A new sensitive spectrophotometric method for determination of saliva and blood glucose

P Mohammadnejad, SS Asl, S Aminzadeh… - … Acta Part A: Molecular …, 2020 - Elsevier
Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2020Elsevier
There is an increasing need for accurate and inexpensive glucometers as the world moves
toward personalized medicine. Among the existing technologies, photometric based devices
are more desired due to the cost-effectiveness, ease-of-use and the potential to be adopted
in the smart-phone technology for remote sensing and self-monitoring purposes. However,
the accuracy, precision, and reproducibility of the results of these devices are heavily
dependent on the details of the chosen glucose measuring method. Considering the …
Abstract
There is an increasing need for accurate and inexpensive glucometers as the world moves toward personalized medicine. Among the existing technologies, photometric based devices are more desired due to the cost-effectiveness, ease-of-use and the potential to be adopted in the smart-phone technology for remote sensing and self-monitoring purposes. However, the accuracy, precision, and reproducibility of the results of these devices are heavily dependent on the details of the chosen glucose measuring method. Considering the delicate problems with the current spectrophotometric methods, a new method was developed for more precise, accurate, and fast measurement of blood glucose via the coupled reactions of glucose oxidase and peroxidase using 4-[(4-Hydroxy-3-methoxyphenyl) azo]-benzenesulfonic acid (GASA) as the substrate. Stability of GASA and its oxidized products along with its direct and fast consumption by peroxidase, made it possible to determine blood glucose concentration in <20 s with high reproducibility. The low detection limit of GASA method (0.36 mg dL1) with a linear range from 0.36 to 399.6 mg.dL1 also allowed determination of salivary glucose concentration (SGC). As compared with the blood samples, the SGC results were more dispersed, especially for the diabetic participants, assumingly due to the diverse nature of salivary samples. However, a good correlation coefficient of 0.81 for non-diabetic individuals showed that it is accurate enough to recognize non-diabetic from diabetic condition. Results of this study disclose the potential application of GASA method as a reliable alternative for the current spectrophotometric methods with the ability to be adopted in miniaturized glucometers.
Elsevier
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