Evidence map›Paper›PMID 21953096›Full record

ArticleJournal of the American Society for Mass Spectrometry2011

Separation and classification of lipids using differential ion mobility spectrometry.

Alexandre A Shvartsburg, Giorgis Isaac, Nathalie Leveque, Richard D Smith, Thomas O Metz

Erratum issuedAbstract read
In one paragraph

Article in Journal of the American Society for Mass Spectrometry, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

  1. Aziridination-Enabled Structural and Quantitative Lipidomics.Journal of the American Society for Mass Spectrometry · 2026
    Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Unveiling Glycerolipid Fragmentation by Cryogenic Infrared Spectroscopy.Journal of the American Chemical Society · 2021
    Article
  8. Review
  9. Review
  10. Article
  11. Article
  12. Imaging Isomers on a Biological Surface: A Review.Mass spectrometry (Tokyo, Japan) · 2019
    Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry and its application to complex biological samples.Journal of chromatography. B, Analytical technologies in the biomedical and life sciences · 2017
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

5 authors.

Alexandre A ShvartsburgBiological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA. alexandre.shvartsburg@pnl.gov
Giorgis Isaac
Nathalie Leveque
Richard D Smith
Thomas O Metz

Funding

The Burden of Chikungunya and Dengue Infection in KenyaU54AI081680 · NIAID · OREGON HEALTH & SCIENCE UNIVERSITY · PI KATZE, MICHAEL G · 2009 to 2013
$40.4M
WORKSHOP AND TRAINING ACTIVITIESP41RR018522 · NCRR · BATTELLE PACIFIC NORTHWEST LABORATORIES · PI SMITH, RICHARD D · 2003 to 2011
$25.1M
Adv.Proteomics & Metabolomics:Type 2 Diabet & Pre-DiabetR33DK071283 · NIDDK · BATTELLE PACIFIC NORTHWEST LABORATORIES · PI SMITH, RICHARD D · 2007 to 2009
$1.6M
Adv.Proteomics &Metabolomics:Type 2 Diabet &Pre-DiabetR21DK071283 · NIDDK · BATTELLE PACIFIC NORTHWEST LABORATORIES · PI SMITH, RICHARD D · 2005 to 2006
$656k
NCRR NIH HHS P41 RR018522NCRR NIH HHS RR 18522NIAID NIH HHS U54 AI081680NIAID NIH HHS U54AI081680NIDDK NIH HHS DK071283NIDDK NIH HHS R21 DK071283NIDDK NIH HHS R33 DK071283
6 · The paper itself

Abstract

Correlations between the dimensions of a 2-D separation create trend lines that depend on structural or chemical characteristics of the compound class and thus facilitate classification of unknowns. This broadly applies to conventional ion mobility spectrometry (IMS)/mass spectrometry (MS), where the major biomolecular classes (e.g., lipids, peptides, nucleotides) occupy different trend line domains. However, strong correlation between the IMS and MS separations for ions of same charge has impeded finer distinctions. Differential IMS (or FAIMS) is generally less correlated to MS and thus could separate those domains better. We report the first observation of chemical class separation by trend lines using FAIMS, here for lipids. For lipids, FAIMS is indeed more independent of MS than conventional IMS, and subclasses (such as phospho-, glycero-, or sphingolipids) form distinct, often non-overlapping domains. Even finer categories with different functional groups or degrees of unsaturation are often separated. As expected, resolution improves in He-rich gases: at 70% He, glycerolipid isomers with different fatty acid positions can be resolved. These results open the door for application of FAIMS to lipids, particularly in shotgun lipidomics and targeted analyses of bioactive lipids.

Indexed as

GlyceridesGlycerophospholipidsGlycolipidsHeliumIonsIsomerismLinear ModelsMass SpectrometryGlyceridesGlycerophospholipidsGlycolipidsHeliumIons

Identifiers

PMID21953096
PMCPMC3187568

What OpenQuestion holds

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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.