| Literature DB >> 28879656 |
Rosalyn D Abbott1, Francis E Borowsky1, Carlo A Alonzo1, Adam Zieba1, Irene Georgakoudi1, David L Kaplan1.
Abstract
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 strategies-enhancing therapeutic precision, improving patient outcomes, and reducing clinical costs.Entities:
Keywords: adipose tissue; coherent anti-Raman scattering; patient specific approach; second harmonic generation; tumour necrosis factor alpha; unilocular
Mesh:
Substances:
Year: 2017 PMID: 28879656 PMCID: PMC5839961 DOI: 10.1002/term.2572
Source DB: PubMed Journal: J Tissue Eng Regen Med ISSN: 1932-6254 Impact factor: 3.963