Enzymatic Low Volume Passive Sweat Based Assays for Multi-Biomarker Detection

Simple item page
dc.contributor.authorBhide, Ashlesha
dc.contributor.authorCheeran, Sarah
dc.contributor.authorMuthukumar, Sriram
dc.contributor.authorPrasad, Shalini
dc.contributor.utdAuthorBhide, Ashlesha
dc.contributor.utdAuthorCheeran, Sarah
dc.contributor.utdAuthorPrasad, Shalini
dc.date.accessioned2020-09-20T13:50:04Z
dc.date.available2020-09-20T13:50:04Z
dc.date.issued2019-01-16
dc.description.abstractSimultaneous detection of correlated multi-biomarkers on a single low-cost platform in ultra-low fluid volumes with robustness is in growing demand for the development of wearable diagnostics. A non-faradaic biosensor for the simultaneous detection of alcohol, glucose, and lactate utilizing low volumes (1-5 μL) of sweat is demonstrated. Biosensing is implemented using nanotextured ZnO films integrated on a flexible porous membrane to achieve enhanced sensor performance. The ZnO sensing region is functionalized with enzymes specific for the detection of alcohol, glucose, and lactate in the ranges encompassing their physiologically relevant levels. A non-faradaic chronoamperometry technique is used to measure the current changes associated with interactions of the target biomarkers with their specific enzyme. The specificity performance of the biosensing platform was established in the presence of cortisol as the non-specific molecule. Biosensing performance of the platform in a continuous mode performed over a 1.5-h duration showed a stable current response to cumulative lifestyle biomarker concentrations with capability to distinguish reliably between low, mid, and high concentration ranges of alcohol (0.1, 25, 100 mg/dL), glucose (0.1, 10, 50 mg/dL), and lactate (1, 50, 100 mM). The low detection limits and a broader dynamic range for the lifestyle biomarker detection are quantified in this research demonstrating its suitability for translation into a wearable device.
dc.description.departmentErik Jonsson School of Engineering and Computer Science
dc.description.sponsorshipNational Institute on Alcohol Abuse and Alcoholism of the National Institutes of Health (R43AA026114)
dc.identifier.bibliographicCitationBhide, Ashlesha, Sarah Cheeran, Sriram Muthukumar, and Shalini Prasad. 2019. "Enzymatic Low Volume Passive Sweat Based Assays for Multi-Biomarker Detection." Biosensors 9(1): art. 13, doi: 10.3390/bios9010013
dc.identifier.issn2079-6374
dc.identifier.issue1
dc.identifier.urihttps://dx.doi.org/10.3390/bios9010013
dc.identifier.urihttps://hdl.handle.net/10735.1/8907
dc.identifier.volume9
dc.language.isoen
dc.publisherMDPI
dc.rightsCC BY 4.0 (Attribution)
dc.rights©2019 The Authors
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.source.journalBiosensors
dc.subjectBiosensors
dc.subjectDrinking of alcoholic beverages
dc.subjectLactates
dc.subjectChronoamperometry
dc.subjectPerspiration
dc.subjectAlcohol
dc.subject.meshBlood Glucose
dc.titleEnzymatic Low Volume Passive Sweat Based Assays for Multi-Biomarker Detection
dc.type.genrearticle

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
JECS-3738-261968.33.pdf
Size:
1.46 MB
Format:
Adobe Portable Document Format
Description:
Article
Download

Collections

Prasad, Shalini