Many children suffer from bone deformities, which severely hinders their ability to walk. Some children may require invasive surgical treatment, such as cutting their bones, whilst others may recover their mobility through less invasive treatments such as guided growth surgery. However, surgeons have difficulties choosing the best treatment options because there is no reliable tool to help them predict the post-operative evolution of bone joints. CutGrow aims to provide a numerical platform whereby bone growth will be predicted virtually. The platform will rely on a novel finite element technology, CutFEM, developed by the applicant, Dr. Claus, which circumvents the need for meshing complex geometries. This algorithmic concept will bestow numerical agility upon all steps of the simulation process, from acquiring patient-specific data to handling complex contact conditions between interacting bones, the latter being the domain of excellence of the host supervisor Prof. Erleben. In the first stage of CutGrow, a seamless and robust simulation pipeline in the specific context of bone joint mechanics and growth will be created. In a second stage, the simulation will be used as a basis to develop a unifying and highly versatile model for children’s bone growth, capable of easily handling a range of mathematical growth stimulus theories. Finally, we will specialize the developments to the context of guided bone growth and prove that the proposed modelling framework can reproduce clinical data gathered by MD Wong at Hvidovre Hospital. The CutGrow simulation environment has the potential to transform paediatric orthopaedic surgery, by providing researchers with an agile tool to investigate new treatment options virtually and to design new operation planning procedures based on reliable, physics based simulation technologies.

This proposal lies at the intersection of algebra, topology, and geometry, with the scientific goal of answering central questions about homological stability, geodesics on manifolds, and the moduli space of Riemann surfaces. Homological stability is a subject that has seen spectacular progress in recent years, and recent work of the PI has opened up new perspectives on this field, through, among other things, associating a canonical family of spaces to any stability problem. The first two goals of the proposal are to give conditions under which this family of spaces is highly connected, and to use this to prove homological and representation stability theorems, with determination of the stable homology. Particular attention is given to Thompson-like groups, building on a recent breakthrough of the PI with Szymik. The last two goals concern geodesics and moduli spaces via string topology: The third goal seeks a geometric construction of compactified string topology, which we propose to use to address counting problems for geodesics on manifolds. Finally our fourth goal is to use compactified string topology to study the harmonic compactification itself, and give a new approach to finding families of unstable homology classes in the moduli space of Riemann surfaces. The feasibility of the last goals is demonstrated by the PIs earlier algebraic work in this direction; the proposal is to incorporate geometry in a much more fundamental way. The project combines breakthrough methods from homotopy theory with methods from algebraic, differential and geometric topology. Some of the goals are high risk, but we note that in those cases even partial results will be of significant interest. The PI has a proven track record at the international forefront of research, and as a research leader, e.g., through a previous ERC Starting Grant. The research team will consist of the PI together with 3 PhD students and 3 postdocs in total during the 5 years.

Coastal seagrass ecosystems provide important services to nature and mankind in form of coastal protection, nursery grounds and carbon sequestration. However, seagrass meadows are affected by global climate change and anthropogenic stressors such as eutrophication and coastal development. Yet, the mechanistic interactions between these ecosystems and environmental change remain unclear due to the complexity of studying the seagrass habitat, which exhibit a multitude of chemical gradients and dynamics. The requirement for high-resolution measurement techniques for resolving the biogeochemical dynamics and microenvironments surrounding seagrasses in their natural habitat has led to the development of a variety of chemical techniques typically quantifying a single analyte at a time, which gives limited insight to the true dynamics of the seagrass-sediment interaction which is central for seagrass fitness and survival under environmental change. The SIPODET project will develop new multi-parameter chemical imaging techniques by combining luminescence-based optical sensor foils (planar optodes) with diffusional equilibrium in thin-film (DET) enabling simultaneous sensing of pO2, iron, phosphate, nitrite/nitrate, ammonium, manganese, pCO2 and pH. This project will encompass expert training of Dr. Cesbron in the use of planar optodes complementing his expertise in 2D DET mapping of chemical species, which will enable the development of a novel combined chemical imaging technology mentored by a world leader in microenvironmental analysis. The novel technology will investigate the dynamic chemical microenvironment in the seagrass rhizosphere and how this is modulated by environmental change and plant stress (e.g. effects of temperature, pH or eutrophication) in Zostera marina and Zostera noltei.

Anthropogenically-induced environmental pollution has had a dramatic influence on the natural world, including worldwide decreases in species richness and abundance, ecosystem homogenization, genomic modifications, and altered nutrient cycles. Particularly, human-induced environmental pollution of mercury can bioaccumulate in aquatic ecosystems and cause neurological, physiological, immunological and reproductive damage to wildlife, making it both a European, and global threat. However, the evolutionary impact of long-term exposure to mercury has yet to be studied despite evidence that exposure to mercury can negatively affect survival. Avian piscivores and insectivores, important bioindicators in highly diverse aquatic ecosystem, can be ideal for studying mercury impacts. This project will investigate the evolutionary changes induced by long-term exposure to mercury pollution in wild populations of important avian bioindicators in the Amazon using powerful advanced genomic analyses. It combines the latest Next Generation Sequencing (NGS) methods with avian ecology and evolution, ecotoxicology, immunology and endocrinology, to generate new insights into the costs of environmental pollution, and the subsequent adaptations that allow for species to survive sublethal exposure to mercury. In order to document long-term changes, historical specimens will be used to assess past genomic variation and mercury levels to be used as a baseline against which differentiating selection patterns are searched. The results will reveal the effects of anthropogenic change on important avian bioindicators and identify the missing link between causative mechanisms and phenotypes, thereby availing these methods for further research. By capitalizing on the development and application of cutting-edge genomics techniques, these findings can identify adaptive and susceptive genotypes to indicate whether selection allows for the survival of species in the face of acute environmental change.

Around 90% of all cancer-related deaths are due to metastasis. Understanding the process of cancer metastasis is therefore of urgent need to develop new treatments. Aberrant expression of the epidermal growth factor receptor (EGFR), or increased availability of its ligands promote tumour survival and metastasis in multiple cancers. As a result, several anti-EGFR therapeutics are in clinical use, but almost all patients will develop resistance against the treatment. Another strategy to treat EGFR driven cancers is to reduce the pool of available EGFR ligands. The crucial enzyme in EGFR ligand release is A Disintegrin And Metalloproteinase (ADAM) 17. I have unpublished data showing that depletion of ADAM17 significantly inhibits colon cancer growth and metastasis in vivo. However, anti-ADAM17 therapies have failed clinically and thus, we urgently need to understand the regulation of ADAM17. Recent discoveries by Dr. Kveiborg’s group, and collaborators showed that the protein phosphatase PP2A binds to ADAM17, and negatively regulates EGFR ligand release, thereby representing the first known negative regulator for ADAM17. Based on these novel findings, I hypothesize that the PP2A-ADAM17-EGFR axis has the ability to control cancer metastasis. To test this hypothesis, I aim to characterize the functional impact of the PP2A-ADAM17 interaction in cancer spread by creating ADAM17 mutants with different PP2A binding properties in colon cancer cells using CRISPR/Cas9 and functionally evaluate these cells in vitro and in zebrafish and mouse models. Moreover, I aim to unravel the molecular mechanisms of the interplay; applying SILAC coupled mass spectrometry and mutagenesis screening, to evaluate the mechanism by which PP2A affects ADAM17, and the signals involved in PP2A binding. This work will pave the way for the development of novel anti-cancer drugs and thereby expand the therapeutic choices for EGFR driven cancers and improve the patient survival.