多参量集成控制神经组织芯片研究

通过在集成了传感与调控功能的微芯片上培养细胞，对其所处环境的进行物理或化学调控，实现从干细胞到神经细胞、从单个神经元到神经网络的可控培养；对微芯片上的细胞进行高分辨率电信号或神经递质信号的实时动态监测，研究干细胞神经元定向分化过程中的变化特征，建立基于微纳传感的神经组织芯片新技术体系，实现神经传导及应答功能的体外构建。研究环境因素、外加场等理化调控参数在干细胞分化过程中的作用；研究外加电信号和神经组织之间的相互作用，探索细胞水平尺度上影响组织功能的关键理化因素。利用微纳材料及集成技术，将传感器/执行器与微流控芯片相结合，形成可与神经组织进行有效信息互动的关键技术，构建干细胞向神经细胞定向分化的微环境或微系统，提供2种以上的环境调控手段，进行干细胞的神经元定向分化，建立可与神经组织进行电信号或化学信号互动的可控、动态、3D共培养芯片体系。By culturing cells on microfluidic chips integrated with sensing and regulatory functions, and performing physical or chemical modulation on their culture microenvironment, this work achieves controllable culture of cell populations ranging from stem cells to neural cells, and from single neurons to neural networks. We conduct real-time dynamic monitoring of high-resolution electrical signals or neurotransmitter signals from cells on the microchip, investigate the dynamic changing characteristics during the directed differentiation of stem cells into neurons, establish a novel technical system for neural tissue chips based on micro-nano sensing, and realize the in vitro construction of nerve conduction and response functions. We study the roles of physical and chemical regulatory parameters such as environmental factors and applied physical fields during stem cell differentiation; we explore the interactions between applied electrical signals and neural tissues, and identify key physical and chemical factors that regulate tissue functions at the cellular scale. Leveraging micro-nano materials and integration technologies, we combine sensors/actuators with microfluidic chips to develop key technologies enabling effective information interaction with neural tissues. We construct microenvironments or microsystems for the directed differentiation of stem cells into neural cells, provide more than two types of environmental regulation strategies to facilitate the directed differentiation of stem cells into neurons, and establish a controllable, dynamic 3D co-culture chip system that can perform bidirectional information interaction with neural tissues via electrical or chemical signals.

搜集汇总

背景与挑战

背景概述

该数据集专注于多参量集成控制神经组织芯片研究，旨在通过微芯片技术实现干细胞到神经细胞的可控培养，并实时监测电信号以探索神经分化过程。数据集包含来自大鼠、小鼠和人类的多物种样本，涉及脑和胰腺器官，以及癌细胞、神经细胞和神经干细胞等多种细胞类型，重点研究神经细胞与癌细胞的相互作用及物理化学调控参数的影响。