Microchemical Journal最新文献_第6页

Explainable artificial intelligence (XAI) applied to deep computer vision for the assessment and classification of oleogels with varying oleogelator types and concentrations 可解释人工智能（XAI）应用于深度计算机视觉，对不同类型和浓度的油凝胶进行评估和分类

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-04 DOI: 10.1016/j.microc.2026.116821

Ingrid A. Moraes , Leonardo Arrighi , Sylvio Barbon Junior , Rosiane L. Cunha , Douglas F. Barbin

Oleogels represent a promising alternative to trans and saturated fats, as they enable the structuring of liquid oils into semi-solid systems while improving nutritional quality, texture, and stability. Their development relies on oleogelators, which are considered food additives and must be carefully selected and regulated due to differences in functionality, cost, and acceptance.We investigated structural variations in oleogels produced with different oleogelator types and concentrations, using polarized light microscopy images coupled with deep learning and explainable artificial intelligence (XAI). A convolutional neural network (CNN) was employed to classify the samples and explore the relationship between crystalline organization and oil-holding capacity. CNN achieved 95 % accuracy in distinguishing between oleogels formulated with beeswax (BW) and glycerol monostearate (GM), and 77 % accuracy in classifying their concentrations. Morphological analyses revealed that BW-based oleogels form platelet-shaped crystals, while GM-based oleogels exhibit irregular clusters of needle-shaped crystals. XAI, using Grad-CAM++, highlighted that CNN predictions were primarily based on these structural features, particularly at lower concentrations. At higher concentrations (≥6 % w/w), similarities between BW and GM reduced classification accuracy. Overall, integrating microscopy with deep learning and XAI proved to be a robust and innovative methodology for characterizing oleogel structures, offering valuable insights for formulation and development.

油凝胶是反式脂肪和饱和脂肪的一个很有前途的替代品，因为它们可以将液体油结构成半固体体系，同时提高营养质量、质地和稳定性。它们的发展依赖于被认为是食品添加剂的油凝胶，由于功能、成本和接受度的差异，必须仔细选择和监管。我们利用偏振光显微镜图像结合深度学习和可解释人工智能（XAI）研究了不同类型和浓度的油凝胶的结构变化。利用卷积神经网络（CNN）对样品进行分类，探索晶体组织与持油能力之间的关系。CNN在区分由蜂蜡（BW）和单硬脂酸甘油（GM）配制的油凝胶方面达到95%的准确率，在分类它们的浓度方面达到77%的准确率。形态学分析表明，基于bw的油凝胶形成血小板状晶体，而基于gm的油凝胶呈现不规则的针状晶体簇。XAI使用grad - cam++强调，CNN的预测主要基于这些结构特征，特别是在较低浓度下。在较高的浓度下（≥6% w/w），体重和GM之间的相似性降低了分类精度。总的来说，将显微镜与深度学习和XAI相结合被证明是表征油凝胶结构的一种强大而创新的方法，为配方和开发提供了有价值的见解。

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引用次数: 0

Development of a colorimetric biosensor based on G-quadruplex aptamer and gold nanoparticles for rapid and sensitive detection of HPV18 基于g -四联体适体和金纳米粒子的HPV18快速灵敏检测比色生物传感器的研制

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-04 DOI: 10.1016/j.microc.2026.116811

