IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i5p825-d210306.html
   My bibliography  Save this article

Detection of Human Plasma Glucose Using a Self-Powered Glucose Biosensor

Author

Listed:
  • Gymama Slaughter

    (Frank Reidy Research Center for Bioelectrics, Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA 23508, USA)

  • Tanmay Kulkarni

    (Department of Biochemistrry and Molecular Biology, Mayo Clinic, Jacksonville, FL 32224, USA)

Abstract

This work presents the characterization of a self-powered glucose biosensor using individual sequential assays of human plasma glucose obtained from diabetic patients. The self-powered glucose biosensor is exploited to optimize the assay parameters for sensing plasma glucose levels. In particular, the biofuel cell component of the system at pH 7.4, 37 °C generates a power density directly proportional to plasma glucose and exhibited a maximum power density of 0.462 mW·cm −2 at a cell voltage of 0.213 V in 5 mM plasma glucose. Plasma glucose is further sensed by monitoring the charge/discharge frequency (Hz) of the integrated capacitor functioning as the transducer. With this method, the plasma glucose is quantitatively detected in 100 microliters of human plasma with unprecedented sensitivity, as high as 104.51 ± 0.7 Hz·mM −1 ·cm −2 and a detection limit of 2.31 ± 0.3 mM. The results suggest the possibility to sense human plasma glucose at clinically relevant concentrations without the use of an external power source.

Suggested Citation

  • Gymama Slaughter & Tanmay Kulkarni, 2019. "Detection of Human Plasma Glucose Using a Self-Powered Glucose Biosensor," Energies, MDPI, vol. 12(5), pages 1-10, March.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:825-:d:210306
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/5/825/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/5/825/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Cheong Hoon Kwon & Sung-Ho Lee & Young-Bong Choi & Jae Ah Lee & Shi Hyeong Kim & Hyug-Han Kim & Geoffrey M. Spinks & Gordon G. Wallace & Márcio D. Lima & Mikhail E. Kozlov & Ray H. Baughman & Seon Jeo, 2014. "High-power biofuel cell textiles from woven biscrolled carbon nanotube yarns," Nature Communications, Nature, vol. 5(1), pages 1-7, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:5:p:825-:d:210306. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.