TY - GEN AB - The infiltration of immune cells into tissues underlies the establishment of tissue resident macrophages, and responses to infections and tumors. Yet the mechanisms immune cells utilize to negotiate tissue barriers in living organisms are not well understood, and a role for cortical actin has not been examined. Here we find that the tissue invasion of Drosophila macrophages, also known as plasmatocytes or hemocytes, utilizes enhanced cortical F-actin levels stimulated by the Drosophila member of the fos proto oncogene transcription factor family (Dfos, Kayak). RNA sequencing analysis and live imaging show that Dfos enhances F-actin levels around the entire macrophage surface by increasing mRNA levels of the membrane spanning molecular scaffold tetraspanin TM4SF, and the actin cross-linking filamin Cheerio which are themselves required for invasion. Cortical F-actin levels are critical as expressing a dominant active form of Diaphanous, a actin polymerizing Formin, can rescue the Dfos Dominant Negative macrophage invasion defect. In vivo imaging shows that Dfos is required to enhance the efficiency of the initial phases of macrophage tissue entry. Genetic evidence argues that this Dfos-induced program in macrophages counteracts the constraint produced by the tension of surrounding tissues and buffers the mechanical properties of the macrophage nucleus from affecting tissue entry. We thus identify tuning the cortical actin cytoskeleton through Dfos as a key process allowing efficient forward movement of an immune cell into surrounding tissues. AU - Belyaeva, Vera AU - Wachner, Stephanie AU - Gridchyn, Igor AU - Linder, Markus AU - Emtenani, Shamsi AU - György, Attila AU - Sibilia, Maria AU - Siekhaus, Daria E ID - 8557 T2 - bioRxiv TI - Cortical actin properties controlled by Drosophila Fos aid macrophage infiltration against surrounding tissue resistance ER - TY - GEN AB - Holes in planar Ge have high mobilities, strong spin-orbit interaction and electrically tunable g-factors, and are therefore emerging as a promising candidate for hybrid superconductorsemiconductor devices. This is further motivated by the observation of supercurrent transport in planar Ge Josephson Field effect transistors (JoFETs). A key challenge towards hybrid germanium quantum technology is the design of high quality interfaces and superconducting contacts that are robust against magnetic fields. By combining the assets of Al, which has a long superconducting coherence, and Nb, which has a significant superconducting gap, we form low-disordered JoFETs with large ICRN products that are capable of withstanding high magnetic fields. We furthermore demonstrate the ability of phase-biasing individual JoFETs opening up an avenue to explore topological superconductivity in planar Ge. The persistence of superconductivity in the reported hybrid devices beyond 1.8 T paves the way towards integrating spin qubits and proximity-induced superconductivity on the same chip. AU - Aggarwal, Kushagra AU - Hofmann, Andrea C AU - Jirovec, Daniel AU - Prieto Gonzalez, Ivan AU - Sammak, Amir AU - Botifoll, Marc AU - Marti-Sanchez, Sara AU - Veldhorst, Menno AU - Arbiol, Jordi AU - Scappucci, Giordano AU - Katsaros, Georgios ID - 8831 T2 - arXiv TI - Enhancement of proximity induced superconductivity in planar Germanium ER - TY - JOUR AB - The molecular anatomy of synapses defines their characteristics in transmission and plasticity. Precise measurements of the number and distribution of synaptic proteins are important for our understanding of synapse heterogeneity within and between brain regions. Freeze–fracture replica immunogold electron microscopy enables us to analyze them quantitatively on a two-dimensional membrane surface. Here, we introduce Darea software, which utilizes deep learning for analysis of replica images and demonstrate its usefulness for quick measurements of the pre- and postsynaptic areas, density and distribution of gold particles at synapses in a reproducible manner. We used Darea for comparing glutamate receptor and calcium channel distributions between hippocampal CA3-CA1 spine synapses on apical and basal dendrites, which differ in signaling pathways involved in synaptic plasticity. We found that apical synapses express a higher density of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors and a stronger increase of AMPA receptors with synaptic size, while basal synapses show a larger increase in N-methyl-D-aspartate (NMDA) receptors with size. Interestingly, AMPA and NMDA receptors are segregated within postsynaptic sites and negatively correlated in density among both apical and basal synapses. In the presynaptic sites, Cav2.1 voltage-gated calcium channels show similar densities in apical and basal synapses with distributions consistent with an exclusion zone model of calcium channel-release site topography. AU - Kleindienst, David AU - Montanaro-Punzengruber, Jacqueline-Claire AU - Bhandari, Pradeep AU - Case, Matthew J AU - Fukazawa, Yugo AU - Shigemoto, Ryuichi ID - 8532 IS - 18 JF - International Journal of Molecular Sciences SN - 16616596 TI - Deep