Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection

Despite significant advancements over the years, there remains an urgent need for low cost diagnostic approaches that allow for rapid, reliable and sensitive detection of malaria parasites in clinical samples. Our previous work has shown that magnetic resonance relaxometry (MRR) is a potentially hig...

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Main Authors: Fook Kong, Tian, Ye, Weijian, Peng, Weng Kung, Hou, Han Wei, Marcos, Preiser, Peter Rainer, Nguyen, Nam-Trung, Han, Jongyoon
Other Authors: Lee Kong Chian School of Medicine (LKCMedicine)
Format: Journal Article
Language:English
Published: 2015
Online Access:https://hdl.handle.net/10356/103487
http://hdl.handle.net/10220/38750
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author Fook Kong, Tian
Ye, Weijian
Peng, Weng Kung
Hou, Han Wei
Marcos
Preiser, Peter Rainer
Nguyen, Nam-Trung
Han, Jongyoon
author2 Lee Kong Chian School of Medicine (LKCMedicine)
author_facet Lee Kong Chian School of Medicine (LKCMedicine)
Fook Kong, Tian
Ye, Weijian
Peng, Weng Kung
Hou, Han Wei
Marcos
Preiser, Peter Rainer
Nguyen, Nam-Trung
Han, Jongyoon
author_sort Fook Kong, Tian
collection NTU
description Despite significant advancements over the years, there remains an urgent need for low cost diagnostic approaches that allow for rapid, reliable and sensitive detection of malaria parasites in clinical samples. Our previous work has shown that magnetic resonance relaxometry (MRR) is a potentially highly sensitive tool for malaria diagnosis. A key challenge for making MRR based malaria diagnostics suitable for clinical testing is the fact that MRR baseline fluctuation exists between individuals, making it difficult to detect low level parasitemia. To overcome this problem, it is important to establish the MRR baseline of each individual while having the ability to reliably determine any changes that are caused by the infection of malaria parasite. Here we show that an approach that combines the use of microfluidic cell enrichment with a saponin lysis before MRR detection can overcome these challenges and provide the basis for a highly sensitive and reliable diagnostic approach of malaria parasites. Importantly, as little as 0.0005% of ring stage parasites can be detected reliably, making this ideally suited for the detection of malaria parasites in peripheral blood obtained from patients. The approaches used here are envisaged to provide a new malaria diagnosis solution in the near future.
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spelling ntu-10356/1034872022-02-16T16:28:40Z Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection Fook Kong, Tian Ye, Weijian Peng, Weng Kung Hou, Han Wei Marcos Preiser, Peter Rainer Nguyen, Nam-Trung Han, Jongyoon Lee Kong Chian School of Medicine (LKCMedicine) School of Mechanical and Aerospace Engineering School of Biological Sciences Despite significant advancements over the years, there remains an urgent need for low cost diagnostic approaches that allow for rapid, reliable and sensitive detection of malaria parasites in clinical samples. Our previous work has shown that magnetic resonance relaxometry (MRR) is a potentially highly sensitive tool for malaria diagnosis. A key challenge for making MRR based malaria diagnostics suitable for clinical testing is the fact that MRR baseline fluctuation exists between individuals, making it difficult to detect low level parasitemia. To overcome this problem, it is important to establish the MRR baseline of each individual while having the ability to reliably determine any changes that are caused by the infection of malaria parasite. Here we show that an approach that combines the use of microfluidic cell enrichment with a saponin lysis before MRR detection can overcome these challenges and provide the basis for a highly sensitive and reliable diagnostic approach of malaria parasites. Importantly, as little as 0.0005% of ring stage parasites can be detected reliably, making this ideally suited for the detection of malaria parasites in peripheral blood obtained from patients. The approaches used here are envisaged to provide a new malaria diagnosis solution in the near future. Published version 2015-09-25T06:16:34Z 2019-12-06T21:13:42Z 2015-09-25T06:16:34Z 2019-12-06T21:13:42Z 2015 2015 Journal Article Fook Kong, T., Ye, W., Peng, W. K., Hou, H. W., Marcos, Preiser, P. R., et al. (2015). Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection. Scientific Reports, 5, 11425-. 2045-2322 https://hdl.handle.net/10356/103487 http://hdl.handle.net/10220/38750 10.1038/srep11425 26081638 en Scientific Reports This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ application/pdf
spellingShingle Fook Kong, Tian
Ye, Weijian
Peng, Weng Kung
Hou, Han Wei
Marcos
Preiser, Peter Rainer
Nguyen, Nam-Trung
Han, Jongyoon
Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection
title Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection
title_full Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection
title_fullStr Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection
title_full_unstemmed Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection
title_short Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection
title_sort enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection
url https://hdl.handle.net/10356/103487
http://hdl.handle.net/10220/38750
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