Soheil Shajari , Sepehr Nouri , Hassan Mohabatkar , Mandana Behbahani

Human papillomavirus (HPV), the most prevalent sexually transmitted infection and a leading cause of cervical cancer, often lacks rapid and cost-effective diagnostic methods. This study introduces a novel colorimetric biosensor for specific and sensitive HPV18 detection. This biosensor was developed using an in silico-designed G-quadruplex aptamer, chosen for its inherent stability and specific binding capabilities, in conjunction with gold nanoparticles (AuNPs). Our in silico design identified APT43 as the top candidate aptamer, demonstrating high binding affinity and specificity for the HPV18 L1 protein via molecular docking. AuNPs were then experimentally synthesized and functionalized with APT43. Successful conjugation was confirmed by DLS characterization, evidenced by a hydrodynamic size increase from ∼29 nm to ∼36 nm and a zeta potential shift from −36 mV to −29.8 mV. The developed biosensor exhibited high specificity for HPV18, showing no cross-reactivity with types 16, 11, or 6. It also achieved a remarkably low detection limit of 85 viral copies/mL, significantly lower than the typical ∼1000 copies/mL reported for many commercial PCR kits. This rapid, visual, aptamer-induced AuNP aggregation system offers a sensitive, specific, and cost-effective diagnostic tool for HPV18, particularly beneficial in resource-limited settings. This work reports the first computationally designed aptamer capable of type-specific discrimination of HPV18 from other high- and low-risk HPV types in real clinical samples, marking a significant advancement in rapid HPV diagnostics.

人类乳头瘤病毒（HPV）是最普遍的性传播感染，也是宫颈癌的主要原因，但往往缺乏快速和具有成本效益的诊断方法。本研究介绍了一种新型比色生物传感器，用于HPV18的特异性和敏感性检测。这种生物传感器是使用硅设计的g -四重体适配体开发的，选择g -四重体适配体是因为其固有的稳定性和特定的结合能力，并结合金纳米颗粒（AuNPs）。我们的计算机设计将APT43确定为首选适配体，通过分子对接显示出对HPV18 L1蛋白的高结合亲和力和特异性。然后用APT43对AuNPs进行实验合成和功能化。DLS表征证实了成功的偶联，水动力尺寸从~ 29 nm增加到~ 36 nm， zeta电位从−36 mV转移到−29.8 mV。所开发的生物传感器对HPV18具有高特异性，与16型、11型和6型无交叉反应。它还达到了85个病毒拷贝/mL的非常低的检测限，显著低于许多商业PCR试剂盒报道的典型的~ 1000个拷贝/mL。这种快速、直观、适体诱导的AuNP聚集系统为HPV18提供了一种敏感、特异、经济的诊断工具，在资源有限的环境下尤其有益。这项工作报告了第一个计算设计的适体，能够在真实的临床样本中区分HPV18和其他高风险和低风险的HPV类型，标志着HPV快速诊断的重大进步。

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引用次数: 0

A protein-triggered and base-mismatch-accelerated Strand displacement reaction for alpha-fetoprotein detection 蛋白触发和碱基错配加速链置换反应用于甲胎蛋白检测

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-03 DOI: 10.1016/j.microc.2025.116722

Lingying Xia , Liyan Lin , Qiao Xiong , Junbo Chen , Rongxing Zhou

Toehold-mediated strand displacement (TMSD), a fundamental enzyme-free DNA circuit, suffers from slow reaction kinetics due to hindered strand migration, limiting its analytical applications. While strategic base mismatches (BM) can enhance TMSD kinetics, their application in protein detection remains challenging due to the intricate designs required. Herein, we report a strategy by integrating a binding-induced DNA assembly (BINDA) system with a base-mismatch TMSD (BM-TMSD) amplification for highly sensitive protein detection. When triggered BINDA for the detection of AFP, our BM-TMSD-based sensor achieved an approximately 83-fold rate enhancement over the conventional TMSD-based system. Moreover, it achieved a high detection sensitivity with a limit of detection (LOD) as low as 0.014 nM. As a proof of principle, we employed this sensor to detect alpha-fetoprotein (AFP) in actual patient samples and compared the results with clinical standard results, with high consistency between the two, demonstrating that this biosensor is effective for detecting AFP in real patient serum samples. We anticipate that the BM TMSD design will emerge as a versatile and efficient tool for protein biomarker quantification, significantly streamlining the detection workflow.

