Evidence map›Paper›PMID 29250119›Full record

ReviewStem cells international2017

Urine-Derived Stem Cells: The Present and the Future.

Xiaoli Ji, Min Wang, Fang Chen, Junmei Zhou

Abstract readReview
In one paragraph

Review in Stem cells international, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 citing papers in PubMed.

  1. Role of microRNA in Diabetic Osteoporosis.Molecular biotechnology · 2025
    Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Exosomes from CD133Journal of orthopaedic translation · 2023
    Article
  9. Review
  10. Article
  11. Review
  12. Article
  13. World journal of stem cells · 2022
    Article
  14. Article
  15. Advances in Stem Cell Therapies for Rotator Cuff Injuries.Frontiers in bioengineering and biotechnology · 2022
    Review
  16. Article
  17. Review
  18. Article
  19. Review
  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

4 authors.

Xiaoli JiDepartment of Central Laboratory, Shanghai Children's Hospital, Shanghai Jiao Tong University, 1400 Beijing Road West, Shanghai 200040, China.ORCID 0000-0001-9888-0189
Min WangDepartment of Central Laboratory, Shanghai Children's Hospital, Shanghai Jiao Tong University, 1400 Beijing Road West, Shanghai 200040, China.ORCID 0000-0002-2296-5749
Fang ChenDepartment of Urology, Shanghai Children's Hospital, Shanghai Jiao Tong University, 1400 Beijing Road West, Shanghai 200040, China.
Junmei ZhouDepartment of Central Laboratory, Shanghai Children's Hospital, Shanghai Jiao Tong University, 1400 Beijing Road West, Shanghai 200040, China.ORCID 0000-0002-8338-9458

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stem cell research provides promising strategies in improving healthcare for human beings. As a noninvasively obtained and easy-to-culture cell resource with relatively low expense, urine-derived stem cells have special advantages. They have been extensively studied on its proliferation ability and differentiation potential and were being reprogrammed to model diseases during the last decade. In this review, we intend to summarize the latest progress on the research of urine-derived stem cells for its broad application mainly in regenerative medicine and disease modeling, as well as in what is challenging currently. This minireview will highlight the potential application of urine-derived stem cells and provides possible direction of further research in the future.

Identifiers

PMID29250119
PMCPMC5698822

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.