Peculiarities of data interpretation upon direct tissue analysis by Fourier transform ion cyclotron resonance mass spectrometry

other OA: closed public-domain-us
View on PubMed View at publisher
⚙ AI-generated summary by gemini-2.5-flash-lite, 2026-06-09 ⓘ

High-resolution Fourier transform ion cyclotron resonance mass spectrometry enables accurate data interpretation for direct tissue analysis by resolving isobaric species and identifying differentially expressed lipids in endometriosis.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

Abstract

The importance of high-resolution mass spectrometry for the correct data interpretation of a direct tissue analysis is demonstrated with an example of its clinical application for an endometriosis study. Multivariate analysis of the data discovers lipid species differentially expressed in different tissues under investigation. High-resolution mass spectrometry allows unambiguous separation of peaks with close masses that correspond to proton and sodium adducts of phosphatidylcholines and to phosphatidylcholines differing in double bond number.

My notes (saved in your browser only)

Condition tags

endometriosis

MeSH descriptors

Algorithms Lipids Models, Statistical Ovarian Cysts Ovarian Cysts Spectrometry, Mass, Electrospray Ionization Biomarkers Biomarkers Computer Simulation Cyclotrons Data Interpretation, Statistical Female Humans Lipids Lipids Multivariate Analysis Ovarian Cysts Protons Reproducibility of Results Sensitivity and Specificity

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-09-27T09:11:36.575535+00:00
pubmed
last seen: 2026-05-13T22:20:54.390225+00:00
unpaywall
last seen: 2026-09-28T06:20:55.906821+00:00
License: public-domain-us · commercial use OK · attribution required
Courtesy of the U.S. National Library of Medicine