Evidence map›Paper›PMID 36420445›Full record

ReviewFrontiers in bioengineering and biotechnology2022

Extracellular vesicle: A magic lamp to treat skin aging, refractory wound, and pigmented dermatosis?

Haiyan Wu, Zhenchun Zhang, Yuemeng Zhang, Zhenlin Zhao, Hongming Zhu, Changwu Yue

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Review
  8. Review
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  10. Review
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

6 authors.

Haiyan WuKey Laboratory of Microbial Drugs Innovation and Transformation of Yan'an, School of Basic Medicine, Yan'an University, Yan'an, China.
Zhenchun ZhangKey Laboratory of Microbial Drugs Innovation and Transformation of Yan'an, School of Basic Medicine, Yan'an University, Yan'an, China.
Yuemeng ZhangKey Laboratory of Microbial Drugs Innovation and Transformation of Yan'an, School of Basic Medicine, Yan'an University, Yan'an, China.
Zhenlin ZhaoShenzhen Ruipuxun Academy for Stem Cell & Regenerative Medicine, Shenzhen, China.
Hongming ZhuInstitute for Regenerative Medicine & Research Center for Translational Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Changwu YueKey Laboratory of Microbial Drugs Innovation and Transformation of Yan'an, School of Basic Medicine, Yan'an University, Yan'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exposure of the skin to an external stimulus may lead to a series of irreversible dysfunctions, such as skin aging, refractory wounds, and pigmented dermatosis. Nowadays, many cutaneous treatments have failed to strike a balance between cosmetic needs and medical recovery. Extracellular vesicles (EVs) are one of the most promising therapeutic tools. EVs are cell-derived nanoparticles that can carry a variety of cargoes, such as nucleic acids, lipids, and proteins. They also have the ability to communicate with neighboring or distant cells. A growing body of evidence suggests that EVs play a significant role in skin repair. We summarize the current findings of EV therapy in skin aging, refractory wound, and pigmented dermatosis and also describe the novel engineering strategies for optimizing EV function and therapeutic outcomes.

Indexed as

engineering exosomesextracellular vesiclesmedical aestheticspigmented dermatosisrefractory woundskin agingtherapeutic applications

Identifiers

PMID36420445
PMCPMC9676268

What OpenQuestion holds

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LicenceCC BY
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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.