Evidence map›Paper›PMID 40995955›Full record

ArticleThe Analyst2025

Single-cell lipidomics: performance evaluation across four liquid chromatography mass spectrometry (LC-MS) systems.

Johanna von Gerichten, Kyle D G Saunders, Matt Spick, Melanie J Bailey

Abstract read
In one paragraph

Article in The Analyst, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Special Issue "The Role of Lipids in Health and Diseases".International journal of molecular sciences · 2026
    Article
  3. Article
  4. 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

4 authors.

Johanna von GerichtenSchool of Chemistry and Chemical Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, UK.
Kyle D G SaundersSchool of Chemistry and Chemical Engineering, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, UK.
Matt SpickSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
Melanie J BaileyDepartment of Infectious Diseases, Guy's Hospital, King's College London, London, UK. melanie.j.bailey@kcl.ac.uk.ORCID http://orcid.org/0000-0001-9050-7910

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell lipidomics holds tremendous promise for understanding a wide range of pathological conditions involving heterogenous cell populations, including infection, cancer, diabetes, and cardiovascular disease and yet its widespread adoption has been hitherto limited. Although Liquid Chromatography Mass Spectrometry (LC-MS) is a globally established method for lipidomics, its application to single cells has been considered particularly challenging, if not impossible, due to the very low sample volume and the high dynamic range and structural complexity of cellular lipids. Recent advances have shown that LC-MS-based single-cell lipidomics is achievable, offering the benefit of sampling cells in their native state, as well as chromatographic separation to reduce matrix effects and enhance peak annotation. In this study, we advocate for wider adoption of single-cell lipidomics by demonstrating that a range of widely accessible LC-MS platforms can successfully generate single-cell lipid profiles. Using four distinct instrumental configurations, we provide a perspective on the achievable depth of coverage and annotation. We show that polarity switching, ion mobility spectrometry, and electron-activated dissociation significantly enhance both lipidome coverage and confidence in lipid identification from single cells.

Indexed as

LipidomicsLipidsMass SpectrometrySingle-Cell AnalysisChromatography, LiquidHumansLiquid Chromatography-Mass SpectrometryLipids

Identifiers

PMID40995955
PMCPMC12462284

What Socratic 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 Socratic graph.