支点介导的链位移（TMSD）是一种基本的无酶DNA电路，由于链迁移受阻，反应动力学缓慢，限制了其分析应用。虽然策略性碱基错配（BM）可以增强TMSD动力学，但由于需要复杂的设计，它们在蛋白质检测中的应用仍然具有挑战性。在此，我们报告了一种将结合诱导DNA组装（BINDA）系统与碱基错配TMSD （BM-TMSD）扩增相结合的策略，用于高灵敏度的蛋白质检测。当触发bda检测AFP时，我们的基于bm - tmsd的传感器比传统的基于tmsd的系统实现了大约83倍的速率增强。检测灵敏度高，检出限（LOD）低至0.014 nM。作为原理验证，我们利用该传感器检测了实际患者样本中的甲胎蛋白（AFP），并将结果与临床标准结果进行了比较，两者具有较高的一致性，表明该生物传感器对于检测实际患者血清样本中的甲胎蛋白是有效的。我们预计BM TMSD设计将成为蛋白质生物标志物定量的多功能和高效工具，显著简化检测工作流程。

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引用次数: 0

Rapid and efficient colorimetric assay for acid phosphatase via nanoarchitectonics of 2D MOF-supported oxidase-like ultrasmall Pt NPs 利用mof支持的氧化酶样超小Pt纳米粒子的纳米结构快速高效比色法测定酸性磷酸酶

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-03 DOI: 10.1016/j.microc.2026.116815

Yue Zhou , Zhenhui Liyao , Weijie Song , Bo Zheng , Juan Zhou , Yishan Wang , Leiming Lang , Guangxiang Liu , Xinghua Xia

Developing rapid and efficient point-of-care (POC) assays for acid phosphatase (ACP) activity is crucial for the diagnosis and therapeutic monitoring of various diseases. Traditional and commercial ACP assays are commonly plagued by operational inconvenience, non-steady-state measurements, and prolonged assay times. To address these limitations, we herein report an efficient dual-mode (UV–vis spectroscopy and smartphone-based RGB analysis) colorimetric assay for ACP activity quantification, leveraging a robust oxidase-like hybrid nanozyme (Pt@Cu-TCPP NS) novelly fabricated by a “surfactant-assisted encapsulation” strategy. The excellent separability of the hybrid enables batch pre-preparation of oxidized 3,3′,5,5′-tetramethylbenzidine (oxTMB)-based assay solutions with validated spectral stability, thereby facilitating a highly efficient “two-step” assay workflow with superior compatibility for both high-throughput screening and POC analysis.

Coupled with an “inhibitor-assisted” methodology for efficient termination of ACP-catalyzed enzymatic reaction, this work realizes rapid ACP activity determination in ∼4.5 min, markedly shorter than most existing assays. Under optimal conditions, both UV–vis and RGB detection modes achieve an identical linear range of 0.2–9.0 mU/mL, with limits of detection (LODs) of 0.044 mU/mL (UV–vis) and 0.16 mU/mL (RGB), respectively. Validated for practicality in spiked human serum samples, the proposed rapid and efficient dual-mode ACP activity assay shows significant potential for real-world POC applications.

开发快速有效的酸性磷酸酶（ACP）活性即时检测方法对于各种疾病的诊断和治疗监测至关重要。传统的和商业的ACP分析通常受到操作不便、非稳态测量和分析时间延长的困扰。为了解决这些限制，我们在此报告了一种高效的双模式（UV-vis光谱和基于智能手机的RGB分析）比色法，用于ACP活性定量，利用一种强大的类似氧化酶的杂交纳米酶（Pt@Cu-TCPP NS），这种纳米酶是通过“表面活性剂辅助封装”策略新制备的。该混合物具有优异的可分离性，可批量制备氧化3,3 ',5,5 ' -四甲基联苯胺（oxTMB）为基础的分析溶液，具有经过验证的光谱稳定性，从而促进了高效的“两步”分析工作流程，具有高通量筛选和POC分析的优越兼容性。结合有效终止ACP催化酶促反应的“抑制剂辅助”方法，这项工作在约4.5分钟内实现了ACP活性的快速测定，明显短于大多数现有的测定。在最佳条件下，UV-vis和RGB两种检测方式的线性范围为0.2 ~ 9.0 mU/mL，检出限（lod）分别为0.044 mU/mL （UV-vis）和0.16 mU/mL （RGB）。在加标人血清样品中验证了实用性，所提出的快速高效双模ACP活性测定显示出在现实世界中应用POC的巨大潜力。

