Enhanced Differentiation of Human Neural Stem Cells into Cortical Neurons Using 3D Chitosan Scaffolds

Human neural stem cells (hNSCs) have the potential to differentiate into various neural cell types, including cortical neurons, which are of particular interest for understanding and treating neurodegenerative diseases. However, traditional 2D culture methods are limited in their ability to accurately mimic the physiologically relevant microenvironment, leading to slow differentiation rates and low yields of mature neurons. In this study, we developed and optimized 3D chitosan scaffolds to promote the more efficient differentiation of hNSCs into cortical neurons. These scaffolds provide a tunable, biocompatible, and mechanically favorable environment, supporting enhanced cell-to-cell interactions and mimicking the extracellular matrix more effectively than 2D systems. The differentiation process was further accelerated by preseeding scaffolds with hNSCs, leading to increased expression of key cortical neuron markers, such as MAP2 and TUBB3, within a 14-day period. Compared to Geltrex-coated controls, the preseeded scaffolds demonstrated superior cell adhesion, viability, and differentiation efficiency, with significant upregulation of mature cortical neuron markers. Our findings suggest that chitosan-based 3D culture systems represent a promising platform for improving the differentiation of hNSCs, offering a faster and more reliable method to generate cortical neurons for neurodegenerative disease research and potential therapeutic applications.

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Publication Details

Journal
ACS Applied Bio Materials
Published
2025-02-26
DOI
https://doi.org/10.1021/acsabm.4c01927
Citations
1
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.91

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article

Enhanced Differentiation of Human Neural Stem Cells into Cortical Neurons Using 3D Chitosan Scaffolds

Yang Zhou, Matthew Michael James, Miqin Zhang
1 citations
ACS Applied Bio Materials
Neuroscience and Neural Engineering
0.91
article

Enhanced Differentiation of Human Neural Stem Cells into Cortical Neurons Using 3D Chitosan Scaffolds

Yang Zhou, Matthew Michael James, Miqin Zhang
article en
1 citations

Abstract

Human neural stem cells (hNSCs) have the potential to differentiate into various neural cell types, including cortical neurons, which are of particular interest for understanding and treating neurodegenerative diseases. However, traditional 2D culture methods are limited in their ability to accurately mimic the physiologically relevant microenvironment, leading to slow differentiation rates and low yields of mature neurons. In this study, we developed and optimized 3D chitosan scaffolds to promote the more efficient differentiation of hNSCs into cortical neurons. These scaffolds provide a tunable, biocompatible, and mechanically favorable environment, supporting enhanced cell-to-cell interactions and mimicking the extracellular matrix more effectively than 2D systems. The differentiation process was further accelerated by preseeding scaffolds with hNSCs, leading to increased expression of key cortical neuron markers, such as MAP2 and TUBB3, within a 14-day period. Compared to Geltrex-coated controls, the preseeded scaffolds demonstrated superior cell adhesion, viability, and differentiation efficiency, with significant upregulation of mature cortical neuron markers. Our findings suggest that chitosan-based 3D culture systems represent a promising platform for improving the differentiation of hNSCs, offering a faster and more reliable method to generate cortical neurons for neurodegenerative disease research and potential therapeutic applications.

ACS Applied Bio MaterialsVol. 8(3)
University of Washington (US)
Inamori Foundation, National Institute of Dental and Craniofacial Research
Zero hunger
Openalex Percentile: Top 30%
Neuroscience and Neural Engineering
0.91
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Enhanced Differentiation of Human Neural Stem Cells into Cortical Neurons Using 3D Chitosan Scaffolds — Yang Zhou, Matthew Michael James, et al. · ACS Applied Bio Materials (2025) | TGRS Research Map | TGRS