@article{KaltdorfSchulzeHelmprobstetal.2017,
  author    = {Kaltdorf, Kristin Verena and Schulze, Katja and Helmprobst, Frederik and Kollmannsberger, Philip and Dandekar, Thomas and Stigloher, Christian},
  title     = {Fiji macro 3D ART VeSElecT: 3D automated reconstruction tool for vesicle structures of electron tomograms},
  series = {PLoS Computational Biology},
  volume    = {13},
  journal   = {PLoS Computational Biology},
  number    = {1},
  doi       = {10.1371/journal.pcbi.1005317},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-172112},
  year      = {2017},
  abstract  = {Automatic image reconstruction is critical to cope with steadily increasing data from advanced microscopy. We describe here the Fiji macro 3D ART VeSElecT which we developed to study synaptic vesicles in electron tomograms. We apply this tool to quantify vesicle properties (i) in embryonic Danio rerio 4 and 8 days past fertilization (dpf) and (ii) to compare Caenorhabditis elegans N2 neuromuscular junctions (NMJ) wild-type and its septin mutant (unc-59(e261)). We demonstrate development-specific and mutant-specific changes in synaptic vesicle pools in both models. We confirm the functionality of our macro by applying our 3D ART VeSElecT on zebrafish NMJ showing smaller vesicles in 8 dpf embryos then 4 dpf, which was validated by manual reconstruction of the vesicle pool. Furthermore, we analyze the impact of C. elegans septin mutant unc-59(e261) on vesicle pool formation and vesicle size. Automated vesicle registration and characterization was implemented in Fiji as two macros (registration and measurement). This flexible arrangement allows in particular reducing false positives by an optional manual revision step. Preprocessing and contrast enhancement work on image-stacks of 1nm/pixel in x and y direction. Semi-automated cell selection was integrated. 3D ART VeSElecT removes interfering components, detects vesicles by 3D segmentation and calculates vesicle volume and diameter (spherical approximation, inner/outer diameter). Results are collected in color using the RoiManager plugin including the possibility of manual removal of non-matching confounder vesicles. Detailed evaluation considered performance (detected vesicles) and specificity (true vesicles) as well as precision and recall. We furthermore show gain in segmentation and morphological filtering compared to learning based methods and a large time gain compared to manual segmentation. 3D ART VeSElecT shows small error rates and its speed gain can be up to 68 times faster in comparison to manual annotation. Both automatic and semi-automatic modes are explained including a tutorial.},
  language  = {en}
}
@article{KollmannsbergerKerschnitzkiReppetal.2017,
  author    = {Kollmannsberger, Philip and Kerschnitzki, Michael and Repp, Felix and Wagermaier, Wolfgang and Weinkamer, Richard and Fratzl, Peter},
  title     = {The small world of osteocytes: connectomics of the lacuno-canalicular network in bone},
  series = {New Journal of Physics},
  volume    = {19},
  journal   = {New Journal of Physics},
  number    = {073019},
  doi       = {10.1088/1367-2630/aa764b},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-170662},
  year      = {2017},
  abstract  = {Osteocytes and their cell processes reside in a large, interconnected network of voids pervading the mineralized bone matrix of most vertebrates. This osteocyte lacuno-canalicular network (OLCN) is believed to play important roles in mechanosensing, mineral homeostasis, and for the mechanical properties of bone. While the extracellular matrix structure of bone is extensively studied on ultrastructural and macroscopic scales, there is a lack of quantitative knowledge on how the cellular network is organized. Using a recently introduced imaging and quantification approach, we analyze the OLCN in different bone types from mouse and sheep that exhibit different degrees of structural organization not only of the cell network but also of the fibrous matrix deposited by the cells. We define a number of robust, quantitative measures that are derived from the theory of complex networks. These measures enable us to gain insights into how efficient the network is organized with regard to intercellular transport and communication. Our analysis shows that the cell network in regularly organized, slow-growing bone tissue from sheep is less connected, but more efficiently organized compared to irregular and fast-growing bone tissue from mice. On the level of statistical topological properties (edges per node, edge length and degree distribution), both network types are indistinguishable, highlighting that despite pronounced differences at the tissue level, the topological architecture of the osteocyte canalicular network at the subcellular level may be independent of species and bone type. Our results suggest a universal mechanism underlying the self-organization of individual cells into a large, interconnected network during bone formation and mineralization.},
  language  = {en}
}