Current trends and challenges in point-of-care urinalysis of biomarkers in trace amounts
Urinalysis enables non-invasive point-of-care (POC) testing of numerous biomarkers at their physiological and elevated levels, obviating the need for sophisticated equipment or trained personnel. POC urinalysis is used to identify biomarkers that are rich in urine (greater than 1 μM), such as lactat...
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Format: | Journal Article |
Language: | English |
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2023
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Online Access: | https://hdl.handle.net/10356/164591 |
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author | Yeasmin, Sanjida Ammanath, Gopal Onder, Ahmet Yan, Evelias Yildiz, Umit Hakan Palaniappan, Alagappan Liedberg, Bo |
author2 | School of Materials Science and Engineering |
author_facet | School of Materials Science and Engineering Yeasmin, Sanjida Ammanath, Gopal Onder, Ahmet Yan, Evelias Yildiz, Umit Hakan Palaniappan, Alagappan Liedberg, Bo |
author_sort | Yeasmin, Sanjida |
collection | NTU |
description | Urinalysis enables non-invasive point-of-care (POC) testing of numerous biomarkers at their physiological and elevated levels, obviating the need for sophisticated equipment or trained personnel. POC urinalysis is used to identify biomarkers that are rich in urine (greater than 1 μM), such as lactate, uric acid, glucose, ions, and adenosine. Urine also contains biomarkers such as small molecules, nucleic acids, neurotransmitters, and drugs in trace amounts (less than 1 μM). These biomarkers are of significant importance for health care monitoring, diagnosis of various disorders (cancer, metabolic diseases, etc.) and illicit drug control (cocaine, steroids, etc.). While POC detection of urinary biomarkers at higher concentration (μM to mM) levels is feasible, direct assaying of biomarkers in nM to fM levels is challenging, as assay responses are typically masked by interferences from the urine sample matrix. This report is a consolidated review of emerging trends and challenges in the POC urinalysis for detecting biomarkers that are less abundant in urine. The sensing mechanisms, analytical device fabrication, discrete and integrated sample pre-treatment procedures for POC assaying of urinary markers in trace amounts are elaborated. Subsequently, the utilization of smart data analytics for facilitating personalized urinalysis is presented. A comprehensive outlook on associated challenges in POC urinalysis of biomarkers in trace amounts is further provided, which would facilitate the advancement of POC urinalysis for a wide range of healthcare applications. |
first_indexed | 2024-10-01T04:34:49Z |
format | Journal Article |
id | ntu-10356/164591 |
institution | Nanyang Technological University |
language | English |
last_indexed | 2024-10-01T04:34:49Z |
publishDate | 2023 |
record_format | dspace |
spelling | ntu-10356/1645912023-02-06T02:54:28Z Current trends and challenges in point-of-care urinalysis of biomarkers in trace amounts Yeasmin, Sanjida Ammanath, Gopal Onder, Ahmet Yan, Evelias Yildiz, Umit Hakan Palaniappan, Alagappan Liedberg, Bo School of Materials Science and Engineering Engineering::Materials Analytic Equipment Data Analytics Urinalysis enables non-invasive point-of-care (POC) testing of numerous biomarkers at their physiological and elevated levels, obviating the need for sophisticated equipment or trained personnel. POC urinalysis is used to identify biomarkers that are rich in urine (greater than 1 μM), such as lactate, uric acid, glucose, ions, and adenosine. Urine also contains biomarkers such as small molecules, nucleic acids, neurotransmitters, and drugs in trace amounts (less than 1 μM). These biomarkers are of significant importance for health care monitoring, diagnosis of various disorders (cancer, metabolic diseases, etc.) and illicit drug control (cocaine, steroids, etc.). While POC detection of urinary biomarkers at higher concentration (μM to mM) levels is feasible, direct assaying of biomarkers in nM to fM levels is challenging, as assay responses are typically masked by interferences from the urine sample matrix. This report is a consolidated review of emerging trends and challenges in the POC urinalysis for detecting biomarkers that are less abundant in urine. The sensing mechanisms, analytical device fabrication, discrete and integrated sample pre-treatment procedures for POC assaying of urinary markers in trace amounts are elaborated. Subsequently, the utilization of smart data analytics for facilitating personalized urinalysis is presented. A comprehensive outlook on associated challenges in POC urinalysis of biomarkers in trace amounts is further provided, which would facilitate the advancement of POC urinalysis for a wide range of healthcare applications. 2023-02-06T02:54:28Z 2023-02-06T02:54:28Z 2022 Journal Article Yeasmin, S., Ammanath, G., Onder, A., Yan, E., Yildiz, U. H., Palaniappan, A. & Liedberg, B. (2022). Current trends and challenges in point-of-care urinalysis of biomarkers in trace amounts. Trends in Analytical Chemistry, 157, 116786-. https://dx.doi.org/10.1016/j.trac.2022.116786 0165-9936 https://hdl.handle.net/10356/164591 10.1016/j.trac.2022.116786 2-s2.0-85139512882 157 116786 en Trends in Analytical Chemistry © 2022 Elsevier B.V. All rights reserved. |
spellingShingle | Engineering::Materials Analytic Equipment Data Analytics Yeasmin, Sanjida Ammanath, Gopal Onder, Ahmet Yan, Evelias Yildiz, Umit Hakan Palaniappan, Alagappan Liedberg, Bo Current trends and challenges in point-of-care urinalysis of biomarkers in trace amounts |
title | Current trends and challenges in point-of-care urinalysis of biomarkers in trace amounts |
title_full | Current trends and challenges in point-of-care urinalysis of biomarkers in trace amounts |
title_fullStr | Current trends and challenges in point-of-care urinalysis of biomarkers in trace amounts |
title_full_unstemmed | Current trends and challenges in point-of-care urinalysis of biomarkers in trace amounts |
title_short | Current trends and challenges in point-of-care urinalysis of biomarkers in trace amounts |
title_sort | current trends and challenges in point of care urinalysis of biomarkers in trace amounts |
topic | Engineering::Materials Analytic Equipment Data Analytics |
url | https://hdl.handle.net/10356/164591 |
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