1.Intra-articular injection of synovial mesenchymal stem cells to treat articular cartilage injury
Xiaolong YUAN ; Shengrong BI ; Fangyuan YU
Chinese Journal of Tissue Engineering Research 2015;(36):5892-5897
BACKGROUND:Among various seed cel s, synovial mesenchymal stem cel s have unique advantages in the repair of articular cartilage injury. OBJECTIVE:To review the progress of synovial mesenchymal stem cel s and its intra-articular injection in the treatment of articular cartilage injury. METHODS:The first author searched PubMed and CNKI by computer to retrieve articles published from January 2004 to December 2004 using the keywords of“synovial mesenchymal stem cel s;intra-articular injection;cartilage repair”in English and Chinese, respectively. Final y, 57 articles were included in result analysis. RESULTS AND CONCLUSION:It is easy to isolate and culture synovial mesenchymal stem cel s, which has great advantages in cartilage repair. What’s more, intra-articular injection therapy for articular cartilage injury is feasible and safe. Intra-articular injection of synovial mesenchymal stem cel s is a very promising treatment for cartilage damage, but there are stil many problems to be solved in the future.
2.Translational Informatics for Parkinson's Disease:from Big Biomedical Data to Small Actionable Alterations
Shen BAIRONG ; Lin YUXIN ; Bi CHENG ; Zhou SHENGRONG ; Bai ZHONGCHEN ; Zheng GUANGMIN ; Zhou JING
Genomics, Proteomics & Bioinformatics 2019;17(4):415-429
Parkinson's disease (PD) is a common neurological disease in elderly people, and its morbidity and mortality are increasing with the advent of global ageing. The traditional paradigm of moving from small data to big data in biomedical research is shifting toward big data-based identification of small actionable alterations. To highlight the use of big data for precision PD medicine, we review PD big data and informatics for the translation of basic PD research to clinical applications. We emphasize some key findings in clinically actionable changes, such as susceptibility genetic variations for PD risk population screening, biomarkers for the diagnosis and stratification of PD patients, risk factors for PD, and lifestyles for the prevention of PD. The challenges associated with the collection, storage, and modelling of diverse big data for PD precision medicine and healthcare are also summarized. Future perspectives on systems modelling and intelligent medicine for PD monitoring, diagnosis, treatment, and healthcare are discussed in the end.