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volume 7 issue 1 pages 198-206

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

Hsia An Lee 1
Hsia-An Lee 2
Peng Yi Lin 1
Peng-Yi Lin 2
Hui-Wen Lin 5, 6
Sheng-Wei Pan 7, 8
Mei-Lin Ho 1, 2
Publication typeJournal Article
Publication date2021-12-20
scimago Q1
wos Q2
SJR0.773
CiteScore7.1
Impact factor4.3
ISSN24701343
General Chemistry
General Chemical Engineering
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 R2 = 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.
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Lee H. A. et al. Glucose Sensing in Human Whole Blood Based on Near-Infrared Phosphors and Outlier Treatment with the Programming Language "r" // ACS Omega. 2021. Vol. 7. No. 1. pp. 198-206.
GOST all authors (up to 50) Copy
Lee H. A., Lee H., Lin P. Y., Lin P., Solomatina A. I., Koshevoy I. O., Tunik S. P., Lin H., Pan S., Ho M. Glucose Sensing in Human Whole Blood Based on Near-Infrared Phosphors and Outlier Treatment with the Programming Language "r" // ACS Omega. 2021. Vol. 7. No. 1. pp. 198-206.
RIS |
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RIS Copy
TY - JOUR
DO - 10.1021/acsomega.1c04344
UR - https://pubs.acs.org/doi/10.1021/acsomega.1c04344
TI - Glucose Sensing in Human Whole Blood Based on Near-Infrared Phosphors and Outlier Treatment with the Programming Language "r"
T2 - ACS Omega
AU - Lee, Hsia An
AU - Lee, Hsia-An
AU - Lin, Peng Yi
AU - Lin, Peng-Yi
AU - Solomatina, Anastasia I
AU - Koshevoy, Igor O
AU - Tunik, Sergey P.
AU - Lin, Hui-Wen
AU - Pan, Sheng-Wei
AU - Ho, Mei-Lin
PY - 2021
DA - 2021/12/20
PB - American Chemical Society (ACS)
SP - 198-206
IS - 1
VL - 7
PMID - 35036691
SN - 2470-1343
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2021_Lee,
author = {Hsia An Lee and Hsia-An Lee and Peng Yi Lin and Peng-Yi Lin and Anastasia I Solomatina and Igor O Koshevoy and Sergey P. Tunik and Hui-Wen Lin and Sheng-Wei Pan and Mei-Lin Ho},
title = {Glucose Sensing in Human Whole Blood Based on Near-Infrared Phosphors and Outlier Treatment with the Programming Language "r"},
journal = {ACS Omega},
year = {2021},
volume = {7},
publisher = {American Chemical Society (ACS)},
month = {dec},
url = {https://pubs.acs.org/doi/10.1021/acsomega.1c04344},
number = {1},
pages = {198--206},
doi = {10.1021/acsomega.1c04344}
}
MLA
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Lee, Hsia An, et al. “Glucose Sensing in Human Whole Blood Based on Near-Infrared Phosphors and Outlier Treatment with the Programming Language "r".” ACS Omega, vol. 7, no. 1, Dec. 2021, pp. 198-206. https://pubs.acs.org/doi/10.1021/acsomega.1c04344.
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