3D bioprinted unidirectional neural network and its application for alcoholic neurodegeneration
The brain exhibits complex physiology characterized by unique features such as a brain-specific extracellular matrix, compartmentalized structure (white and grey matter), and an aligned axonal network. These physiological characteristics underpin brain function and facilitate signal transduction sim...
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IOP Publishing
2025-01-01
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| Series: | International Journal of Extreme Manufacturing |
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| Online Access: | https://doi.org/10.1088/2631-7990/add632 |
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| author | Mihyeon Bae Joeng Ju Kim Jinah Jang Dong-Woo Cho |
| author_facet | Mihyeon Bae Joeng Ju Kim Jinah Jang Dong-Woo Cho |
| author_sort | Mihyeon Bae |
| collection | DOAJ |
| description | The brain exhibits complex physiology characterized by unique features such as a brain-specific extracellular matrix, compartmentalized structure (white and grey matter), and an aligned axonal network. These physiological characteristics underpin brain function and facilitate signal transduction similar to that in an electrical circuit. Therefore, investigating these features in vitro is crucial for understanding the interactions between neuronal signal transduction processes and the pathology of neurological diseases. Compared to neurons on patterned substrates, three-dimensional (3D) bioprinting-based neural models provide significant advantages in replicating axonal kinetics without physical limitations. This study proposes the development of a 3D bioprinted engineered neural network (BENN) model to replicate the physiological features of the brain, suggesting its application as a tool for studying neurodegenerative diseases. We employed 3D bioprinting to reconstruct the compartmentalized structure of the brain, and controlled the directionality of axonal growth by applying electrical stimuli to the printed neural structure for overcoming spatial constraints. The reconstructed axonal network demonstrated reliability as a neural analog, including the visualization of mature neuronal features and spontaneous calcium reactions. Furthermore, these brain-like neural network models have demonstrated usefulness for studying neurodegeneration by enabling the visualization of degenerative pathophysiology in alcohol-exposed neurons. The BENN facilitates the visualization of region-specific pathological markers in soma or axon populations, including amyloid-beta formation and axonal deformation. Overall, the BENN closely mimics brain physiology, offers insights into the dynamics of axonal networks, and can be applied to studying neurological diseases. |
| format | Article |
| id | doaj-art-da2ac0449b7247c7915331737b14ebcc |
| institution | Kabale University |
| issn | 2631-7990 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | International Journal of Extreme Manufacturing |
| spelling | doaj-art-da2ac0449b7247c7915331737b14ebcc2025-08-20T03:54:01ZengIOP PublishingInternational Journal of Extreme Manufacturing2631-79902025-01-017505500310.1088/2631-7990/add6323D bioprinted unidirectional neural network and its application for alcoholic neurodegenerationMihyeon Bae0Joeng Ju Kim1Jinah Jang2Dong-Woo Cho3https://orcid.org/0000-0001-5869-4330Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH) , Pohang, Kyungbuk, Republic of Korea; POSTECH-Catholic Biomedical Engineering Institute , POSTECH, Pohang, Kyungbuk, Republic of KoreaDepartment of Mechanical Engineering, Pohang University of Science and Technology (POSTECH) , Pohang, Kyungbuk, Republic of Korea; POSTECH-Catholic Biomedical Engineering Institute , POSTECH, Pohang, Kyungbuk, Republic of KoreaDepartment of Mechanical Engineering, Pohang University of Science and Technology (POSTECH) , Pohang, Kyungbuk, Republic of Korea; Department of Convergence IT Engineering, Pohang University of Science and Technology (POSTECH) , Pohang, Kyungbuk, Republic of KoreaDepartment of Mechanical Engineering, Pohang University of Science and Technology (POSTECH) , Pohang, Kyungbuk, Republic of Korea; POSTECH-Catholic Biomedical Engineering Institute , POSTECH, Pohang, Kyungbuk, Republic of KoreaThe brain exhibits complex physiology characterized by unique features such as a brain-specific extracellular matrix, compartmentalized structure (white and grey matter), and an aligned axonal network. These physiological characteristics underpin brain function and facilitate signal transduction similar to that in an electrical circuit. Therefore, investigating these features in vitro is crucial for understanding the interactions between neuronal signal transduction processes and the pathology of neurological diseases. Compared to neurons on patterned substrates, three-dimensional (3D) bioprinting-based neural models provide significant advantages in replicating axonal kinetics without physical limitations. This study proposes the development of a 3D bioprinted engineered neural network (BENN) model to replicate the physiological features of the brain, suggesting its application as a tool for studying neurodegenerative diseases. We employed 3D bioprinting to reconstruct the compartmentalized structure of the brain, and controlled the directionality of axonal growth by applying electrical stimuli to the printed neural structure for overcoming spatial constraints. The reconstructed axonal network demonstrated reliability as a neural analog, including the visualization of mature neuronal features and spontaneous calcium reactions. Furthermore, these brain-like neural network models have demonstrated usefulness for studying neurodegeneration by enabling the visualization of degenerative pathophysiology in alcohol-exposed neurons. The BENN facilitates the visualization of region-specific pathological markers in soma or axon populations, including amyloid-beta formation and axonal deformation. Overall, the BENN closely mimics brain physiology, offers insights into the dynamics of axonal networks, and can be applied to studying neurological diseases.https://doi.org/10.1088/2631-7990/add6323D bioprintingengineered neural networkneurodegeneration |
| spellingShingle | Mihyeon Bae Joeng Ju Kim Jinah Jang Dong-Woo Cho 3D bioprinted unidirectional neural network and its application for alcoholic neurodegeneration International Journal of Extreme Manufacturing 3D bioprinting engineered neural network neurodegeneration |
| title | 3D bioprinted unidirectional neural network and its application for alcoholic neurodegeneration |
| title_full | 3D bioprinted unidirectional neural network and its application for alcoholic neurodegeneration |
| title_fullStr | 3D bioprinted unidirectional neural network and its application for alcoholic neurodegeneration |
| title_full_unstemmed | 3D bioprinted unidirectional neural network and its application for alcoholic neurodegeneration |
| title_short | 3D bioprinted unidirectional neural network and its application for alcoholic neurodegeneration |
| title_sort | 3d bioprinted unidirectional neural network and its application for alcoholic neurodegeneration |
| topic | 3D bioprinting engineered neural network neurodegeneration |
| url | https://doi.org/10.1088/2631-7990/add632 |
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