Glucose Sensing in Human Whole Blood Based on Near-Infrared Phosphors and Outlier Treatment with the Programming Language "R"

ACS Omega. 2021 Dec 20;7(1):198-206. doi: 10.1021/acsomega.1c04344. eCollection 2022 Jan 11.

Abstract

A near-infrared paper-based analytical device (NIR-PAD) for glucose detection in whole blood was based on iridium(III) metal complexes embedded in a three-dimensional (3D) enzyme gel. These complexes emit NIR luminescence, can avoid interference from the color of blood, and increase the sensitivity of sensing glucose. The glucose reaction behaviors of another two different iridium(III) and platinum(II) complexes were also tested. When the glucose solution was added to the device, the oxidation of glucose by glucose oxidase caused oxygen consumption and increased the intensity of the phosphorescence emission. To the best of our knowledge, this is the first time that data have been treated with the programming language "R", which uses Tukey's test to identify the outliers in the data and calculate a median for establishing a calibration curve, in order to improve the accuracy of NIR-PADs for sensing glucose. Compared with other published devices, NIR-PADs exhibit a wider linear range (1-30 mM, [relative emission intensity] = 0.0250[glucose] + 0.0451, and R 2 = 0.9984), a low detection limit (0.7 mM), a short response time (<2 s), and a small sample volume (2 μL). Finally, blood specimens were obtained from 19 patients enrolled in Taipei Veterans General Hospital under an approved IRB protocol (Taiwan; 2017-12-002CC). The sensors exhibited remarkable characteristics for glucose detection in comparison with other methods, including the clinical method in hospitals as well as those without blood sample pretreatment or a dilution factor. The above results confirm that NIR-PAD sensors can be put to practical use for glucose detection.