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激光诱导微纳结构实现了外周神经系统细胞的共培养空间图案化。

Laser-induced topographies enable the spatial patterning of co-cultured peripheral nervous system cells.

机构信息

Institute of Electronic Structure and Laser, Foundation for Research and Technology-Hellas (IESL-FORTH), Heraklion 711 10, Greece; Department of Physics, University of Crete, Heraklion 710 03, Greece.

Institute of Electronic Structure and Laser, Foundation for Research and Technology-Hellas (IESL-FORTH), Heraklion 711 10, Greece.

出版信息

Mater Sci Eng C Mater Biol Appl. 2020 Oct;115:111144. doi: 10.1016/j.msec.2020.111144. Epub 2020 Jun 1.

DOI:10.1016/j.msec.2020.111144
PMID:32600731
Abstract

The peripheral nervous system comprises glia and neurons that receive the necessary cues for their adhesion and proliferation from their extracellular milieu. In this study, a spatial platform of pseudoperiodic morphologies including patterns of nano- and micro- structures on Si were developed via direct ultrafast-laser structuring and were used as substrates for the patterning of co-cultured neuronal cells. The response of murine Schwann (SW10) and Neuro2a (N2a) cells were investigated both in monocultures and in a glia and neuronal co-culture system. Our results denoted that different types of neural tissue cells respond differently to the underlying topography, but furthermore, the presence of the glial cells alters the adhesion behavior of the neuronal cells in their co-culture. Therefore, we envisage that direct laser structuring that enables spatial patterning of the cells of the nervous system in a controllable manner according to the research needs, could in the future be a useful tool for understanding neural network interfaces and their electrical activity, synaptic processes and myelin formation.

摘要

外周神经系统包括神经胶质细胞和神经元,它们从细胞外环境中获得黏附和增殖所需的信号。在这项研究中,通过直接超快激光微纳结构化技术开发了具有周期性形态的空间平台,包括 Si 上的纳米和微结构图案,用作共培养神经元细胞图案化的基底。研究了鼠雪旺氏细胞(SW10)和 Neuro2a(N2a)细胞在单核培养和神经胶质细胞与神经元共培养系统中的反应。我们的结果表明,不同类型的神经组织细胞对基底形貌的反应不同,但此外,神经胶质细胞的存在改变了共培养中神经元细胞的黏附行为。因此,我们设想,直接激光结构化可以根据研究需求以可控的方式对神经系统的细胞进行空间图案化,将来可能成为理解神经网络界面及其电活动、突触过程和髓鞘形成的有用工具。

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