learning-assisted high-throughput analysis of freeze-fracture replica images applied to glutamate receptors and calcium channels at hippocampal synapses VL - 21 ER - TY - CONF AB - Interprocedural data-flow analyses form an expressive and useful paradigm of numerous static analysis applications, such as live variables analysis, alias analysis and null pointers analysis. The most widely-used framework for interprocedural data-flow analysis is IFDS, which encompasses distributive data-flow functions over a finite domain. On-demand data-flow analyses restrict the focus of the analysis on specific program locations and data facts. This setting provides a natural split between (i) an offline (or preprocessing) phase, where the program is partially analyzed and analysis summaries are created, and (ii) an online (or query) phase, where analysis queries arrive on demand and the summaries are used to speed up answering queries. In this work, we consider on-demand IFDS analyses where the queries concern program locations of the same procedure (aka same-context queries). We exploit the fact that flow graphs of programs have low treewidth to develop faster algorithms that are space and time optimal for many common data-flow analyses, in both the preprocessing and the query phase. We also use treewidth to develop query solutions that are embarrassingly parallelizable, i.e. the total work for answering each query is split to a number of threads such that each thread performs only a constant amount of work. Finally, we implement a static analyzer based on our algorithms, and perform a series of on-demand analysis experiments on standard benchmarks. Our experimental results show a drastic speed-up of the queries after only a lightweight preprocessing phase, which significantly outperforms existing techniques. AU - Chatterjee, Krishnendu AU - Goharshady, Amir Kafshdar AU - Ibsen-Jensen, Rasmus AU - Pavlogiannis, Andreas ID - 7810 SN - 03029743 T2 - European Symposium on Programming TI - Optimal and perfectly parallel algorithms for on-demand data-flow analysis VL - 12075 ER - TY - CONF AB - Discrete-time Markov Chains (MCs) and Markov Decision Processes (MDPs) are two standard formalisms in system analysis. Their main associated quantitative objectives are hitting probabilities, discounted sum, and mean payoff. Although there are many techniques for computing these objectives in general MCs/MDPs, they have not been thoroughly studied in terms of parameterized algorithms, particularly when treewidth is used as the parameter. This is in sharp contrast to qualitative objectives for MCs, MDPs and graph games, for which treewidth-based algorithms yield significant complexity improvements. In this work, we show that treewidth can also be used to obtain faster algorithms for the quantitative problems. For an MC with n states and m transitions, we show that each of the classical quantitative objectives can be computed in O((n+m)⋅t2) time, given a tree decomposition of the MC with width t. Our results also imply a bound of O(κ⋅(n+m)⋅t2) for each objective on MDPs, where κ is the number of strategy-iteration refinements required for the given input and objective. Finally, we make an experimental evaluation of our new algorithms on low-treewidth MCs and MDPs obtained from the DaCapo benchmark suite. Our experiments show that on low-treewidth MCs and MDPs, our algorithms outperform existing well-established methods by one or more orders of magnitude. AU - Asadi, Ali AU - Chatterjee, Krishnendu AU - Goharshady, Amir Kafshdar AU - Mohammadi, Kiarash AU - Pavlogiannis, Andreas ID - 8728 SN - 0302-9743 T2 - Automated Technology for Verification and Analysis TI - Faster algorithms for quantitative analysis of MCs and MDPs with small treewidth VL - 12302 ER - TY - CONF AB - We consider the classical problem of invariant generation for programs with polynomial assignments and focus on synthesizing invariants that are a conjunction of strict polynomial inequalities. We present a sound and semi-complete method based on positivstellensaetze, i.e. theorems in semi-algebraic geometry that characterize positive polynomials over a semi-algebraic set. On the theoretical side, the worst-case complexity of our approach is subexponential, whereas the worst-case complexity of the previous complete method (Kapur, ACA 2004) is doubly-exponential. Even when restricted to linear invariants, the best previous complexity for complete invariant generation is exponential (Colon et al, CAV 2003). On the practical side, we reduce the invariant generation problem to quadratic programming (QCLP), which is a classical optimization problem with many industrial solvers. We demonstrate the applicability of our approach by providing experimental results on several academic benchmarks. To the best of our knowledge, the only previous invariant generation method that provides completeness guarantees for invariants consisting of polynomial inequalities is (Kapur, ACA 2004), which relies on quantifier elimination and cannot even handle toy programs such as our running example. AU - Chatterjee, Krishnendu AU - Fu, Hongfei AU - Goharshady, Amir Kafshdar AU - Goharshady, Ehsan Kafshdar ID - 8089 SN - 9781450376136 T2 - Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation TI - Polynomial invariant generation for non-deterministic recursive programs ER - TY - JOUR AB - We consider the classic problem of Network Reliability. A network is given together with a source vertex, one or more target vertices, and probabilities assigned to each of the edges. Each edge of the network is operable with its associated probability and the problem is to determine the probability of having at least one source-to-target path that is entirely composed of operable edges. This problem is known to be NP-hard. We provide a novel scalable algorithm to solve the Network Reliability problem when the treewidth of the underlying network is small. We also show our algorithm’s applicability for real-world transit networks that have small treewidth, including the metro networks of major cities, such as London and Tokyo. Our algorithm leverages tree decompositions to shrink the original graph into much smaller graphs, for which reliability can be efficiently and exactly computed using a brute force method. To the best of our knowledge, this is the first exact algorithm for Network Reliability that can scale to handle real-world instances of the problem. AU - Goharshady, Amir Kafshdar AU - Mohammadi, Fatemeh ID - 6918 JF - Reliability Engineering and System Safety SN - 09518320 TI - An efficient algorithm for computing network reliability in small treewidth VL - 193 ER - TY - JOUR AB - In this paper, we introduce an inertial projection-type method with different updating strategies for solving quasi-variational inequalities with strongly monotone and Lipschitz continuous operators in real Hilbert spaces. Under standard assumptions, we establish different strong convergence results for the proposed algorithm. Primary numerical experiments demonstrate the potential applicability of our scheme compared with some related methods in the literature. AU - Shehu, Yekini AU - Gibali, Aviv AU - Sagratella, Simone ID - 7161 JF - Journal of Optimization Theory and Applications SN - 0022-3239 TI - Inertial projection-type methods for solving quasi-variational inequalities in real Hilbert spaces VL - 184 ER - TY - JOUR AB - Organisms cope with change by taking advantage of transcriptional regulators. However, when faced with rare environments, the evolution of transcriptional regulators and their promoters may be too slow. Here, we investigate whether the intrinsic instability of gene duplication and amplification provides a generic alternative to canonical gene regulation. Using real-time monitoring of gene-copy-number mutations in Escherichia coli, we show that gene duplications and amplifications enable adaptation to fluctuating environments by rapidly generating copy-number and, therefore, expression-level polymorphisms. This amplification-mediated gene expression tuning (AMGET) occurs on timescales that are similar to canonical gene regulation and can respond to rapid environmental changes. Mathematical modelling shows that amplifications also tune gene expression in stochastic environments in which transcription-factor-based schemes are hard to evolve or maintain. The fleeting nature of gene amplifications gives rise to a generic population-level mechanism that relies on genetic heterogeneity to rapidly tune the expression of any gene, without leaving any genomic signature. AU - Tomanek, Isabella AU - Grah, Rok AU - Lagator, M. AU - Andersson, A. M. C. AU - Bollback, Jonathan P AU - Tkačik, Gašper AU - Guet, Calin C ID - 7652 IS - 4 JF - Nature Ecology & Evolution SN - 2397-334X TI - Gene amplification as a form of population-level gene expression regulation VL - 4 ER - TY - THES AB - Many flows encountered in nature and applications are characterized by a chaotic motion known as turbulence. Turbulent flows generate intense friction with pipe walls and are responsible for considerable amounts of energy losses at world scale. The nature of turbulent friction and techniques aimed at reducing it have been subject of extensive research over the last century, but no definite answer has been found yet. In this thesis we show that in pipes at moderate turbulent Reynolds numbers friction is better described by the power law first introduced by Blasius and not by the Prandtl–von Kármán formula. At higher Reynolds numbers, large scale motions gradually become more important in the flow and can be related to the change in scaling of friction. Next, we present a series of new techniques that can relaminarize turbulence by suppressing a key mechanism that regenerates it at walls, the lift–up effect. In addition, we investigate the process of turbulence decay in several experiments and discuss the drag reduction potential. Finally, we examine the behavior of friction under pulsating conditions inspired by the human heart cycle and we show that under such circumstances turbulent friction can be reduced to produce energy savings. AU - Scarselli, Davide ID - 7258 SN - 2663-337X TI - New approaches to reduce friction in turbulent pipe flow ER -