Neurons equipped with intrinsic plasticity learn stimulus intensity statistics - Monk, Travis; Savin, Cristina; Lücke, Jörg
Experience constantly shapes neural circuits through a variety of plasticity mechanisms. While the functional roles of some plasticity mechanisms are well-understood, it remains unclear how changes in neural excitability contribute to learning. Here, we develop a normative interpretation of intrinsic plasticity (IP) as a key component of unsupervised learning. We introduce a novel generative mixture model that accounts for the class-specific statistics of stimulus intensities, and we derive a neural circuit that learns the input classes and their intensities. We will analytically show that inference and learning for our generative model can be achieved by a neural circuit with intensity-sensitive neurons equipped with a specific form of IP. Numerical experiments verify our analytical derivations and show robust behavior for artificial and natural stimuli. Our results link IP to non-trivial input statistics, in particular the statistics of stimulus intensities for classes to which a neuron is sensitive. More generally, our work paves the way toward new classification algorithms that are robust to intensity variations.

Cycles and matchings in randomly perturbed digraphs and hypergraphs - Krivelevich, Michael; Kwan, Matthew Alan; Sudakov, Benny (Combinatorics, Probability and Computing)
We give several results showing that different discrete structures typically gain certain spanning substructures (in particular, Hamilton cycles) after a modest random perturbation. First, we prove that adding linearly many random edges to a dense k-uniform hypergraph ensures the (asymptotically almost sure) existence of a perfect matching or a loose Hamilton cycle. The proof involves an interesting application of Szemerédi's Regularity Lemma, which might be independently useful. We next prove that digraphs with certain strong expansion properties are pancyclic, and use this to show that adding a linear number of random edges typically makes a dense digraph pancyclic. Finally, we prove that perturbing a certain (minimum-degree-dependent) number of random edges in a tournament typically ensures the existence of multiple edge-disjoint Hamilton cycles. All our results are tight.

Structure of RNA polymerase I transcribing ribosomal DNA genes - Neyer, Simon; Kunz, Michael; Geiss, Christian; Hantsche, Merle; Hodirnau, Victor-Valentin; Seybert, Anja; Engel, Christoph; Scheffer, Margot P.; Cramer, Patrick; Frangakis, Achilleas S. (Nature)
RNA polymerase I (Pol I) is a highly processive enzyme that transcribes ribosomal DNA (rDNA) and regulates growth of eukaryotic cells. Crystal structures of free Pol I from the yeast Saccharomyces cerevisiae have revealed dimers of the enzyme stabilized by a 'connector' element and an expanded cleft containing the active centre in an inactive conformation. The central bridge helix was unfolded and a Pol-I-specific 'expander' element occupied the DNA-template-binding site. The structure of Pol I in its active transcribing conformation has yet to be determined, whereas structures of Pol II and Pol III have been solved with bound DNA template and RNA transcript. Here we report structures of active transcribing Pol I from yeast solved by two different cryo-electron microscopy approaches. A single-particle structure at 3.8 Å resolution reveals a contracted active centre cleft with bound DNA and RNA, and a narrowed pore beneath the active site that no longer holds the RNA-cleavage-stimulating domain of subunit A12.2. A structure at 29 Å resolution that was determined from cryo-electron tomograms of Pol I enzymes transcribing cellular rDNA confirms contraction of the cleft and reveals that incoming and exiting rDNA enclose an angle of around 150°. The structures suggest a model for the regulation of transcription elongation in which contracted and expanded polymerase conformations are associated with active and inactive states, respectively.

Nuclear quantum effects in water at the triple point: Using theory as a link between experiments - Cheng, Bingqing; Behler, Jörg; Ceriotti, Michele (The Journal of Physical Chemistry Letters)
One of the most prominent consequences of the quantum nature of light atomic nuclei is that their kinetic energy does not follow a Maxwell–Boltzmann distribution. Deep inelastic neutron scattering (DINS) experiments can measure this effect. Thus, the nuclear quantum kinetic energy can be probed directly in both ordered and disordered samples. However, the relation between the quantum kinetic energy and the atomic environment is a very indirect one, and cross-validation with theoretical modeling is therefore urgently needed. Here, we use state of the art path integral molecular dynamics techniques to compute the kinetic energy of hydrogen and oxygen nuclei in liquid, solid, and gas-phase water close to the triple point, comparing three different interatomic potentials and validating our results against equilibrium isotope fractionation measurements. We will then show how accurate simulations can draw a link between extremely precise fractionation experiments and DINS, therefore establishing a reliable benchmark for future measurements and providing key insights to increase further the accuracy of interatomic potentials for water.

