Evidence map›Paper›PMID 29662797›Full record

ReviewJournal of orthopaedic translation2017

Current concepts on tenogenic differentiation and clinical applications.

Yang Liu, Chun-Wai Suen, Jin-Fang Zhang, Gang Li

Abstract readReview
In one paragraph

Review in Journal of orthopaedic translation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
–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

39 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  19. Autograft Long Head Biceps Tendon Can Be Used as a Scaffold for Biologically Augmenting Rotator Cuff Repairs.Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association · 2022
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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.

Yang LiuDepartment of Orthopaedics and Traumatology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
Chun-Wai SuenDepartment of Orthopaedics and Traumatology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
Jin-Fang ZhangDepartment of Orthopaedics and Traumatology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
Gang LiDepartment of Orthopaedics and Traumatology, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tendon is a tissue that transmits force from muscle to bone. Chronic or acute tendon injuries are very common, and are always accompanied by pain and a limited range of motion in patients. In clinical settings, management of tendon injuries still remains a big challenge. Cell therapies, such as the application of stem cells for tenogenic differentiation, were suggested to be an ideal strategy for clinical translation. However, there is still a lack of specific methods for tenogenic differentiation due to the limited understanding of tendon biology currently. This review focuses on the summary of current published strategies for tenogenic differentiation, such as the application of growth factors, mechanical stimulation, biomaterials, coculture, or induced pluripotent stem cells. Current clinical applications of stem cells for treatment of tendon injuries and their limitations have also been discussed in this review.

Indexed as

mesenchymal stem cellstendon derived stem cellstendon healingtenogenic differentiation

Identifiers

PMID29662797
PMCPMC5822963

What OpenQuestion holds

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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.