Evidence map›Paper›PMID 32850818›Full record

ReviewFrontiers in cell and developmental biology2020

Mesenchymal Stem Cells Adaptively Respond to Environmental Cues Thereby Improving Granulation Tissue Formation and Wound Healing.

Dongsheng Jiang, Karin Scharffetter-Kochanek

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
7.8field-weighted citation impact, top 2% 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

40 citing papers in PubMed, 96 citations in OpenAlex.

  1. Translational development of ABCB5Stem cell research & therapy · 2022
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  3. Adaptation of mesenchymal stromal cells to culture on collagen-based bioscaffold.Journal of materials science. Materials in medicine · 2026
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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

2 authors at 2 institutions in 1 country.

Dongsheng JiangComprehensive Pneumology Center, Institute of Lung Biology and Disease, Helmholtz Zentrum München, Munich, Germany.
Karin Scharffetter-KochanekDepartment of Dermatology and Allergic Diseases, Ulm University, Ulm, Germany.
Helmholtz Zentrum München · DEUniversität Ulm · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Granulation tissue formation constitutes a key step during wound healing of the skin and other organs. Granulation tissue concomitantly initiates regenerative M2 macrophages polarization, fibroblast proliferation, myofibroblast differentiation with subsequent contraction of the wound, new vessel formation, and matrix deposition. Impaired granulation tissue formation either leads to delayed wound healing or excessive scar formation, conditions with high morbidity and mortality. Accumulating evidence has demonstrated that mesenchymal stem cell (MSC)-based therapy is a promising strategy to ameliorate defects in granulation tissue formation and to successfully treat non-healing chronic wounds. In this review we give an updated overview of how therapeutically administered MSCs ensure a balanced granulation tissue formation, and furthermore discuss the cellular and molecular mechanisms underlying the adaptive responses of MSCs to cue in their direct neighborhood. Improved understanding of the interplay between the exogenous MSCs and their niche in granulation tissue will foster the development of MSC-based therapies tailored for difficult-to-treat non-healing wounds.

Indexed as

environment sensinggranulation tissueinflammationmesenchymal stem cellsmyofibroblastsproliferationscarringwound healing

Identifiers

PMID32850818
PMCPMC7403200
OpenAlexW3046149843

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.