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引用次数: 0

Development of an electrochemical sensor modified with polypyrrole/ graphitic carbon nitride composite for methotrexate detection 聚吡咯/石墨氮化碳复合材料修饰的甲氨蝶呤检测电化学传感器的研制

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-03 DOI: 10.1016/j.microc.2026.116814

Wenhao Shao , Min Zhao , Jing Zhang , Jiaqi Kong , Yujie Xiao , Chenming Liu , Mingyang Xu , Fanru Zhong , Lang Zhao , Min He , Xuehong Li , Xia Cui , Pengqi Guo

Methotrexate (MTX) requires therapeutic drug monitoring (TDM) due to its narrow therapeutic window. This study developed a polypyrrole/graphitic carbon nitride composite-modified electrochemical sensor for MTX detection. The composite synergistically enhanced catalytic activity and conductivity, enabling sensitive MTX quantification. The sensor exhibited a wide linear range (3–600 μM, R² > 0.96) and ultralow limit of detection (16.6 nM). In biological samples, it achieved 98–102 % recovery with excellent selectivity. Theoretical calculations elucidated the binding mechanism between the composite and MTX. This sensor offers a cost-effective, rapid solution for clinical MTX monitoring.

甲氨蝶呤（MTX）由于其狭窄的治疗窗口，需要进行治疗药物监测（TDM）。本研究开发了一种用于MTX检测的聚吡咯/石墨氮化碳复合改性电化学传感器。复合材料协同增强了催化活性和电导率，使MTX的定量更加敏感。该传感器具有宽线性范围（3 ~ 600 μM, R2 > 0.96）和超低检测限（16.6 nM）。在生物样品中，回收率为98 - 102%，具有良好的选择性。理论计算阐明了复合材料与MTX的结合机理。该传感器为临床MTX监测提供了一种经济高效、快速的解决方案。

引用次数: 0

Hydrophobic DES for magnetic solid-phase extraction of selected pesticides in fruit and vegetable samples followed by HPLC-UV 疏水DES用于果蔬样品中特定农药的磁固相萃取- HPLC-UV

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-03 DOI: 10.1016/j.microc.2026.116813

Zohreh Valipour , Rahman Hosseinzadeh , Milad Ghani

This study employed the synthesized magnetic nanoparticles functionalized with a hydrophobic deep eutectic solvent composed of arginine and tetraoctylammonium bromide (N₈₈₈₈Br), denoted as MNP@Arg/N₈₈₈₈Br, as an efficient sorbent for magnetic solid-phase extraction (MSPE). The developed MSPE method was applied to the extraction of the target pesticides, prometryn and fipronil, from selected fruit and vegetable samples. The extracted pesticides were subsequently analyzed using high-performance liquid chromatography with ultraviolet detection (HPLC-UV). The successful synthesis of MNP@Arg/N₈₈₈₈Br was approved using various characterization methods, such as SEM, EDX, XRD, FT-IR, TGA, and VSM. Several parameters of magnetic solid-phase extraction including the amount of magnetic sorbent, extraction time, type and volume of eluent, desorption time, and concentration of added salt were selected and optimized. Under optimal condition (pH: 6, sorbent amount: 12.5 mg, salt effect: 1.5 g, extraction time: 15 min, desorption solvent: methanol, desorption solvent volume: 40 μL, and desorption time: 2 min), good linearity range was achieved in the range of 0.5–200 μg/L for both pesticides, with correlation coefficients of 0.9965 for prometryn and 0.9954 for fipronil. The relative standard deviations (RSDs) and limits of detection (LODs) were calculated to be between 1.3 % to 4.1 % and 0.12 and 0.14 μg/L, respectively. Moreover, the limits of quantification (LOQs) and the obtained enrichment factors (EFs) were determined to be between 0.42 and 0.44 μg/L and 132–154, respectively. Additionally, the absolute recoveries ranged from 53 % to 58 %, demonstrating the effectiveness of the proposed method for analyzing pesticides in real samples.

