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Updated: Jul 8, 2026

Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres
Published on: October 23, 2011
Machine-learning-driven optical immunosensor based on microspheres-encoded signal transduction for the rapid and
Cuiyun Zhou1, Chenxi Huang2, Hongyu Zhang3
1College of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China.
Abstract:
Antibiotic residues are the most common contaminants in milk and other related dairy products. Simultaneous, convenient, and stable detection of antibiotic residues in foods is vital to secure public health. Herein, we proposed an optical immunosensor with easily-functionalized polystyrene nanoparticles differing in size and quantity, and bearing multiplex signal probes for the simultaneous detection of multiple antibiotics through a simple one-step signal conversion reaction. After the integration of the machine-learning-based transcoding analysis, this sensor is suitable for multiplexed detection of antibiotics in a broad linear range from pg/mL to ng/mL within 30 min, with an overall accuracy of >99 %. Compared to the conventional standard chemiluminescence immunoassays, this immunosensor is suitable for the accurate quantification of multiple antibiotics in milk, with improved accuracy, reduced costs, and simplified procedure. This ensures its applications in food safety monitoring when simultaneous detection of multiple hazardous substances in food matrices is needed.
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