Litcius/Paper detail

In Situ Detection of Neuroinflammation Using Multicellular 3D Neurovascular‐Unit‐on‐a‐Chip

Jin‐Ha Choi, Hye Kyu Choi, Ki‐Bum Lee

2023Advanced Functional Materials15 citationsDOIOpen Access PDF

Abstract

Abstract The human neurovascular system is a complex network of blood vessels and brain cells that is essential to the proper functioning of the brain. Researchers have become increasingly interested in the system for developing drugs to treat neuroinflammation. Currently, creating neurovascular models begins with animal models, followed by testing on humans in clinical trials. However, the high number of medication failures that pass through animal testing indicates that animal models do not always reflect the outcome of human clinical trials. To overcome the challenges of the issues with animal models, a neurovascular‐unit‐on‐a‐chip system is developed to accurately replicate the in vivo human neurovascular microenvironment. By replicating the human neurovascular unit, a more accurate representation of human physiology can be achieved compared to animal models. The ability to detect proinflammatory cytokines in situ and monitor physiological changes can provide an invaluable tool for evaluating the efficacy and safety of drugs. Using nanosized graphene oxide for in situ detection of inflammatory responses is an innovative approach that can advance the field of neuroinflammation research. Overall, the developed neuroinflammation‐on‐a‐chip system has the potential to provide a more efficient and effective method for developing drugs for treating neurodegenerative diseases and other central nervous system diseases.

Topics & Concepts

Materials scienceNeuroinflammationNeurovascular bundleIn situMulticellular organismNanotechnologyBiomedical engineeringChipInflammationPathologyMedicineBiologyComputer scienceCellInternal medicineOrganic chemistryGeneticsTelecommunicationsChemistryNeuroscience and Neural Engineering3D Printing in Biomedical ResearchNeuroinflammation and Neurodegeneration Mechanisms