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Contact lens-based lysozyme detection in tear using a mobile sensor.

Authors :
Ballard Z
Bazargan S
Jung D
Sathianathan S
Clemens A
Shir D
Al-Hashimi S
Ozcan A
Source :
Lab on a chip [Lab Chip] 2020 Apr 21; Vol. 20 (8), pp. 1493-1502. Date of Electronic Publication: 2020 Mar 30.
Publication Year :
2020

Abstract

We report a method for sensing analytes in tear-fluid using commercial contact lenses (CLs) as sample collectors for subsequent analysis with a cost-effective and field-portable reader. In this study we quantify lysozyme, the most prevalent protein in tear fluid, non-specifically bound to CLs worn by human participants. Our mobile reader uses time-lapse imaging to capture an increasing fluorescent signal in a standard well-plate, the rate-of-change of which is used to indirectly infer lysozyme concentration through the use of a standard curve. We empirically determined the best-suited CL material for our sampling procedure and assay, and subsequently monitored the lysozyme levels of nine healthy human participants over a two-week period. Of these participants who were regular CL wearers (6 out of 9), we observed an increase in lysozyme levels from 6.89 ± 2.02 μg mL <superscript>-1</superscript> to 10.72 ± 3.22 μg mL <superscript>-1</superscript> (mean ± SD) when inducing an instance of digital eye-strain by asking them to play a game on their mobile-phones during the CL wear-duration. We also observed a lower mean lysozyme concentration (2.43 ± 1.66 μg mL <superscript>-1</superscript> ) in a patient cohort with dry eye disease (DED) as compared to the average monitoring level of healthy (no DED) human participants (6.89 ± 2.02 μg mL <superscript>-1</superscript> ). Taken together, this study demonstrates tear-fluid analysis with simple and non-invasive sampling steps along with a rapid, easy-to-use, and cost-effective measurement system, ultimately indicating physiological differences in human participants. We believe this method could be used in future tear-fluid studies, even supporting multiplexed detection of a panel of tear biomarkers toward improved diagnostics and prognostics as well as personalized mobile-health applications.

Details

Language :
English
ISSN :
1473-0189
Volume :
20
Issue :
8
Database :
MEDLINE
Journal :
Lab on a chip
Publication Type :
Academic Journal
Accession number :
32227027
Full Text :
https://doi.org/10.1039/c9lc01039d