Evidence map›Paper›PMID 27110112›Full record

ArticleInternational journal of nanomedicine2016

Labeling of mesenchymal stem cells for MRI with single-cell sensitivity.

Angela Ariza de Schellenberger, Harald Kratz, Tracy D Farr, Norbert Löwa, Ralf Hauptmann, Susanne Wagner, Matthias Taupitz, Jörg Schnorr, Eyk A Schellenberger

Open access · goldAbstract read
In one paragraph

Article in International journal of nanomedicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

20 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Stem Cell Tracing Through MR Molecular Imaging.Tissue engineering and regenerative medicine · 2018
    Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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 2 institutions in 2 countries.

Angela Ariza de SchellenbergerDepartment of Radiology, Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Harald KratzDepartment of Radiology, Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Tracy D FarrDepartment of Experimental Neurology, Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany; School of Life Sciences, University of Nottingham, Medical School, Nottingham, UK.
Norbert LöwaDepartment of Biomagnetic Signals, Physikalisch-Technische Bundesanstalt Berlin, Berlin, Germany.
Ralf HauptmannDepartment of Radiology, Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Susanne WagnerDepartment of Radiology, Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Matthias TaupitzDepartment of Radiology, Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Jörg SchnorrDepartment of Radiology, Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Eyk A SchellenbergerDepartment of Radiology, Center for Stroke Research Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Charité - Universitätsmedizin Berlin · DEPhysikalisch-Technische Bundesanstalt · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sensitive cell detection by magnetic resonance imaging (MRI) is an important tool for the development of cell therapies. However, clinically approved contrast agents that allow single-cell detection are currently not available. Therefore, we compared very small iron oxide nanoparticles (VSOP) and new multicore carboxymethyl dextran-coated iron oxide nanoparticles (multicore particles, MCP) designed by our department for magnetic particle imaging (MPI) with discontinued Resovist(®) regarding their suitability for detection of single mesenchymal stem cells (MSC) by MRI. We achieved an average intracellular nanoparticle (NP) load of >10 pg Fe per cell without the use of transfection agents. NP loading did not lead to significantly different results in proliferation, colony formation, and multilineage in vitro differentiation assays in comparison to controls. MRI allowed single-cell detection using VSOP, MCP, and Resovist(®) in conjunction with high-resolution T2*-weighted imaging at 7 T with postprocessing of phase images in agarose cell phantoms and in vivo after delivery of 2,000 NP-labeled MSC into mouse brains via the left carotid artery. With optimized labeling conditions, a detection rate of ~45% was achieved; however, the experiments were limited by nonhomogeneous NP loading of the MSC population. Attempts should be made to achieve better cell separation for homogeneous NP loading and to thus improve NP-uptake-dependent biocompatibility studies and cell detection by MRI and future MPI. Additionally, using a 7 T MR imager equipped with a cryocoil resulted in approximately two times higher detection. In conclusion, we established labeling conditions for new high-relaxivity MCP, VSOP, and Resovist(®) for improved MRI of MSC with single-cell sensitivity.

Indexed as

Contrast MediaAnimalsCells, CulturedDextransMagnetic Resonance ImagingMagnetite NanoparticlesMesenchymal Stem CellsMiceMice, Inbred C57BLPhantoms, ImagingSingle-Cell AnalysisContrast MediaDextransferumoxidesMagnetite Nanoparticlesmagnetic field microdistortionsMCPmesenchymal stem cellsResovist®single-cell imagingVSOP

Identifiers

PMID27110112
PMCPMC4835118
OpenAlexW2338578301

What OpenQuestion 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 OpenQuestion graph.