The highest-performing HDES, Thy-Ocl, underwent comprehensive quantum chemical analysis, including binding site identification, two-dimensional potential energy surface mapping, and three-dimensional structural characterization, establishing a holistic mechanistic understanding of hydrogen-bond-driven extraction. Experimental optimization determined the optimal conditions: Thy-Ocl 1:2 M ratio, ambient temperature, and 1:1 extractant-to-feed mass ratio. Complementary molecular dynamics (MD) simulations elucidated Thy-Ocl's superiority through interaction energy analysis, spatial distribution functions (SDFs), radial distribution functions (RDFs), and mean square displacement (MSD) calculations. Integrated quantum chemistry (QC) and MD approaches revealed the microscopic extraction mechanism across electronic and classical mechanical regimes. Five consecutive extraction cycles confirmed the HDES's operational stability and reusability. This work provides a robust framework for designing HDESs and optimizing extraction processes for aqueous alcohol/ketone systems and analogous industrial separations.

为了解决含环己酮（CHN）的工业废水和酮醇（KA）油和尼龙生产过程中产生的含环己酮和环己醇（CHL）的工业废水，本研究采用了环己酮和环己醇的模拟水体系。以3种萜类化合物、2种脂肪醇和磷酸三丁酯为萃取剂，合成了9种绿色疏水深共晶溶剂（hess），进行了液液萃取（LLE）实验。性能最好的HDES Thy-Ocl进行了全面的量子化学分析，包括结合位点识别、二维势能表面映射和三维结构表征，建立了对氢键驱动萃取的整体机制理解。实验优化确定了最佳工艺条件：Thy-Ocl 1:2 M比、环境温度、料料质量比1:1。互补分子动力学（MD）模拟通过相互作用能分析、空间分布函数（SDFs）、径向分布函数（RDFs）和均方位移（MSD）计算验证了Thy-Ocl的优越性。综合量子化学（QC）和MD方法揭示了跨电子和经典力学机制的微观萃取机制。连续5次提取循环验证了HDES的运行稳定性和可重复使用性。这项工作为设计hess和优化乙醇/酮水溶液系统和类似工业分离的提取工艺提供了强有力的框架。

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引用次数: 0

Analytical techniques for antibiotic concentration detection in biological samples: A systematic review 生物样品中抗生素浓度检测的分析技术：系统综述

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-18 DOI: 10.1016/j.microc.2026.117034

Xiaoyang Feng

The global challenge of antimicrobial resistance underscores the critical need for optimizing antibiotic dosage in clinical practice. Precise measurement of antibiotic concentrations in biological fluids is fundamental to this optimization, enabling personalized treatment, minimizing adverse effects, and curbing the development of resistance. This review systematically summarizes current analytical techniques for antibiotic concentration detection in biological samples. It covers established methods such as high-performance liquid chromatography for single and combined antibiotic quantification, as well as emerging approaches including fluorescent probes and electrochemical sensors. The quantitative analysis of antibiotics by these techniques relies on the construction of a calibration curve under specific analytical conditions, which allows the concentration in a sample to be calculated by correlating its measured signal with the pre-established equation. Each technique is elaborated in terms of its detection principle, performances (e.g., sensitivity, selectivity, and linear range), and practical applications in clinical settings. Finally, existing challenges, such as interference in complex matrices, real-time monitoring limitations, and result variability from methodological differences are discussed and future directions are suggested, including the integration of multiplex detection, miniaturized devices, and artificial intelligence–assisted data analysis for point-of-care testing.

抗菌素耐药性的全球挑战强调了在临床实践中优化抗生素剂量的迫切需要。精确测量生物液体中的抗生素浓度是这种优化的基础，可以实现个性化治疗，最大限度地减少不良反应，并抑制耐药性的发展。本文系统地综述了目前生物样品中抗生素浓度检测的分析技术。它涵盖了已建立的方法，如用于单一和联合抗生素定量的高效液相色谱法，以及包括荧光探针和电化学传感器在内的新兴方法。这些技术对抗生素的定量分析依赖于在特定分析条件下建立校准曲线，通过将其测量信号与预先建立的方程相关联来计算样品中的浓度。每种技术都阐述了其检测原理、性能（如灵敏度、选择性和线性范围）以及在临床环境中的实际应用。最后，讨论了现有的挑战，如复杂矩阵的干扰、实时监测限制和方法差异带来的结果可变性，并提出了未来的方向，包括多路检测的集成、小型化设备和人工智能辅助数据分析。

