再生(生物学)
组织工程
软骨
文献计量学
引文分析
医学
引用
生物医学工程
图书馆学
计算机科学
生物
解剖
细胞生物学
作者
Yanyan Cao,Cheng Peng,Qianqian Duan,Pengcui Li,Chuan Xiang,Shengbo Sang
标识
DOI:10.1007/s43465-021-00569-1
摘要
BackgroundTremendous progress has been made in the field of cartilage repair and regeneration, particularly with tissue-engineering approaches. This study aims to estimate the global status and current trends in the field of cartilage tissue engineering.MethodsPublications from 2011 to 2020 on tissue engineering for cartilage repair and regeneration were retrieved from Web of Science Core Collection database. The source data were statistically evaluated based on the bibliometrics. In terms of visualized analysis, some bibliometric indicators such as bibliographic coupling, co-citation, co-authorship and co-occurrence analysis were performed by VOSviewer software, to investigate the research trends in tissue engineering for cartilage repair and regeneration.ResultsIn total, 3715 papers were included. Since 2011, the amount of issued papers and relative research interest (RRI) have grown by leaps and bounds globally. The United States was the biggest contributor to the research in this field, due to the greatest citation frequency, the highest H index and the strongest total link strength. Romania had the highest average citation for each. The journal Tissue Engineering Part A published most articles in this field. For institutions, the largest contributors were Shanghai Jiaotong University, University of California System and Sichuan University. Studies could all be grouped into four main clusters: study of biomaterial scaffolds, study of seeding cells and growth factors, experimental animal model and clinical study, and mechanism research.ConclusionGreat efforts should be put into the study of biomaterial scaffolds, seeding cells and growth factors, considered to be the next hot topics in cartilage tissue engineering. This findings provide collaborative insights and research orientation for academic researchers, surgeons and healthcare practitioners to a certain extent.
科研通智能强力驱动
Strongly Powered by AbleSci AI