Evidence map›Paper›PMID 40790030›Full record

ArticleNature communications2025

Computationally unmasking each fatty acyl C=C position in complex lipids by routine LC-MS/MS lipidomics.

Leonida M Lamp, Gosia M Murawska, Joseph P Argus, Aaron M Armando, Radu A Talmazan, Marlene Pühringer, Evelyn Rampler, Oswald Quehenberger, Edward A Dennis, Jürgen Hartler

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2025. 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
–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

2 citing papers in PubMed.

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

10 authors.

Leonida M Lamp *Institute of Pharmaceutical Sciences, University of Graz, Graz, Austria.ORCID http://orcid.org/0000-0003-3622-9432
Gosia M Murawska *Department of Pharmacology, University of California San Diego, La Jolla, CA, USA.
Joseph P Argus *Department of Pharmacology, University of California San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0000-0001-9855-1975
Aaron M ArmandoDepartment of Pharmacology, University of California San Diego, La Jolla, CA, USA.ORCID http://orcid.org/0009-0003-4598-7371
Radu A TalmazanLaboratoire de Physique et Chimie Théoriques, Université de Lorraine, Nancy, France.ORCID http://orcid.org/0000-0001-6678-7801
Marlene PühringerDepartment of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.ORCID http://orcid.org/0000-0003-1357-1884
Evelyn RamplerDepartment of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Vienna, Austria.ORCID http://orcid.org/0000-0002-9429-7663
Oswald QuehenbergerDepartment of Pharmacology, University of California San Diego, La Jolla, CA, USA.
Edward A DennisDepartment of Pharmacology, University of California San Diego, La Jolla, CA, USA. edennis@ucsd.edu.ORCID http://orcid.org/0000-0003-3738-3140
Jürgen HartlerInstitute of Pharmaceutical Sciences, University of Graz, Graz, Austria. juergen.hartler@uni-graz.at.ORCID http://orcid.org/0000-0002-1095-6458

Funding

ACTION OF LIPOLYTIC ENZYMESR01GM020501 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DENNIS, EDWARD A · 1985 to 2020
$7.3M
Action of Lipolytic EnzymesR35GM139641 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI EDWARD A DENNIS · 2021 to 2026
$2.6M
NIGMS NIH HHS R01 GM020501NIGMS NIH HHS R35 GM139641
6 · The paper itself

Abstract

Identifying carbon-carbon double bond (C=C) positions in complex lipids is essential for elucidating physiological and pathological processes. Currently, this is impossible in high-throughput analyses of native lipids without specialized instrumentation that compromises ion yields. Here, we demonstrate automated, chain-specific identification of C=C positions in complex lipids based on the retention time derived from routine reverse-phase chromatography tandem mass spectrometry (RPLC-MS/MS). We introduce LC=CL, a computational solution that utilizes a comprehensive database capturing the elution profile of more than 2400 complex lipid species identified in RAW264.7 macrophages, including 1145 newly reported compounds. Using machine learning, LC=CL provides precise and automated C=C position assignments, adaptable to any suitable chromatographic condition. To illustrate the power of LC=CL, we re-evaluated previously published data and discovered new C=C position-dependent specificity of cytosolic phospholipase A

Indexed as

LipidomicsLipidsAnimalsLiquid Chromatography-Mass SpectrometryMachine LearningMiceRAW 264.7 CellsLipids

Identifiers

PMID40790030
PMCPMC12340080

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.