期刊
COORDINATION CHEMISTRY REVIEWS
卷 457, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.ccr.2022.214416
关键词
Microcystins; Fluorescence; Cross-disciplinary; Detection
资金
- Special project for social development of Yunnan Province [202103AC100001]
- NSFC [51973082, 51503077]
- Yunnan Provincial Department of Science and Technology [202001BB050078]
- Strategic Priority Research Program of the Chinese Academy of Sciences [XDB31000000]
- high-level talents program of Yunnan University [20198006, 20200105]
This review highlights the development and application of fluorescence-based detection methods for microcystins. Through interdisciplinary research, the advantages and disadvantages of different detection methods are discussed and compared with traditional detection methods. The review also focuses on the advantages of MC-based novel detection technologies with fluorescence participation and discusses the challenges in the field of bioimaging.
Among cyanotoxins, microcystins (MCs) are the most toxic substances widely distributed in lakes and related closely to human life. A large number of detection methods have been developed to avoid the harm of MCs. Fluorescence detection is a powerful approach for noninvasive and real-time detecting biomolecules in the field of ecosystem. It improves sensitivity and selectivity in detection and imaging. This review initially highlights the detection methods of MCs via fluorescence technology, which is operated on the basis of cross-disciplinary fields, including biochemistry, photoelectric, nanotechnology, and biotechnology in the past two decades. It not only explains the basic principle of MC fluorescence detection but also compares and analyzes the advantages and disadvantages in different detection methods. This review also comprehensively analyzes the advantages of MC-based novel detection technologies under the participation of fluorescence technologies and compares between fluorescence participation and traditional detection methods. This review focuses on the comprehensive application in crossdisciplinary fields and further addresses the challenges of MC-based detection in the bioimaging field.(c) 2022 Elsevier B.V. All rights reserved.
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