@article{6857, abstract = {Gene Drives are regarded as future tools with a high potential for population control. Due to their inherent ability to overcome the rules of Mendelian inheritance, gene drives (GD) may spread genes rapidly through populations of sexually reproducing organisms. A release of organisms carrying a GD would constitute a paradigm shift in the handling of genetically modified organisms because gene drive organisms (GDO) are designed to drive their transgenes into wild populations and thereby increase the number of GDOs. The rapid development in this field and its focus on wild populations demand a prospective risk assessment with a focus on exposure related aspects. Presently, it is unclear how adequate risk management could be guaranteed to limit the spread of GDs in time and space, in order to avoid potential adverse effects in socio‐ecological systems. The recent workshop on the “Evaluation of Spatial and Temporal Control of Gene Drives” hosted by the Institute of Safety/Security and Risk Sciences (ISR) in Vienna aimed at gaining some insight into the potential population dynamic behavior of GDs and appropriate measures of control. Scientists from France, Germany, England, and the USA discussed both topics in this meeting on April 4–5, 2019. This article summarizes results of the workshop.}, author = {Giese, B and Friess, J L and Schetelig, M F and Barton, Nicholas H and Messer, Philip and Debarre, Florence and Meimberg, H and Windbichler, N and Boete, C}, issn = {1521-1878}, journal = {BioEssays}, number = {11}, publisher = {Wiley}, title = {{Gene Drives: Dynamics and regulatory matters – A report from the workshop “Evaluation of spatial and temporal control of Gene Drives”, 4 – 5 April 2019, Vienna}}, doi = {10.1002/bies.201900151}, volume = {41}, year = {2019}, } @article{6940, abstract = {We study the effect of a linear tunneling coupling between two-dimensional systems, each separately exhibiting the topological Berezinskii-Kosterlitz-Thouless (BKT) transition. In the uncoupled limit, there are two phases: one where the one-body correlation functions are algebraically decaying and the other with exponential decay. When the linear coupling is turned on, a third BKT-paired phase emerges, in which one-body correlations are exponentially decaying, while two-body correlation functions exhibit power-law decay. We perform numerical simulations in the paradigmatic case of two coupled XY models at finite temperature, finding evidences that for any finite value of the interlayer coupling, the BKT-paired phase is present. We provide a picture of the phase diagram using a renormalization group approach.}, author = {Bighin, Giacomo and Defenu, Nicolò and Nándori, István and Salasnich, Luca and Trombettoni, Andrea}, issn = {1079-7114}, journal = {Physical Review Letters}, number = {10}, publisher = {American Physical Society}, title = {{Berezinskii-Kosterlitz-Thouless paired phase in coupled XY models}}, doi = {10.1103/physrevlett.123.100601}, volume = {123}, year = {2019}, } @article{6919, author = {Qi, Chao and Minin, Giulio Di and Vercellino, Irene and Wutz, Anton and Korkhov, Volodymyr M.}, issn = {23752548}, journal = {Science Advances}, number = {9}, publisher = {American Association for the Advancement of Science}, title = {{Structural basis of sterol recognition by human hedgehog receptor PTCH1}}, doi = {10.1126/sciadv.aaw6490}, volume = {5}, year = {2019}, } @article{6983, abstract = {Malaria, a disease caused by parasites of the Plasmodium genus, begins when Plasmodium-infected mosquitoes inject malaria sporozoites while searching for blood. Sporozoites migrate from the skin via blood to the liver, infect hepatocytes, and form liver stages which in mice 48 h later escape into blood and cause clinical malaria. Vaccine-induced activated or memory CD8 T cells are capable of locating and eliminating all liver stages in 48 h, thus preventing the blood-stage disease. However, the rules of how CD8 T cells are able to locate all liver stages within a relatively short time period remains poorly understood. We recently reported formation of clusters consisting of variable numbers of activated CD8 T cells around Plasmodium yoelii (Py)-infected hepatocytes. Using a combination of experimental data and mathematical models we now provide additional insights into mechanisms of formation of these clusters. First, we show that a model in which cluster formation is driven exclusively by T-cell-extrinsic factors, such as variability in “attractiveness” of different liver stages, cannot explain distribution of cluster sizes in different experimental conditions. In contrast, the model in which cluster formation is driven by the positive feedback loop (i.e., larger clusters attract more CD8 T cells) can accurately explain the available data. Second, while both Py-specific CD8 T cells and T cells of irrelevant specificity (non-specific CD8 T cells) are attracted to the clusters, we found no evidence that non-specific CD8 T cells play a role in cluster formation. Third and finally, mathematical modeling suggested that formation of clusters occurs rapidly, within few hours after adoptive transfer of CD8 T cells, thus illustrating high efficiency of CD8 T cells in locating their targets in complex peripheral organs, such as the liver. Taken together, our analysis provides novel insights into and attempts to discriminate between alternative mechanisms driving the formation of clusters of antigen-specific CD8 T cells in the liver.}, author = {Kelemen, Réka K and Rajakaruna, H and Cockburn, IA and Ganusov, VV}, issn = {1664-3224}, journal = {Frontiers in Immunology}, publisher = {Frontiers}, title = {{Clustering of activated CD8 T cells around Malaria-infected hepatocytes is rapid and is driven by antigen-specific cells}}, doi = {10.3389/fimmu.2019.02153}, volume = {10}, year = {2019}, } @article{6972, abstract = {We give fault-tolerant algorithms for establishing synchrony in distributed systems in which each of thennodes has its own clock. Our algorithms operate in a very strong fault model: we require self-stabilisation, i.e.,the initial state of the system may be arbitrary, and there can be up to f