Researches on Mesenchymal Stem Cells for Treatment of Spinal Cord Injury: A Visualization Analysis
10.3969/j.issn.1006-9771.2020.04.006
- VernacularTitle:间充质干细胞治疗脊髓损伤的可视化分析
- Author:
Jia-mei YE
1
;
Xiao-min HU
2
;
Li-qun WANG
2
;
Wen-chun WANG
2
;
An-ren ZHANG
2
Author Information
1. School of Health and Rehabilitation, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China
2. Department of Rehabilitation Medicine, The General Hospital of Western Theater Command, Chengdu, Sichuan 610083, China
- Publication Type:Research Article
- Keywords:
spinal cord injury;
mesenchymal stem cells;
CiteSpace;
Web of Science;
visual analysis
- From:
Chinese Journal of Rehabilitation Theory and Practice
2020;26(4):400-406
- CountryChina
- Language:Chinese
-
Abstract:
Results and Conclusion A total of 236 authors were included, out of whom 49 authors published more than three papers, and high-yielding authors were mainly represented by Zeng Y S and Chen L. There were 162 countries/institutions involved, out of which 85 published more than three papers. Seventy-five journals were included, out of which Exp Neurol was the one with the most articles. There were 107 key words included, and the hot words were spinal cord injury, MSCs, transplantation, bone marrow, repair, and functional recovery, which formed six cluster groups. The trend was to extract and culture progenitor cells and induce their directional differentiation; mechanism of immune regulation, anti-inflammatory and nerve regeneration in the treatment of spinal cord injury by MSCs, as well as the research of tissue engineering technology, biological materials in this field. Objective:To analyze the research status and hotspots of mesenchymal stem cells (MSCs) for treatment of spinal cord injury in the past five years. Methods:The related literatures from 2014 to 2018 in Science Citation Index-Expanded (SCI-E) of Web of Science (WOS) were included. CiteSpace software was used to analyze the cooperation relationship of authors, countries and research institutions. The keywords were taken as nodes for co-occurrence analysis, cluster analysis, dynamic frontier evolution and burst analysis. The co-citation of journals and literatures were taken as nodes for analysis, meanwhile, the visual maps were drawn and the results were analyzed.
