Resource-oriented therapeutic models in psychiatry:conceptual review

International audienc

Early stages of ramified growth in quasi-two-dimensional electrochemical deposition

I have measured the early stages of the growth of branched metal aggregates formed by electrochemical deposition in very thin layers. The growth rate of spatial Fourier modes is described qualitatively by the results of a linear stability analysis [D.P. Barkey, R.H. Muller, and C.W. Tobias, J. Electrochem. Soc. {\bf 136}, 2207 (1989)]. The maximum growth rate is proportional to $(I/c)^\delta$ where $I$ is the current through the electrochemical cell, $c$ the electrolyte concentration, and $\delta = 1.37 \pm 0.08$. Differences between my results and the theoretical predictions suggest that electroconvection in the electrolyte has a large influence on the instability leading to ramified growth.Comment: REVTeX, four ps figure

Species-specific activity of antibacterial drug combinations

International audienceThe spread of antimicrobial resistance has become a serious public health concern, making once treatable diseases deadly again and undermining breakthrough achievements of modern medicine 1,2. Drug combinations can aid in fighting multi-drug resistant (MDR) bacterial infections, yet, are largely unexplored and rarely used in clinics. To identify general principles for antibacterial drug combinations and understand their potential, we profiled ~3,000 dose-resolved combinations of antibiotics, human-targeted drugs and food additives in 6 strains from three Gram-negative pathogens, Escherichia coli, Salmonella Typhimurium and Pseudomonas aeruginosa. Despite their phylogenetic relatedness, more than 70% of the detected drug-drug interactions are species-specific and 20% display strain specificity, revealing a large potential for narrow-spectrum therapies. Overall, antagonisms are more common than synergies and occur almost exclusively between drugs targeting different cellular processes, whereas synergies are more conserved and enriched in drugs targeting the same process. We elucidate mechanisms underlying this dichotomy and further use our resource to dissect the interactions of the food additive, vanillin. Finally, we demonstrate that several synergies are effective against MDR clinical isolates in vitro and during Galleria mellonella infections with one reverting resistance to the last-resort antibiotic, colistin

The VALUE perfect predictor experiment: evaluation of temporal variability

Temporal variability is an important feature of climate, comprising systematic vari-ations such as the annual cycle, as well as residual temporal variations such asshort-term variations, spells and variability from interannual to long-term trends.The EU-COST Action VALUE developed a comprehensive framework to evaluatedownscaling methods. Here we present the evaluation of the perfect predictorexperiment for temporal variability. Overall, the behaviour of the differentapproaches turned out to be as expected from their structure and implementation.The chosen regional climate model adds value to reanalysis data for most consid-ered aspects, for all seasons and for both temperature and precipitation. Bias cor-rection methods do not directly modify temporal variability apart from the annualcycle. However, wet day corrections substantially improve transition probabilitiesand spell length distributions, whereas interannual variability is in some cases dete-riorated by quantile mapping. The performance of perfect prognosis (PP) statisticaldownscaling methods varies strongly from aspect to aspect and method to method,and depends strongly on the predictor choice. Unconditional weather generatorstend to perform well for the aspects they have been calibrated for, but underrepre-sent long spells and interannual variability. Long-term temperature trends of thedriving model are essentially unchanged by bias correction methods. If precipita-tion trends are not well simulated by the driving model, bias correction furtherdeteriorates these trends. The performance of PP methods to simulate trendsdepends strongly on the chosen predictors.VALUE has been funded as EU COST Action ES1102

