Tear Glucose Measurement by Reflectance Spectrum of a Nanoparticle Embedded Contact Lens
Open accessAbstract
Glucose level is a primary indicator in the diagnosis and treatment of diabetes mellitus. According to the correlation between glucose concentration in blood and tears, measuring tear glucose can be an alternative to traditional strips test for blood glucose. Thus, measuring tear glucose levels could provide noninvasive monitoring of blood glucose. As a biocompatible biosensor, a nanoparticle embedded contact lens (NECL) is developed which is composed of glucose oxidase and cerium oxide (III). Using spectroscopy, we found the detectable changes in reflection spectrum of contact lenses with respect to the glucose concentration, and developed correlation curve of the reflection spectrum with known glucose level. Furthermore, we assessed tear glucose level and compared blood glucose level with the diabetic mouse model to evaluate this approach. Our algorithm for regular monitoring of glucose using contact lens biosensor may lead to noninvasive monitoring of tear glucose level. NECL may provide simple and noninvasive glucose monitoring based on the spectral changes in contact lens biosensor.
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Scientific data evidenced how commercially available test strips exhibit the required performance to evaluate glucose concentration in low-volume tears.
“Scientific data evidenced how commercially available test strips exhibit the required performance to evaluate glucose concentration in low-volume tears 166-168.”
From Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices (2022) · cites this paper as [167]
The Introduction describes commercial test strips as part of finger-prick blood glucometers, while the Discussion reports tear-glucose measurements using a nanoparticle-embedded contact lens. Searches for commercially available strips and low-volume tears found no passage assessing whether test strips perform adequately with tear samples. (LLM, conf=0.77)
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References 30 · Cited by 83
Research works printed but not linked: 26
- [1]Diabetes 2030 Insights from Yesterday Today, and Future Trends. 2017 20 6 12 10.1089/pop.2015.0181 PMC5278808 27124621 · DOI
- [2]Zhao Y Ye W Boye KS Holcombe JH Swindle R Healthcare charges and utilization associated with diabetic neuropathy: impact of Type 1 diabetes and presence of other diabetes-related complications and comorbidities. 2009 26 61 69 10.1111/j.1464-5491.2008.02616.x 19125762 · DOI
- [3]Pasic A Koehler H Klimant I Schaupp L Miniaturized fiber-optic hybrid sensor for continuous glucose monitoring in subcutaneous tissue Sensors and Actuators B: Chemical 2007 122 60 68 10.1016/j.snb.2006.05.010 · DOI
- [4]Gay CL Reinforced follow-up for children and adolescents with type 1 diabetes and inadequate glycaemic control: a randomized controlled trial intervention via the local pharmacist and telecare Diabetes & Metabolism 2006 32 159 165 10.1016/s1262-3636(07)70263-x 16735965 · DOI
- [6]Arakawa T Mouthguard biosensor with telemetry system for monitoring of saliva glucose: A novel cavitas sensor Biosens Bioelectron 2016 84 106 111 10.1016/j.bios.2015.12.014 26725934 · DOI · Paper page
- [7]Pappa, A.-M. et al. Organic Transistor Arrays Integrated with Finger-Powered Microfluidics for Multianalyte Saliva Testing. 5, 2295–302, 10.1002/adhm.201600494 (2016). 27385673 · DOI
- [9]Valdés-Ramírez G Microneedle-based self-powered glucose sensor Electrochemistry Communications 2014 47 58 62 10.1016/j.elecom.2014.07.014 · DOI
- [11]Yao, H. et al. A contact lens with integrated telecommunication circuit and sensors for wireless and continuous tear glucose monitoring. Journal of Micromechanics and Microengineering22, 10.1088/0960-1317/22/7/075007 (2012). · DOI · Paper page
- [12]Lane JD Krumholz DM Sack RA Morris C Tear glucose dynamics in diabetes mellitus Curr Eye Res 2006 31 895 901 10.1080/02713680600976552 17114114 · DOI
- [13]Peng B Evaluation of enzyme-based tear glucose electrochemical sensors over a wide range of blood glucose concentrations Biosens Bioelectron 2013 49 204 209 10.1016/j.bios.2013.05.014 23747996 · DOI · Paper page
- [14]Agustini D Bergamini MF Marcolino-Junior LH Tear glucose detection combining microfluidic thread based device, amperometric biosensor and microflow injection analysis Biosens Bioelectron 2017 98 161 167 10.1016/j.bios.2017.06.035 28672191 · DOI
