Hyperglycemia and dyslipidemia are common comorbidities that often coincide and have a significant impact on the severity of diabetes. This current study investigates the pathology and mechanism behind skeletal muscle cachexia and cardiac dysfunction in diabetic dyslipidemia. Stem cells continue to be critical as a regenerative strategy to restore damaged tissue, however, several drawbacks have been observed with use of stem cells including thrombogenesis, low survival, and tumorigenicity. Therefore, we isolated exosomes from stem cells and assessed their ability to attenuate diabetes-induced sarcopenia and cardiomyopathy. Exosomes are nanosized particles released by cells, containing proteins and nucleic acids that allow it to exhibit similar properties to the cell type of origin. To model diabetic dyslipidemia, we utilized ApoE knockout mice (10±2 weeks) and divided them into 4 groups consisting of control (saline intraperitoneal (IP) injection), diabetic (STZ IP injection), treatment group administered intravenous (IV) exosomes derived from miR-1 ES-Exos (microRNA-1 enriched Embryonic Stem Cells) or MSC-Exos (Mesenchymal Stem Cells), and negative control treatment MEF-Exos (Mouse Embryonic Fibroblasts). Heart and soleus tissue samples were analyzed for inflammation, inflammatory cell death expression, and adverse tissue remodeling using histology, immunohistochemistry, western blotting, RT-PCR, cytokine, and luciferase-based arrays. In summary we found diabetic dyslipidemic mice acquire cardiac and skeletal muscle dysfunction. Administration of miR-1 ES-Exos and MSC-Exos significantly mitigated inflammation and cell death marker expression, resulting in improved cardiac and skeletal muscle function. In conclusion our data shows that miR-1 ES-Exos and MSC-Exos are effective therapeutic agents in attenuating diabetes-induced sarcopenia and cardiomyopathy.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2023-1280 |
Date | 01 January 2024 |
Creators | Banerjee, Abha |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Graduate Thesis and Dissertation 2023-2024 |
Rights | In copyright |
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