Advanced

3D-Printed Soft Lithography for Complex Compartmentalized Microfluidic Neural Devices

Kajtez, Janko LU ; Buchmann, Sebastian ; Vasudevan, Shashank ; Birtele, Marcella LU ; Rocchetti, Stefano ; Pless, Christian Jonathan ; Heiskanen, Arto LU ; Barker, Roger A. LU ; Martínez-Serrano, Alberto and Parmar, Malin LU , et al. (2020) In Advanced Science
Abstract

Compartmentalized microfluidic platforms are an invaluable tool in neuroscience research. However, harnessing the full potential of this technology remains hindered by the lack of a simple fabrication approach for the creation of intricate device architectures with high-aspect ratio features. Here, a hybrid additive manufacturing approach is presented for the fabrication of open-well compartmentalized neural devices that provides larger freedom of device design, removes the need for manual postprocessing, and allows an increase in the biocompatibility of the system. Suitability of the method for multimaterial integration allows to tailor the device architecture for the long-term maintenance of healthy human stem-cell derived neurons and... (More)

Compartmentalized microfluidic platforms are an invaluable tool in neuroscience research. However, harnessing the full potential of this technology remains hindered by the lack of a simple fabrication approach for the creation of intricate device architectures with high-aspect ratio features. Here, a hybrid additive manufacturing approach is presented for the fabrication of open-well compartmentalized neural devices that provides larger freedom of device design, removes the need for manual postprocessing, and allows an increase in the biocompatibility of the system. Suitability of the method for multimaterial integration allows to tailor the device architecture for the long-term maintenance of healthy human stem-cell derived neurons and astrocytes, spanning at least 40 days. Leveraging fast-prototyping capabilities at both micro and macroscale, a proof-of-principle human in vitro model of the nigrostriatal pathway is created. By presenting a route for novel materials and unique architectures in microfluidic systems, the method provides new possibilities in biological research beyond neuroscience applications.

(Less)
Please use this url to cite or link to this publication:
@article{25d4bdda-1994-4c87-92d6-2da3ae622a5c,
  abstract     = {<p>Compartmentalized microfluidic platforms are an invaluable tool in neuroscience research. However, harnessing the full potential of this technology remains hindered by the lack of a simple fabrication approach for the creation of intricate device architectures with high-aspect ratio features. Here, a hybrid additive manufacturing approach is presented for the fabrication of open-well compartmentalized neural devices that provides larger freedom of device design, removes the need for manual postprocessing, and allows an increase in the biocompatibility of the system. Suitability of the method for multimaterial integration allows to tailor the device architecture for the long-term maintenance of healthy human stem-cell derived neurons and astrocytes, spanning at least 40 days. Leveraging fast-prototyping capabilities at both micro and macroscale, a proof-of-principle human in vitro model of the nigrostriatal pathway is created. By presenting a route for novel materials and unique architectures in microfluidic systems, the method provides new possibilities in biological research beyond neuroscience applications.</p>},
  author       = {Kajtez, Janko and Buchmann, Sebastian and Vasudevan, Shashank and Birtele, Marcella and Rocchetti, Stefano and Pless, Christian Jonathan and Heiskanen, Arto and Barker, Roger A. and Martínez-Serrano, Alberto and Parmar, Malin and Lind, Johan Ulrik and Emnéus, Jenny},
  issn         = {2198-3844},
  language     = {eng},
  publisher    = {John Wiley and Sons Inc.},
  series       = {Advanced Science},
  title        = {3D-Printed Soft Lithography for Complex Compartmentalized Microfluidic Neural Devices},
  url          = {http://dx.doi.org/10.1002/advs.202001150},
  doi          = {10.1002/advs.202001150},
  year         = {2020},
}