Multifunctional Dopamine‐Based Hydrogel Microneedle Electrode for Continuous Ketone Sensing

Author:

Ausri Irfani Rahmi12ORCID,Sadeghzadeh Sadegh12,Biswas Subhamoy12,Zheng Hanjia12,GhavamiNejad Peyman12,Huynh Michelle Dieu Thao12,Keyvani Fatemeh12,Shirzadi Erfan12,Rahman Fasih A3,Quadrilatero Joe3,GhavamiNejad Amin4,Poudineh Mahla12ORCID

Affiliation:

1. Department of Electrical and Computer Engineering University of Waterloo Waterloo ON N2L 3G1 Canada

2. Waterloo Institute for Nanotechnology University of Waterloo Waterloo ON N2L 3G1 Canada

3. Department of Kinesiology and Health Sciences University of Waterloo Waterloo ON N2L 3G1 Canada

4. Advanced Pharmaceutics and Drug Delivery Laboratory, Leslie L. Dan Faculty of Pharmacy University of Toronto Toronto ON M5S 3M2 Canada

Abstract

AbstractDiabetic ketoacidosis (DKA), a severe complication of type 1 diabetes (T1D), is triggered by production of large quantities of ketone bodies, requiring patients with T1D to constantly monitor their ketone levels. Here, a skin‐compatible hydrogel microneedle (HMN)‐continuous ketone monitoring (HMN‐CKM) device is reported. The sensing mechanism relies on the catechol–quinone chemistry inherent to the dopamine (DA) molecules that are covalently linked to the polymer structure of the HMN patch. The DA serves the dual‐purpose of acting as a redox mediator for measuring the byproduct of oxidation of 3‐beta‐hydroxybutyrate (β‐HB), the primary ketone bodies; while, also facilitating the formation of a crosslinked HMN patch. A universal approach involving pre‐oxidation and detection of the generated catechol compounds is introduced to correlate the sensor response to the β‐HB concentrations. It is further shown that real‐time tracking of a decrease in ketone levels of T1D rat model is possible using the HMN‐CKM device, in conjunction with a data‐driven machine learning model that considers potential time delays.

Publisher

Wiley

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