Evidence map›Paper›PMID 33613550›Full record

ArticleFrontiers in immunology2020

Bioinformatic Analysis of the Wound Peptidome Reveals Potential Biomarkers and Antimicrobial Peptides.

Erik Hartman, Karl Wallblom, Mariena J A van der Plas, Jitka Petrlova, Jun Cai, Karim Saleh, Sven Kjellström, Artur Schmidtchen

Open access · goldAbstract readComparative Study
In one paragraph

Article in Frontiers in immunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

17 citing papers in PubMed, 26 citations in OpenAlex.

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  10. Origins, Technological Advancement, and Applications of Peptidomics.Methods in molecular biology (Clifton, N.J.) · 2024
    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

8 authors at 3 institutions in 2 countries.

Erik HartmanDivision of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden.
Karl WallblomDivision of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden.
Mariena J A van der PlasDivision of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden.
Jitka PetrlovaDivision of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden.
Jun CaiLEO Foundation Center for Cutaneous Drug Delivery, Department of Pharmacy, University of Copenhagen, Copenhagen, Denmark.
Karim SalehDivision of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden.
Sven KjellströmDivision of Mass Spectrometry, Department of Clinical Sciences, Lund University, Lund, Sweden.
Artur SchmidtchenDivision of Dermatology and Venereology, Department of Clinical Sciences, Lund University, Lund, Sweden.
Lund University · SEUniversity of Copenhagen · DKBispebjerg Hospital · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Wound infection is a common and serious medical condition with an unmet need for improved diagnostic tools. A peptidomic approach, aided by mass spectrometry and bioinformatics, could provide novel means of identifying new peptide biomarkers for wound healing and infection assessment. Wound fluid is suitable for peptidomic analysis since it is both intimately tied to the wound environment and is readily available. In this study we investigate the peptidomes of wound fluids derived from surgical drainages following mastectomy and from wound dressings following facial skin grafting. By applying sorting algorithms and open source third party software to peptidomic label free tandem mass spectrometry data we provide an unbiased general methodology for analyzing and differentiating between peptidomes. We show that the wound fluid peptidomes of patients are highly individualized. However, differences emerge when grouping the patients depending on wound type. Furthermore, the abundance of peptides originating from documented antimicrobial regions of hemoglobin in infected wounds may contribute to an antimicrobial wound environment, as determined by

Indexed as

AlgorithmsAmino Acid SequenceBiomarkersBody FluidsChromatography, LiquidComputational BiologyComputer SimulationDrainageFaceFemaleHemoglobinsHumansMastectomyNeural Networks, ComputerPeptide FragmentsPlasmaBiomarkersHemoglobinsPeptide FragmentsPore Forming Cytotoxic ProteinsProteomeantimicrobial peptidebioinformaticsbiomarkershemoglobinmass spectrometrypeptidomicswound healingwound infection

Identifiers

PMID33613550
PMCPMC7888259
OpenAlexW3129124710

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.