Deep Learning-reinforced Engineering of Pancreatic Organoids with Micro-nano Biomaterials for Type 1 Diabetes Treatment

项目总结 据估计，目前有160万美国人患有1型糖尿病。最常见的方法是 1型糖尿病的治疗是通过每天的血液监测和胰岛素注射，这可能会影响生活质量 并可能导致严重的健康问题。全胰腺移植是一种更持久的治疗选择 但涉及可能导致并发症的侵入性手术，发病率高，需要患者 在他们的余生中服用免疫抑制剂，这可能对健康非常有害。一种方法可用于 胰岛移植是治疗糖尿病的一种有希望的选择，也是许多研究的重点。 这是一种侵入性小得多的方法，但仍需要患者服用免疫抑制剂或冒险 移植排斥反应。防止移植后需要免疫抑制剂的一种方法是通过 将胰岛包裹在生物材料中，允许营养交换，同时通过以下方式减轻免疫排斥反应 防止免疫细胞渗透。囊化胰岛移植仍面临许多问题，包括免疫 移植后的反应和较差的胰岛生存能力，这可以通过工程和 本项目中提出的生物材料。目标1将专注于开发新的微胶囊方法， 我们假设这将导致较低的胰岛细胞死亡和较低的移植后免疫反应 活着。胰岛的微流控胶囊使微囊的成分和形态得到更好的控制 而不是其他封装方法。使用这种方法，一种仿生封装模仿了 胰腺和使用材料的核壳设计是可以实现的。实现无标签深度 一种片上空囊中选择性挑选胰岛微囊的学习检测方法 高纯度的胰岛微囊移植样品，可以大大提高移植的效率和 与使用繁琐的手动分类方法相比，最大限度地减少污染(和相关的免疫反应) 在过去。此外，胰岛将与胰腺基质细胞共同包裹，以创建仿生的 微环境(即胰腺类器官)。微囊化的胰岛将在 通过监测糖尿病小鼠的血糖水平，在体外和体内测试糖尿病小鼠模型。目标2将 专注于开发基于纳米颗粒的战略，以进一步提高微胶囊的存活率 小岛。生理剂量的抗氧化剂显示移植后胰岛存活率提高。正在封装 在胰岛移植过程中，纳米粒中的抗氧化剂可以改善摄取并允许持续释放。 携带抗氧化剂的纳米颗粒对胰岛存活和胰岛素产生的影响将在体外和 然后在体内测试它们对血糖水平的影响。通过支持深度学习的 选择性萃取、核壳水凝胶微胶囊化和纳米颗粒介体抗氧化剂输送， 胰岛移植面临的主要挑战可能会得到解决。这一新的多尺度工程战略具有 临床翻译具有广泛应用于治疗1型糖尿病的巨大潜力。

PROJECT SUMMARY An estimated 1.6 million Americans are currently living with type 1 diabetes. The most common method of treating type 1 diabetes is through daily blood monitoring and insulin injections, which can affect quality of life and may result in severe health issues. Full pancreatic transplantations are a more permanent treatment option but involve invasive surgery that can lead to complications, has a high morbidity rate, and patients are required to take immunosuppressants for the rest of their lives which can be very detrimental to health. One method for diabetes treatment that has become a promising option and focus of a lot of research is islet transplantation, which is a much less invasive method but still requires patients to take immunosuppressants or risk transplantation rejection. A way to prevent the need for immunosuppressants post-transplantation is through encapsulating the islets in biomaterials which can allow nutrient exchange while mitigating immune rejection by preventing immune cell infiltration. Encapsulated islet transplantation still faces many problems including immune responses and poor islet viability post-transplantation, which may be addressed using engineering and biomaterials as proposed in this project. Aim 1 will focus on developing novel microencapsulation methods, which we hypothesize will result in lower islet cell death and lower post-transplantation immune responses in vivo. Microfluidic encapsulation of islets gives greater control over microcapsule composition and configuration than other encapsulation methods. Using this method, a biomimetic encapsulation that mimics the structure of the pancreas and uses materials in a core-and-shell design can be achieved. Implementing a label-free deep learning detection method to selectively pick islet-laden microcapsules from empty capsules on-chip to obtain a highly pure sample of islet-laden microcapsules for transplantation, may greatly improve the efficiency and minimize contamination (and associated immune response), compared to tedious manual sorting methods used in the past. Furthermore, the islets will be co-encapsulated with pancreatic stromal cells to create a biomimetic microenvironment (i.e., pancreatic organoid). The microencapsulated islets will be rigorously characterized in vitro and tested in vivo in a diabetic mouse model by monitoring blood glucose levels of the mice. Aim 2 will focus on developing a nanoparticle-based strategy for further improving the survival of the microencapsulated islets. Physiological amounts of antioxidants show enhanced islet survival post-transplantation. Encapsulating antioxidants in nanoparticles can improve the uptake and allow for sustained release during islet transplantation. Effect of the antioxidant-laden nanoparticles on islet survival and insulin production will be tested in vitro and then their effects on blood glucose levels tested in vivo. Through a combination of deep learning-enabled selective extraction, core-shell hydrogel microencapsulation, and nanoparticle-mediatexd antioxidants delivery, major challenges facing islet transplantation may be addressed. This novel multiscale engineering strategy has great potential for clinical translation to be widely used for treating type 1 diabetes.