Langevin Equation for the Rayleigh model with finite-ranged interactions

Both linear and nonlinear Langevin equations are derived directly from the Liouville equation for an exactly solvable model consisting of a Brownian particle of mass $M$ interacting with ideal gas molecules of mass $m$ via a quadratic repulsive potential. Explicit microscopic expressions for all kinetic coefficients appearing in these equations are presented. It is shown that the range of applicability of the Langevin equation, as well as statistical properties of random force, may depend not only on the mass ratio $m/M$ but also by the parameter $Nm/M$, involving the average number $N$ of molecules in the interaction zone around the particle. For the case of a short-ranged potential, when $N\ll 1$, analysis of the Langevin equations yields previously obtained results for a hard-wall potential in which only binary collisions are considered. For the finite-ranged potential, when multiple collisions are important ($N\gg 1$), the model describes nontrivial dynamics on time scales that are on the order of the collision time, a regime that is usually beyond the scope of more phenomenological models.Comment: 21 pages, 1 figure. To appear in Phys. Rev.

The prevalence of axial spondyloarthritis in the UK: a cross-sectional cohort study

Background: Accurate prevalence data are important when interpreting diagnostic tests and planning for the health needs of a population, yet no such data exist for axial spondyloarthritis (axSpA) in the UK. In this cross-sectional cohort study we aimed to estimate the prevalence of axSpA in a UK primary care population. Methods: A validated self-completed questionnaire was used to screen primary care patients with low back pain for inflammatory back pain (IBP). Patients with a verifiable pre-existing diagnosis of axSpA were included as positive cases. All other patients meeting the Assessment of SpondyloArthritis international Society (ASAS) IBP criteria were invited to undergo further assessment including MRI scanning, allowing classification according to the European Spondyloarthropathy Study Group (ESSG) and ASAS axSpA criteria, and the modified New York (mNY) criteria for ankylosing spondylitis (AS). Results: Of 978 questionnaires sent to potential participants 505 were returned (response rate 51.6 %). Six subjects had a prior diagnosis of axSpA, 4 of whom met mNY criteria. Thirty eight of 75 subjects meeting ASAS IBP criteria attended review (mean age 53.5 years, 37 % male). The number of subjects satisfying classification criteria was 23 for ESSG, 3 for ASAS (2 clinical, 1 radiological) and 1 for mNY criteria. This equates to a prevalence of 5.3 % (95 % CI 4.0, 6.8) using ESSG, 1.3 % (95 % CI 0.8, 2.3) using ASAS, 0.66 % (95 % CI 0.28, 1.3) using mNY criteria in chronic back pain patients, and 1.2 % (95 % CI 0.9, 1.4) using ESSG, 0.3 % (95 % CI 0.13, 0.48) using ASAS, 0.15 % (95 % CI 0.02, 0.27) using mNY criteria in the general adult primary care population. Conclusions: These are the first prevalence estimates for axSpA in the UK, and will be of importance in planning for the future healthcare needs of this population. Trial registration: Current Controlled Trials ISRCTN7687321

Heterologous expression screens in Nicotiana benthamiana identify a candidate effector of the wheat Yellow Rust Pathogen that associates with processing bodies

Rust fungal pathogens of wheat (Triticum spp.) affect crop yields worldwide. The molecular mechanisms underlying the virulence of these pathogens remain elusive, due to the limited availability of suitable molecular genetic research tools. Notably, the inability to perform high-throughput analyses of candidate virulence proteins (also known as effectors) impairs progress. We previously established a pipeline for the fast-forward screens of rust fungal candidate effectors in the model plant Nicotiana benthamiana. This pipeline involves selecting candidate effectors in silico and performing cell biology and protein-protein interaction assays in planta to gain insight into the putative functions of candidate effectors. In this study, we used this pipeline to identify and characterize sixteen candidate effectors from the wheat yellow rust fungal pathogen Puccinia striiformis f sp tritici. Nine candidate effectors targeted a specific plant subcellular compartment or protein complex, providing valuable information on their putative functions in plant cells. One candidate effector, PST02549, accumulated in processing bodies (P-bodies), protein complexes involved in mRNA decapping, degradation, and storage. PST02549 also associates with the P-body-resident ENHANCER OF mRNA DECAPPING PROTEIN 4 (EDC4) from N. benthamiana and wheat. We propose that P-bodies are a novel plant cell compartment targeted by pathogen effectors

Pleosporales

One hundred and five generic types of Pleosporales are described and illustrated. A brief introduction and detailed history with short notes on morphology, molecular phylogeny as well as a general conclusion of each genus are provided. For those genera where the type or a representative specimen is unavailable, a brief note is given. Altogether 174 genera of Pleosporales are treated. Phaeotrichaceae as well as Kriegeriella, Zeuctomorpha and Muroia are excluded from Pleosporales. Based on the multigene phylogenetic analysis, the suborder Massarineae is emended to accommodate five families, viz. Lentitheciaceae, Massarinaceae, Montagnulaceae, Morosphaeriaceae and Trematosphaeriaceae

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Modélisation forme-fonction du système ostéo-articulaire de l'avant-bras en imagerie médicale

- Nous proposons ici une première approche quantitative d'analyse de couplage de formes 3D, dans le but de mieux appréhender l'incidence d'un tel couple sur une fonctionnalité de mouvement. Concernant la morphométrie des os longs, nous étudions l'influence de la forme 3D des structures osseuses de l'avant-bras sur les limitations de l'angle de rotation pendant le mouvement de pronosupination. Sur la base d'une modélisation à plusieurs stades -forme, déformation puis mouvement-, des simulations confortent la conjecture de l'optimalité naturelle des paramètres de forme pour un avant-bras non pathologique isolé. S'il est enfin ici légitimé de se focaliser sur les régions diaphysaires dans ce sous-système ostéo-articulaire particulier, il est de plus avisé de dépasser la restriction purement osseuse pour intégrer le ligament interosseux à un ordre supérieur de modélisation

Polymorphic residues in rice NLRs expand binding and response to effectors of the blast pathogen

Accelerated adaptive evolution is a hallmark of plant-pathogen interactions. Plant intracellular immune receptors (NLRs) often occur as allelic series with differential pathogen specificities. The determinants of this specificity remain largely unknown. Here, we unravelled the biophysical and structural basis of expanded specificity in the allelic rice NLR Pik, which responds to the effector AVR-Pik from the rice blast pathogen Magnaporthe oryzae. Rice plants expressing the Pikm allele resist infection by blast strains expressing any of three AVR-Pik effector variants, whereas those expressing Pikp only respond to one. Unlike Pikp, the integrated heavy metal-associated (HMA) domain of Pikm binds with high affinity to each of the three recognized effector variants, and variation at binding interfaces between effectors and Pikp-HMA or Pikm-HMA domains encodes specificity. By understanding how co-evolution has shaped the response profile of an allelic NLR, we highlight how natural selection drove the emergence of new receptor specificities. This work has implications for the engineering of NLRs with improved utility in agriculture

Multidimentional proteomics for cell biology

The proteome is a dynamic system in which each protein has interconnected properties — dimensions — that together contribute to the phenotype of a cell. Measuring these properties has proved challenging owing to their diversity and dynamic nature. Advances in mass spectrometry-based proteomics now enable the measurement of multiple properties for thousands of proteins, including their abundance, isoform expression, turnover rate, subcellular localization, post-translational modifications and interactions. Complementing these experimental developments are new data analysis, integration and visualization tools as well as data-sharing resources. Together, these advances in the multidimensional analysis of the proteome are transforming our understanding of various cellular and physiological processes