Advances in Extracellular Vesicle Research Over the Past Decade: Source and Isolation Method are Connected with Cargo and Function.

Autor: Poupardin R; Cell Therapy Institute, Paracelsus Medical University, Salzburg, 5020, Austria., Wolf M; Cell Therapy Institute, Paracelsus Medical University, Salzburg, 5020, Austria., Maeding N; Cell Therapy Institute, Paracelsus Medical University, Salzburg, 5020, Austria., Paniushkina L; Cell Therapy Institute, Paracelsus Medical University, Salzburg, 5020, Austria.; Departments of Molecular and Comparative Pathobiology and Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA., Geissler S; BIH Center for Regenerative Therapies (BCRT), Berlin Institute of Health at Charité - Universitätsmedizin Berlin, 10178, Berlin, Germany., Bergese P; Department of Molecular and Translational Medicine, University of Brescia, Brescia, 25121, Italy.; INSTM - National Interuniversity Consortium of Materials Science and Technology, Firenze, 50121, Italy.; National Center for Gene Therapy and Drugs based on RNA Technology - CN3, Padova, 35122, Italy., Witwer KW; Departments of Molecular and Comparative Pathobiology and Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA., Schallmoser K; Institute of Transfusion Medicine, Paracelsus Medical University, Salzburg, 5020, Austria., Fuhrmann G; Department of Biology, Friedrich-Alexander-University Erlangen-Nürnberg, 91054, Erlangen, Germany., Strunk D; Cell Therapy Institute, Paracelsus Medical University, Salzburg, 5020, Austria.; Institute of Transfusion Medicine, Paracelsus Medical University, Salzburg, 5020, Austria.
Jazyk: angličtina
Zdroj: Advanced healthcare materials [Adv Healthc Mater] 2024 Jul; Vol. 13 (19), pp. e2303941. Date of Electronic Publication: 2024 Apr 18.
DOI: 10.1002/adhm.202303941
Abstrakt: The evolution of extracellular vesicle (EV) research has introduced nanotechnology into biomedical cell communication science while recognizing what is formerly considered cell "dust" as constituting an entirely new universe of cell signaling particles. To display the global EV research landscape, a systematic review of 20 364 original research articles selected from all 40 684 EV-related records identified in PubMed 2013-2022 is performed. Machine-learning is used to categorize the high-dimensional data and further dissected significant associations between EV source, isolation method, cargo, and function. Unexpected correlations between these four categories indicate prevalent experimental strategies based on cargo connectivity with function of interest being associated with certain EV sources or isolation strategies. Conceptually relevant association of size-based EV isolation with protein cargo and uptake function will guide strategic conclusions enhancing future EV research and product development. Based on this study, an open-source database is built to facilitate further analysis with conventional or AI tools to identify additional causative associations of interest.
(© 2024 The Authors. Advanced Healthcare Materials published by Wiley‐VCH GmbH.)
Databáze: MEDLINE
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