Hildebrandt is a member of the Academic Committee of the Chengdu Research Base of Giant Panda Breeding and has been elected “Giant Panda Personality of the Year ”, an award at the Giant Panda Global Awards 2019 for his contribution to assisted reproduction of pandas in the Berlin Zoo and in the Chengdu Research Base of Giant Panda Breeding in China. And to determine whether the corpus luteum dormancy phase and pseudopregnancy can be exploited as a tool for genetic diversity management.įor this project, the Departments of Reproductive Management and Reproductive Biology have been establishing a successful and sustainable collaboration during the past years.To pursue induction of diapause in vitro and unravel what factors are potentially involved (maternal and foetal).To develop innovative assisted reproduction technologies (ART) for minimal-invasive recovery of oocytes and to promote early in vitro development of embryos from these oocytes.To link the endocrine profile to development stages of the embryo, supported by ultrasound observations.To expand our knowledge on their reproductive biology by enhanced endocrinology with development of diagnostic tools for on-site birth-monitoring.To support the giant panda breeding program at Zoo Berlin through endocrine monitoring (timing AI and pregnancy diagnosis/monitoring), AI and ultrasound training and observations.In addition, the IZW is essentially involved in the development of systematic protocols for the diagnosis and treatment of infertility in pandas together with the Chengdu Research Base of Giant Panda Breeding. The aim is to establish embryo transfer in this highly endangered species. The knowledge gained will be used for new techniques of assisted reproduction in the giant panda. In this project we aim to gain knowledge explaining their reproductive biology - particularly the regulation of diapause – through a combined approach of high-resolution ultrasound and state-of-the-art endocrinological techniques, facilitated by assisted reproduction techniques (ART) and subsequent in vitro modelling. Exchange and training symposium for hedgehog rescue centers (in German).WTimpact – Citizen Science as a tool for knowledge transfer.Assessment of the reproductive status of wildlife.Wildlife pathology and disease diagnostics.Pathological anatomical reference collection.Summer School on Non-invasive Monitoring of Hormones.International Summer School on Stable Isotopes in Animal Ecology.Meeting on Evidence-based Conservation of Bats.2nd International Bat Research Online Symposium, Jan 2023.International Bat Research Online Symposium.Junior Professorship Parasite Host Interactions. Methodologically, we will develop new Bayesian inference methods to learn MSMs from single-channel data and optimally combine them with simulation data. By combining extensive GPU-driven MD simulations (100 microsecond to milliseconds) with recently developed adaptive sampling techniques and multi-ensemble estimators, we will explore the conformational dynamics of binding domains in AMPA-type glutamate receptors and their modulation by binding auxiliary proteins. In this project, we will provide our expertise in long-timescale simulation and Markov state modeling from both experimental and simulation data to the research group. MSMs have been used to interpret the multi-state nature of experimental single-molecule recordings of ion channels and more recently they have been established as an inference machine to analyse high-throughput molecular dynamics (MD) simulation data. Markov state models (MSMs) are universal frameworks to encode the switching kinetics of biomolecular machines with multiple states. RG 2518/1: Combining Experiment, Simulation and Machine Learning to Elucidate the Activation of Glutamate Receptor Complexes (SP 08)
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