Please use this identifier to cite or link to this item: 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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