Evidence map›Paper›PMID 37310720›Full record

ArticleAnalytical chemistry2023

DiffN Selection of Tandem Mass Spectrometry Precursors.

Tyler S Larson, Cameron D Worthington, Matthew D Verber, James E Keating, Matthew R Lockett, Gary L Glish

Abstract read
In one paragraph

Article in Analytical chemistry, 2023. 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

6 authors.

Tyler S LarsonDepartment of Chemistry, University of North Carolina at Chapel Hill, Kenan and Caudill Laboratories, Chapel Hill, North Carolina 27599-3290, United States.
Cameron D WorthingtonDepartment of Chemistry, University of North Carolina at Chapel Hill, Kenan and Caudill Laboratories, Chapel Hill, North Carolina 27599-3290, United States.
Matthew D VerberChemistry Electronics Core Laboratory, University of North Carolina at Chapel Hill, Kenan Laboratory, Chapel Hill, North Carolina 27599-3290, United States.
James E KeatingDepartment of Chemistry, University of North Carolina at Chapel Hill, Kenan and Caudill Laboratories, Chapel Hill, North Carolina 27599-3290, United States.
Matthew R LockettDepartment of Chemistry, University of North Carolina at Chapel Hill, Kenan and Caudill Laboratories, Chapel Hill, North Carolina 27599-3290, United States.ORCID 0000-0003-4851-7757
Gary L GlishDepartment of Chemistry, University of North Carolina at Chapel Hill, Kenan and Caudill Laboratories, Chapel Hill, North Carolina 27599-3290, United States.ORCID 0000-0003-2418-4126

Funding

Paper-based cultures supporting tissue-like structures for biochemical studies of oxygen gradients and screening applicationsR35GM128697 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Matthew Ryen Lockett · 2018 to 2026
$3.1M
NIGMS NIH HHS R35 GM128697
6 · The paper itself

Abstract

Current data-dependent acquisition (DDA) approaches select precursor ions for tandem mass spectrometry (MS/MS) characterization based on their absolute intensity, known as a TopN approach. Low-abundance species may not be identified as biomarkers in a TopN approach. Herein, a new DDA approach is proposed, DiffN, which uses the relative differential intensity of ions between two samples to selectively target species undergoing the largest fold changes for MS/MS. Using a dual nano-electrospray (nESI) ionization source which allows samples contained in separate capillaries to be analyzed in parallel, the DiffN approach was developed and validated with well-defined lipid extracts. A dual nESI source and DiffN DDA approach was applied to quantify the differences in lipid abundance between two colorectal cancer cell lines. The SW480 and SW620 lines represent a matched pair from the same patient: the SW480 cells from a primary tumor and the SW620 cells from a metastatic lesion. A comparison of TopN and DiffN DDA approaches on these cancer cell samples highlights the ability of DiffN to increase the likelihood of biomarker discovery and the decreased probability of TopN to efficiently select lipid species that undergo large fold changes. The ability of the DiffN approach to efficiently select precursor ions of interest makes it a strong candidate for lipidomic analyses. This DiffN DDA approach may also apply to other molecule classes (e.g., other metabolites or proteins) that are amenable to shotgun analyses.

Indexed as

ProteinsTandem Mass SpectrometryIonsLipidsIonsLipidsProteins

Identifiers

PMID37310720
PMCPMC10640856

What OpenQuestion holds

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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.