measurement-energy-metabolism-explanted-retinal-tissue-using

Measurement of Energy Metabolism in Explanted Retinal Tissue Using Extracellular Flux Analysis

High acuity vision is a heavily energy-consuming process, and the retina has developed several unique adaptations to precisely meet such demands while ...

Washington University School of Medicine

Washington University in Saint Louis

We recently reported the scalable in vitro production of functional stem cell-derived β-cells (SC-β cells). Here we extend this approach to generate the first SC-β cells from type 1 diabetic patients (T1D). β-cells are destroyed during T1D disease progression, making it difficult to extensively study them in the past. These T1D SC-β cells express β-cell markers, respond to glucose both in vitro and in vivo, prevent alloxan-induced diabetes in mice and respond to anti-diabetic drugs. Furthermore, we use an in vitro disease model to demonstrate the cells respond to different forms of β-cell stress. Using these assays, we find no major differences in T1D SC-β cells compared with SC-β cells derived from non-diabetic patients. These results show that T1D SC-β cells could potentially be used for the treatment of diabetes, drug screening and the study of β-cell biology.

Generation of stem cell-derived β-cells from patients with type 1 diabetes.

Transplantation of human pluripotent stem cells (hPSC) differentiated into insulin-producing β cells is a regenerative medicine approach being investigated for diabetes cell replacement therapy. This report presents a multifaceted transplantation strategy that combines differentiation into stem cell-derived β (SC-β) cells with 3D printing. By modulating the parameters of a low-cost 3D printer, we created a macroporous device composed of polylactic acid (PLA) that houses SC-β cell clusters within a degradable fibrin gel. Using finite element modeling of cellular oxygen diffusion-consumption and an in vitro culture system that allows for culture of devices at physiological oxygen levels, we identified cluster sizes that avoid severe hypoxia within 3D-printed devices and developed a microwell-based technique for resizing clusters within this range. Upon transplantation into mice, SC-β cell-embedded 3D-printed devices function for 12 weeks, are retrievable, and maintain structural integrity. Here, we demonstrate a novel 3D-printing approach that advances the use of differentiated hPSC for regenerative medicine applications and serves as a platform for future transplantation strategies.

Economic 3D-printing approach for transplantation of human stem cell-derived β-like cells.

Development of stem cell technologies for cell replacement therapy has progressed rapidly in recent years. Diabetes has long been seen as one of the first applications for stem cell-derived cells because of the loss of only a single cell type-the insulin-producing β-cell. Recent reports have detailed strategies that overcome prior hurdles to generate functional β-like cells from human pluripotent stem cells in vitro, including from human induced pluripotent stem cells (hiPSCs). Even with this accomplishment, addressing immunological barriers to transplantation remains a major challenge for the field. The development of clinically relevant hiPSC derivation methods from patients and demonstration that these cells can be differentiated into β-like cells presents a new opportunity to treat diabetes without immunosuppression or immunoprotective encapsulation or with only targeted protection from autoimmunity. This review focuses on the current status in generating and transplanting autologous β-cells for diabetes cell therapy, highlighting the unique advantages and challenges of this approach.

Article	Year
Generation of stem cell-derived β-cells from patients with type 1 diabetes. Nature communications\| PubMed ID: 27163171	2016
Economic 3D-printing approach for transplantation of human stem cell-derived β-like cells. Biofabrication\| PubMed ID: 27906687	2016
Autologous Pluripotent Stem Cell-Derived β-Like Cells for Diabetes Cellular Therapy. Diabetes\| PubMed ID: 28507211	2017

Jeffrey R. Millman

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