Mapping Extracellular Space Features of Viral Encephalitis to Evaluate The Proficiency of Anti‐Viral Drugs

Abstract The extracellular space (ECS) is an important barrier against viral attack on brain cells, and dynamic changes in ECS microstructure characteristics are closely related to the progression of viral encephalitis in the brain and the efficacy of antiviral drugs. However, mapping the precise morphological and rheological features of the ECS in viral encephalitis is still challenging so far. Here, we developed a robust approach using single‐particle diffusional fingerprinting (SPDF) of quantum dots combined with machine learning to map ECS features in the brain and predict the efficacy of antiviral encephalitis drugs. Our results demonstrated that this approach can characterize the microrheology and geometry of the brain ECS at different stages of viral infection and identify subtle changes induced by different drug treatments. This approach provides a potential platform for drug proficiency assessment and is expected to offer a reliable basis for clinical translation of drugs. This article is protected by copyright. All rights reserved