↓ Skip to main content

PLOS

Ultrasensitive Electrochemical Immunoassay for Avian Influenza Subtype H5 Using Nanocomposite

Overview of attention for article published in PLOS ONE, April 2014
Altmetric Badge

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
49 Mendeley
Title
Ultrasensitive Electrochemical Immunoassay for Avian Influenza Subtype H5 Using Nanocomposite
Published in
PLOS ONE, April 2014
DOI 10.1371/journal.pone.0094685
Pubmed ID
Authors

Zhixun Xie, Jiaoling Huang, Sisi Luo, Zhiqin Xie, Liji Xie, Jiabo Liu, Yaoshan Pang, Xianwen Deng, Qing Fan

Abstract

We report a novel electrochemical immunosensor that can sensitively detect avian influenza virus H5 subtype (AIV H5) captured by graphene oxide-H5-polychonal antibodies-bovine serum albumin (GO-PAb-BSA) nanocomposite. The graphene oxide (GO) carried H5-polychonal antibody (PAb) were used as signal amplification materials. Upon signal amplification, the immunosensor showed a 256-fold increase in detection sensitivity compared to the immunosensor without GO-PAb-BSA. We designed a PAb labeling GO strategy and signal amplification procedure that allow ultrasensitive and selective detection of AIV H5. The established method responded to 2(-15) HA unit/50 µL H5, with a linear calibration range from 2(-15) to 2(-8) HA unit/50 µL. In summary, we demonstrated that the immunosenser has a high specificity and sensitivity for AIV H5, and the established assay could be potentially applied in the rapid detection of other pathogenic microorganisms.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 20%
Researcher 9 18%
Student > Master 7 14%
Student > Bachelor 5 10%
Professor > Associate Professor 3 6%
Other 6 12%
Unknown 9 18%
Readers by discipline Count As %
Chemistry 9 18%
Biochemistry, Genetics and Molecular Biology 6 12%
Materials Science 6 12%
Agricultural and Biological Sciences 5 10%
Engineering 4 8%
Other 8 16%
Unknown 11 22%