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

Biomedicine (Taipei). 2024 Dec 1;14(4):61-77. doi: 10.37796/2211-8039.1470. eCollection 2024.

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.

Keywords: Artificial intelligence (AI)-bibliometric tools; CiteSpace; Exosomes; Mesenchymal stem cells (MSCs); VOSviewer; Web of Science.

Grants and funding

This work was supported in part of the project (CMU112-S-44) from China Medical University, Taiwan