With the global population increasing and the demographic shifting toward an aging society, the number of patients diagnosed with conditions such as peripheral neuropathies resulting from diabetes is expected to rise significantly. This growing health burden has emphasized the need for innovative solutions, such as brain–computer interfaces. brain–computer interfaces, a multidisciplinary field that integrates neuroscience, engineering, and computer science, enable direct communication between the human brain and external devices. In this study, we developed an autonomous diabetes therapeutic system that employs visually-induced electroencephalography devices to capture and decode event-related potentials using machine learning techniques. We present the visually-induced optogenetically-engineered system for therapeutic expression regulation (VISITER), which generates diverse output commands to control illumination durations. This system regulates insulin expression through optogenetically-engineered cells, achieving blood glucose homeostasis in mice. Our results demonstrate that VISITER effectively and precisely modulates therapeutic protein expression in mammalian cells, facilitating the rapid restoration of blood glucose homeostasis in diabetic mice. These findings underscore the potential for diabetic patients to manage insulin levels autonomously by focusing on target images, paving the way for a more self-directed approach to blood glucose control.

中文翻译：

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视觉诱导的光遗传学工程系统可在小鼠中实现自主葡萄糖稳态


随着全球人口的增长和人口结构向老龄化社会的转变，预计被诊断患有糖尿病引起的周围神经病变等疾病的患者人数将显着增加。这种日益增长的健康负担凸显了对创新解决方案的需求，例如脑机接口。脑机接口是一个融合了神经科学、工程学和计算机科学的多学科领域，可实现人脑与外部设备之间的直接通信。在这项研究中，我们开发了一种自主糖尿病治疗系统，该系统采用视觉诱导的脑电图设备，使用机器学习技术捕获和解码与事件相关的电位。我们提出了用于治疗性表达调节的视觉诱导光遗传学工程系统 （VISITER），该系统可生成多种输出命令来控制照明持续时间。该系统通过光遗传工程细胞调节胰岛素表达，实现小鼠的血糖稳态。我们的结果表明，VISITER 有效且精确地调节哺乳动物细胞中的治疗性蛋白质表达，促进糖尿病小鼠血糖稳态的快速恢复。这些发现强调了糖尿病患者通过关注目标图像自主管理胰岛素水平的潜力，为更加自我导向的血糖控制方法铺平了道路。