The concentration of C-reactive protein (CRP), a classic acute phase plasma protein, increases rapidly in response to tissue infection or inflammation, especially in cases of cardiovascular disease and stroke. Thus, highly sensitive monitoring of the CRP concentration plays a pivotal role in detecting these diseases. Many researchers have studied methods for the detection of CRP concentrations such as optical, mechanical, and electrochemical techniques inside microfluidic devices.While significant progress has been made towards improving the resolution and sensitivity of detection, only a few studies have systematically analyzed the CRP concentration using both numerical and experimental approaches. Specifically, systematic analyses of the electrochemical detection of high-sensitivity CRP (hsCRP) using an enzyme-linked immunosorbant assay (ELISA) inside a microfluidic device have never been conducted. In this paper, we systematically analyzed the electrochemical detection of CRP modified through the attachment of an alkaline phosphatase (ALPlabeled CRP) using ELISA inside a chip. For this analysis, we developed a model based on antigen-antibody binding kinetics theory for the numerical quantification of the CRP concentration. We also experimentally measured the current value corresponding to the ALP-labeled CRP concentration inside the microfluidic chip. The measured value closely matched the calculated value obtained by numerical simulation using the developed model. Through this comparison, we validated the numerical simulation methods, and the calculated and measured values. Lastly, we examined the effects of various microfluidic parameters on electrochemical detection of the ALP-labeled CRP concentration using numerical simulations. The results of these simulations provide insight into the microfluidic electrochemical reactions used for protein detection. Furthermore, the results described in this study should be useful for the design and optimization of electrochemical immunoassay chips for the detection of target proteins.
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Acknowledgements This work was supported in part by the Ministry of Knowledge Economy (Grant No. MKE 70004324-2009-02) and by the Ministry of Education and Science (Grant Nos. NRF-2010-0026223, NRF-2010-0027238, NRF-2010-0013619, and NRF-2009-0068841). Prof. Nam conducted this research during a sabbatical year (2009) granted by Kwangwoon University. We would like to thank In Seok Jung and Kyujeong Song at i-SENS for valuable discussions and help with the experiments.
All Science Journal Classification (ASJC) codes
- Biomedical Engineering
- Molecular Biology