Recent advances in optical sensing strategies for uric acid detection
- 1Department of Chemistry, SRMIST SRM Nagar, Potheri, Kattankulathur, Kancheepuram District Chennai Tamil Nadu-603203 India [email protected] [email protected].
- 2Department of Chemistry, Raghunathpur College, Sidho-Kanho-Birsha University Purulia West Bengal-723133 India [email protected].
Abstract
Uric acid (UA), a byproduct of purine metabolism, serves as a significant biomarker associated with various medical conditions, including gout, renal and cardiac disorders, and metabolic dysfunctions. This paper presents a comprehensive review of recent advancements in optical sensing technologies for UA detection. The various platforms are systematically categorized into colorimetric and fluorometric sensors, with particular emphasis on their detection parameters, such as sensitivity, selectivity, and detection limits, as well as their operational principles. Fluorometric sensors are noted for achieving exceptionally low detection thresholds (in the nanomolar range) and high specificity, whereas colorimetric sensors are recognized for their rapid, visual results and reliable performance in complex sample matrices. Numerous international research efforts have contributed to the development of highly sensitive and selective UA detection technologies. Despite the development of several optical chemosensors (both fluorescent and colorimetric) a systematic classification remains absent. This review highlights the design strategies and molecular recognition mechanisms of various UA chemosensors, particularly those based on small organic molecules. The integration of these sensors into wearable technology or diagnostic platforms could significantly advance personalized medicine and the management of UA-related conditions. The paper concludes by outlining potential future directions for the field, including the deployment of multiplexed sensing systems and the application of machine learning for signal analysis, to advance the development of next-generation UA optical sensors for point-of-care diagnostics and real-time health monitoring.
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BibTeX
@article{nayak2026recent,
title = {{Recent advances in optical sensing strategies for uric acid detection}},
author = {Suman Nayak and Subhajit Tripathy and Nanjundan Raghul and Priyadip Das and Prasenjit Mahato},
journal = {RSC advances},
year = {2026},
month = nov,
doi = {10.1039/d6ra07276c},
url = {https://europepmc.org/article/PMC/PMC13726138},
note = {CC BY},
}
RIS
TY - JOUR
TI - Recent advances in optical sensing strategies for uric acid detection
AU - Suman Nayak
AU - Subhajit Tripathy
AU - Nanjundan Raghul
AU - Priyadip Das
AU - Prasenjit Mahato
PY - 2026
DA - 2026/11/02
JO - RSC advances
DO - 10.1039/d6ra07276c
UR - https://europepmc.org/article/PMC/PMC13726138
AB - Uric acid (UA), a byproduct of purine metabolism, serves as a significant biomarker associated with various medical conditions, including gout, renal and cardiac disorders, and metabolic dysfunctions. This paper presents a comprehensive review of recent advancements in optical sensing technologies for UA detection. The various platforms are systematically categorized into colorimetric and fluorometric sensors, with particular emphasis on their detection parameters, such as sensitivity, selectivity, and detection limits, as well as their operational principles. Fluorometric sensors are noted for achieving exceptionally low detection thresholds (in the nanomolar range) and high specificity, whereas colorimetric sensors are recognized for their rapid, visual results and reliable performance in complex sample matrices. Numerous international research efforts have contributed to the development of highly sensitive and selective UA detection technologies. Despite the development of several optical chemosensors (both fluorescent and colorimetric) a systematic classification remains absent. This review highlights the design strategies and molecular recognition mechanisms of various UA chemosensors, particularly those based on small organic molecules. The integration of these sensors into wearable technology or diagnostic platforms could significantly advance personalized medicine and the management of UA-related conditions. The paper concludes by outlining potential future directions for the field, including the deployment of multiplexed sensing systems and the application of machine learning for signal analysis, to advance the development of next-generation UA optical sensors for point-of-care diagnostics and real-time health monitoring.
SN - 2046-2069
ER -