Academic Journal
The GA-optimized MSPE measurement for high-performance electrochemical detection of bacterial pathogens in complex matrices.
| Τίτλος: | The GA-optimized MSPE measurement for high-performance electrochemical detection of bacterial pathogens in complex matrices. |
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| Συγγραφείς: | Zhang X; School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China., Zeng Q; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China., Liu D; The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou 310018, China., Chen S; School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China., Dai P; School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China., Xu Y; School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China; Provincial Key Laboratory of Soft Matter & Biomedical Materials, Wenzhou Institute of the University of Chinese Academy of Sciences (WIUCAS), Wenzhou 325000, China. Electronic address: xuyingxy@hdu.edu.cn., Yu H; School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, China. Electronic address: hui.yu@sjtu.edu.cn. |
| Πηγή: | Food chemistry [Food Chem] 2026 Aug 30; Vol. 521, pp. 149904. Date of Electronic Publication: 2026 Jun 02. |
| Τύπος έκδοσης: | Journal Article; Evaluation Study |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Applied Science Publishers Country of Publication: England NLM ID: 7702639 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-7072 (Electronic) Linking ISSN: 03088146 NLM ISO Abbreviation: Food Chem Subsets: MEDLINE |
| Imprint Name(s): | Publication: Barking : Elsevier Applied Science Publishers Original Publication: Barking, Eng., Applied Science Publishers. |
| Ιατρικοί όροι (MeSH): | Bacteria*/isolation & purification , Bacteria*/genetics , Bacteria*/chemistry , Bacteria*/classification , Electrochemical Techniques*/methods , Solid Phase Extraction*/methods , Solid Phase Extraction*/instrumentation , Food Contamination*/analysis , Food Microbiology*/methods, Genetic Algorithms |
| Περίληψη: | To address the limited generalizability and matrix interference in foodborne bacterial detection within complex food matrices, a high-performance electrochemical detection platform enabled by genetic algorithm (GA)-optimized magnetic solid-phase extraction (MSPE) was developed. Magnetic electrochemiluminescent probes were functionalized with bacteria-specific aptamers to achieve target recognition and magnetic separation. Using orthogonal experimental design combined with an extreme gradient boosting (XGBoost) model and GA global optimization, the nonlinear relationships between key MSPE parameters and charge transfer resistance were accurately mapped, and the optimal extraction conditions were intelligently determined. The optimized system exhibited strong binding efficiency toward target bacteria and predictive performance. By integrating the structural analysis capability of electrochemical impedance spectroscopy with the rapid and ultrasensitive features of electrochemiluminescence, the proposed method realized reliable cross-species and cross-matrix transferable detection based on the model transferability. This intelligent approach provides an effective solution for accurate and robust detection of foodborne pathogens in complex food matrices. (Copyright © 2026 Elsevier Ltd. All rights reserved.) |
| Competing Interests: | Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. |
| Contributed Indexing: | Keywords: Bacteria detection; Electrochemical impedance spectroscopy; Electrochemiluminescence; Genetic algorithm optimization; Magnetic solid-phase extraction |
| Entry Date(s): | Date Created: 20260604 Date Completed: 20260703 Latest Revision: 20260703 |
| Update Code: | 20260703 |
| DOI: | 10.1016/j.foodchem.2026.149904 |
| PMID: | 42242051 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1873-7072 |
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| DOI: | 10.1016/j.foodchem.2026.149904 |