Evidence map›Paper›PMID 32854199›Full record

ArticleMetabolites2020

A Metabolomics Workflow for Analyzing Complex Biological Samples Using a Combined Method of Untargeted and Target-List Based Approaches.

Thomas Züllig, Martina Zandl-Lang, Martin Trötzmüller, Jürgen Hartler, Barbara Plecko, Harald C Köfeler

Abstract read
In one paragraph

Article in Metabolites, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Lipid and Metabolite Annotation Using Lipid Data Analyzer.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
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  5. Article
  6. Review
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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.

Thomas ZülligCore Facility Mass Spectrometry, Medical University of Graz, 8036 Graz, Austria.
Martina Zandl-LangDepartment of Paediatrics and Adolescent Medicine, Division of General Paediatrics, University Childrens' Hospital Graz, Medical University of Graz, 8036 Graz, Austria.
Martin TrötzmüllerCore Facility Mass Spectrometry, Medical University of Graz, 8036 Graz, Austria.
Jürgen HartlerInstitute of Pharmaceutical Sciences, University of Graz, 8036 Graz, Austria.ORCID 0000-0002-1095-6458
Barbara PleckoDepartment of Paediatrics and Adolescent Medicine, Division of General Paediatrics, University Childrens' Hospital Graz, Medical University of Graz, 8036 Graz, Austria.
Harald C KöfelerCore Facility Mass Spectrometry, Medical University of Graz, 8036 Graz, Austria.

Funding

Bundesministerium für Wissenschaft, Forschung und Wirtschaft BMWFW-10.420/0005-WF/V/3c/2017
6 · The paper itself

Abstract

In the highly dynamic field of metabolomics, we have developed a method for the analysis of hydrophilic metabolites in various biological samples. Therefore, we used hydrophilic interaction chromatography (HILIC) for separation, combined with a high-resolution mass spectrometer (MS) with the aim of separating and analyzing a wide range of compounds. We used 41 reference standards with different chemical properties to develop an optimal chromatographic separation. MS analysis was performed with a set of pooled biological samples human cerebrospinal fluid (CSF), and human plasma. The raw data was processed in a first step with Compound Discoverer 3.1 (CD), a software tool for untargeted metabolomics with the aim to create a list of unknown compounds. In a second step, we combined the results obtained with our internally analyzed reference standard list to process the data along with the Lipid Data Analyzer 2.6 (LDA), a software tool for a targeted approach. In order to demonstrate the advantages of this combined target-list based and untargeted approach, we not only compared the relative standard deviation (%RSD) of the technical replicas of pooled plasma samples (

Indexed as

CSFLC-MSLDAmetabolomicsplasmaXCMS

Identifiers

PMID32854199
PMCPMC7570008

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.