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引用次数: 0

CRISPR for next-generation point-of-care molecular diagnostics CRISPR用于下一代即时分子诊断

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-17 DOI: 10.1016/j.microc.2026.117008

Jinyu Fu , Jiaming Yang , Shuobo Shi , Zhenglin Zhu , Xing Wang , Yaru Li

Point-of-care testing (POCT) is critical for rapid disease diagnosis, particularly in resource-limited settings. While molecular diagnostics offer high sensitivity, current platforms face significant bottlenecks in portability, scalability, and accuracy for decentralized healthcare. This review highlights the transformative potential of CRISPR-based technologies as a next-generation framework for POCT. We detail the fundamental principles of CRISPR diagnostics, which are based on the programmable complex of Cas proteins and guide RNAs (gRNAs) for specific nucleic acid recognition. This system typically integrates isothermal pre-amplification (e.g., RPA, LAMP) to enhance sensitivity, followed by Cas-mediated target recognition and a target-activated signal readout (e.g., fluorescence, colorimetry, lateral flow assays) that enables equipment-free, visual interpretation. Furthermore, we explore the expanding applications of CRISPR-based POCT, including clinical diagnostics, food safety, environmental pollutant detection, and wearable devices. This review underscores how CRISPR diagnostics, with their operational simplicity, uncompromised sensitivity, and versatile signal output, are poised to advance rapid, accurate, and accessible molecular testing at the point of care.

即时检测（POCT）对于快速诊断疾病至关重要，特别是在资源有限的环境中。虽然分子诊断提供了高灵敏度，但目前的平台在分散式医疗保健的可移植性、可扩展性和准确性方面面临着重大瓶颈。这篇综述强调了基于crispr的技术作为下一代POCT框架的变革潜力。我们详细介绍了CRISPR诊断的基本原理，这些原理基于Cas蛋白的可编程复合物和用于特定核酸识别的引导rna （gRNAs）。该系统通常集成等温预扩增（例如，RPA， LAMP）以提高灵敏度，然后是cas介导的目标识别和目标激活信号读出（例如，荧光，比色法，侧流测定），从而实现无设备，视觉解释。此外，我们探索基于crispr的POCT在临床诊断、食品安全、环境污染物检测和可穿戴设备等方面的应用。这篇综述强调了CRISPR诊断方法如何以其操作简单、不受影响的灵敏度和多用途的信号输出，准备在护理点推进快速、准确和可获得的分子检测。

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引用次数: 0

Advances in sample pretreatment for the analysis of ketamine and its analogs: A review 氯胺酮及其类似物样品前处理研究进展

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-17 DOI: 10.1016/j.microc.2026.117012

Min Qian , Jia-xin Liu , Yuan Zhang , Mei-di Wang , Wen-hao Shao , Yuan Wang , Xue-song Feng

Ketamine (KET) and its analogs, prohibited substances known for inducing dissociation and emergence delirium, continue to be widely abused. Effective monitoring of these substances in complex biological and environmental matrices (such as urine, blood, hair, and wastewater) is essential for forensic investigation, clinical toxicology, and public health surveillance. However, the direct analysis of KETs in these samples is severely hindered by low analyte concentrations, significant matrix interference, and the presence of structurally similar metabolites. Therefore, efficient and selective sample pretreatment is an indispensable prerequisite for achieving accurate quantitation. This review provides a comprehensive overview of pretreatment techniques developed for KETs since 2015. It systematically examines conventional methods (e.g., liquid-liquid extraction) and emerging microextraction strategies (e.g., various modes of liquid-phase and solid-phase microextraction). A particular emphasis is placed on recent innovations, notably the development of novel sorbent materials (e.g., molecularly imprinted polymers and metal-organic frameworks) for enhanced selectivity, and the integration of green solvents with miniaturization/automation to improve efficiency and sustainability. The evolution of these pretreatment strategies is driven by the imperative to enable reliable trace-level detection in real-world samples, thereby playing a crucial role in combating drug abuse and safeguarding public health.