Data from: Elevated virulence of an emerging viral genotype as a driver of honeybee loss - Mcmahon, Dino; Natsopoulou, Myrsini; Doublet, Vincent; Fürst, Matthias; Weging, Silvio; Brown, Mark; Gogol Döring, Andreas; Paxton, Robert
Emerging infectious diseases (EIDs) have contributed significantly to the current biodiversity crisis, leading to widespread epidemics and population loss. Owing to genetic variation in pathogen virulence, a complete understanding of species decline requires the accurate identification and characterization of EIDs. We explore this issue in the Western honeybee, where increasing mortality of populations in the Northern Hemisphere has caused major concern. Specifically, we investigate the importance of genetic identity of the main suspect in mortality, deformed wing virus (DWV), in driving honeybee loss. Using laboratory experiments and a systematic field survey, we demonstrate that an emerging DWV genotype (DWV-B) is more virulent than the established DWV genotype (DWV-A) and is widespread in the landscape. Furthermore, we show in a simple model that colonies infected with DWV-B collapse sooner than colonies infected with DWV-A. We also identify potential for rapid DWV evolution by revealing extensive genome-wide recombination in vivo. The emergence of DWV-B in naive honeybee populations, including via recombination with DWV-A, could be of significant ecological and economic importance. Our findings emphasize that knowledge of pathogen genetic identity and diversity is critical to understanding drivers of species decline.

Data from: How does epistasis influence the response to selection? - Barton, Nicholas H
Much of quantitative genetics is based on the ‘infinitesimal model’, under which selection has a negligible effect on the genetic variance. This is typically justified by assuming a very large number of loci with additive effects. However, it applies even when genes interact, provided that the number of loci is large enough that selection on each of them is weak relative to random drift. In the long term, directional selection will change allele frequencies, but even then, the effects of epistasis on the ultimate change in trait mean due to selection may be modest. Stabilising selection can maintain many traits close to their optima, even when the underlying alleles are weakly selected. However, the number of traits that can be optimised is apparently limited to ~4Ne by the ‘drift load’, and this is hard to reconcile with the apparent complexity of many organisms. Just as for the mutation load, this limit can be evaded by a particular form of negative epistasis. A more robust limit is set by the variance in reproductive success. This suggests that selection accumulates information most efficiently in the infinitesimal regime, when selection on individual alleles is weak, and comparable with random drift. A review of evidence on selection strength suggests that although most variance in fitness may be because of alleles with large Nes, substantial amounts of adaptation may be because of alleles in the infinitesimal regime, in which epistasis has modest effects.

Data from: A sting in the spit: widespread cross-infection of multiple RNA viruses across wild and managed bees - Mcmahon, Dino; Fürst, Matthias; Caspar, Jesicca; Theodorou, Panagiotis; Brown, Mark; Paxton, Robert
Summary: Declining populations of bee pollinators are a cause of concern, with major repercussions for biodiversity loss and food security. RNA viruses associated with honeybees represent a potential threat to other insect pollinators, but the extent of this threat is poorly understood. This study aims to attain a detailed understanding of the current and ongoing risk of emerging infectious disease (EID) transmission between managed and wild pollinator species across a wide range of RNA viruses. Within a structured large-scale national survey across 26 independent sites, we quantify the prevalence and pathogen loads of multiple RNA viruses in co-occurring managed honeybee (Apis mellifera) and wild bumblebee (Bombus spp.) populations. We then construct models that compare virus prevalence between wild and managed pollinators. Multiple RNA viruses associated with honeybees are widespread in sympatric wild bumblebee populations. Virus prevalence in honeybees is a significant predictor of virus prevalence in bumblebees, but we remain cautious in speculating over the principle direction of pathogen transmission. We demonstrate species-specific differences in prevalence, indicating significant variation in disease susceptibility or tolerance. Pathogen loads within individual bumblebees may be high and in the case of at least one RNA virus, prevalence is higher in wild bumblebees than in managed honeybee populations. Our findings indicate widespread transmission of RNA viruses between managed and wild bee pollinators, pointing to an interconnected network of potential disease pressures within and among pollinator species. In the context of the biodiversity crisis, our study emphasizes the importance of targeting a wide range of pathogens and defining host associations when considering potential drivers of population decline.

