9,705 research outputs found

    Plant–soil feedback under drought:does history shape the future?

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    Plant–soil feedback (PSF) is widely recognised as a driver of plant community composition, but understanding of its response to drought remains in its infancy. Here, we provide a conceptual framework for the role of drought in PSF, considering plant traits, drought severity, and historical precipitation over ecological and evolutionary timescales. Comparing experimental studies where plants and microbes do or do not share a drought history (through co-sourcing or conditioning), we hypothesise that plants and microbes with a shared drought history experience more positive PSF under subsequent drought. To reflect real-world responses to drought, future studies need to explicitly include plant–microbial co-occurrence and potential co-adaptation and consider the precipitation history experienced by both plants and microbes.</p

    Gonorrhoea

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    The bacterium Neisseria gonorrhoeae causes the sexually transmitted infection (STI) gonorrhoea, which has an estimated global annual incidence of 86.9 million adults. Gonorrhoea can present as urethritis in men, cervicitis or urethritis in women, and in extragenital sites (pharynx, rectum, conjunctiva and, rarely, systemically) in both sexes. Confirmation of diagnosis requires microscopy of Gram-stained samples, bacterial culture or nucleic acid amplification tests. As no gonococcal vaccine is available, prevention relies on promoting safe sexual behaviours and reducing STI-associated stigma, which hinders timely diagnosis and treatment thereby increasing transmission. Single-dose systemic therapy (usually injectable ceftriaxone plus oral azithromycin) is the recommended first-line treatment. However, a major public health concern globally is that N. gonorrhoeae is evolving high levels of antimicrobial resistance (AMR), which threatens the effectiveness of the available gonorrhoea treatments. Improved global surveillance of the emergence, evolution, fitness, and geographical and temporal spread of AMR in N. gonorrhoeae, and improved understanding of the pharmacokinetics and pharmacodynamics for current and future antimicrobials in the treatment of urogenital and extragenital gonorrhoea, are essential to inform treatment guidelines. Key priorities for gonorrhoea control include strengthening prevention, early diagnosis, and treatment of patients and their partners; decreasing stigma; expanding surveillance of AMR and treatment failures; and promoting responsible antimicrobial use and stewardship. To achieve these goals, the development of rapid and affordable point-of-care diagnostic tests that can simultaneously detect AMR, novel therapeutic antimicrobials and gonococcal vaccine(s) in particular is crucial

    Measurement of Liver Blood Flow: A Review

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    The study of hepatic haemodynamics is of importance in understanding both hepatic physiology and disease processes as well as assessing the effects of portosystemic shunting and liver transplantation. The liver has the most complicated circulation of any organ and many physiological and pathological processes can affect it1,2. This review surveys the methods available for assessing liver blood flow, examines the different parameters being measured and outlines problems of applicability and interpretation for each technique

    Searches for New Quarks and Leptons Produced in Z-Boson Decay

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    We have searched for events with new-particle topologies in 390 hadronic Z decays with the Mark II detector at the SLAC Linear Collider. We place 95%-confidence-level lower limits of 40.7 GeV/c^2 for the top-quark mass, 42.0 GeV/c^2 for the mass of a fourth-generation charge - 1/3 quark, and 41.3 GeV/c^2 for the mass of an unstable Dirac neutral lepton

    Measurement of Z Decays into Lepton Pairs

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    We present measurements by the Mark II experiment of the ratios of the leptonic partial widths of the Z boson to the hadronic partial width. The results are Γ_(ee)/Γ_(had)=0.037_(-0.012^()+0.016),Γ_(µµ)/Γ_(had)=0.053-_(0.015)^(+0.020), and Γ_(ττ)/Γ_(had)=0.066_(-0.017)^(+0.021), in good agreement with the standard-model prediction of 0.048. From the average leptonic width result, Γ_(ll)/Γ_(had)=0.053_(-0.009)^(+0.010), we derive Γ_(had)=1.56_(-0.24)^(+0.28) GeV. We find for the vector coupling constants of the tau and muon v_τ^2=0.31±0.31_(-0.30)^(+0.43) and v_μ^2=0.05±0.30_(-0.23)^(+0.34)

    On the criticality of inferred models

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    Advanced inference techniques allow one to reconstruct the pattern of interaction from high dimensional data sets. We focus here on the statistical properties of inferred models and argue that inference procedures are likely to yield models which are close to a phase transition. On one side, we show that the reparameterization invariant metrics in the space of probability distributions of these models (the Fisher Information) is directly related to the model's susceptibility. As a result, distinguishable models tend to accumulate close to critical points, where the susceptibility diverges in infinite systems. On the other, this region is the one where the estimate of inferred parameters is most stable. In order to illustrate these points, we discuss inference of interacting point processes with application to financial data and show that sensible choices of observation time-scales naturally yield models which are close to criticality.Comment: 6 pages, 2 figures, version to appear in JSTA

    Motif Statistics and Spike Correlations in Neuronal Networks

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    Motifs are patterns of subgraphs of complex networks. We studied the impact of such patterns of connectivity on the level of correlated, or synchronized, spiking activity among pairs of cells in a recurrent network model of integrate and fire neurons. For a range of network architectures, we find that the pairwise correlation coefficients, averaged across the network, can be closely approximated using only three statistics of network connectivity. These are the overall network connection probability and the frequencies of two second-order motifs: diverging motifs, in which one cell provides input to two others, and chain motifs, in which two cells are connected via a third intermediary cell. Specifically, the prevalence of diverging and chain motifs tends to increase correlation. Our method is based on linear response theory, which enables us to express spiking statistics using linear algebra, and a resumming technique, which extrapolates from second order motifs to predict the overall effect of coupling on network correlation. Our motif-based results seek to isolate the effect of network architecture perturbatively from a known network state
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