氯胺酮（Ketamine）及其类似物是已知可诱导解离和出现性谵妄的违禁物质，继续被广泛滥用。在复杂的生物和环境基质（如尿液、血液、毛发和废水）中有效监测这些物质对于法医调查、临床毒理学和公共卫生监测至关重要。然而，在这些样品中直接分析KETs受到低分析物浓度、明显的基质干扰和存在结构相似的代谢物的严重阻碍。因此，高效、选择性的样品前处理是实现准确定量的必要前提。这篇综述提供了自2015年以来为KETs开发的预处理技术的全面概述。它系统地检查了传统方法（例如，液-液萃取）和新兴的微萃取策略（例如，液相和固相微萃取的各种模式）。特别强调的是最近的创新，特别是为提高选择性而开发的新型吸附材料（例如，分子印迹聚合物和金属有机框架），以及将绿色溶剂与小型化/自动化相结合以提高效率和可持续性。这些预处理策略的发展是由于迫切需要在实际样品中进行可靠的痕量检测，从而在打击药物滥用和保障公众健康方面发挥关键作用。

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引用次数: 0

Exploring the potential of molecular imprinted polymers modified carbon nanotubes in electrochemical sensors toward environmental monitoring by detecting hazardous substances: Addressing the selectivity and sensitivity 探索分子印迹聚合物修饰碳纳米管在环境监测电化学传感器中的应用潜力：解决选择性和灵敏度问题

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-15 DOI: 10.1016/j.microc.2026.116981

Sofiene Mansouri , Yousef Alharbi , Abdulrahman Alqahtani , Amira Ouerhani

Nowadays, urbanization and industrialization have caused significant environmental degradation. The demand for high-performance biosensors for efficient detection of hazardous substances is increasing. Among different methods, electrochemical (EC) sensors, as promising and standard analytical approaches, have been widely used for monitoring of hazardous substances in aquatic environments. Emerging EC sensing platforms have focused on improving different aspects of analytical approaches, such as affordability, stability, portability, selectivity, and sensitivity. In this review study, we primarily focus on evaluating recent advances in EC sensors based on molecular imprinted polymers‑carbon nanotubes (MIP-CNTs) composites for environmental analysis. In order to achieve sensitive and specific EC sensors, numerous biomolecules, such as aptamers, antibodies, and enzymes, have been applied in the sensing zones of EC sensors. However, in many cases, their high cost and limited stability under harsh environmental conditions have led to the development of alternative receptors. Interestingly, MIPs have attracted considerable attention in EC sensors. These stable polymers have excellent potential for the recognition of a wide variety of targets. However, the poor conductivity and electrocatalytic activity can limit their application in electrochemical sensors. The integration of nanomaterials, particularly CNTs, into MIP film has attracted research interest in electrochemical sensing due to their role in favor electronic communication to the imprinted cavities and enhancing surface area. Different CNTs have been frequently combined with MIPs due to their great conductivity and high surface area. In this review, the fabrication techniques of MIPs-CNTs and their application in EC sensors are discussed for detection of hazardous substances. In addition, the analytical performance of different EC sensors based on MIPs-CNTs and other non-enzymatic bioreceptors on the CNTs is examined for environmental monitoring.

如今，城市化和工业化造成了严重的环境退化。对高效检测有害物质的高性能生物传感器的需求正在增加。在各种方法中，电化学传感器作为一种有前途的标准分析方法，已广泛应用于水生环境有害物质的监测。新兴的EC传感平台专注于改进分析方法的不同方面，如可负担性、稳定性、可移植性、选择性和灵敏度。在这篇综述研究中，我们主要侧重于评估基于分子印迹聚合物-碳纳米管（MIP-CNTs）复合材料的环境分析EC传感器的最新进展。为了实现灵敏、特异的电感应传感器，许多生物分子如适体、抗体、酶等被应用于电感应传感器的感应区。然而，在许多情况下，它们的高成本和在恶劣环境条件下有限的稳定性导致了替代受体的发展。有趣的是，MIPs在EC传感器中引起了相当大的关注。这些稳定的聚合物具有识别各种目标的优异潜力。但其导电性差、电催化活性差，限制了其在电化学传感器中的应用。纳米材料，特别是碳纳米管，集成到MIP薄膜中，由于其有利于与印迹腔的电子通信和增加表面积的作用，引起了电化学传感领域的研究兴趣。不同的碳纳米管由于其高导电性和高表面积而经常与MIPs结合。本文综述了MIPs-CNTs的制备技术及其在有害物质检测中的应用。此外，研究了基于MIPs-CNTs和其他碳纳米管上的非酶生物受体的不同EC传感器在环境监测中的分析性能。

