Evidence map›Paper›PMID 35391562›Full record

ArticleHistochemistry and cell biology2022

A simple preparation step to remove excess liquid lipids in white adipose tissue enabling improved detection of metabolites via MALDI-FTICR imaging MS.

Qian Wang, Na Sun, Thomas Kunzke, Achim Buck, Jian Shen, Verena M Prade, Barbara Stöckl, Jun Wang, Annette Feuchtinger, Axel Walch

Open access · hybridAbstract read
In one paragraph

Article in Histochemistry and cell biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.6field-weighted citation impact, top 42% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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  5. In focus in HCB.Histochemistry and cell biology · 2022
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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

10 authors at 1 institution in 1 country.

Qian Wang *Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Na Sun *Research Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Thomas KunzkeResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Achim BuckResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Jian ShenResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Verena M PradeResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Barbara StöcklResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Jun WangResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Annette FeuchtingerResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Axel WalchResearch Unit Analytical Pathology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany. axel.walch@helmholtz-muenchen.de.ORCID http://orcid.org/0000-0001-5578-4023
Helmholtz Zentrum München · DE

Funding

China Scholarship Council 202008320313Deutsche Forschungsgemeinschaft SFB 205 / S01Deutsche Forschungsgemeinschaft SFB824 / TP C04
6 · The paper itself

Abstract

Matrix-assisted laser desorption ionization (MALDI) Fourier transform ion cyclotron resonance (FTICR) imaging mass spectrometry (MS) is a powerful technology used to analyze metabolites in various tissues. However, it faces significant challenges in studying adipose tissues. Poor matrix distribution and crystallization caused by excess liquid lipids on the surface of tissue sections hamper m/z species detection, an adverse effect that particularly presents in lipid-rich white adipose tissue (WAT). In this study, we integrated a simple and low-cost preparation step into the existing MALDI-FTICR imaging MS pipeline. The new method-referred to as filter paper application-is characterized by an easy sample handling and high reproducibility. The aforementioned filter paper is placed onto the tissue prior to matrix application in order to remove the layer of excess liquid lipids. Consequently, MALDI-FTICR imaging MS detection was significantly improved, resulting in a higher number of detected m/z species and higher ion intensities. After analyzing various durations of filter paper application, 30 s was found to be optimal, resulting in the detection of more than 3700 m/z species. Apart from the most common lipids found in WAT, other molecules involved in various metabolic pathways were detected, including nucleotides, carbohydrates, and amino acids. Our study is the first to propose a solution to a specific limitation of MALDI-FTICR imaging MS in investigating lipid-rich WAT. The filter paper approach can be performed quickly and is particularly effective for achieving uniform matrix distribution on fresh frozen WAT while maintaining tissue integrity. It thus helps to gain insight into the metabolism in WAT.

Indexed as

Adipose Tissue, WhiteLipidsFourier AnalysisReproducibility of ResultsSpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationLipidsFilter paperLayer of excess liquid lipidsMALDI-FTICR imaging MSMetaboliteWhite adipose tissue

Identifiers

PMID35391562
PMCPMC9114030
OpenAlexW4226026003

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.