Evidence map›Paper›PMID 32256607›Full record

ArticleStem cells international2020

Flufenamic Acid Inhibits Adipogenic Differentiation of Mesenchymal Stem Cells by Antagonizing the PI3K/AKT Signaling Pathway.

Xuenan Liu, Zheng Li, Hao Liu, Yuan Zhu, Dandan Xia, Siyi Wang, Ranli Gu, Ping Zhang, Yunsong Liu, Yongsheng Zhou

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Stem cells international, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

16 citing papers in PubMed, 20 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

10 authors at 1 institution in 1 country.

Xuenan LiuDepartment of Prosthodontics, Peking University School and Hospital of Stomatology, National Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, National Clinical Research Center for Oral Diseases, 22 Zhongguancun South Avenue, Beijing 100081, China.
Zheng LiDepartment of Prosthodontics, Peking University School and Hospital of Stomatology, National Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, National Clinical Research Center for Oral Diseases, 22 Zhongguancun South Avenue, Beijing 100081, China.
Hao LiuDepartment of Prosthodontics, Peking University School and Hospital of Stomatology, National Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, National Clinical Research Center for Oral Diseases, 22 Zhongguancun South Avenue, Beijing 100081, China.
Yuan ZhuDepartment of Prosthodontics, Peking University School and Hospital of Stomatology, National Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, National Clinical Research Center for Oral Diseases, 22 Zhongguancun South Avenue, Beijing 100081, China.
Dandan XiaDepartment of Materials Science and Engineering, College of Engineering, Peking University, Beijing 100871, China.
Siyi WangDepartment of Prosthodontics, Peking University School and Hospital of Stomatology, National Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, National Clinical Research Center for Oral Diseases, 22 Zhongguancun South Avenue, Beijing 100081, China.
Ranli GuDepartment of Prosthodontics, Peking University School and Hospital of Stomatology, National Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, National Clinical Research Center for Oral Diseases, 22 Zhongguancun South Avenue, Beijing 100081, China.
Ping ZhangDepartment of Prosthodontics, Peking University School and Hospital of Stomatology, National Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, National Clinical Research Center for Oral Diseases, 22 Zhongguancun South Avenue, Beijing 100081, China.
Yunsong LiuDepartment of Prosthodontics, Peking University School and Hospital of Stomatology, National Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, National Clinical Research Center for Oral Diseases, 22 Zhongguancun South Avenue, Beijing 100081, China.ORCID https://orcid.org/0000-0001-8364-1898
Yongsheng ZhouDepartment of Prosthodontics, Peking University School and Hospital of Stomatology, National Laboratory for Digital and Material Technology of Stomatology, Beijing Key Laboratory of Digital Stomatology, National Clinical Research Center for Oral Diseases, 22 Zhongguancun South Avenue, Beijing 100081, China.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesFlufenamic acid (FFA) is a representative of the fenamic acids, an important group of NSAIDs. In the present study, we study the effects of FFA on adipogenesis of human mesenchymal stem cells (MSCs) and we explore the potential mechanism.

methodsTo investigate the effects of FFA on adipogenic differentiation of hMSCs, human adipose-derived stem cells (hASCs) and human bone marrow mesenchymal stem cells (hBMMSCs), representative of hMSCs, were treated with FFA during adipogenic differentiation

resultsOur results demonstrate that, at certain concentrations, FFA inhibited adipogenesis of human MSCs both

conclusionsThe present study indicated that FFA could be used to inhibit adipogenesis of human MSCs in tissue engineering and diseases related to excessive adipogenic differentiation of MSCs.

Identifiers

PMID32256607
PMCPMC7102471
OpenAlexW3012512631

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Registered trials

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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.