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Microfluidic array chip based on excimer laser processing technology for the construction of in vitro graphical neuronal network
Journal of Bioactive and Compatible Polymers ( IF 2.1 ) Pub Date : 2020-05-01 , DOI: 10.1177/0883911520918395
Xuefei Shen 1 , Yi Yang 1 , Shanshan Tian 1 , Yu Zhao 1 , Tao Chen 1
Affiliation  

To construct a graphical neural network in vitro and explore the morphological effects of neural network structural changes on neurons, this study aimed to introduce a method for fabricating microfluidic array chips with different graphical structures based on 248-nm excimer laser one-step etching. Through the comparative analysis of the graphical neural network cultured on our microfluidic array chip with the one on the glass slide, the morphological effects of the neural network on the morphology of the neurons were studied. First, the design of the chip was completed according to the specific structure of the neurons and the simulation of the flow field. The chips were fabricated by excimer laser processing combined with the casting technology. Neurons were cultured on the chip, and a graphical neural network was formed. The growth status of the neural network was analyzed by microscopy and immunofluorescence technology, and compared with the random neural network cultured on glass slides. The results showed that the neurons on the array chips grew in microchannels, and neurites grew along the direction of the channel, interlacing to form a neural network. Furthermore, when the structure of the neural network was graphically changed, the internal neuron morphology changed: on the same culture days, the maximum length of the neurites of the graphical neural network was higher than the average length of the neurites of the random neural network. This research can provide the foundation for the exploration of the neural network mechanism of neurological diseases.

中文翻译:

基于准分子激光加工技术的微流控阵列芯片构建体外图形神经元网络

为在体外构建图形神经网络,探索神经网络结构变化对神经元形态学的影响,本研究旨在介绍一种基于248nm准分子激光一步蚀刻制备具有不同图形结构的微流控阵列芯片的方法。通过在我们的微流控阵列芯片上培养的图形神经网络与载玻片上的图形神经网络的对比分析,研究了神经网络对神经元形态的影响。首先根据神经元的具体结构和流场的模拟完成芯片的设计。芯片是通过准分子激光加工结合铸造技术制造的。在芯片上培养神经元,形成图形神经网络。通过显微镜和免疫荧光技术分析神经网络的生长状态,并与在载玻片上培养的随机神经网络进行比较。结果表明,阵列芯片上的神经元在微通道中生长,神经突沿通道方向生长,交错形成神经网络。此外,当神经网络的结构图形化改变时,内部神经元形态发生变化:在相同的培养天数下,图形神经网络的神经突的最大长度高于随机神经网络的神经突的平均长度. 该研究可为探索神经系统疾病的神经网络机制提供基础。并与在载玻片上培养的随机神经网络进行比较。结果表明,阵列芯片上的神经元在微通道中生长,神经突沿通道方向生长,交错形成神经网络。此外,当神经网络的结构图形化改变时,内部神经元形态发生变化:在相同的培养天数下,图形神经网络的神经突的最大长度高于随机神经网络的神经突的平均长度. 该研究可为探索神经系统疾病的神经网络机制提供基础。并与在载玻片上培养的随机神经网络进行比较。结果表明,阵列芯片上的神经元在微通道中生长,神经突沿通道方向生长,交错形成神经网络。此外,当神经网络的结构图形化改变时,内部神经元形态发生变化:在相同的培养天数下,图形神经网络的神经突的最大长度高于随机神经网络的神经突的平均长度. 该研究可为探索神经系统疾病的神经网络机制提供基础。交错形成神经网络。此外,当神经网络的结构图形化改变时,内部神经元形态发生变化:在相同的培养天数下,图形神经网络的神经突的最大长度高于随机神经网络的神经突的平均长度. 该研究可为探索神经系统疾病的神经网络机制提供基础。交错形成神经网络。此外,当神经网络的结构图形化改变时,内部神经元形态发生变化:在相同的培养天数下,图形神经网络的神经突的最大长度高于随机神经网络的神经突的平均长度. 该研究可为探索神经系统疾病的神经网络机制提供基础。
更新日期:2020-05-01
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