Article (Scientific journals)
Morphometric Cell Classification for Single-Cell MALDI-Mass Spectrometry Imaging
Scupakova, Klara; Dewez, Frédéric; Walch, Axel et al.
2020In Angewandte Chemie
 

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Keywords :
imaging; lipids; mass spectrometry; morphometry; single-cell analysis
Abstract :
[en] The large‐scale and label‐free molecular characterization of single cells in their natural tissue habitat remains a major challenge in molecular biology. We present a method that integrates morphometric image analysis to delineate and classify individual cells with their single‐cell‐specific molecular profiles. This approach provides a new means to study spatial biological processes such as cancer field effects and the relationship between morphometric and molecular features.
Disciplines :
Chemistry
Author, co-author :
Scupakova, Klara;  Universiteit Maastricht > Maastricht MultiModal Molecular Imaging Institute
Dewez, Frédéric ;  Université de Liège - ULiège > MolSys
Walch, Axel;  Helmholtz Zentrum Munchen > Research Unit Analytical Pathology
Heeren, Ron M.A;  Universiteit Maastricht > Maastricht MultiModal Molecular Imaging Institute
Balluff, Benjamin;  Universiteit Maastricht > Maastricht MultiModal Molecular Imaging Institute
Language :
English
Title :
Morphometric Cell Classification for Single-Cell MALDI-Mass Spectrometry Imaging
Publication date :
15 July 2020
Journal title :
Angewandte Chemie
ISSN :
0170-9046
Publisher :
Verlag Chemie, Weinheim, Germany
Funders :
EU - European Union [BE]
NIH - National Institutes of Health [US-MD] [US-MD]
Maastricht Imaging Valley [NL]
Funding text :
The authors would like to thank Prof. dr. N. D. Bouvy from MUMC+, Maastricht, The Netherlands, for providing the porcine colon tissue. This work was financially supported by the Dutch province of Limburg as part of the “LINK” program, as well as funding from the National Institutes of Health (NIH) of the United States of America (NIH R01 CA213492). BB and FD acknowledge the financial support of the European Union (ERA-NET TRANSCAN 2; Grant No. 643638). FD received support from the Joint Imaging Valley program of the University of Liège and the Maastricht University.
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