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

anti-viral drugs machine learning quantum dots single-particle tracking virus infection

Journal

Advanced materials (Deerfield Beach, Fla.)
ISSN: 1521-4095
Titre abrégé: Adv Mater
Pays: Germany
ID NLM: 9885358

Informations de publication

Date de publication:
19 Jan 2024
Historique:
revised: 16 01 2024
received: 31 10 2023
medline: 20 1 2024
pubmed: 20 1 2024
entrez: 20 1 2024
Statut: aheadofprint

Résumé

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.

Identifiants

pubmed: 38243660
doi: 10.1002/adma.202311457
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e2311457

Informations de copyright

This article is protected by copyright. All rights reserved.

Auteurs

Lei Wang (L)

State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Research Center for Analytical Sciences, College of Chemistry, and School of Medicine, Nankai University, Tianjin, 300071, P. R. China.

Hua-Jie Chen (HJ)

Engineering Research Center of Nano-Geomaterials of Ministry of Education, Faculty of Materials Science and Chemistry, China University of Geosciences, Wuhan, 430074, P. R. China.

Zhi-Gang Wang (ZG)

State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Research Center for Analytical Sciences, College of Chemistry, and School of Medicine, Nankai University, Tianjin, 300071, P. R. China.

Di Ning (D)

State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Research Center for Analytical Sciences, College of Chemistry, and School of Medicine, Nankai University, Tianjin, 300071, P. R. China.

Wei Zhao (W)

State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Research Center for Analytical Sciences, College of Chemistry, and School of Medicine, Nankai University, Tianjin, 300071, P. R. China.

Virgile Rat (V)

Physical Chemistry, Department of Chemistry, and Center for Integrated Protein Science Munich (CIPSM) and Nanosystems Initiative Munich (NIM), Ludwig-Maximilians-Universität, 81377, München, Germany.

Don C Lamb (DC)

Physical Chemistry, Department of Chemistry, and Center for Integrated Protein Science Munich (CIPSM) and Nanosystems Initiative Munich (NIM), Ludwig-Maximilians-Universität, 81377, München, Germany.

Dai-Wen Pang (DW)

State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Research Center for Analytical Sciences, College of Chemistry, and School of Medicine, Nankai University, Tianjin, 300071, P. R. China.

Shu-Lin Liu (SL)

State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Research Center for Analytical Sciences, College of Chemistry, and School of Medicine, Nankai University, Tianjin, 300071, P. R. China.
Physical Chemistry, Department of Chemistry, and Center for Integrated Protein Science Munich (CIPSM) and Nanosystems Initiative Munich (NIM), Ludwig-Maximilians-Universität, 81377, München, Germany.

Classifications MeSH