Point-of-care surface plasmon resonance biosensor for stroke biomarkers
Stroke is the second most common cause of death. Stroke is a time sensitive disease and reducing the time-to-treatment can increase patient’s access to treatment and therefore save patients’ lives. Recent studies have shown that blood-based biomarkers measurement may assist in monitoring stroke risk...
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sg-ntu-dr.10356-767562023-03-04T15:39:39Z Point-of-care surface plasmon resonance biosensor for stroke biomarkers Koh, Brescia Rui Wen Alfred Tok Iing Yoong School of Materials Science and Engineering DRNTU::Engineering::Materials Stroke is the second most common cause of death. Stroke is a time sensitive disease and reducing the time-to-treatment can increase patient’s access to treatment and therefore save patients’ lives. Recent studies have shown that blood-based biomarkers measurement may assist in monitoring stroke risk and prognosis. By monitoring specific stroke biomarker, stroke can be characterized and risk can be predicted thereby reducing the time-to-treatment. In this project, a point-of-care surface plasmon resonance (SPR) biosensor is developed for the detection of stroke biomarkers (NT-proBNP and S100B) using SPR Module (PhotonicSys SPR H5). SPR is a quantum electromagnetic phenomenon which emerges from the interaction of light with free electrons at a metal-dielectric interface. The novelty of this project is in the substrate as well as the reading methodology. The antibody was bonded onto the novel substrate via covalent bond for specific detection and tested with water samples. Stroke biomarkers (NT-proBNP and S100B) were detected on two substrate (Silicon Dioxide and Gold) in a detection range of 0.10 ng/mL to 10.00 ng/mL. The biosensor demonstrated a clinically relevant limit-of-detection in ng/mL range. Bachelor of Engineering (Materials Engineering) 2019-04-08T14:19:29Z 2019-04-08T14:19:29Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/76756 en Nanyang Technological University 50 p. application/pdf |
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DRNTU::Engineering::Materials Koh, Brescia Rui Wen Point-of-care surface plasmon resonance biosensor for stroke biomarkers |
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Stroke is the second most common cause of death. Stroke is a time sensitive disease and reducing the time-to-treatment can increase patient’s access to treatment and therefore save patients’ lives. Recent studies have shown that blood-based biomarkers measurement may assist in monitoring stroke risk and prognosis. By monitoring specific stroke biomarker, stroke can be characterized and risk can be predicted thereby reducing the time-to-treatment. In this project, a point-of-care surface plasmon resonance (SPR) biosensor is developed for the detection of stroke biomarkers (NT-proBNP and S100B) using SPR Module (PhotonicSys SPR H5). SPR is a quantum electromagnetic phenomenon which emerges from the interaction of light with free electrons at a metal-dielectric interface. The novelty of this project is in the substrate as well as the reading methodology. The antibody was bonded onto the novel substrate via covalent bond for specific detection and tested with water samples. Stroke biomarkers (NT-proBNP and S100B) were detected on two substrate (Silicon Dioxide and Gold) in a detection range of 0.10 ng/mL to 10.00 ng/mL. The biosensor demonstrated a clinically relevant limit-of-detection in ng/mL range. |
author2 |
Alfred Tok Iing Yoong |
author_facet |
Alfred Tok Iing Yoong Koh, Brescia Rui Wen |
format |
Final Year Project |
author |
Koh, Brescia Rui Wen |
author_sort |
Koh, Brescia Rui Wen |
title |
Point-of-care surface plasmon resonance biosensor for stroke biomarkers |
title_short |
Point-of-care surface plasmon resonance biosensor for stroke biomarkers |
title_full |
Point-of-care surface plasmon resonance biosensor for stroke biomarkers |
title_fullStr |
Point-of-care surface plasmon resonance biosensor for stroke biomarkers |
title_full_unstemmed |
Point-of-care surface plasmon resonance biosensor for stroke biomarkers |
title_sort |
point-of-care surface plasmon resonance biosensor for stroke biomarkers |
publishDate |
2019 |
url |
http://hdl.handle.net/10356/76756 |
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1759856996034543616 |