Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry

Probe electrospray ionization mass spectrometry (PESI‐MS) is an ambient ionization‐based mass spectrometry method that surpasses the original electrospray ionization technique in features such as the rapidity of analysis, simplicity of the equipment and procedure, and lower cost. This study found th...

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Detalles Bibliográficos
Autores principales: Iwano, T., Yoshimura, K., Inoue, S., Odate, T., Ogata, K., Funatsu, S., Tanihata, H., Kondo, T., Ichikawa, D., Takeda, S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Ltd. 2020
Materias:
Rapid Research Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216899/
https://www.ncbi.nlm.nih.gov/pubmed/32246473
http://dx.doi.org/10.1002/bjs.11613
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author Iwano, T.
Yoshimura, K.
Inoue, S.
Odate, T.
Ogata, K.
Funatsu, S.
Tanihata, H.
Kondo, T.
Ichikawa, D.
Takeda, S.
author_facet Iwano, T.
Yoshimura, K.
Inoue, S.
Odate, T.
Ogata, K.
Funatsu, S.
Tanihata, H.
Kondo, T.
Ichikawa, D.
Takeda, S.
author_sort Iwano, T.
collection PubMed
description Probe electrospray ionization mass spectrometry (PESI‐MS) is an ambient ionization‐based mass spectrometry method that surpasses the original electrospray ionization technique in features such as the rapidity of analysis, simplicity of the equipment and procedure, and lower cost. This study found that the PESI‐MS system with machine learning has the potential to establish a lipid‐based diagnosis of breast cancer with higher accuracy, using a simpler approach. [Image: see text] Rapid mass spectrometry for breast cancer
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spelling pubmed-72168992020-05-13 Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry Iwano, T. Yoshimura, K. Inoue, S. Odate, T. Ogata, K. Funatsu, S. Tanihata, H. Kondo, T. Ichikawa, D. Takeda, S. Br J Surg Rapid Research Communication Probe electrospray ionization mass spectrometry (PESI‐MS) is an ambient ionization‐based mass spectrometry method that surpasses the original electrospray ionization technique in features such as the rapidity of analysis, simplicity of the equipment and procedure, and lower cost. This study found that the PESI‐MS system with machine learning has the potential to establish a lipid‐based diagnosis of breast cancer with higher accuracy, using a simpler approach. [Image: see text] Rapid mass spectrometry for breast cancer John Wiley & Sons, Ltd. 2020-04-04 2020-05 /pmc/articles/PMC7216899/ /pubmed/32246473 http://dx.doi.org/10.1002/bjs.11613 Text en © 2020 The Authors. British Journal of Surgery published by John Wiley & Sons Ltd on behalf of BJS Society Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non?commercial and no modifications or adaptations are made.
spellingShingle Rapid Research Communication
Iwano, T.
Yoshimura, K.
Inoue, S.
Odate, T.
Ogata, K.
Funatsu, S.
Tanihata, H.
Kondo, T.
Ichikawa, D.
Takeda, S.
Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry
title Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry
title_full Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry
title_fullStr Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry
title_full_unstemmed Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry
title_short Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry
title_sort breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry
topic Rapid Research Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216899/
https://www.ncbi.nlm.nih.gov/pubmed/32246473
http://dx.doi.org/10.1002/bjs.11613
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