Evidence map›Paper›PMID 30102274›Full record

ArticleJournal of visualized experiments : JoVE2018

An Efficient Sample Preparation Method to Enhance Carbohydrate Ion Signals in Matrix-assisted Laser Desorption/Ionization Mass Spectrometry.

Yu-Meng Ou, Shu-Yun Kuo, Hsun Lee, Huan-Tsung Chang, Yi-Sheng Wang

Open access · greenAbstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 53% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Article
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

5 authors at 2 institutions in 1 country.

Yu-Meng OuGenomic Research Center, Academia Sinica; Department of Chemistry, National Taiwan University.
Shu-Yun KuoGenomic Research Center, Academia Sinica.
Hsun LeeGenomic Research Center, Academia Sinica.
Huan-Tsung ChangDepartment of Chemistry, National Taiwan University.
Yi-Sheng WangGenomic Research Center, Academia Sinica; wer@gate.sinica.edu.tw.
Academia Sinica · TWNational Taiwan University · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sample preparation is a critical process in mass spectrometry (MS) analysis of carbohydrates. Although matrix-assisted laser desorption/ionization (MALDI) MS is the method of choice in carbohydrate analysis, poor ion signal and data reproducibility of carbohydrate samples continue to be severe problems. For quantitative analysis of carbohydrates, an effective analytical protocol providing superior data quality is necessary. This video demonstrates sample preparation protocols to improve signal intensity and minimize data variation of carbohydrates in MALDI-MS. After drying and crystallization of sample droplets, the crystal morphology is reformed by methanol before mass spectrometric analysis. The enhancement in carbohydrate signal is examined with MALDI imaging mass spectrometry (IMS). Experimental results show that crystal reformation adjusts crystalline structures and redistributes carbohydrate analytes. In comparison with the dried droplet preparation method in conventional MALDI-MS, reforming carbohydrate crystal morphologies with methanol shows significantly better signal intensity, ion image distribution, and data stability. Since the protocols demonstrated herein do not involve changes in sample composition, they are generally applicable to various carbohydrates and matrixes.

Indexed as

CarbohydratesSpecimen HandlingSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationCarbohydrates

Identifiers

PMID30102274
PMCPMC6126579
OpenAlexW2887504670

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.