Evidence map›Paper›PMID 39891659›Full record

ArticleAnalytical and bioanalytical chemistry2025

Species-specific optimization of oxylipin ionization in LC-MS: a design of experiments approach to improve sensitivity.

Louis Schmidt, Ulrike Garscha

Abstract read
In one paragraph

Article in Analytical and bioanalytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Louis SchmidtDepartment of Pharmaceutical/Medicinal Chemistry, Institute of Pharmacy, Greifswald University, 17489, Greifswald, Germany.ORCID http://orcid.org/0000-0001-6977-9102
Ulrike GarschaDepartment of Pharmaceutical/Medicinal Chemistry, Institute of Pharmacy, Greifswald University, 17489, Greifswald, Germany. ulrike.garscha@uni-greifswald.de.ORCID http://orcid.org/0000-0002-3645-7833

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Oxylipins are diverse bioactive signaling molecules, which occur in very low concentrations in complex matrices, posing challenges in achieving consistent and sensitive analysis. UHPLC-MS/MS is the preferred technique to separate and quantify these molecules, often optimized using a time-consuming trial-and-error approach. In this study, we applied the design of experiments (DoE) approach to systematically investigate the ionization properties of multiple oxylipin species. Fractional factorial and central composite designs were employed to detect relevant instrument parameters and optimize signal intensity in ESI-MS/MS analysis. Response surface modeling revealed distinct ionization and fragmentation behaviors between polar and apolar oxylipins, driven by their responses to interface temperature and collision-induced dissociation (CID) gas pressure. Particularly, prostaglandins and lipoxins benefit from higher CID gas pressure and lower temperatures compared to the lipophilic HODEs and HETEs to achieve optimal intensity in multiple reaction monitoring analysis. While global source parameters were optimized, analyte-specific entrance/exit potentials and collision energies required individual adjustments. The final method was applied to analyze seven oxylipin classes including leukotrienes, prostaglandins, lipoxins, resolvins, HETEs, HODE

Indexed as

OxylipinsSpectrometry, Mass, Electrospray IonizationTandem Mass SpectrometryChromatography, High Pressure LiquidLimit of DetectionLiquid Chromatography-Mass SpectrometrySpecies SpecificityOxylipinsDesign of experiments (DoE)LipidomicsMethod optimizationOxylipinsUHPLC-ESI–MS/MS

Identifiers

PMID39891659
PMCPMC11913994

What Socratic holds

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LicenceCC BY
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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 Socratic graph.