Cerebrovascular diseases are one of the leading causes of mortality and disability globally [1]. Variations in cerebral circulation are found in many neurological disorders, such as Parkinson’s disease, Alzheimer’s and dementia. Abnormal flow patterns (e.g., shear stress) play an important role in jeopardizing vascular endothelium morphology and function, triggering neuronal dysfunction and neurodegeneration [2]. Yet, the mechanisms involved in the vascular-neuronal relationship are poorly understood, primarily due to the scarcity of adequate models that replicate the brain physiology in health and disease [3]. To bridge the gap in knowledge, it is essential to have a model that allows the study of cell-cell interactions within the NVU, and potentially provides insights into disease mechanisms. Here we propose a human-relevant microfluidic platform known as Organ-on-a-Chip (OoC) to investigate how brain flow alteration affects vascular interaction and alters calcium activity. The OoC we developed is a 3D printed platform made of polypropylene, composed of three pieces: (1) cell culture chamber, with a channel to replicate the vasculature; (2) the porous membrane in PET; and (3) the PDMS sealing cap, to create a close channel. The model we present allows a more accurate simulation of the impact of blood flow alterations on vasculature and provides an exceptional opportunity to investigate cell-cell interactions. Overall, this project represents a comprehensive approach to unveiling the complexities of neuro-vascular interaction and their impact on neurological function, providing valuable insights into disease mechanisms and identifying potential avenues for therapeutic intervention. 1.Yu, Y., & Chen, D. Y.-T. (2023). Machine learning for cerebrovascular disorders. In O. Colliot (Ed.), Machine Learning for Brain Disorders, Vol. 197, pp. 921–961. Springer US. https://doi.org/10.1007/978-1- 0716-3195-9_29 2. Lendahl, U., Nilsson, P., & Betsholtz, C. (2019). Emerging links between cerebrovascular and neurodegenerative diseases-A special role for pericytes. EMBO Reports, 20(11), e48070. https://doi.org/10.15252/embr.201948070. 3. Bai, T., Yu, S., & Feng, J. (2022). Advances in the role of endothelial cells in cerebral small vessel disease. Frontiers in Neurology, 13, 861714. https://doi.org/10.3389/fneur.2022.861714

3D Printed Organ-on-a-Chip Model to Study Cerebral Blood Flow Alterations and Their Effect on Vascular Endothelial Functions

Ludovica Montesi;Mattia Tiboni;Rossana Rauti
2025

Abstract

Cerebrovascular diseases are one of the leading causes of mortality and disability globally [1]. Variations in cerebral circulation are found in many neurological disorders, such as Parkinson’s disease, Alzheimer’s and dementia. Abnormal flow patterns (e.g., shear stress) play an important role in jeopardizing vascular endothelium morphology and function, triggering neuronal dysfunction and neurodegeneration [2]. Yet, the mechanisms involved in the vascular-neuronal relationship are poorly understood, primarily due to the scarcity of adequate models that replicate the brain physiology in health and disease [3]. To bridge the gap in knowledge, it is essential to have a model that allows the study of cell-cell interactions within the NVU, and potentially provides insights into disease mechanisms. Here we propose a human-relevant microfluidic platform known as Organ-on-a-Chip (OoC) to investigate how brain flow alteration affects vascular interaction and alters calcium activity. The OoC we developed is a 3D printed platform made of polypropylene, composed of three pieces: (1) cell culture chamber, with a channel to replicate the vasculature; (2) the porous membrane in PET; and (3) the PDMS sealing cap, to create a close channel. The model we present allows a more accurate simulation of the impact of blood flow alterations on vasculature and provides an exceptional opportunity to investigate cell-cell interactions. Overall, this project represents a comprehensive approach to unveiling the complexities of neuro-vascular interaction and their impact on neurological function, providing valuable insights into disease mechanisms and identifying potential avenues for therapeutic intervention. 1.Yu, Y., & Chen, D. Y.-T. (2023). Machine learning for cerebrovascular disorders. In O. Colliot (Ed.), Machine Learning for Brain Disorders, Vol. 197, pp. 921–961. Springer US. https://doi.org/10.1007/978-1- 0716-3195-9_29 2. Lendahl, U., Nilsson, P., & Betsholtz, C. (2019). Emerging links between cerebrovascular and neurodegenerative diseases-A special role for pericytes. EMBO Reports, 20(11), e48070. https://doi.org/10.15252/embr.201948070. 3. Bai, T., Yu, S., & Feng, J. (2022). Advances in the role of endothelial cells in cerebral small vessel disease. Frontiers in Neurology, 13, 861714. https://doi.org/10.3389/fneur.2022.861714
2025
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11576/2760851
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