title: Enhancing Glycemic Control via Detection of Insulin Using Electrochemical Impedance Spectroscopy.
abstract: Currently, glycemic management for individuals with diabetes mellitus involves monitoring glucose only, which is insufficient as glucose metabolism involves other biomarkers such as insulin. Monitoring additional biomarkers alongside glucose has been proposed to improve glycemic control. In this work, the development of a rapid and label-free insulin biosensor with high sensitivity and accuracy is presented. The insulin sensor prototype also serves as a prior study for a multimarker sensing platform technology that can further improve glycemic control in the future.
  
  
  
  Electrochemical impedance spectroscopy was used to identify an optimal frequency specific to insulin detection on a gold disk electrode with insulin antibody immobilized, which was accomplished by conjugating the primary amines of insulin antibody to the carboxylic bond of the self-assembling monolayer on the gold surface. After blocking with ethanolamine, the insulin physiological concentration gradient was tested. The imaginary impedance was correlated to insulin concentration and the results were compared with standard equivalent circuit analysis and correlation of charge transfer resistance to target concentration.
  
  
  
  The optimal frequency of insulin is 810.5 Hz, which is characterized by having the highest sensitivity and sufficient specificity. The lower limit of detection was 2.26 [Formula: see text] which is comparable to a standard and better than traditional approaches.
  
  
  
  An insulin biosensor prototype capable of detecting insulin in physiological range without complex data normalization was developed. This prototype will be the ground works of a multimarker platform sensor technology for future all-in-one glycemic management sensors.
authors.affiliation: 1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
authors.forename: Aldin
authors.initials: A
authors.lastname: Malkoc
authors.affiliation: 1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
authors.forename: David
authors.initials: D
authors.lastname: Probst
authors.affiliation: 1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
authors.forename: Chi
authors.initials: C
authors.lastname: Lin
authors.affiliation: 1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
authors.forename: Mukund
authors.initials: M
authors.lastname: Khanwalker
authors.affiliation: 1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
authors.forename: Connor
authors.initials: C
authors.lastname: Beck
authors.affiliation: 2 Mayo Clinic Arizona, Scottsdale, AZ, USA.
authors.forename: Curtiss B
authors.initials: CB
authors.lastname: Cook
authors.affiliation: 1 School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.|2 Mayo Clinic Arizona, Scottsdale, AZ, USA.
authors.forename: Jeffrey T
authors.initials: JT
authors.lastname: La Belle
mesh_terms: D015415:Biomarkers / Q000097:blood; D015374:Biosensing Techniques / Q000295:instrumentation* / Q000379:methods*; D058266:Dielectric Spectroscopy / Q000295:instrumentation / Q000379:methods; D006801:Humans; D007328:Insulin / Q000032:analysis* / Q000097:blood
chemical_list: D015415:Biomarkers; D007328:Insulin
keywords: diabetes mellitus; electrochemical impedance spectroscopy; imaginary impedance; insulin; label free; point-of-care