Expanding the interactome of the noncanonical NF-κB signaling pathway - Willmann, Katharina L; Roberto Sacco; Martins, Rui; Garncarz, Wojciech; Krolo, Ana; Knapp, Sylvia; Bennett, Keiryn L; Boztug, Kaan (Journal of Proteome Research)
NF-κB signaling is a central pathway of immunity and integrates signal transduction upon a wide array of inflammatory stimuli. Noncanonical NF-κB signaling is activated by a small subset of TNF family receptors and characterized by NF-κB2/p52 transcriptional activity. The medical relevance of this pathway has recently re-emerged from the discovery of primary immunodeficiency patients that have loss-of-function mutations in the MAP3K14 gene encoding NIK. Nevertheless, knowledge of protein interactions that regulate noncanonical NF-κB signaling is sparse. Here we report a detailed state-of-the-art mass spectrometry-based protein–protein interaction network including the noncanonical NF-κB signaling nodes TRAF2, TRAF3, IKKα, NIK, and NF-κB2/p100. The value of the data set was confirmed by the identification of interactions already known to regulate this pathway. In addition, a remarkable number of novel interactors were identified. We provide validation of the novel NIK and IKKα interactor FKBP8, which may regulate processes downstream of noncanonical NF-κB signaling. To understand perturbed noncanonical NF-κB signaling in the context of misregulated NIK in disease, we also provide a differential interactome of NIK mutants that cause immunodeficiency. Altogether, this data set not only provides critical insight into how protein–protein interactions can regulate immune signaling but also offers a novel resource on noncanonical NF-κB signaling.

The complexity of deciding legality of a single step of magic: The gathering - Chatterjee, Krishnendu; Ibsen-Jensen, Rasmus
Magic: the Gathering is a game about magical combat for any number of players. Formally it is a zero-sum, imperfect information stochastic game that consists of a potentially unbounded number of steps. We consider the problem of deciding if a move is legal in a given single step of Magic. We show that the problem is (a) coNP-complete in general; and (b) in P if either of two small sets of cards are not used. Our lower bound holds even for single-player Magic games. The significant aspects of our results are as follows: First, in most real-life game problems, the task of deciding whether a given move is legal in a single step is trivial, and the computationally hard task is to find the best sequence of legal moves in the presence of multiple players. In contrast, quite uniquely our hardness result holds for single step and with only one-player. Second, we establish efficient algorithms for important special cases of Magic.

Use runtime verification to improve the quality of medical care practice - Jiang, Yu; Liu, Han; Kong, Hui; Wang, Rui; Hosseini, Mohamad; Sun, Jiaguang; Sha, Lui (Proceedings of the 38th International Conference on Software Engineering Companion)
Clinical guidelines and decision support systems (DSS) play an important role in daily practices of medicine. Many text-based guidelines have been encoded for work-flow simulation of DSS to automate health care. During the collaboration with Carle hospital to develop a DSS, we identify that, for some complex and life-critical diseases, it is highly desirable to automatically rigorously verify some complex temporal properties in guidelines, which brings new challenges to current simulation based DSS with limited support of automatical formal verification and real-time data analysis. In this paper, we conduct the first study on applying runtime verification to cooperate with current DSS based on real-time data. Within the proposed technique, a user-friendly domain specific language, named DRTV, is designed to specify vital real-time data sampled by medical devices and temporal properties originated from clinical guidelines. Some interfaces are developed for data acquisition and communication. Then, for medical practice scenarios described in DRTV model, we will automatically generate event sequences and runtime property verifier automata. If a temporal property violates, real-time warnings will be produced by the formal verifier and passed to medical DSS. We have used DRTV to specify different kinds of medical care scenarios, and applied the proposed technique to assist existing DSS. As presented in experiment results, in terms of warning detection, it outperforms the only use of DSS or human inspection, and improves the quality of clinical health care of hospital

