Nanofabricating neural networks: Strategies, advances, and challenges

Regina Luttge (Corresponding author)

Onderzoeksoutput: Bijdrage aan tijdschriftArtikel recenserenpeer review

2 Citaten (Scopus)
151 Downloads (Pure)

Samenvatting

Nanofabrication can help us to emulate natural intelligence. Forward-engineering brain gained enormous momentum but still falls short in human neurodegenerative disease modeling. Here, organ-on-chip (OoC) implementation of tissue culture concepts in microfluidic formats already progressed with the identification of our knowledge gap in toxicology and drug metabolism studies. We believe that the self-organization of stem cells and chip technology is a key to advance such complex in vitro tissue models, including models of the human nervous system as envisaged in this review. However, current cultured networks of neurons show limited resemblance with the biological functions in the real nervous system or brain tissues. To take full advantage of scaling in the engineering domain of electron-, ion-, and photon beam technology and nanofabrication methods, more research is needed to meet the requirements of this specific field of chip technology applications. So far, surface topographies, microfluidics, and sensor and actuator integration concepts have all contributed to the patterning and control of neural network formation processes in vitro. However, when probing the state of the art for this type of miniaturized three-dimensional tissue models in PubMed, it was realized that there is very little systematic cross-disciplinary research with biomaterials originally formed for tissue engineering purposes translated to on-chip solutions for in vitro modeling. Therefore, this review contributes to the formulation of a sound design concept based on the understanding of the existing knowledge and the technical challenges toward finding better treatments and potential cures for devastating neurodegenerative diseases, like Parkinson's disease. Subsequently, an integration strategy based on a modular approach is proposed for nervous system-on-chip (NoC) models that can yield efficient and informative optical and electronic NoC readouts in validating and optimizing these conceptual choices in the innovative process of a fast growing and exciting new OoC industry.

Originele taal-2Engels
Artikelnummer020801
Aantal pagina's16
TijdschriftJournal of Vacuum Science and Technology B
Volume40
Nummer van het tijdschrift2
DOI's
StatusGepubliceerd - 1 mrt. 2022

Bibliografische nota

Funding Information:
This work has received funding from the European Union’s Horizon 2020 research and innovation programme H2020-FETPROACT-2018-01 under Grant Agreement No 824070. Furthermore, the author wishes to thank all principal investigators of the CONNECT project, Jens Schwamborn, (University of Luxembourg, Esch sur Alzette), Pieter Vanden Berghe (KU Leuven, Belgium), Femke de Vrij and Steven Kushner (Erasmus MC, the Netherlands), Anestis Tsakiridis and Peter Andrews (University of Sheffield, United Kingdom), and Sami Franssila and Tomi Laurila (Aalto University, Finland) for providing their critical opinions on the first draft of this manuscript and putting a highly dedicated investigator team together.

Publisher Copyright:
© 2022 Author(s).

Financiering

This work has received funding from the European Union’s Horizon 2020 research and innovation programme H2020-FETPROACT-2018-01 under Grant Agreement No 824070. Furthermore, the author wishes to thank all principal investigators of the CONNECT project, Jens Schwamborn, (University of Luxembourg, Esch sur Alzette), Pieter Vanden Berghe (KU Leuven, Belgium), Femke de Vrij and Steven Kushner (Erasmus MC, the Netherlands), Anestis Tsakiridis and Peter Andrews (University of Sheffield, United Kingdom), and Sami Franssila and Tomi Laurila (Aalto University, Finland) for providing their critical opinions on the first draft of this manuscript and putting a highly dedicated investigator team together.

Vingerafdruk

Duik in de onderzoeksthema's van 'Nanofabricating neural networks: Strategies, advances, and challenges'. Samen vormen ze een unieke vingerafdruk.

Citeer dit