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引用次数: 0

Magnetic nanoparticle-modified electrodes for electrochemical sensing of antiepileptic drugs: advances and perspectives 磁性纳米粒子修饰电极用于抗癫痫药物的电化学传感：进展与展望

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-14 DOI: 10.1016/j.microc.2026.116925

Muhammad Tariq Shah , Fatma Nur Arslan , Abdullah

Epilepsy is a complex neurological disorder that significantly impacts various aspects of a patients life, including their socioeconomic well-being. Failure to identify epileptic activity early can cause serious damage to the central nervous system (CNS) and irreversible changes in various organs. Consequently, antiepileptic drugs (AEDs) are widely used to control and reduce the frequency of seizures. Because there is a direct relationship between clinical outcomes and plasma drug levels, measuring AED concentrations in different biological matrices has gained considerable attention for tailoring therapeutic dosing. Monitoring antiepileptic drugs (AEDs) in biological samples and pharmaceutical products is essential for therapeutic drug monitoring (TDM), ensuring accurate dosing and reducing the risk of toxicity. Electrochemical sensors, particularly those enhanced with magnetic nanoparticles (MNPs), have garnered recognition for their exceptional sensitivity, selectivity, quick response time, and affordability. This review provides a comprehensive and critical evaluation of literature published from 2004 to 2024 on MNPs-based electrochemical sensing platforms for AEDs. The review offers an in-depth summary of recent advances in the electrochemical detection of AEDs using MNP-modified electrodes. It explores methods for synthesizing MNPs, techniques for electrode modification, underlying electrochemical detection mechanisms, and sensor performance assessments. Additionally, the review outlines current challenges and provides insights into future research directions in this area.

癫痫是一种复杂的神经系统疾病，严重影响患者生活的各个方面，包括他们的社会经济福祉。未能及早识别癫痫活动可导致中枢神经系统（CNS）的严重损害和各种器官的不可逆变化。因此，抗癫痫药物被广泛用于控制和减少癫痫发作的频率。由于临床结果与血浆药物水平之间存在直接关系，因此测量不同生物基质中的AED浓度对于定制治疗剂量已经引起了相当大的关注。监测生物样品和药品中的抗癫痫药物（aed）对于治疗药物监测（TDM）至关重要，可以确保准确给药并降低毒性风险。电化学传感器，特别是磁性纳米颗粒（MNPs）增强的电化学传感器，因其卓越的灵敏度、选择性、快速响应时间和可负担性而获得认可。本文对2004年至2024年发表的关于基于mnps的aed电化学传感平台的文献进行了全面而批判性的评价。本文综述了利用mnp修饰电极对aed进行电化学检测的最新进展。它探讨了合成MNPs的方法，电极修饰技术，潜在的电化学检测机制和传感器性能评估。此外，该综述概述了当前的挑战，并提供了对该领域未来研究方向的见解。

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引用次数: 0

Instrumental-analytical integration in food sensory evaluation: Current trends and future horizons 食品感官评价中的仪器分析集成：当前趋势和未来前景

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-13 DOI: 10.1016/j.microc.2026.116942

