Evidence map›Paper›PMID 38384676›Full record

ArticleMicrobial cell (Graz, Austria)2024

Quantifying yeast lipidomics by high-performance thin-layer chromatography (HPTLC) and comparison to mass spectrometry-based shotgun lipidomics.

Thorsten Meyer, Oskar Knittelfelder, Martin Smolnig, Patrick Rockenfeller

Open access · goldAbstract read
In one paragraph

Article in Microbial cell (Graz, Austria), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Review
  2. Review
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

4 authors at 2 institutions in 1 country.

Thorsten MeyerChair of Biochemistry and Molecular Medicine, Center for Biomedical Education and Research (ZBAF), University of Witten/Herdecke (UW/H), Stockumer Str. 10, 58453 Witten, Germany.
Oskar KnittelfelderMax Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.
Martin SmolnigChair of Biochemistry and Molecular Medicine, Center for Biomedical Education and Research (ZBAF), University of Witten/Herdecke (UW/H), Stockumer Str. 10, 58453 Witten, Germany.
Patrick RockenfellerChair of Biochemistry and Molecular Medicine, Center for Biomedical Education and Research (ZBAF), University of Witten/Herdecke (UW/H), Stockumer Str. 10, 58453 Witten, Germany.
Witten/Herdecke University · DEMax Planck Institute of Molecular Cell Biology and Genetics · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipidomic analysis in diverse biological settings has become a frequent tool to increase our understanding of the processes of life. Cellular lipids play important roles not only as being the main components of cellular membranes, but also in the regulation of cell homeostasis as lipid signaling molecules. Yeast has been harnessed for biomedical research based on its good conservation of genetics and fundamental cell organisation principles and molecular pathways. Further application in so-called humanised yeast models have been developed which take advantage of yeast as providing the basics of a living cell with full control over heterologous expression. Here we present evidence that high-performance thin-layer chromatography (HPTLC) represents an effective alternative to replace cost intensive mass spectrometry-based lipidomic analyses. We provide statistical comparison of identical samples by both methods, which support the use of HPTLC for quantitative analysis of the main yeast lipid classes.

Indexed as

HPTLClipid analysislipid metabolismlipidomicsthin-layer chromatography

Identifiers

PMID38384676
PMCPMC10879857
OpenAlexW4391974735

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.