Parametric Evaluation of Hybrid Hydrogel-Based Colorimetric Assay for Rapid Quantitative Analysis of Uric Acid
Issued Date
2025-04-01
Resource Type
ISSN
2576988X
eISSN
25769898
DOI
Scopus ID
2-s2.0-86000334148
Journal Title
Engineered Science
Volume
34
Rights Holder(s)
SCOPUS
Bibliographic Citation
Engineered Science Vol.34 (2025)
Suggested Citation
Pantakitcharoenkul J., Mekkhayai K., Paengkhumpung K., Asgharpour A., Coblyn M., Pornputtapitak W., Jovanovic G., Jangpatarapongsa K. Parametric Evaluation of Hybrid Hydrogel-Based Colorimetric Assay for Rapid Quantitative Analysis of Uric Acid. Engineered Science Vol.34 (2025). doi:10.30919/es1398 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/106701
Title
Parametric Evaluation of Hybrid Hydrogel-Based Colorimetric Assay for Rapid Quantitative Analysis of Uric Acid
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Abstract
Colorimetric assays offer a fast and accurate quantification of uric acid in biological samples. However, commercial kits require multiple preparation steps and are prone to user errors. In this work, a hydrogel-based uric acid colorimetric assay is developed in conjunction with computational modeling to study the key parameters that govern assay performance and rapidity. Hybrid alginate/polyvinyl alcohol (PVA) hydrogels demonstrate superior shape retention compared to single-type hydrogels. The developed assay shows a linear range of 2-600 µM with a detection limit of 1.92 uM. The computational model provides a good prediction of the dynamic readout profile of fluorescent intensity. The enzyme in hydrogel-based assays shows a prolonged stability compared to a paper-based immobilization approach, maintaining the effectiveness after 4 months of storage under the same conditions. The fastest result from the hydrogel-based assay was achieved within 15 minutes. The circumscribed central composite design, implemented with the computational model, revealed the significance of enzyme concentration and uric acid diffusivity in the hydrogel on the readout time. The quadratic model demonstrated strong predictive potential, suggesting its possible application for further development of hydrogel-based assays.