Chapter title |
Quantitative Point-of-Care (POC) Assays Using Measurements of Time as the Readout: A New Type of Readout for mHealth.
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Chapter number | 15 |
Book title |
Mobile Health Technologies
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Published in |
Methods in molecular biology, January 2015
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DOI | 10.1007/978-1-4939-2172-0_15 |
Pubmed ID | |
Book ISBNs |
978-1-4939-2171-3, 978-1-4939-2172-0
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Authors |
Gregory G Lewis, Scott T Phillips, Gregory G. Lewis, Scott T. Phillips |
Abstract |
A paper-based microfluidic device was used to quantitatively detect active enzyme analytes in samples at mid to low femtomolar levels. The device uses a hydrophobic oligomer that controls the wetting properties of the paper within the device. When the target analyte is present within the sample, the oligomer depolymerizes, thus switching the paper to hydrophilic, allowing for the sample to wick through the device. Measuring the time for the sample to wick to a control region relative to an assay region within the device results in sensitive, quantitative measurements of the target enzyme (e.g., alkaline phosphatase or β-D-galactosidase). This device requires the use of only a timer for quantifying a target analyte, and thus the platform may be appropriate for use in resource-limited environments, where access to expensive diagnostic equipment is limited. A smartphone with integrated application software (the software has yet to be developed) could be used for timing the assay and for relating the time measurement to the quantitative readout for the assay. In future versions of this assay, it should be possible to configure the smartphone to start and stop the time-based measurement to further simplify the assay for the user. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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United Kingdom | 1 | 5% |
Unknown | 21 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Postgraduate | 3 | 14% |
Student > Master | 3 | 14% |
Student > Doctoral Student | 2 | 9% |
Student > Ph. D. Student | 2 | 9% |
Researcher | 2 | 9% |
Other | 3 | 14% |
Unknown | 7 | 32% |
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Medicine and Dentistry | 2 | 9% |
Social Sciences | 2 | 9% |
Agricultural and Biological Sciences | 1 | 5% |
Computer Science | 1 | 5% |
Other | 5 | 23% |
Unknown | 8 | 36% |