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Friedrich-Alexander Universität Erlangen-Nürnberg

4 ARTICLES PUBLISHED IN JoVE

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Medicine

Multi-modal Imaging of Angiogenesis in a Nude Rat Model of Breast Cancer Bone Metastasis Using Magnetic Resonance Imaging, Volumetric Computed Tomography and Ultrasound
Tobias Bäuerle 1, Dorde Komljenovic 1, Martin R. Berger 2, Wolfhard Semmler 1
1Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany, 2Unit of Chemotherapy and Toxicology, German Cancer Research Center, Heidelberg, Germany

In the pathogenesis of bone metastasis, angiogenesis is a crucial process and therefore represents a target for imaging and therapy. Here, we present a rat model of site-specific breast cancer bone metastasis and describe strategies to non-invasively image angiogenesis in vivo using magnetic resonance imaging, volumetric computed tomography and ultrasound.

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Developmental Biology

Mechanism of Regulation of Adipocyte Numbers in Adult Organisms Through Differentiation and Apoptosis Homeostasis
Aline Bozec 1,2, Nicole Hannemann 1,2
1Department of Medicine 3, Rheumatology and Immunology, Universitätsklinikum Erlangen, 2Nikolaus Fiebiger Center of Molecular Medicine, Universitätsklinikum Erlangen

Adipose tissue (AT) can influence whole body homeostasis, therefore understanding the molecular mechanisms of adipocyte differentiation and function is of importance. We provide a protocol for gaining new insights into these processes by analyzing adipocyte homeostasis, differentiation and hypoxia exposure as a model for induced adipocyte apoptosis.

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Cancer Research

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
Stephan Ellmann 1, Lisa Seyler 1, Clarissa Gillmann 2, Vanessa Popp 1, Christoph Treutlein 1, Aline Bozec 3, Michael Uder 1, Tobias Bäuerle 1
1Department of Radiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, 2Department of Medical Physics in Radiation Oncology, German Cancer Research Center, 3Department of Internal Medicine 3, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg

This protocol was designed to train a machine learning algorithm to use a combination of imaging parameters derived from magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) in a rat model of breast cancer bone metastases to detect early metastatic disease and predict subsequent progression to macrometastases.

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Biology

High Throughput Image-Based Phenotyping for Determining Morphological and Physiological Responses to Single and Combined Stresses in Potato
Lamis Osama Anwar Abdelhakim 1, Barbora Pleskačová 1, Natalia Yaneth Rodriguez-Granados 2, Rashmi Sasidharan 2, Lucia Sandra Perez-Borroto 3, Sophia Sonnewald 4, Kristina Gruden 5, Ute C. Vothknecht 6, Markus Teige 7, Klára Panzarová 1
1PSI (Photon Systems Instruments), spol. s r.o. Drasov, 2Plant Stress Resilience, Institute of Environmental Biology, Utrecht University, 3Plant Breeding, Wageningen University and Research, 4Department of Biology, Biochemistry, Friedrich-Alexander Universität Erlangen-Nürnberg, 5Department of Biotechnology and Systems Biology, National Institute of Biology, 6Plant Cell Biology, Institute of Cellular and Molecular Botany, University of Bonn, 7Department of Functional & Evolutionary Ecology, University of Vienna

We designed an image-based phenotyping protocol to determine the morphological and physiological responses to single and combined heat, drought, and waterlogging treatments. This approach enabled the identification of early, late, and recovery responses at a whole plant level, particularly above-ground parts, and highlighted the necessity of using multiple imaging sensors.

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