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https://doi.org/10.1186/s13287-019-1141-0
Title: | Fast Adipogenesis Tracking System (FATS) - A robust, high-throughput, automation-ready adipogenesis quantification technique 10 Technology 1004 Medical Biotechnology | Authors: | Yuan, C Chakraborty, S Chitta, K.K Subramanian, S Lim, T.E Han, W Bhanu Prakash, K.N Sugii, S |
Keywords: | cell nucleus receptor 3T3-L1 cell line accuracy adipocyte adipogenesis adipose derived mesenchymal stem cell adipose tissue cell algorithm animal cell Article cell density cell differentiation controlled study embryoid body fast adipogenesis tracking system human human cell induced pluripotent stem cell ligand binding mesenchymal stem cell mouse nonhuman priority journal quantitative analysis |
Issue Date: | 2019 | Citation: | Yuan, C, Chakraborty, S, Chitta, K.K, Subramanian, S, Lim, T.E, Han, W, Bhanu Prakash, K.N, Sugii, S (2019). Fast Adipogenesis Tracking System (FATS) - A robust, high-throughput, automation-ready adipogenesis quantification technique 10 Technology 1004 Medical Biotechnology. Stem Cell Research and Therapy 10 (1) : 38. ScholarBank@NUS Repository. https://doi.org/10.1186/s13287-019-1141-0 | Rights: | Attribution 4.0 International | Abstract: | Adipogenesis is essential in in vitro experimentation to assess differentiation capability of stem cells, and therefore, its accurate measurement is important. Quantitative analysis of adipogenic levels, however, is challenging and often susceptible to errors due to non-specific reading or manual estimation by observers. To this end, we developed a novel adipocyte quantification algorithm, named Fast Adipogenesis Tracking System (FATS), based on computer vision libraries. The FATS algorithm is versatile and capable of accurately detecting and quantifying percentage of cells undergoing adipogenic and browning differentiation even under difficult conditions such as the presence of large cell clumps or high cell densities. The algorithm was tested on various cell lines including 3T3-L1 cells, adipose-derived mesenchymal stem cells (ASCs), and induced pluripotent stem cell (iPSC)-derived cells. The FATS algorithm is particularly useful for adipogenic measurement of embryoid bodies derived from pluripotent stem cells and was capable of accurately distinguishing adipogenic cells from false-positive stains. We then demonstrate the effectiveness of the FATS algorithm for screening of nuclear receptor ligands that affect adipogenesis in the high-throughput manner. Together, the FATS offer a universal and automated image-based method to quantify adipocyte differentiation of different cell lines in both standard and high-throughput workflows. © 2019 The Author(s). | Source Title: | Stem Cell Research and Therapy | URI: | https://scholarbank.nus.edu.sg/handle/10635/178049 | ISSN: | 17576512 | DOI: | 10.1186/s13287-019-1141-0 | Rights: | Attribution 4.0 International |
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