Evidence mapPaperPMID 39777112Full record

ArticleBioMedicine2024

Artificial intelligence (AI)-powered bibliometric analysis of global trends in mesenchymal stem cells (MSCs)-derived exosome research: 2014-2023.

Shih-Chang Tsai, Bing-Han Wan, Fuu-Jen Tsai, Jai-Sing Yang

Abstract read
In one paragraph

Article in BioMedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Shih-Chang TsaiDepartment of Biological Science and Technology, China Medical University, Taichung, Taiwan.
Bing-Han WanDepartment of Biological Science and Technology, China Medical University, Taichung, Taiwan.
Fuu-Jen TsaiSchool of Chinese Medicine, College of Chinese Medicine, China Medical University, Taichung, Taiwan.
Jai-Sing YangDepartment of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In recent years, significant progress has been made in regenerative medicine, specifically in using mesenchymal stem cells (MSCs) due to their regenerative and differentiating abilities. An exciting development in this area is the utilization of exosomes derived from MSCs, which have shown promise in tissue restoration, immune system modulation, and cancer treatment. Objectives: This study aims to analyze global research trends and the academic impact of MSCs-derived exosomes from 2014 to 2023, providing a comprehensive overview of this emerging field. Materials and methods: The Web of Science database selected 948 relevant publications from 2014 to 2023. Artificial intelligence (AI)-bibliometric tools, including Bibliometrix, CiteSpace, and VOSviewer, were employed to analyze and visualize the data. The focus was on publication quantity, research nations, institutional partnerships, keywords, and research focal points. Results: The study revealed that China, Japan, Taiwan, and the United States are the leaders in publication volume and impact in MSCs-derived exosome research. China has the highest number of publications, while the United States and Iran excel in research quality and influence. Primary research themes were identified through keyword and clustering analyses, including tissue repair, immune modulation, bone regeneration, and cancer treatment. The study also emphasized the importance of international collaboration, with China and the United States demonstrating the most robust cooperation. Conclusion: MSCs-derived exosome research rapidly expands worldwide, showing promising prospects in regenerative medicine and cell therapy. With continued research and international collaboration, MSCs-derived exosomes are expected to play a vital role in future therapeutic application.

Indexed as

Artificial intelligence (AI)-bibliometric toolsCiteSpaceExosomesMesenchymal stem cells (MSCs)VOSviewerWeb of Science

Identifiers

PMID39777112
PMCPMC11703396

What Socratic holds

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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 Socratic graph.