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1000 Titel
  • Protocols for staining of bile canalicular and sinusoidal networks of human, mouse and pig livers, three-dimensional reconstruction and quantification of tissue microarchitecture by image processing and analysis
1000 Autor/in
  1. Hammad, Seddik |
  2. Hoehme, Stefan |
  3. Friebel, Adrian |
  4. von Recklinghausen, Iris |
  5. Othman, Amnah |
  6. Begher-Tibbe, Brigitte |
  7. Johann, Tim |
  8. Vartak, Amruta |
  9. Bucur, Petru O. |
  10. Vibert, Eric |
  11. Christ, Bruno |
  12. Dooley, Steven |
  13. Meyer, Christoph |
  14. Ilkavets, Iryna |
  15. Dahmen, Uta |
  16. Dirsch, Olaf |
  17. Böttger, Jan |
  18. Gebhardt, Rolf |
  19. Drasdo, Dirk |
  20. http://d-nb.info/gnd/1101680555 |
  21. Godoy, Patricio |
  22. Golka, Klaus |
  23. Marchan, Rosemarie |
  24. Hengstler, Jan G. |
1000 Erscheinungsjahr 2014
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2014-04-19
1000 Erschienen in
1000 Quellenangabe
  • 88(5): 1161–1183
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2014
1000 Lizenz
1000 Verlagsversion
  • http://doi.org/10.1007/s00204-014-1243-5 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3996365/ |
1000 Ergänzendes Material
  • https://link.springer.com/article/10.1007%2Fs00204-014-1243-5 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Histological alterations often constitute a fingerprint of toxicity and diseases. The extent to which these alterations are cause or consequence of compromised organ function, and the underlying mechanisms involved is a matter of intensive research. In particular, liver disease is often associated with altered tissue microarchitecture, which in turn may compromise perfusion and functionality. Research in this field requires the development and orchestration of new techniques into standardized processing pipelines that can be used to reproducibly quantify tissue architecture. Major bottlenecks include the lack of robust staining, and adequate reconstruction and quantification techniques. To bridge this gap, we established protocols employing specific antibody combinations for immunostaining, confocal imaging, three-dimensional reconstruction of approximately 100-μm-thick tissue blocks and quantification of key architectural features. We describe a standard procedure termed ‘liver architectural staining’ for the simultaneous visualization of bile canaliculi, sinusoidal endothelial cells, glutamine synthetase (GS) for the identification of central veins, and DAPI as a nuclear marker. Additionally, we present a second standard procedure entitled ‘S-phase staining’, where S-phase-positive and S-phase-negative nuclei (stained with BrdU and DAPI, respectively), sinusoidal endothelial cells and GS are stained. The techniques include three-dimensional reconstruction of the sinusoidal and bile canalicular networks from the same tissue block, and robust capture of position, size and shape of individual hepatocytes, as well as entire lobules from the same tissue specimen. In addition to the protocols, we have also established image analysis software that allows relational and hierarchical quantifications of different liver substructures (e.g. cells and vascular branches) and events (e.g. cell proliferation and death). Typical results acquired for routinely quantified parameters in adult mice (C57Bl6/N) include the hepatocyte volume (5,128.3 ± 837.8 μm3) and the fraction of the hepatocyte surface in contact with the neighbouring hepatocytes (67.4 ± 6.7 %), sinusoids (22.1 ± 4.8 %) and bile canaliculi (9.9 ± 3.8 %). Parameters of the sinusoidal network that we also routinely quantify include the radius of the sinusoids (4.8 ± 2.25 μm), the branching angle (32.5 ± 11.2°), the length of intersection branches (23.93 ± 5.9 μm), the number of intersection nodes per mm3 (120.3 × 103 ± 42.1 × 103), the average length of sinusoidal vessel per mm3 (5.4 × 103 ± 1.4 × 103mm) and the percentage of vessel volume in relation to the whole liver volume (15.3 ± 3.9) (mean ± standard deviation). Moreover, the provided parameters of the bile canalicular network are: length of the first-order branches (7.5 ± 0.6 μm), length of the second-order branches (10.9 ± 1.8 μm), length of the dead-end branches (5.9 ± 0.7 μm), the number of intersection nodes per mm3 (819.1 × 103 ± 180.7 × 103), the number of dead-end branches per mm3 (409.9 × 103 ± 95.6 × 103), the length of the bile canalicular network per mm3 (9.4 × 103 ± 0.7 × 103 mm) and the percentage of the bile canalicular volume with respect to the total liver volume (3.4 ± 0.005). A particular strength of our technique is that quantitative parameters of hepatocytes and bile canalicular as well as sinusoidal networks can be extracted from the same tissue block. Reconstructions and quantifications performed as described in the current protocols can be used for quantitative mathematical modelling of the underlying mechanisms. Furthermore, protocols are presented for both human and pig livers. The technique is also applicable for both vibratome blocks and conventional paraffin slices.
