Filters

2014 - 201912020 - 20211

More filters

2019 - 201912020 - 20211
Reset filters

Settings

Author: Koch, Marcus × End date: 2023 × DDC: 570 × Publisher: Hoboken, NJ : Wiley × WGL Institute: INM ×

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    A correlative analysis of gold nanoparticles internalized by A549 cells
    (Hoboken, NJ : Wiley, 2014) Böse, Katharina; Koch, Marcus; Cavelius, Christian; Kiemer, Alexandra K.; Kraegeloh, Annette
    Fluorescently labeled nanoparticles are widely used to investigate nanoparticle cell interactions by fluorescence microscopy. Owing to limited lateral and axial resolution, nanostructures (<100 nm) cannot be resolved by conventional light micro­scopy techniques. Especially after uptake into cells, a common fate of the fluorescence label and the particle core cannot be taken for granted. In this study, a correlative approach is presented to image fluorescently labeled gold nanoparticles inside whole cells by correlative light and electron microscopy (CLEM). This approach allows for detection of the fluorescently labeled particle shell as well as for the gold core in one sample. In this setup, A549 cells are exposed to 8 nm Atto 647N-labeled gold nanoparticles (3.3 × 109 particles mL−1, 0.02 μg Au mL−1) for 5 h and are subsequently imaged by confocal laser scanning microscopy (CLSM) and transmission electron microscopy (TEM). Eight fluorescence signals located at different intracellular positions are further analyzed by TEM. Five of the eight fluorescence spots are correlated with isolated or agglomerated gold nanoparticles. Three fluorescence signals could not be related to the presence of gold, indicating a loss of the particle shell.
  • Thumbnail Image
    Item
    A novel universal algorithm for filament network tracing and cytoskeleton analysis
    (Hoboken, NJ : Wiley, 2021) Flormann, Daniel A.D.; Schu, Moritz; Terriac, Emmanuel; Thalla, Divyendu; Kainka, Lucina; Koch, Marcus; Gad, Annica K.B.; Lautenschläger, Franziska
    The rapid development of advanced microscopy techniques over recent decades has significantly increased the quality of imaging and our understanding of subcellular structures, such as the organization of the filaments of the cytoskeleton using fluorescence and electron microscopy. However, these recent improvements in imaging techniques have not been matched by similar development of techniques for computational analysis of the images of filament networks that can now be obtained. Hence, for a wide range of applications, reliable computational analysis of such two-dimensional methods remains challenging. Here, we present a new algorithm for tracing of filament networks. This software can extract many important parameters from grayscale images of filament networks, including the mesh hole size, and filament length and connectivity (also known as Coordination Number). In addition, the method allows sub-networks to be distinguished in two-dimensional images using intensity thresholding. We show that the algorithm can be used to analyze images of cytoskeleton networks obtained using different advanced microscopy methods. We have thus developed a new improved method for computational analysis of two-dimensional images of filamentous networks that has wide applications for existing imaging techniques. The algorithm is available as open-source software.