Mass Spectrometry is a peer-reviewed, open access journal publishing articles in all areas of mass spectrometry. Published continuously online, the journal is fully indexed in J-STAGE and PubMed Central.
Mass Spectrometry welcomes submissions from around the world.

About the journal

Mass Spectrometry is an academic journal on both fundamentals and applications of mass spectrometry, owned and published by the Mass Spectrometry Society of Japan (MSSJ).

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Readers

Anyone may access all articles in Mass Spectrometry from J-STAGE and PMC.

 

Contact

This site is operated by the Mass Spectrometry Society of Japan.

The Mass Spectrometry Society of Japan
c/o Academy Center, Yamabuki-cho 358-5, Shinjuku-ku, Tokyo 162-0801, Japan
TEL: +81-3-6824-9378
E-mail: mssj-post[at]bunken.co.jp
(Note : change [at] to @ when typing in address.)

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Latest articles

Original ArticleJuly 24, 2024

Analysis of the Correlation between Cholesterol Levels in Blood Using Clinical Data and Hair Using Mass Spectrometry Imaging

Erika Nagano, Hiromi Saito, Tetsuya Mannari, Munekazu Kuge, Kazuki Odake, Shuichi Shimma

Mass spectrometry imaging (MSI) is a technique that visualizes the distribution of molecules by ionizing the components on the surface of a sample and directly detecting them. Previously, MSI using hair has primarily been used in the forensic field to detect illegal drugs.

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Original ArticleJuly 17, 2024

Electrospray ionization mass spectrometry of neat undiluted ionic liquid (IL) and the analysis of protein with the doping of IL were performed using high-pressure electrospray. The use of disposable micropipette tips as emitters eased the handling of viscous and easy-to-clog samples and improved the reproducibility of the measurement.

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Original ArticleJuly 11, 2024

Ambient Mass Spectrometry and Machine Learning-Based Diagnosis System for Acute Coronary Syndrome

Que N. N. Tran, Takeshi Moriguchi, Masateru Ueno, Tomohiko Iwano, Kentaro Yoshimura

Aims: The purpose of this study is to establish a novel diagnosis system in early acute coronary syndrome (ACS) using probe electrospray ionization-mass spectrometry (PESI-MS) and machine learning (ML) and to validate the diagnostic accuracy.

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