An electrochemical biosensor based on gold microspheres and nanoporous gold for real-time detection of superoxide anion in skeletal muscle tissue

Ramin Banan Sadeghian, Serge Ostrovidov, Sahar Salehi, Jiuhui Han, Mingwei Chen, Ali Khademhosseini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Superoxide anion (SOA) as a member of reactive oxygen species (ROS) group is involved in various physiological and pathological states. For instance, generation of SOA is known to increase with skeletal muscle contractile activity and fatigue. It is therefore important to selectively detect and accurately quantify the release of SOA within both physiological and pathological levels. We report fabrication and characterization of a cytochrome-c functionalized SOA biosensor built on commercially available miniaturized screen-printed electrodes made of gold microspheres. The device was first tested and calibrated in a xanthine/xanthine oxidase (XOD) system and then employed to detect SOA release from C2C12 myoblasts and myotubes upon stimulation with PMA.

Original languageEnglish
Title of host publication2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7962-7965
Number of pages4
ISBN (Electronic)9781424492718
DOIs
Publication statusPublished - 2015 Nov 4
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 - Milan, Italy
Duration: 2015 Aug 252015 Aug 29

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2015-November
ISSN (Print)1557-170X

Other

Other37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015
CountryItaly
CityMilan
Period15/8/2515/8/29

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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