Magnetoelastic Immunosensor via Antibody Immobilization for the Specific Detection of Lysozymes.

lysozyme magnetoelastic immunosensor resonance frequency shift specific detection surface functionalization

Journal

ACS sensors
ISSN: 2379-3694
Titre abrégé: ACS Sens
Pays: United States
ID NLM: 101669031

Informations de publication

Date de publication:
26 11 2021
Historique:
pubmed: 23 10 2021
medline: 15 12 2021
entrez: 22 10 2021
Statut: ppublish

Résumé

Lysozymes in human urine have crucial clinical significance as an indicator of renal tubular and glomerular diseases. Most lysozyme detection methods rely on the enzyme-linked immunosorbent assay (ELISA), which is usually a tedious procedure. Meanwhile, aptamer sensors and fluorescence-based techniques for lysozyme detection have emerged in recent studies. However, these methods are time-consuming and highly complex in operation, and some even require exorbitant reagents and instruments, which restricts real-time clinical monitoring as diagnostic approaches. Therefore, a rapid and low-cost lysozyme detection method with facile preparation is still in demand for modern precision medicine. Herein, we propose a magnetoelastic (ME) immunosensor for lysozyme detection by detecting changes in resonance frequency under a magnetostrictive effect. The detection system is composed of a magnetoelastic chip with an immobilized lysozyme antibody, a solenoid coil, and a vector network analyzer. Since the ME sensor is ultrasensitive to mass change, the frequency offset caused by mass change can be utilized to detect the content of lysozyme. The immunosensor is evaluated to possess superior sensitivity of 138 Hz/μg mL

Identifiants

pubmed: 34677933
doi: 10.1021/acssensors.1c00802
doi:

Substances chimiques

Antibodies, Immobilized 0
Muramidase EC 3.2.1.17

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

3933-3939

Auteurs

Xinru Huang (X)

MicroNano System Research Center, College of Information & Computer Engineering, Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and Shanxi Province, Taiyuan University of Technology, Taiyuan 030024, China.

Shengbo Sang (S)

MicroNano System Research Center, College of Information & Computer Engineering, Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and Shanxi Province, Taiyuan University of Technology, Taiyuan 030024, China.

Zhongyun Yuan (Z)

MicroNano System Research Center, College of Information & Computer Engineering, Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and Shanxi Province, Taiyuan University of Technology, Taiyuan 030024, China.

Qianqian Duan (Q)

MicroNano System Research Center, College of Information & Computer Engineering, Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and Shanxi Province, Taiyuan University of Technology, Taiyuan 030024, China.

Xing Guo (X)

MicroNano System Research Center, College of Information & Computer Engineering, Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and Shanxi Province, Taiyuan University of Technology, Taiyuan 030024, China.

Hongpeng Zhang (H)

Department of Vascular Surgery, Chinese PLA General Hospital, Beijing 100853, China.

Chun Zhao (C)

College of Information and Communication Engineering, Sungkyunkwan University, Suwon 440-746, Korea.

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Classifications MeSH