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DBDA as a Novel Matrix for the Analyses of Small Molecules and Quantification of Fatty Acids by Negative Ion MALDI-TOF MS

Overview of attention for article published in Journal of the American Society for Mass Spectrometry, January 2018
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Title
DBDA as a Novel Matrix for the Analyses of Small Molecules and Quantification of Fatty Acids by Negative Ion MALDI-TOF MS
Published in
Journal of the American Society for Mass Spectrometry, January 2018
DOI 10.1007/s13361-017-1881-y
Pubmed ID
Authors

Ling Ling, Ying Li, Sheng Wang, Liming Guo, Chunsheng Xiao, Xuesi Chen, Xinhua Guo

Abstract

Matrix interference ions in low mass range has always been a concern when using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze small molecules (<500 Da). In this work, a novel matrix, N1,N4-dibenzylidenebenzene-1,4-diamine (DBDA) was synthesized for the analyses of small molecules by negative ion MALDI-TOF MS. Notably, only neat ions ([M-H]-) of fatty acids without matrix interference appeared in the mass spectra and the limit of detection (LOD) reached 0.3 fmol. DBDA also has great performance towards other small molecules such as amino acids, peptides, and nucleotide. Furthermore, with this novel matrix, the free fatty acids in serum were quantitatively analyzed based on the correlation curves with correlation coefficient of 0.99. In addition, UV-Vis experiments and molecular orbital calculations were performed to explore mechanism about DBDA used as matrix in the negative ion mode. The present work shows that the DBDA matrix is a highly sensitive matrix with few interference ions for analysis of small molecules. Meanwhile, DBDA is able to precisely quantify the fatty acids in real biological samples. Graphical Abstract ᅟ.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 16%
Student > Master 5 14%
Researcher 4 11%
Professor 2 5%
Student > Bachelor 2 5%
Other 7 19%
Unknown 11 30%
Readers by discipline Count As %
Chemistry 11 30%
Agricultural and Biological Sciences 5 14%
Biochemistry, Genetics and Molecular Biology 3 8%
Medicine and Dentistry 2 5%
Veterinary Science and Veterinary Medicine 1 3%
Other 2 5%
Unknown 13 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 April 2018.
All research outputs
#20,663,600
of 25,382,440 outputs
Outputs from Journal of the American Society for Mass Spectrometry
#3,086
of 3,835 outputs
Outputs of similar age
#345,012
of 451,277 outputs
Outputs of similar age from Journal of the American Society for Mass Spectrometry
#38
of 54 outputs
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We're also able to compare this research output to 54 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.