{"title":"纳米制造神经网络:策略、进展和挑战","authors":"R. Luttge","doi":"10.1116/6.0001649","DOIUrl":null,"url":null,"abstract":"Nanofabrication can help us to emulate natural intelligence. Forward-engineering brain gained enormous momentum but still falls short in human neurodegenerative disease modeling. Here, organ-on-chip (OoC) implementation of tissue culture concepts in microfluidic formats already progressed with the identification of our knowledge gap in toxicology and drug metabolism studies. We believe that the self-organization of stem cells and chip technology is a key to advance such complex in vitro tissue models, including models of the human nervous system as envisaged in this review. However, current cultured networks of neurons show limited resemblance with the biological functions in the real nervous system or brain tissues. To take full advantage of scaling in the engineering domain of electron-, ion-, and photon beam technology and nanofabrication methods, more research is needed to meet the requirements of this specific field of chip technology applications. So far, surface topographies, microfluidics, and sensor and actuator integration concepts have all contributed to the patterning and control of neural network formation processes in vitro. However, when probing the state of the art for this type of miniaturized three-dimensional tissue models in PubMed, it was realized that there is very little systematic cross-disciplinary research with biomaterials originally formed for tissue engineering purposes translated to on-chip solutions for in vitro modeling. Therefore, this review contributes to the formulation of a sound design concept based on the understanding of the existing knowledge and the technical challenges toward finding better treatments and potential cures for devastating neurodegenerative diseases, like Parkinson's disease. Subsequently, an integration strategy based on a modular approach is proposed for nervous system-on-chip (NoC) models that can yield efficient and informative optical and electronic NoC readouts in validating and optimizing these conceptual choices in the innovative process of a fast growing and exciting new OoC industry.","PeriodicalId":17495,"journal":{"name":"Journal of Vacuum Science & Technology B","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Nanofabricating neural networks: Strategies, advances, and challenges\",\"authors\":\"R. Luttge\",\"doi\":\"10.1116/6.0001649\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nanofabrication can help us to emulate natural intelligence. Forward-engineering brain gained enormous momentum but still falls short in human neurodegenerative disease modeling. Here, organ-on-chip (OoC) implementation of tissue culture concepts in microfluidic formats already progressed with the identification of our knowledge gap in toxicology and drug metabolism studies. We believe that the self-organization of stem cells and chip technology is a key to advance such complex in vitro tissue models, including models of the human nervous system as envisaged in this review. However, current cultured networks of neurons show limited resemblance with the biological functions in the real nervous system or brain tissues. To take full advantage of scaling in the engineering domain of electron-, ion-, and photon beam technology and nanofabrication methods, more research is needed to meet the requirements of this specific field of chip technology applications. So far, surface topographies, microfluidics, and sensor and actuator integration concepts have all contributed to the patterning and control of neural network formation processes in vitro. However, when probing the state of the art for this type of miniaturized three-dimensional tissue models in PubMed, it was realized that there is very little systematic cross-disciplinary research with biomaterials originally formed for tissue engineering purposes translated to on-chip solutions for in vitro modeling. Therefore, this review contributes to the formulation of a sound design concept based on the understanding of the existing knowledge and the technical challenges toward finding better treatments and potential cures for devastating neurodegenerative diseases, like Parkinson's disease. Subsequently, an integration strategy based on a modular approach is proposed for nervous system-on-chip (NoC) models that can yield efficient and informative optical and electronic NoC readouts in validating and optimizing these conceptual choices in the innovative process of a fast growing and exciting new OoC industry.\",\"PeriodicalId\":17495,\"journal\":{\"name\":\"Journal of Vacuum Science & Technology B\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Vacuum Science & Technology B\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1116/6.0001649\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Vacuum Science & Technology B","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1116/6.0001649","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Nanofabricating neural networks: Strategies, advances, and challenges
Nanofabrication can help us to emulate natural intelligence. Forward-engineering brain gained enormous momentum but still falls short in human neurodegenerative disease modeling. Here, organ-on-chip (OoC) implementation of tissue culture concepts in microfluidic formats already progressed with the identification of our knowledge gap in toxicology and drug metabolism studies. We believe that the self-organization of stem cells and chip technology is a key to advance such complex in vitro tissue models, including models of the human nervous system as envisaged in this review. However, current cultured networks of neurons show limited resemblance with the biological functions in the real nervous system or brain tissues. To take full advantage of scaling in the engineering domain of electron-, ion-, and photon beam technology and nanofabrication methods, more research is needed to meet the requirements of this specific field of chip technology applications. So far, surface topographies, microfluidics, and sensor and actuator integration concepts have all contributed to the patterning and control of neural network formation processes in vitro. However, when probing the state of the art for this type of miniaturized three-dimensional tissue models in PubMed, it was realized that there is very little systematic cross-disciplinary research with biomaterials originally formed for tissue engineering purposes translated to on-chip solutions for in vitro modeling. Therefore, this review contributes to the formulation of a sound design concept based on the understanding of the existing knowledge and the technical challenges toward finding better treatments and potential cures for devastating neurodegenerative diseases, like Parkinson's disease. Subsequently, an integration strategy based on a modular approach is proposed for nervous system-on-chip (NoC) models that can yield efficient and informative optical and electronic NoC readouts in validating and optimizing these conceptual choices in the innovative process of a fast growing and exciting new OoC industry.
期刊介绍:
Journal of Vacuum Science & Technology B emphasizes processing, measurement and phenomena associated with micrometer and nanometer structures and devices. Processing may include vacuum processing, plasma processing and microlithography among others, while measurement refers to a wide range of materials and device characterization methods for understanding the physics and chemistry of submicron and nanometer structures and devices.