Comming soon ...

@ARTICLE{Schurz2022-kh,
  title    = "{EVAnalyzer}: High content imaging for rigorous characterisation
              of single extracellular vesicles using standard laboratory
              equipment and a new open-source {ImageJ/Fiji} plugin",
  author   = "Sch{\"u}rz, Melanie and Danmayr, Joachim and Jaritsch, Maria and
              Klinglmayr, Eva and Benirschke, Heloisa Melo and Matea,
              Cristian-Tudor and Zimmerebner, Patrick and Rauter, Jakob and
              Wolf, Martin and Gomes, Fausto Gueths and Kratochvil, Zdenek and
              Heger, Zbynek and Miller, Andrew and Heuser, Thomas and
              Stanojlovic, Vesna and Kiefer, Jana and Plank, Tanja and Johnson,
              Litty and Himly, Martin and Bl{\"o}chl, Constantin and Huber,
              Christian G and Hintersteiner, Martin and Meisner-Kober, Nicole",
  abstract = "Extracellular vesicle (EV) research increasingly demands for
              quantitative characterisation at the single vesicle level to
              address heterogeneity and complexity of EV subpopulations.
              Emerging, commercialised technologies for single EV analysis
              based on, for example, imaging flow cytometry or imaging after
              capture on chips generally require dedicated instrumentation and
              proprietary software not readily accessible to every lab. This
              limits their implementation for routine EV characterisation in
              the rapidly growing EV field. We and others have shown that
              single vesicles can be detected as light diffraction limited
              fluorescent spots using standard confocal and widefield
              fluorescence microscopes. Advancing this simple strategy into a
              process for routine EV quantitation, we developed 'EVAnalyzer',
              an ImageJ/Fiji (Fiji is just ImageJ) plugin for automated,
              quantitative single vesicle analysis from imaging data. Using
              EVAnalyzer, we established a robust protocol for capture,
              (immuno-)labelling and fluorescent imaging of EVs. To exemplify
              the application scope, the process was optimised and
              systematically tested for (i) quantification of EV
              subpopulations, (ii) validation of EV labelling reagents, (iii)
              in situ determination of antibody specificity, sensitivity and
              species cross-reactivity for EV markers and (iv) optimisation of
              genetic EV engineering. Additionally, we show that the process
              can be applied to synthetic nanoparticles, allowing to determine
              siRNA encapsulation efficiencies of lipid-based nanoparticles
              (LNPs) and protein loading of SiO(2) nanoparticles. EVAnalyzer
              further provides a pipeline for automated quantification of cell
              uptake at the single cell-single vesicle level, thereby enabling
              high content EV cell uptake assays and plate-based screens.
              Notably, the entire procedure from sample preparation to the
              final data output is entirely based on standard reagents,
              materials, laboratory equipment and open access software. In
              summary, we show that EVAnalyzer enables rigorous
              characterisation of EVs with generally accessible tools. Since we
              further provide the plugin as open-source code, we expect
              EVAnalyzer to not only be a resource of immediate impact, but an
              open innovation platform for the EV and nanoparticle research
              communities.",
  journal  = "J Extracell Vesicles",
  volume   =  11,
  number   =  12,
  pages    = "e12282",
  month    =  dec,
  year     =  2022,
  address  = "United States",
  keywords = "EV immunolabelling; cell uptake; exosomes; extracellular
              vesicles; lipid nanoparticles; liposomes; open innovation; silica
              nanoparticles; single particle imaging; single vesicle imaging",
  language = "en"
}