Evidence map›Paper›PMID 24988198›Full record

ArticleTissue engineering. Part C, Methods2015

Viability, differentiation capacity, and detectability of super-paramagnetic iron oxide-labeled muscle precursor cells for magnetic-resonance imaging.

Fahd Azzabi, Markus Rottmar, Virginija Jovaisaite, Markus Rudin, Tullio Sulser, Andreas Boss, Daniel Eberli

Abstract read
In one paragraph

Article in Tissue engineering. Part C, Methods, 2015. 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
–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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
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  6. 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

7 authors.

Fahd Azzabi1 Division of Urology, University Hospital Zurich , Zurich, Switzerland .
Markus Rottmar
Virginija Jovaisaite
Markus Rudin
Tullio Sulser
Andreas Boss
Daniel Eberli

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell therapies are a promising approach for the treatment of a variety of human conditions including stress urinary incontinence, but their success greatly depends on the biodistribution, migration, survival, and differentiation of the transplanted cells. Noninvasive in vivo cell tracking therefore presents an important aspect for translation of such a procedure into the clinics. Upon labeling with superparamagnetic iron oxide (SPIO) nanoparticles, cells can be tracked by magnetic resonance imaging (MRI), but possible adverse effect of the labeling have to be considered when labeling stem cells with SPIOs. In this study, human muscle precursor cells (hMPC) were labeled with increasing concentrations of SPIO nanoparticles (100-1600 μg/mL) and cell viability and differentiation capacity upon labeling was assessed in vitro. While a linear dependence between cell viability and nanoparticle concentration could be observed, differentiation capacity was not affected by the presence of SPIOs. Using a nude mouse model, a concentration (400 μg/mL) could be defined that allows reliable detection of hMPCs by MRI but does not influence myogenic in vivo differentiation to mature and functional muscle tissue. This suggests that such an approach can be safely used in a clinical setting to track muscle regeneration in patients undergoing cell therapy without negative effects on the functionality of the bioengineered muscle.

Indexed as

Cell DifferentiationAnimalsCell ProliferationCell SurvivalDextransFemaleHumansMagnetic Resonance ImagingMagnetite NanoparticlesMice, NudeMuscle ContractionMuscle DevelopmentMuscle ProteinsMyoblastsOrgan SpecificityPhenotypeDextransferumoxidesMagnetite NanoparticlesMuscle Proteins

Identifiers

PMID24988198
PMCPMC4313399

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.