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte

Modeling Vortex Swarming In Daphnia

Based on experimental observations in \textit{Daphnia}, we introduce an agent-based model for the motion of single and swarms of animals. Each agent is described by a stochastic equation that also considers the conditions for active biological motion. An environmental potential further reflects local conditions for \textit{Daphnia}, such as attraction to light sources. This model is sufficient to describe the observed cycling behavior of single \textit{Daphnia}. To simulate vortex swarming of many \textit{Daphnia}, i.e. the collective rotation of the swarm in one direction, we extend the model by considering avoidance of collisions. Two different ansatzes to model such a behavior are developed and compared. By means of computer simulations of a multi-agent system we show that local avoidance - as a special form of asymmetric repulsion between animals - leads to the emergence of a vortex swarm. The transition from uncorrelated rotation of single agents to the vortex swarming as a function of the swarm size is investigated. Eventually, some evidence of avoidance behavior in \textit{Daphnia} is provided by comparing experimental and simulation results for two animals.Comment: 24 pages including 11 multi-part figs. Major revisions compared to version 1, new results on transition from uncorrelated rotation to vortex swarming. Extended discussion. For related publications see http://www.sg.ethz.ch/people/scfrank/Publication

Swarming Behavior in Plant Roots

Interactions between individuals that are guided by simple rules can generate swarming behavior. Swarming behavior has been observed in many groups of organisms, including humans, and recent research has revealed that plants also demonstrate social behavior based on mutual interaction with other individuals. However, this behavior has not previously been analyzed in the context of swarming. Here, we show that roots can be influenced by their neighbors to induce a tendency to align the directions of their growth. In the apparently noisy patterns formed by growing roots, episodic alignments are observed as the roots grow close to each other. These events are incompatible with the statistics of purely random growth. We present experimental results and a theoretical model that describes the growth of maize roots in terms of swarming

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Measurements of ψ(2S) and X(3872) → J/ψπ+π− production in pp collisions at √s=8 TeV with the ATLAS detector

Differential cross sections are presented for the prompt and non-prompt production of the hidden-charm states X(3872) and ψ(2S), in the decay mode J/ψπ+π−, measured using 11.4 fb−1 of pp collisions at √s=8 TeV by the ATLAS detector at the LHC. The ratio of cross-sections X(3872)/ψ(2S) is also given, separately for prompt and non-prompt components, as well as the non-prompt fractions of X(3872) and ψ(2S). Assuming independent single effective lifetimes for non-prompt X(3872) and ψ(2S) production gives RB=B(B→X(3872)+any)B(X(3872)→J/ψπ+π−)B(B→ψ(2S)+any)B(ψ(2S)→J/ψπ+π−)=(3.95±0.32(stat)±0.08(sys))×10−2RB=B(B→X(3872)+any)B(X(3872)→J/ψπ+π−)B(B→ψ(2S)+any)B(ψ(2S)→J/ψπ+π−)=(3.95±0.32(stat)±0.08(sys))×10−2 separating short- and long-lived contributions, assuming that the short-lived component is due to Bc decays, gives RB = (3.57 ± 0.33(stat) ± 0.11(sys)) × 10−2, with the fraction of non-prompt X(3872) produced via Bc decays for pT(X(3872)) > 10 GeV being (25 ± 13(stat) ± 2(sys) ± 5(spin))%. The distributions of the dipion invariant mass in the X(3872) and ψ(2S) decays are also measured and compared to theoretical predictions

Heat stress increase under climate change twice as large in cities as in rural areas : a study for a densely populated midlatitude maritime region

Urban areas are usually warmer than their surrounding natural areas, an effect known as the urban heat island effect. As such, they are particularly vulnerable to global warming and associated increases in extreme temperatures. Yet ensemble climate-model projections are generally performed on a scale that is too coarse to represent the evolution of temperatures in cities. Here, for the first time, we combine unprecedented long-term (35years) urban climate model integrations at the convection-permitting scale (2.8km resolution) with information from an ensemble of general circulation models to assess temperature-based heat stress for Belgium, a densely populated midlatitude maritime region. We discover that the heat stress increase toward the mid-21st century is twice as large in cities compared to their surrounding rural areas. The exacerbation is driven by the urban heat island itself, its concurrence with heat waves, and urban expansion. Cities experience a heat stress multiplication by a factor 1.4 and 15 depending on the scenario. Remarkably, the future heat stress surpasses everywhere the urban hot spots of today. Our results demonstrate the need to combine information from climate models, acting on different scales, for climate change risk assessment in heterogeneous regions. Moreover, these results highlight the necessity for adaptation to increasing heat stress, especially in urban areas