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Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer

Francesco Del Giudice Orcid Logo, Claire Barnes Orcid Logo

Analytical Chemistry, Volume: 94, Issue: 8, Pages: 3617 - 3628

Swansea University Authors: Francesco Del Giudice Orcid Logo, Claire Barnes Orcid Logo

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DOI (Published version): 10.1021/acs.analchem.1c05208

Abstract

Biofluids such as synovial fluid, blood plasma, and saliva contain several proteins which impart non-Newtonian properties to the biofluids. The concentration of such protein macromolecules in biofluids is regarded as an important biomarker for the diagnosis of several health conditions, including ca...

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Published in: Analytical Chemistry
ISSN: 0003-2700 1520-6882
Published: American Chemical Society (ACS) 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa59330
first_indexed 2022-02-08T10:48:56Z
last_indexed 2023-01-11T14:40:32Z
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spelling 2022-10-31T17:47:52.3640168 v2 59330 2022-02-08 Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer 742d483071479b44d7888e16166b1309 0000-0002-9414-6937 Francesco Del Giudice Francesco Del Giudice true false 024232879fc13d5ceac584360af8742c 0000-0003-1031-7127 Claire Barnes Claire Barnes true false 2022-02-08 EAAS Biofluids such as synovial fluid, blood plasma, and saliva contain several proteins which impart non-Newtonian properties to the biofluids. The concentration of such protein macromolecules in biofluids is regarded as an important biomarker for the diagnosis of several health conditions, including cardiovascular disorders, joint quality, and Alzheimer’s. Existing technologies for the measurements of macromolecules in biofluids are limited; they require a long turnaround time, or require complex protocols, thus calling for alternative, more suitable, methodologies aimed at such measurements. According to the well-established relations for polymer solutions, the concentration of macromolecules in solutions can also be derived via measurement of rheological properties such as shear-viscosity and the longest relaxation time. We here introduce a microfluidic rheometer for rapid simultaneous measurement of shear viscosity and longest relaxation time of non-Newtonian solutions at different temperatures. At variance with previous technologies, our microfluidic rheometer provides a very short turnaround time of around 2 min or less thanks to the implementation of a machine-learning algorithm. We validated our platform on several aqueous solutions of poly(ethylene oxide). We also performed measurements on hyaluronic acid solutions in the clinical range for joint grade assessment. We observed monotonic behavior with the concentration for both rheological properties, thus speculating on their use as potential rheo-markers, i.e., rheological biomarkers, across several disease states. Journal Article Analytical Chemistry 94 8 3617 3628 American Chemical Society (ACS) 0003-2700 1520-6882 1 3 2022 2022-03-01 10.1021/acs.analchem.1c05208 COLLEGE NANME Engineering and Applied Sciences School COLLEGE CODE EAAS Swansea University External research funder(s) paid the OA fee (includes OA grants disbursed by the Library) F.D.G. acknowledges support from EPSRC New Investigator Award (grant ref no. EP/S036490/1). 2022-10-31T17:47:52.3640168 2022-02-08T10:47:31.7461290 Faculty of Science and Engineering School of Engineering and Applied Sciences - Biomedical Engineering Francesco Del Giudice 0000-0002-9414-6937 1 Claire Barnes 0000-0003-1031-7127 2 59330__22415__29110a600e09443fb47dd349727c5246.pdf 59330.pdf 2022-02-21T16:37:44.7776069 Output 2682260 application/pdf Version of Record true Released under the terms of a CC-BY license true eng https://creativecommons.org/licenses/by/4.0/
title Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer
spellingShingle Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer
Francesco Del Giudice
Claire Barnes
title_short Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer
title_full Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer
title_fullStr Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer
title_full_unstemmed Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer
title_sort Rapid Temperature-Dependent Rheological Measurements of Non-Newtonian Solutions Using a Machine-Learning Aided Microfluidic Rheometer
author_id_str_mv 742d483071479b44d7888e16166b1309
024232879fc13d5ceac584360af8742c
author_id_fullname_str_mv 742d483071479b44d7888e16166b1309_***_Francesco Del Giudice
024232879fc13d5ceac584360af8742c_***_Claire Barnes
author Francesco Del Giudice
Claire Barnes
author2 Francesco Del Giudice
Claire Barnes
format Journal article
container_title Analytical Chemistry
container_volume 94
container_issue 8
container_start_page 3617
publishDate 2022
institution Swansea University
issn 0003-2700
1520-6882
doi_str_mv 10.1021/acs.analchem.1c05208
publisher American Chemical Society (ACS)
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Biomedical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Biomedical Engineering
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description Biofluids such as synovial fluid, blood plasma, and saliva contain several proteins which impart non-Newtonian properties to the biofluids. The concentration of such protein macromolecules in biofluids is regarded as an important biomarker for the diagnosis of several health conditions, including cardiovascular disorders, joint quality, and Alzheimer’s. Existing technologies for the measurements of macromolecules in biofluids are limited; they require a long turnaround time, or require complex protocols, thus calling for alternative, more suitable, methodologies aimed at such measurements. According to the well-established relations for polymer solutions, the concentration of macromolecules in solutions can also be derived via measurement of rheological properties such as shear-viscosity and the longest relaxation time. We here introduce a microfluidic rheometer for rapid simultaneous measurement of shear viscosity and longest relaxation time of non-Newtonian solutions at different temperatures. At variance with previous technologies, our microfluidic rheometer provides a very short turnaround time of around 2 min or less thanks to the implementation of a machine-learning algorithm. We validated our platform on several aqueous solutions of poly(ethylene oxide). We also performed measurements on hyaluronic acid solutions in the clinical range for joint grade assessment. We observed monotonic behavior with the concentration for both rheological properties, thus speculating on their use as potential rheo-markers, i.e., rheological biomarkers, across several disease states.
published_date 2022-03-01T05:52:51Z
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