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RCA-Based Biosensor for Electrical and Colorimetric Detection of Pathogen DNA

Overview of attention for article published in Discover Nano, May 2016
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Title
RCA-Based Biosensor for Electrical and Colorimetric Detection of Pathogen DNA
Published in
Discover Nano, May 2016
DOI 10.1186/s11671-016-1440-7
Pubmed ID
Authors

Jaepil Jeong, Hyejin Kim, Dong Jun Lee, Byung Jun Jung, Jong Bum Lee

Abstract

For the diagnosis and prevention of diseases, a range of strategies for the detection of pathogens have been developed. In this study, we synthesized the rolling circle amplification (RCA)-based biosensor that enables detection of pathogen DNA in two analytical modes. Only in the presence of the target DNA, the template DNA can be continuously polymerized by simply carrying out RCA, which gives rise to a change of surface structure of Au electrodes and the gap between the electrodes. Electrical signal was generated after introducing hydrogen tetrachloroaurate (HAuCl4) to the DNA-coated biosensor for the improvement of the conductivity of DNA, which indicates that the presence of the pathogen DNA can be detected in an electrical approach. Furthermore, the existence of the target DNA was readily detected by the naked eyes through change in colors of the electrodes from bright yellow to orange-red after RCA reaction. The RCA-based biosensor offers a new platform for monitoring of pathogenic DNA with two different detection modes in one system.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 7%
Unknown 14 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 20%
Professor > Associate Professor 2 13%
Librarian 1 7%
Student > Ph. D. Student 1 7%
Other 1 7%
Other 2 13%
Unknown 5 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 2 13%
Engineering 2 13%
Agricultural and Biological Sciences 2 13%
Business, Management and Accounting 1 7%
Linguistics 1 7%
Other 2 13%
Unknown 5 33%