Evidence map›Paper›PMID 23236524›Full record

ArticlePloS one2012

Magnetic resonance imaging of soft tissue infection with iron oxide labeled granulocytes in a rat model.

Hassina Baraki, Norman Zinne, Dirk Wedekind, Martin Meier, André Bleich, Silke Glage, Hans-Juergen Hedrich, Ingo Kutschka, Axel Haverich

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. 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
2.1field-weighted citation impact, top 13% 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, 18 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

9 authors at 1 institution in 1 country.

Hassina BarakiDepartment of Cardio-Thoracic, Transplantation and Vascular Surgery, Hannover Medical School, Hannover, Germany. baraki.hassina@mh-hannover.de
Norman Zinne
Dirk Wedekind
Martin Meier
André Bleich
Silke Glage
Hans-Juergen Hedrich
Ingo Kutschka
Axel Haverich
Medizinische Hochschule Hannover · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectWe sought to detect an acute soft tissue infection in rats by magnetic resonance imaging (MRI) using granulocytes, previously labeled with superparamagnetic particles of iron oxide (SPIO). MATERIALS AND

methodsParasternal infection was induced by subcutaneous inoculation of Staphylococcus aureus suspension in rats. Granulocytes isolated from isogenic donor rats were labeled with SPIO. Infected rats were imaged by MRI before, 6 and 12 hours after intravenous injection of SPIO-labeled or unlabeled granulocytes. MR findings were correlated with histological analysis by Prussian blue staining and with re-isolated SPIO-labeled granulocytes from the infectious area by magnetic cell separation.

resultsSusceptibility effects were present in infected sites on post-contrast T2*-weighted MR images in all animals of the experimental group. Regions of decreased signal intensity (SI) in MRI were detected at 6 hours after granulocyte administration and were more pronounced at 12 hours. SPIO-labeled granulocytes were identified by Prussian blue staining in the infected tissue and could be successfully re-isolated from the infected area by magnetic cell separation.

conclusionThe application of SPIO-labeled granulocytes in MRI offers new perspectives in diagnostic specificity and sensitifity to detect early infectious processes.

Indexed as

Ferric CompoundsStaphylococcus aureusAnimalsFerrocyanidesGranulocytesMagnetic Resonance ImagingRatsSoft Tissue InfectionsStaphylococcal InfectionsFerric Compoundsferric ferrocyanideferric oxideFerrocyanides

Identifiers

PMID23236524
PMCPMC3517554
OpenAlexW2081496368

What OpenQuestion holds

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Registered trials

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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.