- [15]Park, J. et al. Soft, smart contact lenses with integrations of wireless circuits, glucose sensors, and displays. Science Advances4, eaap9841, 10.1126/sciadv.aap9841 (2018). PMC5787380 29387797 · DOI · Paper page
- [16]Yao H Shum AJ Cowan M Lahdesmaki I Parviz BA A contact lens with embedded sensor for monitoring tear glucose level Biosens Bioelectron 2011 26 3290 3296 10.1016/j.bios.2010.12.042 21257302 PMC3043144 · DOI · Paper page
- [17]Kim J Wearable smart sensor systems integrated on soft contact lenses for wireless ocular diagnostics Nat Commun 2017 8 14997 10.1038/ncomms14997 28447604 PMC5414034 · DOI · Paper page
- [18]Zhang M Highly sensitive glucose sensors based on enzyme-modified whole-graphene solution-gated transistors Sci Rep 2015 5 8311 10.1038/srep08311 25655666 PMC4319171 · DOI
- [19]Sheng Q Zhang D Wu Q Zheng J Tang H Electrodeposition of Prussian blue nanoparticles on polyaniline coated halloysite nanotubes for nonenzymatic hydrogen peroxide sensing Analytical Methods 2015 7 6896 6903 10.1039/c5ay01329a · DOI
- [20]Haddad R Mattei JG Thery J Auger A Novel ferrocene-anchored ZnO nanoparticle/carbon nanotube assembly for glucose oxidase wiring: application to a glucose/air fuel cell Nanoscale 2015 7 10641 10647 10.1039/c5nr00497g 26024212 · DOI
- [21]Kim S Variability of electrochemical skin conductance for screening diabetes mellitus Biomed Eng Lett 2019 9 267 274 10.1007/s13534-019-00111-1 31168431 PMC6520414 · DOI
- [22]Connelly JT Rolland JP Whitesides GM “Paper Machine” for Molecular Diagnostics Analytical Chemistry 2015 87 7595 7601 10.1021/acs.analchem.5b00411 26104869 · DOI
- [23]Choi J Soft, skin-mounted microfluidic systems for measuring secretory fluidic pressures generated at the surface of the skin by eccrine sweat glands Lab on a Chip 2017 17 2572 2580 10.1039/c7lc00525c 28664954 PMC5561737 · DOI
- [24]Choi, J., Kang, D., Han, S., Kim, S. B. & Rogers, J. A. Thin, Soft, Skin-Mounted Microfluidic Networks with Capillary Bursting Valves for Chrono-Sampling of Sweat. Advanced Healthcare Materials6, 10.1002/adhm.201601355 (2017). 28105745 · DOI
- [25]Liao Y-T Yao H Lingley A Parviz B Otis BP A 3-uW CMOS Glucose Sensor for Wireless Contact-Lens Tear Glucose Monitoring IEEE Journal of Solid-State Circuits 2012 47 335 344 10.1109/jssc.2011.2170633 · DOI · Paper page
- [26]Elsherif M Hassan MU Yetisen AK Butt H Wearable Contact Lens Biosensors for Continuous Glucose Monitoring Using Smartphones ACS Nano 2018 12 5452 5462 10.1021/acsnano.8b00829 29750502 PMC6107296 · DOI · Paper page
- [27]Lee H Hong YJ Baik S Hyeon T Kim DH Enzyme-Based Glucose Sensor: From Invasive to Wearable Device Adv Healthc Mater 2018 7 e1701150 10.1002/adhm.201701150 29334198 · DOI · Paper page
- [28]Kang, J. et al. Direct observation of glucose fingerprint using in vivo Raman spectroscopy. Science Advances6, eaay5206, 10.1126/sciadv.aay5206 (2020). PMC6981082 32042901 · DOI
- [29]Rinnan Å Berg FVD Engelsen SB Review of the most common pre-processing techniques for near-infrared spectra TrAC Trends in Analytical Chemistry 2009 28 1201 1222 10.1016/j.trac.2009.07.007 · DOI
- Authors
- Kim, S., Jeon, H.-J., Park, S., Lee, D. Y., & Chung, E.
- Affiliations
- Gwangju Institute of Science and Technology (KR)
- Hanyang University (KR)
- Corresponding author
- Chung, Euiheon
- Venue
- Scientific Reports
- Published
- 2020-05-19
- Volume
- 10
- Issue
- 1
- Pages
- 8254-8254
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC7237479
- OpenAlex
- W3027399444
- Cited by
- 83
- References
- 30
- Citations by year
- 2026: 7 · 2025: 16 · 2024: 14 · 2023: 10 · 2022: 18 · 2021: 14 · 2020: 4
- FWCI
- 3.95
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Research Foundation
- Ministry of Science, ICT and Future Planning (NRF-2017M3C7A 1044964)
- National Research Foundation of Korea (NRF-2019M3C7A1044964, NRF-2015M3A9E2030125, NRF‐2017M3C7A 1044964)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electrochemical sensors and biosensors
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Spectroscopy Techniques in Biomedical and Chemical Research
- Physical Sciences › Chemical Engineering › Bioengineering › Analytical Chemistry and Sensors
- Keywords
- tear glucose, non-invasive glucose monitoring, glucose oxidase, cerium oxide nanoparticles, reflectance spectrum, diabetes mellitus, blood glucose, diabetic mouse model
- MeSH terms
- Animals, Contact Lenses, Diabetes Mellitus, Female, Glucose, Glucose Oxidase, Humans, Male, Mice, Inbred C57BL, Tears, Blood Glucose Self-Monitoring, Biosensing Techniques, Mice, Nanoparticles
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