ArticleStem cell research & therapy2019
Fast Adipogenesis Tracking System (FATS)-a robust, high-throughput, automation-ready adipogenesis quantification technique.
Article in Stem cell research & therapy, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 19 citations in OpenAlex.
- Hyperspectral coherent anti-Stokes Raman scattering volumetric projection microscopy for assessing drug-cell interaction.Biomedical optics express · 2026Article
- Bioprocess Engineering for Cultivated Meat.Advances in biochemical engineering/biotechnology · 2026Review
- Differential Phase Contrast Imaging to Predict MSC Immune Function.Advanced healthcare materials · 2025Article
- Optimized Adipogenic Differentiation and Delivery of Bovine Umbilical Cord Stem Cells for Cultivated Meat.Gels (Basel, Switzerland) · 2024Article
- Perspectives on scaling production of adipose tissue for food applications.Biomaterials · 2022Article
- Article
- CD10 marks non-canonical PPARγ-independent adipocyte maturation and browning potential of adipose-derived stem cells.Stem cell research & therapy · 2021Article
- Article
- The new kids on the block: Emerging obesogens.Advances in pharmacology (San Diego, Calif.) · 2021Review
- Histological validation of adipogenic differentiation potential of ASC on collagen-based 2D scaffolds.Histochemistry and cell biology · 2020Article
- Adipocyte-Based Cell Therapy in Oncology: The Role of Cancer-Associated Adipocytes and Their Reinterpretation as Delivery Platforms.Pharmaceutics · 2020Review
- Exosomes secreted by mesenchymal stromal/stem cell-derived adipocytes promote breast cancer cell growth via activation of Hippo signaling pathway.Stem cell research & therapy · 2019Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
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