Evidence map›Paper›PMID 36264332›Full record

ArticleJournal of proteome research2022

High Throughput LC-MS Platform for Large Scale Screening of Bioactive Polar Lipids in Human Plasma and Serum.

Nyasha Munjoma, Giorgis Isaac, Ammara Muazzam, Olivier Cexus, Fowz Azhar, Hardev Pandha, Anthony D Whetton, Paul A Townsend, Ian D Wilson, Lee A Gethings and 1 more

Open access · greenAbstract read
In one paragraph

Article in Journal of proteome research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.4field-weighted citation impact, top 19% of its field
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

13 citing papers in PubMed, 18 citations in OpenAlex.

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  12. Small molecule biomarker discovery: Proposed workflow for LC-MS-based clinical research projects.Journal of mass spectrometry and advances in the clinical lab · 2023
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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

11 authors at 6 institutions in 2 countries.

Nyasha MunjomaScientific Operations, Waters Corporation, Wilmslow, SK9 4AX, United Kingdom.ORCID 0000-0001-8135-3972
Giorgis IsaacScientific Operations, Waters Corporation, Milford, Massachusetts 01757, United States.
Ammara MuazzamDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, Manchester Cancer Research Centre, University of Manchester, Manchester, M13 9NT, United Kingdom.
Olivier CexusFaculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7YH, United Kingdom.
Fowz AzharSalford Royal NHS Foundation Trust, Salford Royal Hospital, Salford, Manchester, M6 8HD, United Kingdom.
Hardev PandhaFaculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7YH, United Kingdom.
Anthony D WhettonDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, Manchester Cancer Research Centre, University of Manchester, Manchester, M13 9NT, United Kingdom.ORCID 0000-0002-1098-3878
Paul A TownsendDivision of Cancer Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, Manchester Cancer Research Centre, University of Manchester, Manchester, M13 9NT, United Kingdom.
Ian D WilsonDivision of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College, Du Cane Road, London, W12 0NN, United Kingdom.ORCID 0000-0002-8558-7394
Lee A GethingsScientific Operations, Waters Corporation, Wilmslow, SK9 4AX, United Kingdom.
Robert S PlumbScientific Operations, Waters Corporation, Milford, Massachusetts 01757, United States.ORCID 0000-0002-1380-9285
Manchester Academic Health Science Centre · GBUniversity of Surrey · GBWaters (United States) · USImperial College London · GBSalford Royal NHS Foundation Trust · GBWaters (United Kingdom) · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipids play a key role in many biological processes, and their accurate measurement is critical to unraveling the biology of diseases and human health. A high throughput HILIC-based (LC-MS) method for the semiquantitative screening of over 2000 lipids, based on over 4000 MRM transitions, was devised to produce an accessible and robust lipidomic screen for phospholipids in human plasma/serum. This methodology integrates many of the advantages of global lipid analysis with those of targeted approaches. Having used the method as an initial "wide class" screen, it can then be easily adapted for a more targeted analysis and quantification of key, dysregulated lipids. Robustness was assessed using 1550 continuous injections of plasma extracts onto a single column and via the evaluation of columns from 5 different batches of stationary phase. Initial screens in positive (239 lipids, 431 MRM transitions) and negative electrospray ionization (ESI) mode (232 lipids, 446 MRM transitions) were assessed for reproducibility, sensitivity, and dynamic range using analysis times of 8 min. The total number of lipids monitored using these screening methods was 433 with an overlap of 38 lipids in both modes. A polarity switching method for accurate quantification, using the same LC conditions, was assessed for intra- and interday reproducibility, accuracy, dynamic range, stability, carryover, dilution integrity, and matrix interferences and found to be acceptable. This polarity switching method was then applied to lipids important in the stratification of human prostate cancer samples.

Indexed as

LipidomicsTandem Mass SpectrometryChromatography, LiquidHumansMalePhospholipidsReproducibility of ResultsPhospholipidshigh throughputlipidomicsplasmaprostate cancerquantificationserum

Identifiers

PMID36264332
PMCPMC9639203
OpenAlexW4306912789

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.