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Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
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Sensors and Materials, Volume 30, Number 2 (2018)
Copyright(C) MYU K.K.
pp. 157-166
S&M1482 30th Commemorative Article
https://doi.org/10.18494/SAM.2018.1711
Published: January 26, 2018

Nuclear Magnetic Resonance Microscopy for In Vivo Metabolomics, Digitally Twinned by Computational Systems Biology, Needs a Sensitivity Boost [PDF]

Jan Gerrit Korvink, Vlad Badilita, Lorenzo Bordonali, Mazin Jouda, Dario Mager, and Neil MacKinnon

(Received July 26, 2017; Accepted September 26, 2017)

Keywords: nuclear magnetic resonance, magnetic resonance imaging, Caenorhabiditis elegans, microcoils, microresonators

The metabolism of an organism is regulated at the cellular level, yet is strongly influenced by its environment. The precise metabolomic study of living organisms is currently hampered by measurement sensitivity; most metabolomic measurement techniques involve some compromise, whereby averaging is performed over a volume significantly larger than a single cell, or require the invasion of the organism, or an arrested state of the organism. Nuclear magnetic resonance (NMR) is an inherently noninvasive chemometric and imaging method, and hence, in principle, suitable for metabolomic measurements. The digital twin of metabolomics is computational systems biology, such that NMR microscopy is potentially a viable approach to joining the theoretical and experimental explorations of the metabolomic and behavioural responses of organisms. In this study, we consider the challenge of performing in vivo NMRbased metabolomics on the small organism Caenorhabiditis elegans, point the way towards possible solutions created using MEMS techniques, and highlight currently insurmountable challenges.

Corresponding author: Jan Gerrit Korvink


Cite this article
Jan Gerrit Korvink, Vlad Badilita, Lorenzo Bordonali, Mazin Jouda, Dario Mager, and Neil MacKinnon, Nuclear Magnetic Resonance Microscopy for In Vivo Metabolomics, Digitally Twinned by Computational Systems Biology, Needs a Sensitivity Boost, Sens. Mater., Vol. 30, No. 2, 2018, p. 157-166.



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