Currently, the means to gather real-time molecular information from the diseased human brain is limited, and high-throughput platforms that can assay neurological disease severity representative of the in vivo environment are still lacking. This proposal reflects a foundational effort in my lab to generate a high throughout, quantitative, real-time method of imaging cell and nanoparticle behavior, in 3-dimensions, within the neonatal or perinatal brain in the presence of disease. We will specifically focus on neuroinflammation as a common disease hallmark and use a transgenic rat model of autism. This approach will open up new avenues of research in the life sciences and clinical sciences, by providing a platform for assessment of processes that are currently inaccessible to high-throughput study, including developmental processes (i.e. synaptogenesis) and normal regulation of fluid flow (i.e. regulation of waste removal via the glymphatic system). In addition, tracking and modelling nanoparticle co-localization in, or interaction with, cells following injury could also provide new potential therapeutic targets. Developing therapeutic technologies by leveraging their in vivo interactions with common disease hallmarks can lead to more efficient translation of therapies across diseases with shared pathophysiological features. Given that inflammation is a common factor across many central nervous system (CNS) diseases, results are expected to provide insights and translate from the autism model used in this proposal to other models, including adult, of brain disease.

Public Health Relevance

This proposal aims to develop a real-time, 3-dimensional, quantitative imaging methodology in organotypic brain slices to track nanoparticle and cellular behavior in the developing brain and in the presence of neuroinflammation. This approach will open up new avenues of research in the life sciences and clinical sciences, by providing a platform for assessment of neurological processes that are currently inaccessible to high-throughput study.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Unknown (R35)
Project #
1R35GM124677-01
Application #
9380508
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Sammak, Paul J
Project Start
2017-08-01
Project End
2022-07-31
Budget Start
2017-08-01
Budget End
2018-07-31
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of Washington
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
605799469
City
Seattle
State
WA
Country
United States
Zip Code
98195