4.7 Article

Spot test for determination of uric acid in saliva by smartphone-based digital images: A new proposal for detecting kidney dysfunctions

Journal

MICROCHEMICAL JOURNAL
Volume 162, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.microc.2020.105862

Keywords

Clinical analysis; In-situ analysis; Photometry; RGB values; Digital-image colorimetry

Funding

  1. Sao Paulo Research Foundation (FAPESP) [2018/07687-5]
  2. National Council of Technological and Scientific Development (CNPq) [424080/2016-8, 309581/2017-6]
  3. Coordination for the Improvement of Higher Education Personnel (CAPES) [001]

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A simple and cost-effective approach was developed for the determination of uric acid in saliva, combining a spot test with smartphone-based digital image colorimetry. This method reduced reagent consumption and waste volume, providing reliable results comparable to those obtained by HPLC.
Changes in uric acid levels in biological fluids may be indicative of certain diseases related to kidney dysfunctions. Analytical methods recommended for the quantification of uric acid, such as high-performance liquid chromatography, are typically time-consuming and require high-cost equipment. In this study, a simple and costeffective approach was developed for the determination of uric acid in saliva, by combining a spot test with smartphone-based digital image colorimetry. It was based on the reduction of Cu(II) to Cu(I) by uric acid, followed by complexation with 2,2 '-biquinoline-4,4 '-dicarboxylic acid (BCA), resulting in a violet product. Derivatization reactions and photometric measurements were both carried out in Eppendorf (R) tubes to facilitate the manipulation of biological samples. A smartphone camera and a free application (PhotoMetrix (R) 1.8) were used to capture the image and convert it to RGB values. Photometric measurements were based on reflected radiation in the G channel, corresponding to the complementary color of the product, yielding a linear response between 25 and 150 mu mol L-1. The coefficient of variation (n = 10) and the limit of detection were 1.4% and 8 mu mol L-1, respectively. Both reagent consumption (8.3 mu g Cu(II), 3.8 mg ammonium acetate, and 156 mu g BCA per determination) and waste volume (900 mu L per determination) were minimized. The results agreed with those obtained by HPLC, demonstrating that the approach is a reliable alternative for large scale clinical analysis.

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