Evidence map›Paper›PMID 23440031›Full record

ArticleJournal of tissue engineering2013

Cell separation: Terminology and practical considerations.

Matthew J Tomlinson, Sophie Tomlinson, Xuebin B Yang, Jennifer Kirkham

Abstract read
In one paragraph

Article in Journal of tissue engineering, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.

0numbers the graph read from it
0cells of the map it votes in
63citing 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

63 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Dynamic and precise electromagnetic levitation of single cells.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Monitoring Autophagy in Human Aging: Key Cell Models and Insights.Frontiers in bioscience (Landmark edition) · 2025
    Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Review
  17. Article
  18. Review
  19. Article
  20. Analysis ofFrontiers in cellular and infection microbiology · 2023
    Review

3 more citing papers are in PubMed but not listed here.

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

4 authors.

Matthew J TomlinsonDepartment of Oral Biology, Leeds Dental Institute, University of Leeds, Leeds, UK.
Sophie Tomlinson
Xuebin B Yang
Jennifer Kirkham

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell separation is a powerful tool in biological research. Increasing usage, particularly within the tissue engineering and regenerative medicine communities, means that researchers from a diverse range of backgrounds are utilising cell separation technologies. This review aims to offer potential solutions to cell sorting problems and to clarify common ambiguities in terminology and experimental design. The frequently used cell separation terms of 'purity', 'recovery' and 'viability' are discussed, and attempts are made to reach a consensus view of their sometimes ambiguous meanings. The importance of appropriate experimental design is considered, with aspects such as marker expression, tissue isolation and original cell population analysis discussed. Finally, specific technical issues such as cell clustering, dead cell removal and non-specific antibody binding are considered and potential solutions offered. The solutions offered may provide a starting point to improve the quality of cell separations achieved by both the novice and experienced researcher alike.

Indexed as

cell clusterscell separationcell sortingdead cellsterminologytissue preparation

Identifiers

PMID23440031
PMCPMC3578272

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.