A Phase Field Model for Continuous Clustering on Vector Fields

A new method for the simplification of flow fields is presented. It is based on continuous clustering. A well-known physical clustering model, the Cahn Hilliard model, which describes phase separation, is modified to reflect the properties of the data to be visualized. Clusters are defined implicitly as connected components of the positivity set of a density function. An evolution equation for this function is obtained as a suitable gradient flow of an underlying anisotropic energy functional. Here, time serves as the scale parameter. The evolution is characterized by a successive coarsening of patterns-the actual clustering-during which the underlying simulation data specifies preferable pattern boundaries. We introduce specific physical quantities in the simulation to control the shape, orientation and distribution of the clusters as a function of the underlying flow field. In addition, the model is expanded, involving elastic effects. In the early stages of the evolution shear layer type representation of the flow field can thereby be generated, whereas, for later stages, the distribution of clusters can be influenced. Furthermore, we incorporate upwind ideas to give the clusters an oriented drop-shaped appearance. Here, we discuss the applicability of this new type of approach mainly for flow fields, where the cluster energy penalizes cross streamline boundaries. However, the method also carries provisions for other fields as well. The clusters can be displayed directly as a flow texture. Alternatively, the clusters can be visualized by iconic representations, which are positioned by using a skeletonization algorithm.

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Isolation of native EVs from primary biofluids—Free‐flow electrophoresis as a novel approach to purify ascites‐derived EVs

Abstract Although extracellular vesicles (EVs) have been extensively characterized, efficient purification methods, especially from primary biofluids, remain challenging. Here we introduce free‐flow electrophoresis (FFE) as a novel approach for purifying EVs from primary biofluids, in particular from the peritoneal fluid (ascites) of ovarian cancer patients. FFE represents a versatile, fast, matrix‐free approach for separating different analytes with inherent differences in charge density and/or isoelectric point (pI). Using a series of buffered media with different pH values allowed us to collect 96 fractions of ascites samples. To characterize the composition of the individual fractions, we used state‐of‐the‐art methods such as nanoflow and imaging flow cytometry (nFCM and iFCM) in addition to classical approaches. Of note, tetraspanin‐positive events measured using nFCM were enriched in a small number of distinct fractions. This observation was corroborated by Western blot analysis and electron microscopy, demonstrating only minor contamination with soluble proteins and lipid particles. In addition, these gently purified EVs remain functional. Thus, FFE represents a new, efficient and fast method for separating native and highly purified EVs from complicated primary samples