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Critical Reviews™ in Biomedical Engineering
SJR: 0.207 SNIP: 0.376 CiteScore™: 0.79

ISSN Печать: 0278-940X
ISSN Онлайн: 1943-619X

Выпуски:
Том 47, 2019 Том 46, 2018 Том 45, 2017 Том 44, 2016 Том 43, 2015 Том 42, 2014 Том 41, 2013 Том 40, 2012 Том 39, 2011 Том 38, 2010 Том 37, 2009 Том 36, 2008 Том 35, 2007 Том 34, 2006 Том 33, 2005 Том 32, 2004 Том 31, 2003 Том 30, 2002 Том 29, 2001 Том 28, 2000 Том 27, 1999 Том 26, 1998 Том 25, 1997 Том 24, 1996 Том 23, 1995

Critical Reviews™ in Biomedical Engineering

DOI: 10.1615/CritRevBiomedEng.2019026533
pages 179-191

Development of Electrochemical Methods to Enzymatically Detect Lactate and Glucose Using Imaginary Impedance for Enhanced Management of Glycemic Compromised Patients

Blake Morrow
School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ
Aldin Malkoc
School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ; St. George's University School of Medicine, True Blue, Grenada
Tiffany Gong
School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ
David Probst
School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona
Chi Lin
School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ
Ayan Sen
Mayo Clinic, Critical Care, Phoenix, AZ
Jeffrey T. La Belle
School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona

Краткое описание

Lactate is an important biological marker that can provide valuable information for patients who have experienced a traumatic injury. Additionally, when coupled with glucose, the severity and likely prognosis of a traumatic injury can be determined. Because monitoring various markers proves useful in diagnosis and treatment of trauma patients, monitoring both glucose and lactate simultaneously may be especially useful for diabetic patients who have suffered a traumatic injury. Previously, using electrochemical impedance spectroscopy (EIS), a sensor capable of measuring two affinity-based biomarkers simultaneously was demonstrated using the biomarker's specific optimal frequency to develop a deconvolution algorithm, which allowed for the measurement of two biomarkers from a single signal. Herein, while developing an EIS lactate sensor, dual enzymatic biomarker detection of lactate and glucose via EIS was also attempted. Both biomarkers were validated individually with the lactate sensor being additionally validated on whole blood samples. The EIS lactate biosensor achieved a range of detection from 0 to 32 mM of lactate and the glucose sensor a range of 0–100 mg/dL of glucose, which are representative of the likely physiological ranges that trauma patients experience. However, the preliminary attempt of dual marker detection was unsuccessful due to suspected accumulation of reduced redox probe on the surface of the self-assembled monolayer (SAM). Individually, the optimal frequency of lactate was determined to be 69.75 Hz and that of glucose was determined to be 31.5 Hz. However, when combined onto one sensor, no discernable optimal frequency could be determined which again was suspected to be due to the accumulation of the reduced redox probe at the surface of the SAM.

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