ArticleBiomaterials research2023
Chromophoric cerium oxide nanoparticle-loaded sucking disk-type strip sensor for optical measurement of glucose in tear fluid.
Article in Biomaterials research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- The Convergence of Polymer Science and Predictive Modeling for Noninvasive Glucose Monitoring.Pharmaceutics · 2025Review
- Recent advances and prospects of nanoparticle-based drug delivery for diabetic ocular complications.Theranostics · 2025Review
- Advances in Platelet-Dysfunction Diagnostic Technologies.Biomolecules · 2024Review
- The regulatory mechanisms of cerium oxide nanoparticles in oxidative stress and emerging applications in refractory wound care.Frontiers in pharmacology · 2024Review
- Advances in machine learning-enhanced nanozymes.Frontiers in chemistry · 2024Review
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Authors and funding
10 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundNoninvasive monitoring of tear glucose levels can be convenient for patients to manage their diabetes mellitus. However, there are issues with monitoring tear glucose levels, such as the invasiveness of some methods, the miniaturization, inaccuracy, or the high cost of wearable devices. To overcome the issues, we newly designed a sucking disk-type (SD) strip biosensor that can quickly suck tear fluid and contains cerium oxide nanoparticle (CNP) that causes a unique color change according to the glucose level of the tear without complicated electronic components.
methodsThe SD strip biosensor composed of three distinct parts (tip, channel, and reaction chamber) was designed to contain the sensing paper, onto which tear fluid can be collected and delivered. The sensing paper treated with CNP/APTS (aminopropyltriethoxysilane) /GOx (glucose oxidase) was characterized. Then we carried out the reliability of the SD strip biosensor in the diabetic rabbit animals. We quantitatively analyzed the color values of the SD strip biosensor through the colorimetric analysis algorithm.
resultsWe contacted the inferior palpebral conjunctiva (IPC) of a diabetic rabbit eye using an SD strip biosensor to collect tears without eye irritation and successfully verified the performance and quantitative efficacy of the sensor. An image processing algorithm that can optimize measurement accuracy is developed for accurate color change measurement of SD strip biosensors. The validation tests show a good correlation between glucose concentrations measured in the tear and blood.
conclusionOur findings demonstrate that the CNP-embedded SD strip biosensor and the associated image processing can simply monitor tear glucose to manage diabetes mellitus.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.