A magneto-microfluidic platform for fluorescence immunosensing using quantum dot nanoparticles. (26th September 2019)

• Record Type: Journal Article
• Authors: Tsai, H Y; Wu, H H; Chou, B C; Li, C S; Gau, B Z; Lin, Z Y; Fuh, C Bor
• Is Part Of: Nanotechnology. Volume 30:Number 50(2019)
• Publication Date: 2019-09-26
• Subjects: functional nanoparticles -- online detection -- protein detection -- carcinoembryonic antigen (CEA) -- α-fetoprotein (AFP) -- microfluidic channel; Nanotechnology -- Periodicals; Nanotechnology -- Periodicals; Nanotechnology; Publications périodiques; Nanotechnologies; Periodicals; 620.5
• DOI: 10.1088/1361-6528/ab423d
• Languages: English
• ISSNs: 0957-4484

Abstract

Abstract: This study reports the online fluorescent detection of carcinoembryonic antigen (CEA) and α-fetoprotein (AFP) biomarker proteins in microfluidic channels using functional nanoparticles. Functional magnetic nanoparticles labeled with two antibodies were predeposited on separated microfluidic channels. Antigens were passed through each microfluidic channel to react with the respective antibodies. Two types of fluorescent nanoparticles labeled with antibodies were then used to detect and confirm antigens in the immunocomplex. Results indicate that online fluorescent detection of proteins can provide advantages for real-time monitoring and diagnostic applications. The running time was less than 20 min for each trial. The detection limits of CEA and AFP were found to be 0.6 and 0.2 pg ml −1 . These detection limits are lower than those of ELISA. The linear ranges of CEA and AFP detection were from 1.8 pg ml −1 to 1.8 ng ml −1 and from 0.68 pg ml −1 to 0.68 ng ml −1 for two deposition zones in a magnetic sandwich immunoassay. The linear ranges of this method are wider than those of ELISA and those of most other methods. The measurements of CEA and AFP in serum samples from this method differed from ELISA results by 11% and 9.4%, respectively. The detection limit of online detection has achieved the same range as those of previous offline detection. This method has a good potential for automation and multichannel analysis to increase the throughput with some modifications in the future. The proposed method can provide simple, fast, and sensitive online detection for biomarkers.