Title |
Purification and differentiation of human adipose-derived stem cells by membrane filtration and membrane migration methods
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Published in |
Scientific Reports, January 2017
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DOI | 10.1038/srep40069 |
Pubmed ID | |
Authors |
Hong Reng Lin, Chao-Wen Heish, Cheng-Hui Liu, Saradaprasan Muduli, Hsing-Fen Li, Akon Higuchi, S. Suresh Kumar, Abdullah A. Alarfaj, Murugan A. Munusamy, Shih-Tien Hsu, Da-Chung Chen, Giovanni Benelli, Kadarkarai Murugan, Nai-Chen Cheng, Han-Chow Wang, Gwo-Jang Wu |
Abstract |
Human adipose-derived stem cells (hADSCs) are easily isolated from fat tissue without ethical concerns, but differ in purity, pluripotency, differentiation ability, and stem cell marker expression, depending on the isolation method. We isolated hADSCs from a primary fat tissue solution using: (1) conventional culture, (2) a membrane filtration method, (3) a membrane migration method where the primary cell solution was permeated through membranes, adhered hADSCs were cultured, and hADSCs migrated out from the membranes. Expression of mesenchymal stem cell markers and pluripotency genes, and osteogenic differentiation were compared for hADSCs isolated by different methods using nylon mesh filter membranes with pore sizes ranging from 11 to 80 μm. hADSCs isolated by the membrane migration method had the highest MSC surface marker expression and efficient differentiation into osteoblasts. Osteogenic differentiation ability of hADSCs and MSC surface marker expression were correlated, but osteogenic differentiation ability and pluripotent gene expression were not. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 52 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 10 | 19% |
Student > Ph. D. Student | 7 | 13% |
Student > Bachelor | 7 | 13% |
Researcher | 4 | 8% |
Student > Doctoral Student | 3 | 6% |
Other | 9 | 17% |
Unknown | 12 | 23% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 11 | 21% |
Medicine and Dentistry | 10 | 19% |
Biochemistry, Genetics and Molecular Biology | 7 | 13% |
Engineering | 2 | 4% |
Mathematics | 1 | 2% |
Other | 5 | 10% |
Unknown | 16 | 31% |