Evidence map›Paper›PMID 30257709›Full record

ArticleStem cell research & therapy2018

Development and validation of broad-spectrum magnetic particle labelling processes for cell therapy manufacturing.

Richard Harrison, Hilda Anaid Lugo Leija, Stephanie Strohbuecker, James Crutchley, Sarah Marsh, Chris Denning, Alicia El Haj, Virginie Sottile

Abstract read
In one paragraph

Article in Stem cell research & therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. In Vitro Innovation of Tendon Tissue Engineering Strategies.International journal of molecular sciences · 2020
    Review
  4. Review
  5. 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

8 authors.

Richard HarrisonWolfson Centre for Stem Cells, Tissue Engineering and Modelling (STEM), School of Medicine, The University of Nottingham, Nottingham, NG7 2RD, UK.
Hilda Anaid Lugo LeijaWolfson Centre for Stem Cells, Tissue Engineering and Modelling (STEM), School of Medicine, The University of Nottingham, Nottingham, NG7 2RD, UK.
Stephanie StrohbueckerWolfson Centre for Stem Cells, Tissue Engineering and Modelling (STEM), School of Medicine, The University of Nottingham, Nottingham, NG7 2RD, UK.
James CrutchleyWolfson Centre for Stem Cells, Tissue Engineering and Modelling (STEM), School of Medicine, The University of Nottingham, Nottingham, NG7 2RD, UK.
Sarah MarshWolfson Centre for Stem Cells, Tissue Engineering and Modelling (STEM), School of Medicine, The University of Nottingham, Nottingham, NG7 2RD, UK.
Chris DenningWolfson Centre for Stem Cells, Tissue Engineering and Modelling (STEM), School of Medicine, The University of Nottingham, Nottingham, NG7 2RD, UK.
Alicia El HajInstitute for Science and Technology in Medicine-Keele University, Stoke-on-Trent, ST4 7QB, UK.
Virginie SottileWolfson Centre for Stem Cells, Tissue Engineering and Modelling (STEM), School of Medicine, The University of Nottingham, Nottingham, NG7 2RD, UK. virginie.sottile@nottingham.ac.uk.ORCID 0000-0002-6064-5738

Funding

Biotechnology and Biological Sciences Research Council BB/L013827/1
6 · The paper itself

Abstract

backgroundStem cells are increasingly seen as a solution for many health challenges for an ageing population. However, their potential benefits in the clinic are currently curtailed by technical challenges such as high cell dose requirements and point of care delivery, which pose sourcing and logistics challenges. Cell manufacturing solutions are currently in development to address the supply issue, and ancillary technologies such as nanoparticle-based labelling are being developed to improve stem cell delivery and enable post-treatment follow-up.

methodsThe application of magnetic particle (MP) labelling to potentially scalable cell manufacturing processes was investigated in a range of therapeutically relevant cells, including mesenchymal stromal cells (MSC), cardiomyocytes (CMC) and neural progenitor cells (ReN). The efficiency and the biological effect of particle labelling were analysed using fluorescent imaging and cellular assays.

resultsFlow cytometry and fluorescent microscopy confirmed efficient labelling of monolayer cultures. Viability was shown to be retained post labelling for all three cell types. MSC and CMC demonstrated higher tolerance to MP doses up to 100× the standard concentration. This approach was also successful for MP labelling of suspension cultures, demonstrating efficient MP uptake within 3 h, while cell viability was unaffected by this suspension labelling process. Furthermore, a procedure to enable the storing of MP-labelled cell populations to facilitate cold chain transport to the site of clinical use was investigated. When MP-labelled cells were stored in hypothermic conditions using HypoThermosol solution for 24 h, cell viability and differentiation potential were retained post storage for ReN, MSC and beating CMC.

conclusionsOur results show that a generic MP labelling strategy was successfully developed for a range of clinically relevant cell populations, in both monolayer and suspension cultures. MP-labelled cell populations were able to undergo transient low-temperature storage whilst maintaining functional capacity in vitro. These results suggest that this MP labelling approach can be integrated into cell manufacturing and cold chain transport processes required for future cell therapy approaches.

Indexed as

Cell- and Tissue-Based TherapyCell TrackingFlow CytometryHumansMagnetite NanoparticlesMesenchymal Stem CellsMyocytes, CardiacNeural Stem CellsStem CellsMagnetite NanoparticlesCell functionalisationCell labellingCell therapyMagnetic particlesStem cells

Identifiers

PMID30257709
PMCPMC6158868

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LicenceCC BY
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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.