The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Role of Exosomes/Microvesicles in the Nervous System and Use in Emerging Therapies
Open accessAbstract
Extracellular membrane vesicles (EMVs) are nanometer sized vesicles, including exosomes and microvesicles capable of transferring DNAs, mRNAs, microRNAs, non-coding RNAs, proteins, and lipids among cells without direct cell-to-cell contact, thereby representing a novel form of intercellular communication. Many cells in the nervous system have been shown to release EMVs, implicating their active roles in development, function, and pathologies of this system. While substantial progress has been made in understanding the biogenesis, biophysical properties, and involvement of EMVs in diseases, relatively less information is known about their biological function in the normal nervous system. In addition, since EMVs are endogenous vehicles with low immunogenicity, they have also been actively investigated for the delivery of therapeutic genes/molecules in treatment of cancer and neurological diseases. The present review summarizes current knowledge about EMV functions in the nervous system under both physiological and pathological conditions, as well as emerging EMV-based therapies that could be applied to the nervous system in the foreseeable future.
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Cited by
Biological properties of extracellular vesicles and their physiological functions
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Self-citationExosomes as drug delivery vehicles for Parkinson’s disease therapy
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Sumoylated hnRNPA2B1 controls the sorting of miRNAs into exosomes through binding to specific motifs
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Using exosomes, naturally-equipped nanocarriers, for drug delivery
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Metadata
- Authors
- Lai, C. P.-K., & Breakefield, X. O.
- Venue
- Frontiers in Physiology
- Publisher
- Frontiers Media SA
- Published
- 2012
- Volume
- 3
- Pages
- 228-228
- ISSN
- 1664-042X (ISSN-L)
- OpenAlex
- W2163711839
- Cited by
- 315
- References
- 16
- FWCI
- 7.32
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.