Samenvatting
To highlight the particular needs with respect to modeling the unique and complex organization of the human brain structure, we reviewed the state-of-the-art in devising brain models with engineered instructive microenvironments. To acquire a better perspective on the brain’s working mechanisms, we first summarize the importance of regional stiffness gradients in brain tissue, varying per layer and the cellular diversities of the layers. Through this, one can acquire an understanding of the essential parameters in emulating the brain in vitro. In addition to the brain’s organizational architecture, we addressed also how the mechanical properties have an impact on neuronal cell responses. In this respect, advanced in vitro platforms emerged and profoundly changed the methods of brain modeling efforts from the past, mainly focusing on animal or cell line research. The main challenges in imitating features of the brain in a dish are with regard to composition and functionality. In neurobiological research, there are now methods that aim to cope with such challenges by the self-assembly of human-derived pluripotent stem cells (hPSCs), i.e., brainoids. Alternatively, these brainoids can be used stand-alone or in conjunction with Brain-on-Chip (BoC) platform technology, 3D-printed gels, and other types of engineered guidance features. Currently, advanced in vitro methods have made a giant leap forward regarding cost-effectiveness, ease-of-use, and availability. We bring these recent developments together into one review. We believe our conclusions will give a novel perspective towards advancing instructive microenvironments for BoCs and the understanding of the brain’s cellular functions either in modeling healthy or diseased states of the brain.
Originele taal-2 | Engels |
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Artikelnummer | 551 |
Aantal pagina's | 28 |
Tijdschrift | Biosensors |
Volume | 13 |
Nummer van het tijdschrift | 5 |
DOI's | |
Status | Gepubliceerd - mei 2023 |
Bibliografische nota
Funding Information:The research tasks of Regina Luttge are partially funded by the European Union’s Horizon 2020 research and innovation program H2020-FETPROACT-2018-01, under grant no. 824070.