Evidence map›Paper›PMID 36071445›Full record

ArticleBMC research notes2022

An optimized mouse model of Staphylococcus aureus infected diabetic ulcers.

Ana Isabel Mendes, Maria João Peixoto, Alexandra Pinto Marques, Jorge Pedrosa, Alexandra Gabriel Fraga

Open access · goldAbstract read
In one paragraph

Article in BMC research notes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 20% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Ana Isabel MendesSchool of Medicine, Life and Health Sciences Research Institute (ICVS), University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal.
Maria João PeixotoSchool of Medicine, Life and Health Sciences Research Institute (ICVS), University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal.
Alexandra Pinto MarquesICVS/3B's-PT Government Associate Laboratory, Braga, Guimarães, Portugal.
Jorge PedrosaSchool of Medicine, Life and Health Sciences Research Institute (ICVS), University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal.
Alexandra Gabriel FragaSchool of Medicine, Life and Health Sciences Research Institute (ICVS), University of Minho, Campus de Gualtar, 4710-057, Braga, Portugal. d8529@med.uminho.pt.
University of Minho · PT

Funding

European Commission UMINHO/BD/53/2017 from the project NORTE-08-5369-FSE-000041Fundação para a Ciência e a Tecnologia UIDB/50026/2020Fundação para a Ciência e a Tecnologia UIDP/50026/2020
6 · The paper itself

Abstract

objectiveDiabetic foot infection (DFI) represents a major healthcare burden, for which treatment is challenging owing to the pathophysiological alterations intrinsic to diabetes and the alarming increase of antimicrobial resistance. Novel therapies targeting DFI are therefore a pressing research need for which proper models of disease are required.

resultsHere, we present an optimized diabetic mouse model of methicillin-resistant Staphylococcus aureus (MRSA)-infected wounds, that resemble key features of DFI, such as pathogen invasion through wound bed and surrounding tissue, necrosis, persistent inflammation and impaired wound healing. Thus, in a time-efficient manner and using simple techniques, this model represents a suitable approach for studying emerging therapies targeting DFI caused by MRSA.

Indexed as

Diabetes MellitusDiabetic FootMethicillin-Resistant Staphylococcus aureusSkin DiseasesStaphylococcal InfectionsAnimalsDisease Models, AnimalMiceStaphylococcus aureusUlcerChronic woundsDiabetic mouse modelImpaired wound healingInflammationMRSA infection

Identifiers

PMID36071445
PMCPMC9450231
OpenAlexW4294876989

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.