Two Quantitative Colorimetric Screening Tests for the Noninvasive Detection of Type II Diabetes

Overview

Objectives/Goals The objective of this study was to create a simple test for the early diagnosis of Type II Diabetes using a noninvasive sample. Over 30 million Americans have diabetes and 86 million have prediabetes, while 28% and 89% remain undiagnosed respectively. Methods/Materials Sodium concentration in sweat was identified as a novel biomarker for the detection of diabetes. Two methods to determine the levels of sodium in sweat were devised in this study. The compatibility of sodium assay kit reagents was tested with the stabilizing reagent Trehalose dihydrate. In one detection method, a sodium assay kit was miniaturized to require 40 µl of reagents, a transfer pipette and smartphone. In the second detection method, wax printing was utilized to fabricate a paper sensor. Reagents were stabilized and embedded in the test zones of the sensor to create a semi-automated paper-based screening test. Both screening tests were tested for accuracy and precision with samples containing a range of sodium concentrations. The resulting color change was quantified using ImageJ. Results Sodium assay kit reagents were compatible with Trehalose dihydrate. Wax printing was an inexpensive and rapid method to produce paper sensors. The paper was able to filter out contaminates from samples and the sensor and consistently absorbed 7 µl of sample. Reagents stabilized with Trehalose dihydrate maintained activity and can be stored on paper and in aqueous form. ImageJ proved to be an accurate tool to quantitatively analyze the colorimetric results of both detection methods. Conclusions/Discussion The first detection method has a standard curve with an R2 value of .9817, costs $1.54, requires a 5 µl sample, and generates results in under an hour. The paper sensor detection method has a standard curve with an R2 value of .9926, requires a 3 µl sample, costs $0.25 and generates results in under one hour.

Competition history

• CSEF 2017 Mammalian Biology · Entry S1308

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