Mehmet Melikoglu

Sensory evaluation is a cornerstone of food science, bridging product characteristics with human perception. In a rapidly changing food landscape, its evolution is vital for assessing quality, developing new products, and gaining consumer insights. This paper reviews recent advancements (2020–2025) in sensory evaluation, highlighting three key trends. Firstly, there is a paradigm shift towards integrating state-of-the-art analytical chemistry methodologies with traditional sensory evaluation. Tools like high-resolution separation techniques (e.g., GC–MS, SGC/GC²-O-MS), and intelligent sensor arrays (e-noses, e-tongues) are combined with chemometrics, machine learning, and artificial intelligence. This approach offers objective, precise, and high-throughput predictive capabilities for deciphering complex food matrices. This significantly enhances quality assessment and reduces reliance on subjective human panels. Secondly, the literature explores the significant influence of production, processing, and storage conditions on sensory quality, providing practical analytical insights for optimizing the food supply chain and ensuring consistent product quality. Lastly, the review covers advancements in sensory methodologies and a deeper understanding of consumer perception and behavior, which are crucial for market success and addressing societal challenges like food waste. Future research should focus on developing more robust and analytically generalizable predictive models, elucidating dynamic sensory perception, tailoring experiences for personalized nutrition, and applying analytical sensory science within sustainable food systems. This holistic and interdisciplinary approach is essential for addressing the complex challenges and opportunities in the future of food.

感官评价是食品科学的基石，将产品特性与人类感知联系起来。在快速变化的食品环境中，它的演变对于评估质量、开发新产品和获得消费者洞察力至关重要。本文回顾了感官评估的最新进展（2020-2025），强调了三个关键趋势。首先，将最先进的分析化学方法与传统的感官评估相结合是一种范式转变。高分辨率分离技术（如GC-MS、SGC/GC2-O-MS）和智能传感器阵列（电子鼻、电子舌）等工具与化学计量学、机器学习和人工智能相结合。这种方法为破译复杂的食物矩阵提供了客观、精确和高通量的预测能力。这大大提高了质量评估，减少了对主观的人类小组的依赖。其次，文献探讨了生产、加工和储存条件对感官质量的显著影响，为优化食品供应链和确保产品质量一致提供了实用的分析见解。最后，回顾了感官方法的进步和对消费者感知和行为的更深入理解，这对市场成功和解决食品浪费等社会挑战至关重要。未来的研究应侧重于开发更强大和分析上可推广的预测模型，阐明动态感官知觉，为个性化营养量身定制体验，以及在可持续食品系统中应用分析感官科学。这种整体和跨学科的方法对于应对未来粮食领域的复杂挑战和机遇至关重要。

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引用次数: 0

Design strategies for multiplexed electrochemical biosensors: advances in accurate diagnosis and health monitoring 多路电化学生物传感器的设计策略：准确诊断和健康监测的进展

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-13 DOI: 10.1016/j.microc.2026.116923

Jianghong Wu, Tong Wu, Yuqing Li

A paradigm shift toward early diagnosis and proactive health management is becoming an inevitable trend in contemporary society. With evolving lifestyles, there is an increasing demand for simple, portable health-monitoring devices. Electrochemical biosensors are emerging as promising solutions to meet this demand due to their high sensitivity, rapid response, miniaturization, and low cost. However, whether for health monitoring or disease diagnosis, a single physiological parameter is insufficient to provide accurate and valuable clinical information. Multiplexed electrochemical biosensors, which can detect multiple targets simultaneously, offer a promising approach to meet this need. This review summarizes the progress in electrochemical biosensors for multiplexed detection over the past decades. We mainly focus on two fundamental strategies: the multiple label strategy and the multiple electrode strategy, including discussion of redox label selection, electrode layout design, and multiple signal transduction mechanisms. For the multi-label approaches, several common labels used for multiplexed electrochemical detection are discussed, including metal ions, dyes, metal nanoparticles, and electroactive polymers. For multiple electrodes, we introduced typical techniques for designing and fabricating sensors categorized by multiple working electrodes and multiple sensors. With deeper insight, we further reviewed the applications of these multiplexed electrochemical biosensors in disease diagnosis and health monitoring. These sensors have shown promise in the detection of a variety of diseases, including cancers, pathogen infections, sepsis, and metabolic diseases. We also highlight the multi-biomarkers associated with these diseases that are analyzed using multiplexed electrochemical biosensors. Finally, we evaluated the strengths and limitations of different strategies and proposed our perspective on the challenges and potential solutions for further exploration and improvement of multiplexed electrochemical biosensors.

