Evidence map›Paper›PMID 30808403›Full record

ArticleStem cell research & therapy2019

Automated digital image quantification of histological staining for the analysis of the trilineage differentiation potential of mesenchymal stem cells.

Benjamin Eggerschwiler, Daisy D Canepa, Hans-Christoph Pape, Elisa A Casanova, Paolo Cinelli

Open access · goldAbstract read
In one paragraph

Article in Stem cell research & therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

22 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. MethodsX · 2024
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  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

5 authors at 3 institutions in 1 country.

Benjamin EggerschwilerDepartment of Trauma, University Hospital Zurich, Sternwartstrasse 14, 8091, Zurich, Switzerland.
Daisy D CanepaDepartment of Trauma, University Hospital Zurich, Sternwartstrasse 14, 8091, Zurich, Switzerland.
Hans-Christoph PapeDepartment of Trauma, University Hospital Zurich, Sternwartstrasse 14, 8091, Zurich, Switzerland.
Elisa A CasanovaDepartment of Trauma, University Hospital Zurich, Sternwartstrasse 14, 8091, Zurich, Switzerland. elisa.casanovazimmermann@usz.ch.
Paolo CinelliDepartment of Trauma, University Hospital Zurich, Sternwartstrasse 14, 8091, Zurich, Switzerland. paolo.cinelli@usz.ch.ORCID 0000-0002-0163-9055
University of Zurich · CHUniversity Hospital of Zurich · CHZHAW Zurich University of Applied Sciences · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultipotent mesenchymal stem cells (MSCs) have the potential to repair and regenerate damaged tissues and are considered as attractive candidates for the development of cell-based regenerative therapies. Currently, there are more than 200 clinical trials involving the use of MSCs for a wide variety of indications. However, variations in their isolation, expansion, and particularly characterization have made the interpretation of study outcomes or the rigorous assessment of therapeutic efficacy difficult. An unbiased characterization of MSCs is of major importance and essential to guaranty that only the most suitable cells will be used. The development of standardized and reproducible assays to predict MSC potency is therefore mandatory. The currently used quantification methodologies for the determination of the trilineage potential of MSCs are usually based on absorbance measurements which are imprecise and prone to errors. We therefore aimed at developing a methodology first offering a standardized way to objectively quantify the trilineage potential of MSC preparations and second allowing to discriminate functional differences between clonally expanded cell populations.

methodMSCs originating from several patients were differentiated into osteoblasts, adipocytes, and chondroblasts for 14, 17, and 21 days. Differentiated cells were then stained with the classical dyes: Alizarin Red S for osteoblasts, Oil Red O for adipocytes, and Alcian Blue 8GX for chondroblasts. Quantification of differentiation was then performed with our newly developed digital image analysis (DIA) tool followed by the classical absorbance measurement. The results from the two techniques were then compared.

resultQuantification based on DIA allowed highly standardized and objective dye quantification with superior sensitivity compared to absorbance measurements. Furthermore, small differences between MSC lines in the differentiation potential were highlighted using DIA whereas no difference was detected using absorbance quantification.

conclusionOur approach represents a novel method that simplifies the laboratory procedures not only for the quantification of histological dyes and the degree of differentiation of MSCs, but also due to its color independence, it can be easily adapted for the quantification of a wide range of staining procedures in histology. The method is easily applicable since it is based on open source software and standard light microscopy.

Indexed as

AdipocytesBone Marrow CellsCell Culture TechniquesCell DifferentiationCell LineageCell ProliferationCell TrackingChondrocytesHumansImage Processing, Computer-AssistedMesenchymal Stem CellsMultipotent Stem CellsOsteoblastsAdipocytesChondroblastsDigital image analysisDye quantificationHistologyMesenchymal stem cellsMicroscopyOsteoblastsQuantification of differentiation potential

Identifiers

PMID30808403
PMCPMC6390603
OpenAlexW2918110099

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.