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首页> 外文期刊>Biotechnology Journal: Healthcare,Nutrition,Technology >Neuronal circuits on a chip for biological network monitoring
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Neuronal circuits on a chip for biological network monitoring

机译:生物网络监测芯片上的神经元电路

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Cultured neuronal networks (CNNs) are a robust model to closely investigate neuronal circuits' formation and monitor their structural properties evolution. Typically, neurons are cultured in plastic plates or, more recently, in microfluidic platforms with potentially a wide variety of neuroscience applications. As a biological protocol, cell culture integration with a microfluidic system provides benefits such as accurate control of cell seeding area, culture medium renewal, or lower exposure to contamination. The objective of this report is to present a novel neuronal network on a chip device, including a chamber, fabricated from PDMS, vinyl and glass connected to a microfluidic platform to perfuse the continuous flow of culture medium. Network growth is compared in chips and traditional Petri dishes to validate the microfluidic chip performance. The network assessment is performed by computing relevant topological measures like the number of connected neurons, the clustering coefficient, and the shortest path between any pair of neurons throughout the culture's life. The results demonstrate that neuronal circuits on a chip have a more stable network structure and lifespan than developing in conventional settings, and therefore this setup is an advantageous alternative to current culture methods. This technology could lead to challenging applications such as batch drug testing of in vitro cell culture models. From the engineering perspective, a device's advantage is the chance to develop custom designs more efficiently than other microfluidic systems.
机译:培养的神经元网络(CNNS)是密切研究神经元电路的形成和监测其结构性质演化的鲁棒模型。通常,神经元在塑料板中培养,或者最近在微流体平台中培养,具有各种各样的神经科学应用。作为生物学协议,与微流体系统的细胞培养整合提供了诸如精确控制细胞播种面积,培养基更新或降低暴露于污染的益处。本报告的目的是在芯片装置上提出一种新的神经元网络,包括腔室,由连接到微流体平台的PDMS,乙烯基和玻璃制成以灌注培养基的连续流动。在芯片和传统的培养皿中比较网络增长,以验证微流体芯片性能。通过计算相应的神经元,聚类系数和整个文化生命中的任何一对神经元之间的最短路径等相关的拓扑测量来执行网络评估。结果表明,芯片上的神经元电路具有比在传统设置中开发更稳定的网络结构和寿命,因此该设置是当前培养方法的有利替代方案。该技术可能导致挑战性的应用,例如体外细胞培养模型的批量药物检测。从工程角度来看,设备的优势是机会比其他微流体系统更有效地开发定制设计。

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