Evidence map›Paper›PMID 34381771›Full record

ReviewFrontiers in cell and developmental biology2021

A Scarless Healing Tale: Comparing Homeostasis and Wound Healing of Oral Mucosa With Skin and Oesophagus.

Diana Pereira, Inês Sequeira

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
3.6field-weighted citation impact, top 7% 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

31 citing papers in PubMed, 48 citations in OpenAlex.

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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 1 institution in 1 country.

Diana PereiraInstitute of Dentistry, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.
Inês SequeiraInstitute of Dentistry, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.
Queen Mary University of London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial tissues are the most rapidly dividing tissues in the body, holding a natural ability for renewal and regeneration. This ability is crucial for survival as epithelia are essential to provide the ultimate barrier against the external environment, protecting the underlying tissues. Tissue stem and progenitor cells are responsible for self-renewal and repair during homeostasis and following injury. Upon wounding, epithelial tissues undergo different phases of haemostasis, inflammation, proliferation and remodelling, often resulting in fibrosis and scarring. In this review, we explore the phenotypic differences between the skin, the oesophagus and the oral mucosa. We discuss the plasticity of these epithelial stem cells and contribution of different fibroblast subpopulations for tissue regeneration and wound healing. While these epithelial tissues share global mechanisms of stem cell behaviour for tissue renewal and regeneration, the oral mucosa is known for its outstanding healing potential with minimal scarring. We aim to provide an updated review of recent studies that combined cell therapy with bioengineering exporting the unique scarless properties of the oral mucosa to improve skin and oesophageal wound healing and to reduce fibrotic tissue formation. These advances open new avenues toward the ultimate goal of achieving scarless wound healing.

Indexed as

homeostasisoesophagusoral mucosaregenerative medicineregenerative therapyskintissue engineeringwound repair

Identifiers

PMID34381771
PMCPMC8350526
OpenAlexW3186500984

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.