Search Results - fat+quantification

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Identification of Small Molecules as Novel Adipogenic Enhancers for Edible Adipose Tissues (Case No. 2024-125)
Summary: UCLA researchers in the Department of Integrative Biology & Physiology have developed a novel small molecule-based approach for enhancing lipid accumulation and adipogenesis in edible adipose tissues for cultured meat production. Background: With the global population expanding rapidly, there is an urgent demand for sustainable protein...
Published: 6/11/2026   |   Updated: 6/5/2026   |   Inventor(s): Amy Rowat, Robert Damoiseaux, Qingwen Xie
Keywords(s): 3D biofabrication, Agbio, Agriculture, Biomaterial, Cell and tissue culture, Cell Culture, Cell Growth, cell proliferation, cell-extracellular matrix (ECM), cellular aggregates, Cellular agriculture, Cellular Differentiation, Confocal Microscopy, Cultured meat, fat quantification, fatty acids, High-Content Screening, High-Throughput Screening, Industrial applications: food processing, fermentation, lipidomics, meat, meat production, nutrition, scaffolds, Screening Libraries, Small molecule screening, small molecules, subcutaneous adipose tissue, Sustainable nutrition, Tissue Engineering
Category(s): Life Science Research Tools > Research Methods, Life Science Research Tools > Screening Libraries, Life Science Research Tools > Cell Lines, Life Science Research Tools > Cell Counting And Imaging, Life Science Research Tools > Microscopy And Imaging, Therapeutics > Agtech And Animal Health, Chemical > Chemical Processing & Manufacturing, Materials > Functional Materials
A Deep-Learning Framework for Quantitative Magnetic Resonance Imaging (Case No. 2021-268)
Summary: Researchers from UCLA’s Departments of Bioengineering and Radiological Sciences have developed a novel deep learning framework for accelerated quantitative magnetic resonance imaging. Background: Fatty liver disease, or hepatic steatosis, affects nearly 2 billion people globally and has pernicious implications for deadlier diseases...
Published: 7/17/2025   |   Updated: 9/13/2023   |   Inventor(s): Holden Wu, Shu-Fu Shih
Keywords(s): Deep Learning, fat quantification, IIM framework, Imaging, Medical Imaging, Metabolic/Endocrinology, MRI, multiparametric MRI (mpMRI), radial MRI, uncertainty estimation
Category(s): Medical Devices, Medical Devices > Medical Imaging, Medical Devices > Medical Imaging > MRI, Electrical, Electrical > Imaging, Software & Algorithms