Lithium carbonate in amyotrophic lateral sclerosis patients homozygous for the C-allele at SNP rs12608932 in UNC13A: protocol for a confirmatory, randomized, group-sequential, event-driven, double-blind, placebo-controlled trial

BackgroundGiven the large genetic heterogeneity in amyotrophic lateral sclerosis (ALS), it seems likely that genetic subgroups may benefit differently from treatment. An exploratory meta-analysis identified that patients homozygous for the C-allele at SNP rs12608932, a single nucleotide polymorphism in the gene UNC13A, had a statistically significant survival benefit when treated with lithium carbonate. We aim to confirm the efficacy of lithium carbonate on the time to death or respiratory insufficiency in patients with ALS homozygous for the C-allele at SNP rs12608932 in UNC13A. MethodsA randomized, group-sequential, event-driven, double-blind, placebo-controlled trial will be conducted in 15 sites across Europe and Australia. Patients will be genotyped for UNC13A; those homozygous for the C-allele at SNP rs12608932 will be eligible. Patients must have a diagnosis of ALS according to the revised El Escorial criteria, and a TRICALS risk-profile score between -6.0 and -2.0. An expected number of 1200 patients will be screened in order to enroll a target sample size of 171 patients. Patients will be randomly allocated in a 2:1 ratio to lithium carbonate or matching placebo, and treated for a maximum duration of 24 months. The primary endpoint is the time to death or respiratory insufficiency, whichever occurs first. Key secondary endpoints include functional decline, respiratory function, quality of life, tolerability, and safety. An interim analysis for futility and efficacy will be conducted after the occurrence of 41 events. DiscussionLithium carbonate has been proven to be safe and well-tolerated in patients with ALS. Given the favorable safety profile, the potential benefits are considered to outweigh the burden and risks associated with study participation. This study may provide conclusive evidence about the life-prolonging potential of lithium carbonate in a genetic ALS subgroup

Molecular diversity of anthracnose pathogen populations associated with UK strawberry production suggests multiple introductions of three different Colletotrichum species.

Fragaria × ananassa (common name: strawberry) is a globally cultivated hybrid species belonging to Rosaceae family. Colletotrichum acutatum sensu lato (s.l.) is considered to be the second most economically important pathogen worldwide affecting strawberries. A collection of 148 Colletotrichum spp. isolates including 67 C. acutatum s.l. isolates associated with the phytosanitary history of UK strawberry production were used to characterize multi-locus genetic variation of this pathogen in the UK, relative to additional reference isolates that represent a worldwide sampling of the diversity of the fungus. The evidence indicates that three different species C. nymphaeae, C. godetiae and C. fioriniae are associated with strawberry production in the UK, which correspond to previously designated genetic groups A2, A4 and A3, respectively. Among these species, 12 distinct haplotypes were identified suggesting multiple introductions into the country. A subset of isolates was also used to compare aggressiveness in causing disease on strawberry plants and fruits. Isolates belonging to C. nymphaeae, C. godetiae and C. fioriniae representative of the UK anthracnose pathogen populations showed variation in their aggressiveness. Among the three species, C. nymphaeae and C. fioriniae appeared to be more aggressive compared to C. godetiae. This study highlights the genetic and pathogenic heterogeneity of the C. acutatum s.l. populations introduced into the UK linked to strawberry production

Dynamically coupling full Stokes and shallow shelf approximation for marine ice sheet flow using Elmer/Ice (v8.3)

Ice flow forced by gravity is governed by the full Stokes (FS) equations, which are computationally expensive to solve due to the nonlinearity introduced by the rheology. Therefore, approximations to the FS equations are commonly used, especially when modeling a marine ice sheet (ice sheet, ice shelf, and/or ice stream) for 103 years or longer. The shallow ice approximation (SIA) and shallow shelf approximation (SSA) are commonly used but are accurate only for certain parts of an ice sheet. Here, we report a novel way of iteratively coupling FS and SSA that has been implemented in Elmer/Ice and applied to conceptual marine ice sheets. The FS–SSA coupling appears to be very accurate; the relative error in velocity compared to FS is below 0.5&thinsp;% for diagnostic runs and below 5&thinsp;% for prognostic runs. Results for grounding line dynamics obtained with the FS–SSA coupling are similar to those obtained from an FS model in an experiment with a periodical temperature forcing over 3000 years that induces grounding line advance and retreat. The rapid convergence of the FS–SSA coupling shows a large potential for reducing computation time, such that modeling a marine ice sheet for thousands of years should become feasible in the near future. Despite inefficient matrix assembly in the current implementation, computation time is reduced by 32&thinsp;%, when the coupling is applied to a 3-D ice shelf.</p

Identification of Hyaloperonospora arabidopsidis Transcript Sequences Expressed during Infection Reveals Isolate-Specific Effectors

