Evidence map›Paper›PMID 25654559›Full record

ArticleAnalytical chemistry2015

Characterizing sialic acid variants at the glycopeptide level.

Katalin F Medzihradszky, Krista Kaasik, Robert J Chalkley

Abstract read
In one paragraph

Article in Analytical chemistry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

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  12. Optimal Dissociation Methods Differ forJournal of proteome research · 2020
    Article
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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

3 authors.

Katalin F MedzihradszkyDepartment of Pharmaceutical Chemistry, School of Pharmacy, University of California, San Francisco , 600 16th Street Genentech Hall, N474A, Box 2240, San Francisco, California 94158-2517, United States.
Krista Kaasik
Robert J Chalkley

Funding

Bio-Organic Biomedical Mass Spectromy ResourceP41GM103481 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI BURLINGAME, ALMA L · 2012 to 2015
$6.4M
Howard Hughes Medical InstituteNIGMS NIH HHS 8P41GM103481NIGMS NIH HHS P41 GM103481
6 · The paper itself

Abstract

Beam-type collision-induced dissociation (CID) data of intact glycopeptides isolated from mouse liver tissue are presented to illustrate characteristic fragmentation of differentially sialylated glycopeptides. Eight glycoforms of an O-linked glycopeptide from Nucleobindin-1 are distinguished on the basis of the precursor masses and characteristic oxonium ions. We report that all sialic acid variants are prone to neutral loss from the charge reduced species in electron-transfer dissociation (ETD) fragmentation. We show how changes in sialic acid composition affect reverse phase chromatographic retention times: sialic acid addition increases glycopeptide retention times significantly; replacing the N-acetylneuraminic acid with the N-glycolyl variant leads to slightly reduced retention times, while O-acetylated sialic acid-containing glycoforms are retained longer. We then demonstrate how MS-Filter in Protein Prospector can use these diagnostic oxonium ions to find glycopeptides, by showing that a wealth of different glycopeptides can be found in a published phosphopeptide data set.

Indexed as

Protein Processing, Post-TranslationalAnimalsCalcium-Binding ProteinsChromatography, AffinityChromatography, LiquidDNA-Binding ProteinsGlycopeptidesGlycosylationLiverMiceN-Acetylneuraminic AcidNerve Tissue ProteinsNucleobindinsOxonic AcidTandem Mass SpectrometryCalcium-Binding ProteinsDNA-Binding ProteinsGlycopeptidesN-Acetylneuraminic AcidNerve Tissue ProteinsNucleobindinsOxonic Acid

Identifiers

PMID25654559
PMCPMC4367445

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.