Literature DB >> 28627257

Toward the Development of a Glucose Dehydrogenase-Based Saliva Glucose Sensor Without the Need for Sample Preparation.

Chi Lin1, Breanna Pratt1, Mackenzie Honikel1, Alaina Jenish1, Bhavna Ramesh1, Amnah Alkhan1, Jeffrey T La Belle1,2.   

Abstract

BACKGROUND: Strict glycemic control is known to be a vital key in the management of diabetes mellitus (DM). However, traditional methods face limitations in their efficacy due to the pain and invasiveness of needle pricking which often discourages DM patients from performing the required number of tests per day. Saliva glucose (SG) sensing has long been considered a noninvasive alternative to blood glucose monitoring for diabetes management, however the sample preparation and sensor detection limit have been deemed as challenges to overcome. Herein, we describe a preliminary clinical validation of a disposable SG sensor without any requirement for sample preparation.
METHODS: The sensor utilizes glucose dehydrogenase flavine-adenine dinucleotide (GDH-FAD) in conjunction with disposable screen printed electrodes to measure glucose levels in saliva collected directly from 9 healthy subjects. Cyclic voltammetry and amperometric-time (Amp-it) assays were used to develop calibration curves and test subjects. Sensor calibration was performed using simulated saliva at 6.5 pH and 37ºC.
RESULTS: The lower limit of detection was determined to be 0.11 mg/dL. A lag time of 15 minutes with a positive correlation between SG and BG levels was found, which agrees with literature results. The detected SG ranges from 2.38 to 3.40 mg/dL over a BG range of 90 to 143 mg/dL.
CONCLUSION: This is the first reported use of measuring SG with GDH-FAD without prior sample preparation. Upon optimization, the sensor has the potential to serve as a supplement to blood glucose monitoring.

Entities:  

Keywords:  biosensor; diabetes mellitus; glucose dehydrogenase flavin-adenine dinucleotide; glucose monitoring; saliva glucose monitoring

Mesh:

Substances:

Year:  2017        PMID: 28627257      PMCID: PMC5761970          DOI: 10.1177/1932296817712526

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  40 in total

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Authors:  L N Forbat; R E Collins; G K Maskell; P H Sönksen
Journal:  J R Soc Med       Date:  1981-10       Impact factor: 18.000

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Authors:  Woon May Ong; Siew Siang Chua; Chirk Jenn Ng
Journal:  Patient Prefer Adherence       Date:  2014-02-15       Impact factor: 2.711

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Review 3.  Contact-Lens Biosensors.

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