Perfect-information stochastic games with generalized mean-payoff objectives - Chatterjee, Krishnendu; Doyen, Laurent
Graph games provide the foundation for modeling and synthesizing reactive processes. In the synthesis of stochastic reactive processes, the traditional model is perfect-information stochastic games, where some transitions of the game graph are controlled by two adversarial players, and the other transitions are executed probabilistically. We consider such games where the objective is the conjunction of several quantitative objectives (specified as mean-payoff conditions), which we refer to as generalized mean-payoff objectives. The basic decision problem asks for the existence of a finite-memory strategy for a player that ensures the generalized mean-payoff objective be satisfied with a desired probability against all strategies of the opponent. A special case of the decision problem is the almost-sure problem where the desired probability is 1. Previous results presented a semi-decision procedure for -approximations of the almost-sure problem. In this work, we show that both the almost-sure problem as well as the general basic decision problem are coNP-complete, significantly improving the previous results. Moreover, we show that in the case of 1-player stochastic games, randomized memoryless strategies are sufficient and the problem can be solved in polynomial time. In contrast, in two-player stochastic games, we show that even with randomized strategies exponential memory is required in general, and present a matching exponential upper bound. We also study the basic decision problem with infinite-memory strategies and present computational complexity results for the problem. Our results are relevant in the synthesis of stochastic reactive systems with multiple quantitative requirements.

Nonlinear single sideband microwave to optical conversion using an electro-optic WGM-resonator - Rueda, Alfredo; Sedlmeir, Florian; Collodo, Michele; Vogl, Ulrich; Stiller, Birgit; Schunk, Gerhard; Strekalov, Dmitry; Marquardt, Christoph; Fink, Johannes M; Painter, Oskar; Leuchs, Gerd; Schwefel, Harald
Nonlinear electro-optical conversion of microwave radiation into the optical telecommunication band is achieved within a crystalline whispering gallery mode resonator, reaching 0.1% photon number conversion efficiency with MHz bandwidth.

The CLE gene family in Populus trichocarpa - Liu, Zhijun; Yang, Nan; Lv, Yanting; Pan, Lixia; Lv, Shuo; Han, Huibin; Wang, Guodong (Plant Signaling & Behavior)
The CLE (CLAVATA3/Embryo Surrounding Region-related) peptides are small secreted signaling peptides that are primarily involved in the regulation of stem cell homeostasis in different plant meristems. Particularly, the characterization of the CLE41-PXY/TDR signaling pathway has greatly advanced our understanding on the potential roles of CLE peptides in vascular development and wood formation. Nevertheless, our knowledge on this gene family in a tree species is limited. In a recent study, we reported on a systematically investigation of the CLE gene family in Populus trichocarpa . The potential roles of PtCLE genes were studied by comparative analysis and transcriptional pro fi ling. Among fi fty PtCLE members, many PtCLE proteins share identical CLE motifs or contain the same CLE motif as that of AtCLEs, while PtCLE genes exhibited either comparable or distinct expression patterns comparing to their Arabidopsis counterparts. These fi ndings indicate the existence of both functional conservation and functional divergence between PtCLEs and their AtCLE orthologues. Our results provide valuable resources for future functional investigations of these critical signaling molecules in woody plants.

