Evidence map›Paper›PMID 28294158›Full record

ArticleScientific reports2017

Improved MALDI imaging MS analysis of phospholipids using graphene oxide as new matrix.

Zhongjie Wang, Yan Cai, Yi Wang, Xinwen Zhou, Ying Zhang, Haojie Lu

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.4field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 50 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Zhongjie WangShanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, P. R. China.
Yan CaiDepartment of Chemistry, Fudan University, Shanghai, 200433, P. R. China.
Yi WangShanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, P. R. China.
Xinwen ZhouShanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, P. R. China.
Ying ZhangShanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, P. R. China.
Haojie LuShanghai Cancer Center and Institutes of Biomedical Sciences, Fudan University, Shanghai 200032, P. R. China.
Fudan University Shanghai Cancer Center · CNFudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Matrix assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is an increasingly important technique for detection and spatial localization of phospholipids on tissue. Due to the high abundance and being easy-to-ionize of phosphatidylcholine (PC), therefore, selecting matrix to yield signals of other lipids has become the most crucial factor for a successful MALDI-IMS analysis of phospholipids. Herein, graphene oxide (GO) was proposed as a new matrix to selectively enhance the detection of other types of phospholipids that are frequently suppressed by the presence of PC in positive mode. Compared to the commonly used matrix DHB, GO matrix significantly improved signal-to-noise ratios of phospholipids as a result of its high desorption/ionization efficiency for nonpolar compounds. Also, GO afforded homogeneous crystallizations with analytes due to its monolayer structure and good dispersion, resulting in better reproducibility of shot-to-shot (CV < 13%) and spot-to-spot (CV < 14%) analysis. Finally, GO matrix was successfully applied to simultaneous imaging of PC, PE, PS and glycosphingolipid in the mouse brain, with a total of 65 phospholipids identified.

Identifiers

PMID28294158
PMCPMC5353552
OpenAlexW2666543565

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.