Evidence map›Paper›PMID 31728801›Full record

ArticleCytotechnology2020

Sorting living mesenchymal stem cells using a TWIST1 RNA-based probe depends on incubation time and uptake capacity.

Chantal Voskamp, Jeroen van de Peppel, Simona Gasparini, Paolo Giannoni, Johannes P T M van Leeuwen, Gerjo J V M van Osch, Roberto Narcisi

Abstract read
In one paragraph

Article in Cytotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

7 authors.

Chantal VoskampDepartment of Orthopaedics, Erasmus MC, 3015 CN, Rotterdam, The Netherlands.
Jeroen van de PeppelDepartment of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands.
Simona GaspariniDepartment of Orthopaedics, Erasmus MC, 3015 CN, Rotterdam, The Netherlands.
Paolo GiannoniDepartment of Experimental Medicine, University of Genova, Genoa, Italy.
Johannes P T M van LeeuwenDepartment of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands.
Gerjo J V M van OschDepartment of Orthopaedics, Erasmus MC, 3015 CN, Rotterdam, The Netherlands.
Roberto NarcisiDepartment of Orthopaedics, Erasmus MC, 3015 CN, Rotterdam, The Netherlands. r.narcisi@erasmusmc.nl.ORCID http://orcid.org/0000-0003-0521-8618

Funding

ReumaNederland 16-1-201Veni by NWO 13659
6 · The paper itself

Abstract

Bone marrow derived mesenchymal stromal cells (BMSCs) are multipotent progenitors of particular interest for cell-based tissue engineering therapies. However, one disadvantage that limit their clinical use is their heterogeneity. In the last decades a great effort was made to select BMSC subpopulations based on cell surface markers, however there is still no general consensus on which markers to use to obtain the best BMSCs for tissue regeneration. Looking for alternatives we decided to focus on a probe-based method to detect intracellular mRNA in living cells, the SmartFlare technology. This technology does not require fixation of the cells and allows us to sort living cells based on gene expression into functionally different populations. However, since the technology is available it is debated whether the probes specifically recognize their target mRNAs. We validated the TWIST1 probe and demonstrated that it specifically recognizes TWIST1 in BMSCs. However, differences in probe concentration, incubation time and cellular uptake can strongly influence signal specificity. In addition we found that TWIST1

Indexed as

Cell sortingExpansionMesenchymal stem cells (MSCs)RNA probesTissue engineeringTWIST1

Identifiers

PMID31728801
PMCPMC7002702

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.