本研究采用精氨酸和四辛基溴化铵（N8888Br）组成的疏水深共晶溶剂（表示为MNP@Arg/N8888Br）功能化合成的磁性纳米颗粒作为磁性固相萃取（MSPE）的高效吸附剂。将所建立的MSPE方法用于从选定的水果和蔬菜样品中提取目标农药prometryn和fipronil。提取的农药采用高效液相色谱-紫外检测（HPLC-UV）进行分析。通过SEM、EDX、XRD、FT-IR、TGA、VSM等表征方法对MNP@Arg/N8888Br的成功合成进行了验证。对磁性固相萃取的吸附剂用量、萃取时间、洗脱液种类和体积、解吸时间、加盐浓度等参数进行了选择和优化。在最佳条件下（pH: 6，吸附剂用量：12.5 mg，盐效：1.5 g，提取时间：15 min，解吸溶剂：甲醇，解吸溶剂体积：40 μL，解吸时间：2 min），两种农药在0.5 ~ 200 μg/L范围内呈良好的线性关系，prometryn和fipronil的相关系数分别为0.9965和0.9954。相对标准偏差（rsd）和检出限（lod）分别为1.3% ~ 4.1%和0.12 ~ 0.14 μg/L。定量限为0.42 ~ 0.44 μg/L，富集因子为132 ~ 154 μg/L。此外，绝对回收率在53% ~ 58%之间，证明了该方法对实际样品中农药分析的有效性。

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引用次数: 0

Green extraction, biosynthesis and purification of resveratrol: A bridge between environmental friendliness and industrial application 白藜芦醇的绿色提取、生物合成和纯化：环境友好与工业应用之间的桥梁

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-03 DOI: 10.1016/j.microc.2026.116807

Wen-shu Zou , Ze-rong Pei , Xiao-jie Hou , Xiao-Yang Dong , Juan-juan Yang , Min-yong Zhong , Qiu-fang Cao , Jing Peng , Hui Li , Wen-wen Deng

Resveratrol (RES) is a natural polyphenolic compound renowned for its antioxidant, anti-inflammatory, antiviral, anti-aging, neuroprotective, and longevity properties, making it promising for both food and medicinal applications. The preparation method of natural RESs has attracted a great interest for analysis its content, and acquiring functional food and pharmaceutical ingredients. However, conventional extraction methods from plants face challenges such as inefficiency and environmental contamination, prompting the emergence of eco-friendly extraction technologies. This review examines the principles, benefits, and advancements in green preparation techniques for RES sourced from plants, encompassing methods like ultrasound/microwave-assisted extraction, supercritical fluid extraction, and deep eutectic solvent extraction. Additionally, this review covers advanced biosynthesis and purification methodologies, including plant cell culture, microbial metabolic engineering, macroporous resin adsorption, and high-speed counter-current chromatography. Overall, advancements in these technologies are driving the green and sustainable preparation of RES for industrial production and the development of detection methods.

白藜芦醇（Resveratrol， RES）是一种天然多酚类化合物，以其抗氧化、抗炎、抗病毒、抗衰老、神经保护和长寿特性而闻名，使其在食品和药用方面都有很好的应用前景。天然RESs的制备方法在分析其含量、获取功能性食品和药物成分方面引起了人们的极大兴趣。然而，传统的植物提取方法面临着效率低下和环境污染等挑战，促使环保提取技术的出现。本文综述了植物源可再生能源绿色制备技术的原理、优点和进展，包括超声/微波辅助提取、超临界流体提取和深共晶溶剂提取。此外，本文还介绍了先进的生物合成和纯化方法，包括植物细胞培养、微生物代谢工程、大孔树脂吸附和高速逆流色谱法。总的来说，这些技术的进步正在推动可再生能源的绿色和可持续制备，用于工业生产和检测方法的发展。

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引用次数: 0

Hybrid nanostructured ZnO–CeO2/rGO electrochemical biosensor for enhanced non-enzymatic sweat glucose detection 纳米ZnO-CeO2 /rGO电化学生物传感器增强非酶促汗液葡萄糖检测