Biotrophic plant pathogens secrete effector proteins that are important for infection of the host. The aim of this study was to identify effectors of the downy mildew pathogen Hyaloperonospora arabidopsidis (Hpa) that are expressed during infection of its natural host Arabidopsis thaliana. Infection-related transcripts were identified from Expressed Sequence Tags (ESTs) derived from leaves of the susceptible Arabidopsis Ws eds1-1 mutant inoculated with the highly virulent Hpa isolate Waco9. Assembly of 6364 ESTs yielded 3729 unigenes, of which 2164 were Hpa-derived. From the translated Hpa unigenes, 198 predicted secreted proteins were identified. Of these, 75 were found to be Hpa-specific and six isolate Waco9-specific. Among 42 putative effectors identified there were three Elicitin-like proteins, 16 Cysteine-rich proteins and 18 host-translocated RXLR effectors. Sequencing of alleles in different Hpa isolates revealed that five RXLR genes show signatures of diversifying selection. Thus, EST analysis of Hpa-infected Arabidopsis is proving to be a powerful method for identifying pathogen effector candidates expressed during infection. Delivery of the Waco9-specific protein RXLR29 in planta revealed that this effector can suppress PAMP-triggered immunity and enhance disease susceptibility. We propose that differences in host colonization can be conditioned by isolate-specific effectors

Sequential Delivery of Host-Induced Virulence Effectors by Appressoria and Intracellular Hyphae of the Phytopathogen Colletotrichum higginsianum

Phytopathogens secrete effector proteins to manipulate their hosts for effective colonization. Hemibiotrophic fungi must maintain host viability during initial biotrophic growth and elicit host death for subsequent necrotrophic growth. To identify effectors mediating these opposing processes, we deeply sequenced the transcriptome of Colletotrichum higginsianum infecting Arabidopsis. Most effector genes are host-induced and expressed in consecutive waves associated with pathogenic transitions, indicating distinct effector suites are deployed at each stage. Using fluorescent protein tagging and transmission electron microscopy-immunogold labelling, we found effectors localised to stage-specific compartments at the host-pathogen interface. In particular, we show effectors are focally secreted from appressorial penetration pores before host invasion, revealing new levels of functional complexity for this fungal organ. Furthermore, we demonstrate that antagonistic effectors either induce or suppress plant cell death. Based on these results we conclude that hemibiotrophy in Colletotrichum is orchestrated through the coordinated expression of antagonistic effectors supporting either cell viability or cell death

Comparative Genome Analysis of Filamentous Fungi Reveals Gene Family Expansions Associated with Fungal Pathogenesis

Fungi and oomycetes are the causal agents of many of the most serious diseases of plants. Here we report a detailed comparative analysis of the genome sequences of thirty-six species of fungi and oomycetes, including seven plant pathogenic species, that aims to explore the common genetic features associated with plant disease-causing species. The predicted translational products of each genome have been clustered into groups of potential orthologues using Markov Chain Clustering and the data integrated into the e-Fungi object-oriented data warehouse (http://www.e-fungi.org.uk/). Analysis of the species distribution of members of these clusters has identified proteins that are specific to filamentous fungal species and a group of proteins found only in plant pathogens. By comparing the gene inventories of filamentous, ascomycetous phytopathogenic and free-living species of fungi, we have identified a set of gene families that appear to have expanded during the evolution of phytopathogens and may therefore serve important roles in plant disease. We have also characterised the predicted set of secreted proteins encoded by each genome and identified a set of protein families which are significantly over-represented in the secretomes of plant pathogenic fungi, including putative effector proteins that might perturb host cell biology during plant infection. The results demonstrate the potential of comparative genome analysis for exploring the evolution of eukaryotic microbial pathogenesis

Two implementations of the preconditioned conjugate gradient method on heterogeneous computing grids

Efficient iterative solution of large linear systems on grid computers is a complex problem. The induced heterogeneity and volatile nature of the aggregated computational resources present numerous algorithmic challenges. This paper describes a case study regarding iterative solution of large sparse linear systems on grid computers within the software constraints of the grid middleware GridSolve and within the algorithmic constraints of preconditioned Conjugate Gradient (CG) type methods. We identify the various bottlenecks induced by the middleware and the iterative algorithm. We consider the standard CG algorithm of Hestenes and Stiefel, and as an alternative the Chronopoulos/Gear variant, a formulation that is potentially better suited for grid computing since it requires only one synchronisation point per iteration, instead of two for standard CG. In addition, we improve the computation-to-communication ratio by maximising the work in the preconditioner. In addition to these algorithmic improvements, we also try to minimise the communication overhead within the communication model currently used by the GridSolve middleware. We present numerical experiments on 3D bubbly flow problems using heterogeneous computing hardware that show lower computing times and better speed-up for the Chronopoulos/Gear variant of conjugate gradients. Finally, we suggest extensions to both the iterative algorithm and the middleware for improving granularity