Evidence map›Paper›PMID 34368825›Full record

ArticleMolecular omics2021

Extensive heterogeneity of glycopeptides in plasma revealed by deep glycoproteomic analysis using size-exclusion chromatography.

Mayank Saraswat, Kishore Garapati, Dong-Gi Mun, Akhilesh Pandey

Open access · hybridAbstract read
In one paragraph

Article in Molecular omics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.1field-weighted citation impact, top 12% 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

15 citing papers in PubMed, 30 citations in OpenAlex.

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  15. The glycosylation in SARS-CoV-2 and its receptor ACE2.Signal transduction and targeted therapy · 2021
    Review
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

4 authors at 1 institution in 2 countries.

Mayank SaraswatDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, USA. Pandey.Akhilesh@mayo.edu.
Kishore GarapatiDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, USA. Pandey.Akhilesh@mayo.edu.ORCID 0000-0002-2759-609X
Dong-Gi MunDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, USA. Pandey.Akhilesh@mayo.edu.
Akhilesh PandeyDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, USA. Pandey.Akhilesh@mayo.edu.ORCID 0000-0001-9943-6127
Mayo Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several plasma glycoproteins are clinically useful as biomarkers in a variety of diseases. Although thousands of proteins are present in plasma, >95% of the plasma proteome by mass is represented by only 22 proteins. This necessitates strategies to deplete the abundant proteins and enrich other subsets of proteins. Although glycoproteins are abundant in plasma, in routine proteomic analyses, glycopeptides are not often investigated. Traditional methods such as lectin-based enrichment of glycopeptides followed by deglycosylation have helped understand the glycoproteome, but they lack any information about the attached glycans. Here, we apply size-exclusion chromatography (SEC) as a simple strategy to enrich intact

Indexed as

GlycopeptidesProteomicsChromatography, GelChromatography, LiquidHumansTandem Mass SpectrometryGlycopeptides

Identifiers

PMID34368825
PMCPMC8664156
OpenAlexW3190091548

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.