Rules and self-organizing properties of post-embryonic plant organ cell division patterns - Daniel von Wangenheim; Fangerau, Jens; Schmitz, Alexander; Smith, Richard S; Leitte, Heike; Stelzer, Ernst H; Maizel, Alexis (Current Biology)
Plants form new organs with patterned tissue organization throughout their lifespan. It is unknown whether this robust post-embryonic organ formation results from stereotypic dynamic processes, in which the arrangement of cells follows rigid rules. Here, we combine modeling with empirical observations of whole-organ development to identify the principles governing lateral root formation in Arabidopsis. Lateral roots derive from a small pool of founder cells in which some take a dominant role as seen by lineage tracing. The first division of the founders is asymmetric, tightly regulated, and determines the formation of a layered structure. Whereas the pattern of subsequent cell divisions is not stereotypic between different samples, it is characterized by a regular switch in division plane orientation. This switch is also necessary for the appearance of patterned layers as a result of the apical growth of the primordium. Our data suggest that lateral root morphogenesis is based on a limited set of rules. They determine cell growth and division orientation. The organ-level coupling of the cell behavior ensures the emergence of the lateral root's characteristic features. We propose that self-organizing, non-deterministic modes of development account for the robustness of plant organ morphogenesis.

Quantitative interprocedural analysis - Chatterjee, Krishnendu; Pavlogiannis, Andreas; Velner, Yaron
We consider the quantitative analysis problem for interprocedural control-flow graphs (ICFGs). The input consists of an ICFG, a positive weight function that assigns every transition a positive integer-valued number, and a labelling of the transitions (events) as good, bad, and neutral events. The weight function assigns to each transition a numerical value that represents ameasure of how good or bad an event is. The quantitative analysis problem asks whether there is a run of the ICFG where the ratio of the sum of the numerical weights of good events versus the sum of weights of bad events in the long-run is at least a given threshold (or equivalently, to compute the maximal ratio among all valid paths in the ICFG). The quantitative analysis problem for ICFGs can be solved in polynomial time, and we present an efficient and practical algorithm for the problem. We show that several problems relevant for static program analysis, such as estimating the worst-case execution time of a program or the average energy consumption of a mobile application, can be modeled in our framework. We have implemented our algorithm as a tool in the Java Soot framework. We demonstrate the effectiveness of our approach with two case studies. First, we show that our framework provides a sound approach (no false positives) for the analysis of inefficiently-used containers. Second, we show that our approach can also be used for static profiling of programs which reasons about methods that are frequently invoked. Our experimental results show that our tool scales to relatively large benchmarks, and discovers relevant and useful information that can be used to optimize performance of the programs.

Termination and worst-case analysis of recursive programs - Anonymous, 1; Anonymous, 2; Anonymous, 3
We study the problem of developing efficient approaches for proving termination of recursive programs with one-dimensional arrays. Ranking functions serve as a sound and complete approach for proving termination of non-recursive programs without array operations. First, we generalize ranking functions to the notion of measure functions, and prove that measure functions (i) provide a sound method to prove termination of recursive programs (with one-dimensional arrays), and (ii) is both sound and complete over recursive programs without array operations. Our second contribution is the synthesis of measure functions of specific forms in polynomial time. More precisely, we prove that (i) polynomial measure functions over recursive programs can be synthesized in polynomial time through Farkas’ Lemma and Handelman’s Theorem, and (ii) measure functions involving logarithm and exponentiation can be synthesized in polynomial time through abstraction of logarithmic or exponential terms and Handelman’s Theorem. A key application of our method is the worst-case analysis of recursive programs. While previous methods obtain worst-case polynomial bounds of the form O(n^k), where k is an integer, our polynomial time methods can synthesize bounds of the form O(n log n), as well as O(n^x), where x is not an integer. We show the applicability of our automated technique to obtain worst-case complexity of classical recursive algorithms such as (i) Merge-Sort, the divideand- conquer algorithm for the Closest-Pair problem, where we obtain O(n log n) worst-case bound, and (ii) Karatsuba’s algorithm for polynomial multiplication and Strassen’s algorithm for matrix multiplication, where we obtain O(n^x) bound, where x is not an integer and close to the best-known bounds for the respective algorithms. Finally, we present experimental results to demonstrate the effectiveness of our approach.

