Bibliographic Details
| Title: |
Encoded Microspheres in Multiplex Detection of Mycotoxins and Other Analytes. |
| Authors: |
Yu, Wenhan, Zhong, Haili, Fu, Xianshu, Zhang, Lingling, Zhang, Mingzhou, Yu, Xiaoping, Ye, Zihong |
| Source: |
Foods; Jan2026, Vol. 15 Issue 2, p247, 30p |
| Subject Terms: |
MYCOTOXINS, MICROSPHERES, INFORMATION technology, HAZARDOUS substances, MAGNETIC separation, DETECTION algorithms, SIGNAL detection, SIGNAL processing |
| Abstract: |
This paper provides a systematic review of the progress in encoded microsphere suspension array technology and its application in the multiplex detection of mycotoxins. Mycotoxins are diverse and frequently coexist in food matrices, leading to synergistic toxic effects. This poses significant challenges to existing risk assessment systems. Current multiplex detection methods still face technical bottlenecks such as target loss, matrix interference, and reliance on large-scale instruments. Suspension array technology based on encoded microspheres, combined with efficient signal amplification strategies, offers an ideal platform for achieving highly sensitive and high-throughput analysis of mycotoxins. This paper systematically reviews the core aspects of this technology, including encoding strategies such as physical, optical, and multi-dimensional approaches, along with new encoding materials like aggregation-induced emission materials and fluorescent proteins. It further covers matrix materials and preparation methods with an emphasis on green, biocompatible options and integrated fabrication techniques, as well as signal amplification mechanisms based on nucleic acid amplification, enzyme catalysis, and nanomaterials. The integration of magnetic separation techniques and the combination with portable, smartphone-based platforms for intelligent on-site detection are also highlighted. Finally, this review outlines future development trends such as the incorporation of artificial intelligence, 3D printing, and smart algorithms, aiming to provide theoretical references and technical support for research and applications in related fields. [ABSTRACT FROM AUTHOR] |
|
Copyright of Foods is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Complementary Index |