Cargando…
Building predictive disease models using extracellular vesicle microscale flow cytometry and machine learning
Extracellular vesicles (EVs) are highly abundant in human biofluids, containing a repertoire of macromolecules and biomarkers representative of the tissue of origin. EVs released by tumours can communicate key signals both locally and to distant sites to promote growth and survival or impact invasiv...
Autores principales: | Paproski, Robert J., Pink, Desmond, Sosnowski, Deborah L., Vasquez, Catalina, Lewis, John D. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9980304/ https://www.ncbi.nlm.nih.gov/pubmed/36520580 http://dx.doi.org/10.1002/1878-0261.13362 |
Ejemplares similares
-
Clinical analysis of EV‐Fingerprint to predict grade group 3 and above prostate cancer and avoid prostate biopsy
por: Fairey, Adrian, et al.
Publicado: (2023) -
Extracellular Vesicle Flow Cytometry Analysis and Standardization
por: Welsh, Joshua A., et al.
Publicado: (2017) -
Labeling Extracellular Vesicles for Nanoscale Flow Cytometry
por: Morales-Kastresana, Aizea, et al.
Publicado: (2017) -
Cover Image
por: Fairey, Adrian, et al.
Publicado: (2023) -
Reliable measurements of extracellular vesicles by clinical flow cytometry
por: Kuiper, Martine, et al.
Publicado: (2020)