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Patterning of functional human astrocytes onto parylene-C/SiO2 substrates for the study of Ca2+ dynamics in astrocytic networks.

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OBJECTIVE Recent literature suggests that astrocytes form organized functional networks and communicate through transient changes in cytosolic Ca2+. Traditional techniques to investigate network activity, such as pharmacological blocking or genetic… Click to show full abstract

OBJECTIVE Recent literature suggests that astrocytes form organized functional networks and communicate through transient changes in cytosolic Ca2+. Traditional techniques to investigate network activity, such as pharmacological blocking or genetic knockout, are difficult to restrict to individual cells. The objective of this work is to develop cell-patterning techniques to physically manipulate astrocytic interactions to enable the study of Ca2+ in astrocytic networks. APPROACH We investigate how an in vitro cell-patterning platform that utilizes geometric patterns of parylene-C on SiO2 can be used to physically isolate single astrocytes and small astrocytic networks. MAIN RESULTS We report that single astrocytes are effectively isolated on 75  ×  75 µm square parylene nodes, whereas multi-cellular astrocytic networks are isolated on larger nodes, with the mean number of astrocytes per cluster increasing as a function of node size. Additionally, we report that astrocytes in small multi-cellular clusters exhibit spatio-temporal clustering of Ca2+ transients. Finally, we report that the frequency and regularity of Ca2+ transients was positively correlated with astrocyte connectivity. SIGNIFICANCE The significance of this work is to demonstrate how patterning hNT astrocytes replicates spatio-temporal clustering of Ca2+ signalling that is observed in vivo but not in dissociated in vitro cultures. We therefore highlight the importance of the structure of astrocytic networks in determining ensemble Ca2+ behaviour.

Keywords: astrocytic networks; parylene sio2; study ca2; patterning functional

Journal Title: Journal of neural engineering
Year Published: 2018

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