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利用石英晶体微天平检测软骨寡聚基质蛋白。

Detection of cartilage oligomeric matrix protein using a quartz crystal microbalance.

机构信息

Department of Chemical Engineering, I-Shou University, and Department of Orthopaedic Surgery, E-Da Hospital, No. 1, Sec. 1, Syuecheng Rd., Dashu Township, Kaohsiung County 840, Taiwan.

出版信息

Sensors (Basel). 2010;10(12):11633-43. doi: 10.3390/s101211633. Epub 2010 Dec 20.

DOI:10.3390/s101211633
PMID:22163547
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3231063/
Abstract

Current methods for diagnosing early stage osteoarthritis (OA) based on the magnetic resonance imaging and enzyme-linked immunosorbent assay methods are specific, but require specialized laboratory facilities and highly trained personal to obtain a definitive result. In this work, a user friendly and non-invasive quartz crystal microbalance (QCM) immunosensor method has been developed to detect Cartilage Oligomeric Matrix Protein (COMP) for early stage OA diagnosis. This QCM immunosensor was fabricated to immobilize COMP antibodies utilizing the self-assembled monolayer technique. The surface properties of the immunosensor were characterized by its FTIR and electrochemical impedance spectra (EIS). The feasibility study was based on urine samples obtained from 41 volunteers. Experiments were carried out in a flow system and the reproducibility of the electrodes was evaluated by the impedance measured by EIS. Its potential dynamically monitored the immunoreaction processes and could increase the efficiency and sensitivity of COMP detection in laboratory-cultured preparations and clinical samples. The frequency responses of the QCM immunosensor changed from 6 kHz when testing 50 ng/mL COMP concentration. The linear regression equation of frequency shift and COMP concentration was determined as: y=0.0872 x+1.2138 (R2=0.9957). The COMP in urine was also determined by both QCM and EIS for comparison. A highly sensitive, user friendly and cost effective analytical method for the early stage OA diagnosis has thus been successfully developed.

摘要

目前基于磁共振成像和酶联免疫吸附测定方法的早期骨关节炎 (OA) 诊断方法具有特异性,但需要专门的实验室设备和经过高度培训的人员才能得出明确的结果。在这项工作中,开发了一种用户友好且非侵入性的石英晶体微天平 (QCM) 免疫传感器方法,用于检测早期 OA 诊断用软骨寡聚基质蛋白 (COMP)。该 QCM 免疫传感器通过自组装单层技术固定 COMP 抗体。通过傅里叶变换红外光谱 (FTIR) 和电化学阻抗谱 (EIS) 对免疫传感器的表面特性进行了表征。可行性研究基于从 41 名志愿者获得的尿液样本。实验在流动系统中进行,并通过 EIS 测量的阻抗评估电极的重现性。其潜力动态监测免疫反应过程,可提高实验室培养制剂和临床样本中 COMP 检测的效率和灵敏度。当测试 50ng/mL COMP 浓度时,QCM 免疫传感器的频率响应从 6kHz 变化。频率位移和 COMP 浓度的线性回归方程确定为:y=0.0872x+1.2138(R2=0.9957)。还通过 QCM 和 EIS 同时测定尿液中的 COMP 以进行比较。因此,成功开发了一种用于早期 OA 诊断的高灵敏度、用户友好且具有成本效益的分析方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/e7453039026d/sensors-10-11633-v2f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/56028111f04d/sensors-10-11633-v2f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/e5acc1e6589c/sensors-10-11633-v2f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/a0095040d966/sensors-10-11633-v2f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/d07142383054/sensors-10-11633-v2f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/425173918f56/sensors-10-11633-v2f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/090aed5c905b/sensors-10-11633-v2f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/60fa756d16cc/sensors-10-11633-v2f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/e7453039026d/sensors-10-11633-v2f8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/56028111f04d/sensors-10-11633-v2f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/e5acc1e6589c/sensors-10-11633-v2f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/a0095040d966/sensors-10-11633-v2f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/d07142383054/sensors-10-11633-v2f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/425173918f56/sensors-10-11633-v2f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/090aed5c905b/sensors-10-11633-v2f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/60fa756d16cc/sensors-10-11633-v2f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0224/3231063/e7453039026d/sensors-10-11633-v2f8.jpg

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