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-03 DOI: 10.1016/j.microc.2026.116812

Xuan Weng , Guanbo Wang , Ming Li , Hai Jiang

Many electrochemical glucose sensors rely on enzymatic catalysts such as glucose oxidase (GOx). However, such enzyme-based sensors are susceptible to environmental perturbations, which can compromise sensitivity and measurement reproducibility. Here, we report a flexible, enzyme-free sweat-glucose sensor for wearable diagnostic systems by co-depositing hydrothermally prepared zinc oxide–cerium oxide/reduced graphene oxide (ZnO–CeO₂/rGO) nanocomposites onto laser-scribed graphene electrodes (LSGE) patterned on polyimide (PI) films. Scanning electron microscope (SEM), X-ray diffraction (XRD), UV–vis spectroscopy, and Raman spectroscopy verified the formation and structural integrity of the hybrid nanocomposite. The electrochemical characterization, cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), indicated accelerated charge transfer after modification. Under optimized conditions, the biosensor quantified sweat glucose over 0.01–3.0 mM with a sensitivity of 32.5 μA·mM⁻¹ cm⁻² and a low detection limit of 14 μM. Proof-of-concept measurements on volunteers before and after meals further supported its feasibility for wearable and personalized healthcare diagnostics.

许多电化学葡萄糖传感器依赖于酶催化，如葡萄糖氧化酶（GOx）。然而，这种基于酶的传感器容易受到环境扰动的影响，这可能会损害灵敏度和测量的可重复性。在这里，我们报告了一种柔性的无酶汗液葡萄糖传感器，用于可穿戴诊断系统，通过将水热制备的氧化锌-氧化铈/还原氧化石墨烯（ZnO-CeO2 /rGO）纳米复合材料共沉积在聚酰亚胺（PI）薄膜上的激光刻写石墨烯电极（LSGE）上。扫描电镜（SEM）、x射线衍射（XRD）、紫外可见光谱（UV-vis）和拉曼光谱（Raman）验证了混合纳米复合材料的形成和结构完整性。电化学表征，循环伏安法（CV）和电化学阻抗谱（EIS）表明修饰后的电荷转移加速。在优化条件下，该传感器可定量测定0.01 ~ 3.0 mM范围内的汗液葡萄糖，灵敏度为32.5 μA·mM−1 cm−2，低检出限为14 μM。在志愿者餐前和餐后进行的概念验证测量进一步支持了其可穿戴和个性化医疗保健诊断的可行性。

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引用次数: 0

Monitoring tetracycline levels using the tetracycline monooxygenase enzyme and investigating the effects of sucrose and glycerol on enzymatic function 利用四环素单加氧酶监测四环素水平，并研究蔗糖和甘油对酶功能的影响

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-03 DOI: 10.1016/j.microc.2026.116809

Sadegh Zomorodimanesh , Seyed Hadi Razavi , Saman Hosseinkhani , Zahra Emam-Djomeh , Batool Hosseinkhani

Rapid detection of tetracycline antibiotics is critical for mitigating risks to human health and ensuring food safety. While various detection methods exist, enzymatic approaches offer high specificity, yet they are often limited by the inherent instability of enzymes in fluctuating environmental conditions. This study focuses on enhancing the stability and catalytic efficiency of TetX2 monooxygenase, an enzyme that selectively hydroxylates tetracycline dependent on NADPH oxidation. To address the challenge of enzymatic instability, we investigated the effects of glycerol (6 %) and sucrose (0.2 M) on the structural and functional properties of TetX2. Spectroscopic and dynamic light scattering (DLS) analyses revealed that these stabilizing agents induced favorable microenvironmental changes, preventing aggregation and thermal denaturation. Kinetic studies demonstrated that the presence of glycerol and sucrose increased both the Michaelis constant (Km) and maximum velocity (Vmax), suggesting a trade-off between substrate rigidity and catalytic turnover favored by the stabilizers. Although the method yielded a detection limit of approximately 12 μM suitable for initial screening of high-concentration residues the primary achievement was the significant enhancement in enzyme thermal stability and shelf-life. The proposed stabilization strategy offers a robust foundation for developing durable enzymatic sensors for tetracycline monitoring in resource-limited settings (Graphical abstract).

