Journal
JOURNAL OF TISSUE ENGINEERING AND REGENERATIVE MEDICINE
Volume 12, Issue 3, Pages 840-847Publisher
WILEY
DOI: 10.1002/term.2572
Keywords
adipose tissue; coherent anti-Raman scattering; patient specific approach; second harmonic generation; tumour necrosis factor alpha; unilocular
Categories
Funding
- National Science Foundation [1531683]
- Armed Forces Institute of Regenerative Medicine [W81XWH-08-2-0032]
- National Institutes of Health [P41 EB002520]
- Div Of Chem, Bioeng, Env, & Transp Sys
- Directorate For Engineering [1531683] Funding Source: National Science Foundation
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Obesity is a risk factor for a myriad of diseases including diabetes, cardiovascular dysfunction, cirrhosis, and cancer, and there is a need for new systems to study how excess adipose tissue relates to the onset of disease processes. This study provides proof-of-concept patient-specific tissue models of human white adipose tissue to accommodate the variability in human samples. Our 3D tissue engineering approach established lipolytic responses and changes in insulin-stimulated glucose uptake from small volumes of human lipoaspirate, making this methodology useful for patient specific sample source assessments of treatment strategies, drug responses, disease mechanisms, and other responses that vary between patients. Mature unilocular cells were maintained ex vivo in silk porous scaffolds for up to a month of culture and imaged non-invasively with coherent anti-Stokes Raman scattering. Interestingly, differences in responsiveness between tissues were observed in terms of magnitude of lipolysis, ability to suppress lipolysis, differences in glucose uptake, and lipid droplet size. Body mass index was not a factor in determining tissue responsiveness; rather, it is speculated that other unknown variables in the backgrounds of different patients (ethnicity, athleticism, disease history, lifestyle choices, etc.) likely had a more significant effect on the observed differences. This study reinforces the need to account for the variability in backgrounds and genetics within the human population to determine adipose tissue responsiveness. In the future, this tissue system could be used to inform individualized care strategiesenhancing therapeutic precision, improving patient outcomes, and reducing clinical costs.
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