Evidence map›Paper›PMID 37612726›Full record

ArticleStem cell research & therapy2023

Cell-free fat extract restores hair loss: a novel therapeutic strategy for androgenetic alopecia.

Yizuo Cai, Zhuoxuan Jia, Yichen Zhang, Bijun Kang, Chingyu Chen, Wei Liu, Wei Li, Wenjie Zhang

Open access · goldAbstract read
In one paragraph

Article in Stem cell research & therapy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
5.0field-weighted citation impact, top 4% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 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

8 authors at 2 institutions in 2 countries.

Yizuo Cai *Department of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Tissue Engineering, National Tissue Engineering Center of China, 639 ZhiZaoJu Road, Shanghai, 200011, China.
Zhuoxuan Jia *Department of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Tissue Engineering, National Tissue Engineering Center of China, 639 ZhiZaoJu Road, Shanghai, 200011, China.
Yichen ZhangDepartment of Biological and Environmental Engineering, Cornell University, Ithaca, USA.
Bijun KangDepartment of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Tissue Engineering, National Tissue Engineering Center of China, 639 ZhiZaoJu Road, Shanghai, 200011, China.
Chingyu ChenDepartment of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Tissue Engineering, National Tissue Engineering Center of China, 639 ZhiZaoJu Road, Shanghai, 200011, China.
Wei LiuDepartment of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Tissue Engineering, National Tissue Engineering Center of China, 639 ZhiZaoJu Road, Shanghai, 200011, China. liuwei_md@126.com.
Wei LiDepartment of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Tissue Engineering, National Tissue Engineering Center of China, 639 ZhiZaoJu Road, Shanghai, 200011, China. liweiboshi@163.com.ORCID http://orcid.org/0000-0002-2366-0621
Wenjie ZhangDepartment of Plastic and Reconstructive Surgery, Shanghai 9th People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Tissue Engineering, National Tissue Engineering Center of China, 639 ZhiZaoJu Road, Shanghai, 200011, China. wenjieboshi@aliyun.com.
Shanghai Jiao Tong University · CNCornell University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAndrogenetic alopecia (AGA) is one of the most common hair loss diseases worldwide. However, current treatments including medicine, surgery, and stem cells are limited for various reasons. Cell-free fat extract (CEFFE), contains various cell factors, may have potential abilities in treating AGA. This study aims to evaluate the safety, effectiveness and the underlying mechanism of CEFFE in treating AGA.

methodsSex hormone evaluation, immunogenicity assay and genotoxicity assay were conducted for CEFFE. In vivo study, male C57BL/6 mice were injected subcutaneously with dihydrotestosterone (DHT) and were treated with different concentration of CEFFE for 18 days (five groups and n = 12 in each group: Control, Model, CEFFE

resultsIn CEFFE-treated mice, an increase in the anagen entry rate and hair coverage percentage was observed. The number of CD31-positive capillaries and Ki67-positive cells were increased, suggesting that CEFFE promoted the proliferation of DPCs, modulated the cell cycle arrest, inhibited apoptosis caused by DHT, reduced the intracellular concentration of DHT in DPCs, and downregulated the expression of AR.

conclusionsCEFFE is a novel and effective treatment option for AGA through producing an increased hair follicle density and hair growth rate. The proposed mechanisms are through the DHT/AR pathway regulation and regional angiogenesis ability.

Indexed as

Adipose TissueAlopeciaAnimalsApoptosisBiological AssayCell ExtractsMaleMiceMice, Inbred C57BLCell ExtractsAndrogenetic alopeciaCell-free therapyFat extract

Identifiers

PMID37612726
PMCPMC10464375
OpenAlexW4386091698

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.