向早期诊断和主动健康管理的范式转变正在成为当代社会的必然趋势。随着生活方式的发展，人们对简单、便携的健康监测设备的需求越来越大。电化学生物传感器因其高灵敏度、快速响应、小型化和低成本而成为满足这一需求的有前途的解决方案。然而，无论是健康监测还是疾病诊断，单一的生理参数都不足以提供准确而有价值的临床信息。多路电化学生物传感器可以同时检测多个目标，为满足这一需求提供了一种很有前途的方法。本文综述了近几十年来电化学生物传感器在多路检测方面的研究进展。我们主要关注两种基本策略：多标签策略和多电极策略，包括氧化还原标签选择、电极布局设计和多种信号转导机制的讨论。对于多标记方法，讨论了用于多路电化学检测的几种常见标记，包括金属离子、染料、金属纳米粒子和电活性聚合物。对于多电极，我们介绍了按多工作电极和多传感器分类的传感器设计和制造的典型技术。在此基础上，我们进一步综述了这些多路电化学生物传感器在疾病诊断和健康监测中的应用。这些传感器在检测各种疾病方面显示出了希望，包括癌症、病原体感染、败血症和代谢性疾病。我们还强调了使用多路电化学生物传感器分析与这些疾病相关的多种生物标志物。最后，我们评估了不同策略的优势和局限性，并提出了进一步探索和改进多路电化学生物传感器所面临的挑战和可能的解决方案。

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引用次数: 0

Green digital analytical approaches for sustainable development of plant-based meat: Integrating AI, computational modeling, and non-destructive testing 植物性肉类可持续发展的绿色数字分析方法：整合人工智能、计算建模和无损检测

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-09 DOI: 10.1016/j.microc.2026.116904

Saeid Jafari , Halak N. Mehta , Rahul D. Kamath , Sochannet Chheng , Vinoothna Ramisetty , Isaya Kijpatanasilp , Mahdi Ebrahimi , Subhashis Chakraborty , Kitipong Assatarakul , Dharmendra K. Mishra

The integration of green analytical methods into food innovation is essential for advancing sustainability and reducing the environmental footprint of product development. This review explores how emerging digital tools—such as artificial intelligence (AI), machine learning (ML), hyperspectral imaging (HSI), electronic nose (E-nose), electronic tongue (E-tongue), and computational simulations—can serve as non-destructive, solvent-free, and energy-efficient analytical methods in the development of plant-based meat analogs (PBMAs). These technologies enable real-time monitoring of product structure, texture, and nutritional attributes without generating chemical waste, replacing resource-intensive conventional analyses. AI and ML optimize formulation by predicting quality and safety attributes from spectral or sensor data, while computational modeling reduces the need for repetitive experimental trials. HSI allows rapid pixel-level mapping of composition and quality, and E-nose/E-tongue systems profile flavor and aroma without physical sample destruction. Collectively, these approaches embody the principles of green analytical chemistry by minimizing reagent use, waste generation, and energy demand, while enhancing process efficiency and product quality. For instance, integrated digital workflows have been shown to reduce analytical waste and energy use by approximately 60–70% compared to conventional destructive methods. This review further examines their applicability beyond PBMAs to broader food and environmental monitoring, highlighting their role in sustainable food systems and circular economy strategies.

将绿色分析方法整合到食品创新中对于推进可持续性和减少产品开发的环境足迹至关重要。本文探讨了新兴的数字工具，如人工智能（AI）、机器学习（ML）、高光谱成像（HSI）、电子鼻（E-nose）、电子舌（E-tongue）和计算模拟，如何在植物性肉类类似物（pbma）的开发中作为非破坏性、无溶剂和节能的分析方法。这些技术能够实时监测产品结构、质地和营养属性，而不会产生化学废物，取代了资源密集型的传统分析。AI和ML通过预测光谱或传感器数据的质量和安全属性来优化配方，而计算建模则减少了重复实验试验的需要。HSI允许快速像素级的成分和质量映射，以及电子鼻/电子舌系统在没有物理样品破坏的情况下描述风味和香气。总的来说，这些方法通过最大限度地减少试剂使用、废物产生和能源需求，同时提高工艺效率和产品质量，体现了绿色分析化学的原则。例如，与传统的破坏性方法相比，集成的数字工作流程已被证明可以减少大约60-70%的分析浪费和能源使用。本综述进一步探讨了它们在更广泛的食品和环境监测方面的适用性，强调了它们在可持续食品系统和循环经济战略中的作用。

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