Organotypic whole hemisphere models to probe structure-function in neurodevelopment and neurological disease

用于探索神经发育和神经系统疾病结构功能的器官型全半球模型

• 批准号: 2222074
• 负责人: Elizabeth Nance
• 金额: $ 44.38万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-02-01 至 2026-01-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2222074&HistoricalAwards=false
• 关键词: Organotypic; whole; hemisphere; models; probe

The brain is our most complex organ and governs everything from cognition and emotion to movement and stress response. Much of the brain’s function is determined by interactions of cells with their surrounding local environment within the brain. The precise interplay between brain microenvironment and brain function is still not well-understood, limiting our ability to know when and how changes in the brain microenvironment are compensatory, reparative, or pathological. The proposed work develops a brain tissue platform to study the changes in brain microstructure in different ages, sexes, brain regions, and in response to different stimuli. Successful completion of the proposed work will provide new insights into changes in the brain microenvironment that impact function of cells in the brain and lead to disease onset or progression. Machine learning application to the data generated via studying changes in brain microstructure and function will be used to predict disease-dependent changes in the brain. This research will also impact education and outreach through development of validated open-source software that can be broadly applicable to tissues other than the brain, other diseases, tissue probes, or datasets. The interplay between brain microstructure and brain function is still not well-understood, although connections between brain microstructure and function are prospective markers for aging, neurological, and psychiatric disorders. Investigating this relationship is challenging - the brain microenvironment is dynamic and variable region to region within the brain, and current imaging platforms are limited in spatial and temporal resolution, in access to all brain regions, and in tailoring to different ages or disease models using the same platform. To address these current limitations and to provide greater insight into the spatiotemporal changes in microstructure, the principal investigator will use an organotypic whole hemisphere brain slice (OWH) platform that retains in vivo cellular and extracellular parenchymal physiology, allows study of multiple brain regions in a single slice, is responsive to different stimuli, and can be produced for different ages and species. The investigator will use their established multiple particle tracking (MPT) technology in a newly proposed OWH model of neurodegeneration to study diffusion as a measure of microstructure and apply molecular biology and functional assay tools to identify associated mechanisms of microstructural changes. Expertise in machine learning model application to MPT data will be used to build a neural network model to predict functional disease state. The use of tailorable OWH brain slice models with MPT and molecular biology tools will enable high spatiotemporal probing and quantification of regional microstructure-function relationships in development and in response to injury/insult. The proposed platform and integrated technologies can find great utility throughout diverse fields, including neurobiology, drug delivery and screening, neurological disease, tissue engineering, and data sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

大脑是我们最复杂的器官，控制着从认知和情感到运动和压力反应的一切。大脑的大部分功能是由大脑内细胞与周围局部环境的相互作用决定的。大脑微环境和大脑功能之间的精确相互作用仍然没有得到很好的理解，限制了我们了解大脑微环境变化何时以及如何补偿，修复或病理的能力。 本研究开发了一个脑组织平台，用于研究不同年龄、性别、脑区以及对不同刺激的反应中脑组织微结构的变化。成功完成拟议的工作将为大脑微环境的变化提供新的见解，这些变化影响大脑细胞的功能并导致疾病的发作或进展。通过研究大脑微观结构和功能的变化而产生的数据的机器学习应用将用于预测大脑中疾病相关的变化。这项研究还将通过开发经过验证的开源软件来影响教育和推广，这些软件可广泛适用于大脑以外的组织、其他疾病、组织探针或数据集。大脑微观结构和大脑功能之间的相互作用仍然没有得到很好的理解，尽管大脑微观结构和功能之间的联系是衰老，神经和精神疾病的潜在标志。研究这种关系是具有挑战性的-大脑微环境是动态的，并且在大脑内的区域与区域之间是可变的，并且当前的成像平台在空间和时间分辨率方面受到限制，无法访问所有大脑区域，并且无法使用相同的平台来定制不同的年龄或疾病模型。为了解决这些当前的限制，并提供更深入的了解时空变化的微观结构，主要研究者将使用器官型全半球脑切片（OWH）平台，保留在体内细胞和细胞外实质生理学，允许研究多个大脑区域在一个单一的切片，是响应不同的刺激，并可以产生不同的年龄和物种。研究人员将在新提出的OWH神经退行性变模型中使用他们建立的多粒子追踪（MPT）技术，研究扩散作为微观结构的衡量标准，并应用分子生物学和功能分析工具来确定微观结构变化的相关机制。机器学习模型应用于MPT数据的专业知识将用于构建神经网络模型，以预测功能性疾病状态。可定制的OWH脑切片模型与MPT和分子生物学工具的使用将使高时空探测和定量的区域微结构功能的关系，在发展和响应损伤/侮辱。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。