@article{SchneiderKruseBernardellideMattosetal.2021,
  author    = {Schneider, Verena and Kruse, Daniel and Bernardelli de Mattos, Ives and Z{\"o}phel, Saskia and Tiltmann, Kendra-Kathrin and Reigl, Amelie and Khan, Sarah and Funk, Martin and Bodenschatz, Karl and Groeber-Becker, Florian},
  title     = {A 3D in vitro model for burn wounds: monitoring of regeneration on the epidermal level},
  series = {Biomedicines},
  volume    = {9},
  journal   = {Biomedicines},
  number    = {9},
  issn      = {2227-9059},
  doi       = {10.3390/biomedicines9091153},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-246068},
  year      = {2021},
  abstract  = {Burns affect millions every year and a model to mimic the pathophysiology of such injuries in detail is required to better understand regeneration. The current gold standard for studying burn wounds are animal models, which are under criticism due to ethical considerations and a limited predictiveness. Here, we present a three-dimensional burn model, based on an open-source model, to monitor wound healing on the epidermal level. Skin equivalents were burned, using a preheated metal cylinder. The healing process was monitored regarding histomorphology, metabolic changes, inflammatory response and reepithelialization for 14 days. During this time, the wound size decreased from 25\% to 5\% of the model area and the inflammatory response (IL-1β, IL-6 and IL-8) showed a comparable course to wounding and healing in vivo. Additionally, the topical application of 5\% dexpanthenol enhanced tissue morphology and the number of proliferative keratinocytes in the newly formed epidermis, but did not influence the overall reepithelialization rate. In summary, the model showed a comparable healing process to in vivo, and thus, offers the opportunity to better understand the physiology of thermal burn wound healing on the keratinocyte level.},
  language  = {en}
}
@article{HepbasliGredyUllrichetal.2021,
  author    = {Hepbasli, Denis and Gredy, Sina and Ullrich, Melanie and Reigl, Amelie and Abeßer, Marco and Raabe, Thomas and Schuh, Kai},
  title     = {Genotype- and Age-Dependent Differences in Ultrasound Vocalizations of SPRED2 Mutant Mice Revealed by Machine Deep Learning},
  series = {Brain Sciences},
  volume    = {11},
  journal   = {Brain Sciences},
  number    = {10},
  issn      = {2076-3425},
  doi       = {10.3390/brainsci11101365},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-248525},
  year      = {2021},
  abstract  = {Vocalization is an important part of social communication, not only for humans but also for mice. Here, we show in a mouse model that functional deficiency of Sprouty-related EVH1 domain-containing 2 (SPRED2), a protein ubiquitously expressed in the brain, causes differences in social ultrasound vocalizations (USVs), using an uncomplicated and reliable experimental setting of a short meeting of two individuals. SPRED2 mutant mice show an OCD-like behaviour, accompanied by an increased release of stress hormones from the hypothalamic-pituitary-adrenal axis, both factors probably influencing USV usage. To determine genotype-related differences in USV usage, we analyzed call rate, subtype profile, and acoustic parameters (i.e., duration, bandwidth, and mean peak frequency) in young and old SPRED2-KO mice. We recorded USVs of interacting male and female mice, and analyzed the calls with the deep-learning DeepSqueak software, which was trained to recognize and categorize the emitted USVs. Our findings provide the first classification of SPRED2-KO vs. wild-type mouse USVs using neural networks and reveal significant differences in their development and use of calls. Our results show, first, that simple experimental settings in combination with deep learning are successful at identifying genotype-dependent USV usage and, second, that SPRED2 deficiency negatively affects the vocalization usage and social communication of mice.},
  language  = {en}
}