快速检测四环素类抗生素对于减轻人类健康风险和确保食品安全至关重要。虽然存在各种检测方法，酶法具有高特异性，但它们往往受到酶在波动环境条件下固有的不稳定性的限制。本研究的重点是提高TetX2单加氧酶的稳定性和催化效率，TetX2单加氧酶是一种依赖于NADPH氧化选择性羟化四环素的酶。为了解决酶稳定性的挑战，我们研究了甘油（6%）和蔗糖（0.2 M）对TetX2结构和功能特性的影响。光谱和动态光散射（DLS）分析表明，这些稳定剂诱导了有利的微环境变化，防止了聚集和热变性。动力学研究表明，甘油和蔗糖的存在增加了米切里斯常数（Km）和最大速度（Vmax），表明稳定剂有利于底物刚性和催化周转之间的权衡。虽然该方法的检出限约为12 μM，适用于高浓度残留物的初始筛选，但主要成果是酶的热稳定性和保质期显著提高。所提出的稳定策略为在资源有限的环境中开发用于四环素监测的耐用酶传感器提供了坚实的基础（图形摘要）。

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引用次数: 0

Artificial intelligence-assisted NIR spectroscopy for identification of halal mislabeling in commercial meatball products 人工智能辅助近红外光谱法识别商业肉丸产品中清真假标

IF 4.9 2区化学 Q1 CHEMISTRY, ANALYTICAL

Microchemical Journal

Pub Date : 2026-01-03 DOI: 10.1016/j.microc.2026.116816

Agustami Sitorus , Nunik Destria Arianti

Halal product demand is growing globally. Therefore, this study investigates a rapid and non-destructive method for detecting halal mislabeling in commercial meatball products. A handheld micro-near-infrared (NIR) spectrometer (885–1679 nm) combined with artificial intelligence (AI) was used to analyze 1000 meatball samples comprising halal and non-halal products. The NIR analysis provided spectral data, which included absorbance values at specific wavelengths, enabling the identification of characteristic patterns associated with halal and non-halal products. Chemometric techniques, including multivariate analysis (principal component analysis (PCA), partial least squares discriminant analysis (PLSDA), linear discriminant analysis (LDA)), machine learning (support vector machine (SVM), k-nearest neighbor (KNN), artificial neural network (ANN)), and deep learning (convolutional neural network (CNN), AlexNET, ResNET) were applied to classify the samples. Full-wavelength, dimensional reduction features and important wavelengths were evaluated. The best models achieved up to 100 % accuracy in distinguishing halal from non-halal products. The study demonstrates the feasibility of AI-assisted micro-NIR as a fast, cost-effective, and reliable tool for halal authentication. This method provides a practical alternative for stakeholders in the supply chain to ensure compliance with halal standards.

清真产品的需求在全球范围内不断增长。因此，本研究探讨了一种快速、非破坏性的方法来检测商业肉丸产品中的清真标签错误。使用手持式微近红外光谱仪（885-1679 nm）结合人工智能（AI）分析了1000个包含清真和非清真产品的肉丸样品。近红外分析提供了光谱数据，其中包括特定波长的吸光度值，从而能够识别与清真和非清真产品相关的特征模式。采用多变量分析(主成分分析（PCA）、偏最小二乘判别分析（PLSDA）、线性判别分析（LDA）、机器学习（支持向量机（SVM）、k近邻（KNN）、人工神经网络（ANN））和深度学习（卷积神经网络（CNN）、AlexNET、ResNET）等化学计量学技术对样本进行分类。评估了全波长、降维特征和重要波长。最好的模型在区分清真和非清真产品方面达到了100%的准确性。该研究证明了人工智能辅助微近红外作为一种快速、经济、可靠的清真认证工具的可行性。这种方法为供应链中的利益相关者提供了一种实用的替代方案，以确保符合清真标准。

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引用次数: 0