Liu Chao, Liu Ning, Xia Qi, Cao Yi, Huang Qing
CAS Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Science Island Branch of Graduate School, University of Science and Technology of China, Hefei 230026, China.
CAS Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China; Anhui Agriculture University, Hefei 230026, China.
Food Chem. 2025 Oct 30;490:145102. doi: 10.1016/j.foodchem.2025.145102. Epub 2025 Jun 10.
Distinguishing between natural antioxidant phenolic compounds or contaminants in food matrices is crucial for ensuring food quality and safety. In this context, nanozyme-based sensors have emerged as promising tools, demonstrating significant potential for effective detection and discrimination. However, the construction of multifunctional, low-cost nanozyme-biosensors with high catalytic activity remains a key challenge. This study presents a dielectric barrier discharge (DBD) plasma approach to synthesize amorphous CoO (a-CoO) laccase-like nanozyme using Co-MOF. The a-CoO exhibited laccase-like activity through Co/Co redox pairs and CoO active sites, mimicking natural laccase's coordination environment. Leveraging its catalytic versatility, stability, and pH-dependent substrate affinity, a new type of sensor array was developed for sensitive (0.1-12 μM) discrimination of various phenolic compounds. Integration with smartphone imaging and machine learning enabled real-sample analysis. As such, this work offers a scalable low-temperature plasma (LTP)-based nanozyme fabrication strategy and expands applications in biosensing and food safety inspection.
区分食品基质中的天然抗氧化酚类化合物或污染物对于确保食品质量和安全至关重要。在这种背景下，基于纳米酶的传感器已成为有前途的工具，在有效检测和区分方面显示出巨大潜力。然而，构建具有高催化活性的多功能、低成本纳米酶生物传感器仍然是一个关键挑战。本研究提出了一种介质阻挡放电（DBD）等离子体方法，以使用钴基金属有机框架（Co-MOF）合成非晶态CoO（a-CoO）类漆酶纳米酶。a-CoO通过Co/Co氧化还原对和CoO活性位点表现出类漆酶活性，模拟了天然漆酶的配位环境。利用其催化多功能性、稳定性和pH依赖性底物亲和力，开发了一种新型传感器阵列，用于灵敏（0.1-12 μM）区分各种酚类化合物。与智能手机成像和机器学习相结合实现了实际样品分析。因此，这项工作提供了一种基于可扩展低温等离子体（LTP）的纳米酶制造策略，并扩展了其在生物传感和食品安全检测中的应用。