1000 Sacherschließung
lokal Quantitative imaging
lokal Hepatocyte polarity
lokal Confocal microscopy
lokal Liver microarchitecture
lokal Systems biology
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/creator/SGFtbWFkLCBTZWRkaWsg|https://frl.publisso.de/adhoc/creator/SG9laG1lLCBTdGVmYW4g|https://frl.publisso.de/adhoc/creator/RnJpZWJlbCwgQWRyaWFuIA==|https://frl.publisso.de/adhoc/creator/dm9uIFJlY2tsaW5naGF1c2VuLCBJcmlzIA==|https://frl.publisso.de/adhoc/creator/T3RobWFuLCBBbW5haCA=|https://frl.publisso.de/adhoc/creator/QmVnaGVyLVRpYmJlLCBCcmlnaXR0ZSA=|https://frl.publisso.de/adhoc/creator/Sm9oYW5uLCBUaW0g|https://frl.publisso.de/adhoc/creator/VmFydGFrLCBBbXJ1dGEg|https://frl.publisso.de/adhoc/creator/QnVjdXIsIFBldHJ1IE8uIA==|https://frl.publisso.de/adhoc/creator/VmliZXJ0LCBFcmljIA==|https://frl.publisso.de/adhoc/creator/Q2hyaXN0LCBCcnVubyA=|https://frl.publisso.de/adhoc/creator/RG9vbGV5LCBTdGV2ZW4g|https://frl.publisso.de/adhoc/creator/TWV5ZXIsIENocmlzdG9waCA=|https://frl.publisso.de/adhoc/creator/SWxrYXZldHMsIElyeW5hIA==|https://frl.publisso.de/adhoc/creator/RGFobWVuLCBVdGEg|https://frl.publisso.de/adhoc/creator/RGlyc2NoLCBPbGFmIA==|https://frl.publisso.de/adhoc/creator/QsO2dHRnZXIsIEphbiA=|https://frl.publisso.de/adhoc/creator/R2ViaGFyZHQsIFJvbGYg|https://frl.publisso.de/adhoc/creator/RHJhc2RvLCBEaXJrIA==|http://d-nb.info/gnd/1101680555|http://orcid.org/0000-0001-7882-5369|http://orcid.org/0000-0003-0954-3805|http://orcid.org/0000-0003-4414-1633|http://d-nb.info/gnd/175862257
1000 Label
1000 Förderer
  1. BMBF (German Federal Ministry of Education and Research) |
  2. Virtual Liver Network (VLN) |
1000 Fördernummer
  1. -
  2. ANR-13-TECS-0006
1000 Förderprogramm
  1. Virtual Liver Network (VLN)
  2. Project Intraoperative Fluorescent Liver Optimization Work-up—iFLOW
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer BMBF (German Federal Ministry of Education and Research) |
    1000 Förderprogramm Virtual Liver Network (VLN)
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer Virtual Liver Network (VLN) |
    1000 Förderprogramm Project Intraoperative Fluorescent Liver Optimization Work-up—iFLOW
    1000 Fördernummer ANR-13-TECS-0006
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6403024.rdf
1000 Erstellt am 2017-06-13T11:46:47.116+0200
1000 Erstellt von 24
1000 beschreibt frl:6403024
1000 Bearbeitet von 218
1000 Zuletzt bearbeitet Fri Nov 27 13:56:28 CET 2020
1000 Objekt bearb. Fri Nov 27 13:56:27 CET 2020
1000 Vgl. frl:6403024
1000 Oai Id
  1. oai:frl.publisso.de:frl:6403024 |
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