Average-case analysis of programs: Automated recurrence analysis for almost-linear bounds - Anonymous, 1; Anonymous, 2; Anonymous, 3
We consider the problem of developing automated techniques to aid the average-case complexity analysis of programs. Several classical textbook algorithms have quite efficient average-case complexity, whereas the corresponding worst-case bounds are either inefficient (e.g., QUICK-SORT), or completely ineffective (e.g., COUPONCOLLECTOR). Since the main focus of average-case analysis is to obtain efficient bounds, we consider bounds that are either logarithmic, linear, or almost-linear (O(log n), O(n), O(n · log n), respectively, where n represents the size of the input). Our main contribution is a sound approach for deriving such average-case bounds for randomized recursive programs. Our approach is efficient (a simple linear-time algorithm), and it is based on (a) the analysis of recurrence relations induced by randomized algorithms, and (b) a guess-and-check technique. Our approach can infer the asymptotically optimal average-case bounds for classical randomized algorithms, including RANDOMIZED-SEARCH, QUICKSORT, QUICK-SELECT, COUPON-COLLECTOR, where the worstcase bounds are either inefficient (such as linear as compared to logarithmic of average-case, or quadratic as compared to linear or almost-linear of average-case), or ineffective. We have implemented our approach, and the experimental results show that we obtain the bounds efficiently for various classical algorithms.

Data-centric dynamic partial order reduction - Anonymous, 1; Anonymous, 2; Anonymous, 3; Anonymous, 4
We present a new dynamic partial-order reduction method for stateless model checking of concurrent programs. A common approach for exploring program behaviors relies on enumerating the traces of the program, without storing the visited states (aka stateless exploration). As the number of distinct traces grows exponentially, dynamic partial-order reduction (DPOR) techniques have been successfully used to partition the space of traces into equivalence classes (Mazurkiewicz partitioning), with the goal of exploring only few representative traces from each class. We introduce a new equivalence on traces under sequential consistency semantics, which we call the observation equivalence. Two traces are observationally equivalent if every read event observes the same write event in both traces. While the traditional Mazurkiewicz equivalence is control-centric, our new definition is data-centric. We show that our observation equivalence is coarser than the Mazurkiewicz equivalence, and in many cases even exponentially coarser. We devise a DPOR exploration of the trace space, called data-centric DPOR, based on the observation equivalence. 1. For acyclic architectures, our algorithm is guaranteed to explore exactly one representative trace from each observation class, while spending polynomial time per class. Hence, our algorithm is optimal wrt the observation equivalence, and in several cases explores exponentially fewer traces than any enumerative method based on the Mazurkiewicz equivalence. 2. For cyclic architectures, we consider an equivalence between traces which is finer than the observation equivalence; but coarser than the Mazurkiewicz equivalence, and in some cases is exponentially coarser. Our data-centric DPOR algorithm remains optimal under this trace equivalence. Finally, we perform a basic experimental comparison between the existing Mazurkiewicz-based DPOR and our data-centric DPOR on a set of academic benchmarks. Our results show a significant reduction in both running time and the number of explored equivalence classes.

Amplification on undirected population structures: Comets beat stars - Pavlogiannis, Andreas; Tkadlec, Josef; Chatterjee, Krishnendu; Nowak, Martin
The fixation probability is the probability that a new mutant introduced in a homogeneous population eventually takes over the entire population. The fixation probability is a fundamental quantity of natural selection, and known to depend on the population structure. Amplifiers of natural selection are population structures which increase the fixation probability of advantageous mutants, as compared to the baseline case of well-mixed populations. In this work we focus on symmetric population structures represented as undirected graphs. In the regime of undirected graphs, the strongest amplifier known has been the Star graph, and the existence of undirected graphs with stronger amplification properties has remained open for over a decade. In this work we present the Comet and Comet-swarm families of undirected graphs. We show that for a range of fitness values of the mutants, the Comet and Comet-swarm graphs have fixation probability strictly larger than the fixation probability of the Star graph, for fixed population size and at the limit of large populations, respectively.

Strong amplifiers of natural selection - Pavlogiannis, Andreas; Tkadlec, Josef; Chatterjee, Krishnendu; Nowak, Martin