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The infant brain undergoes a remarkable period of neural development that is crucial for the development of cognitive and behavioral capacities (Hasegawa et al., 2018). Longitudinal magnetic resonance imaging (MRI) is able to characterize the developmental trajectories and is critical in neuroimaging studies of early brain development. However, missing data at different time points is an unavoidable occurrence in longitudinal studies owing to participant attrition and scan failure. Compared to dropping incomplete data, data imputation is considered a better solution to address such missing data in order to preserve all available samples. In this paper, we adapt generative adversarial networks (GAN) to a new application: longitudinal image prediction of structural MRI in the first year of life. In contrast to existing medical image-to-image translation applications of GANs, where inputs and outputs share a very close anatomical structure, our task is more challenging as brain size, shape and tissue contrast vary significantly between the input data and the predicted data. Several improvements over existing GAN approaches are proposed to address these challenges in our task. To enhance the realism, crispness, and accuracy of the predicted images, we incorporate both a traditional voxel-wise reconstruction loss as well as a perceptual loss term into the adversarial learning scheme. As the differing contrast changes in T1w and T2w MR images in the first year of life, we incorporate multi-contrast images leading to our proposed 3D multi-contrast perceptual adversarial network (MPGAN). Extensive evaluations are performed to assess the qualityand fidelity of the predicted images, including qualitative and quantitative assessments of the image appearance, as well as quantitative assessment on two segmentation tasks. Our experimental results show that our MPGAN is an effective solution for longitudinal MR image data imputation in the infant brain. We further apply our predicted/imputed images to two practical tasks, a regression task and a classification task, in order to highlight the enhanced task-related performance following image imputation. The results show that the model performance in both tasks is improved by including the additional imputed data, demonstrating the usability of the predicted images generated from our approach.

Gap junction communication (GJC) mediated by connexins is critical for heart function. To gain insight into the causal relationship of molecular mechanisms of disease pathology, it is important to understand which mechanisms contribute to impairment of gap junctional communication. Here, we present an update on the known modulators of connexins, including various interaction partners, kinases, and signaling cascades. This gap junction network (GJN) can serve as a blueprint for data mining approaches exploring the growing number of publicly available data sets from experimental and clinical studies.

In contemporary copyright law, there is an ongoing debate around the nature and scope of the rights users should have to copyright works, exacerbated by ongoing technological developments. Within that debate, this article queries the value of looking at the remedies users may have against copyright holders restricting their legitimate uses of works, as a means to further elucidate the nature and scope of user rights. While there is some value in looking at remedies to situate copyright user rights, an access to justice perspective to rights and remedies suggests that such approach may be too limiting with respect to the position of potential claimants in a legal system. On that basis, this paper identifies structural deficiencies of copyright user rights and proposes an analytical framework towards achieving greater &ldquo both in the realm of public law and private law. justice for users&rdquo

AbstractBackgroundSequencing technology and assembly algorithms have matured to the point that high-quality de novo assembly is possible for large, repetitive genomes. Current assemblies traverse transposable elements (TEs) and provide an opportunity for comprehensive annotation of TEs. Numerous methods exist for annotation of each class of TEs, but their relative performances have not been systematically compared. Moreover, a comprehensive pipeline is needed to produce a non-redundant library of TEs for species lacking this resource to generate whole-genome TE annotations.ResultsWe benchmark existing programs based on a carefully curated library of rice TEs. We evaluate the performance of methods annotating long terminal repeat (LTR) retrotransposons, terminal inverted repeat (TIR) transposons, short TIR transposons known as miniature inverted transposable elements (MITEs), and Helitrons. Performance metrics include sensitivity, specificity, accuracy, precision, FDR, andF1. Using the most robust programs, we create a comprehensive pipeline called Extensivede-novoTE Annotator (EDTA) that produces a filtered non-redundant TE library for annotation of structurally intact and fragmented elements. EDTA also deconvolutes nested TE insertions frequently found in highly repetitive genomic regions. Using other model species with curated TE libraries (maize and Drosophila), EDTA is shown to be robust across both plant and animal species.ConclusionsThe benchmarking results and pipeline developed here will greatly facilitate TE annotation in eukaryotic genomes. These annotations will promote a much more in-depth understanding of the diversity and evolution of TEs at both intra- and inter-species levels. EDTA is open-source and freely available:https://github.com/oushujun/EDTA.

Background Early warning score systems have been widely recommended for use to detect clinical deterioration in patients. The Irish National Emergency Medicine Programme has developed and piloted an emergency department specific early warning score system. The objective of this study was to develop a consensus among frontline healthcare staff, quality and safety staff and health systems researchers regarding evaluation measures for an early warning score system in the Emergency Department. Methods Participatory action research including a modified Delphi consensus building technique with frontline hospital staff, quality and safety staff, health systems researchers, local and national emergency medicine stakeholders was the method employed in this study. In Stage One, a workshop was held with the participatory action research team including frontline hospital staff, quality and safety staff and health systems researchers to gather suggestions regarding the evaluation measures. In Stage Two, an electronic modified-Delphi study was undertaken with a panel consisting of the workshop participants, key local and national emergency medicine stakeholders. Descriptive statistics were used to summarise the characteristics of the panellists who completed the questionnaires in each round. The mean Likert rating, standard deviation and 95% bias-corrected bootstrapped confidence interval for each variable was calculated. Bonferroni corrections were applied to take account of multiple testing. Data were analysed using Stata 14.0 SE. Results Using the Institute for Healthcare Improvement framework, 12 process, outcome and balancing metrics for measuring the effectiveness of an ED-specific early warning score system were developed. Conclusion There are currently no published measures for evaluating the effectiveness of an ED early warning score system. It was possible in this study to develop a suite of evaluation measures using a modified Delphi consensus approach. Using the collective expertise of frontline hospital staff, quality and safety staff and health systems researchers to develop and categorise the initial set of potential measures was an innovative and unique element of this study. Electronic supplementary material The online version of this article (10.1186/s12873-018-0220-3) contains supplementary material, which is available to authorized users.

Epigenetic inheritance was transmitted through selection over generations of extreme early, but not late flowering time phenotypic lines in F. vesca. Epigenetic variation was initially induced using the DNA demethylating reagent 5-azacytidine (5-azaC). It is the first report exploring epigenetic variant selection and phenotypic trait inheritance in strawberry, a model plant species for one of the most important temperate fruit crop families, Rosaceae. Transmission frequency of these traits was determined across generations. Early flowering (EF4) and late stolon (LS) phenotypic traits were successfully transmitted through meiosis across at least five and two generations, respectively. Stable mitotic transmission of the early flowering phenotype was also demonstrated using clonal daughters derived from the 4th Generation (S4) mother plant. In order to further explore the DNA methylation patterns underlying the early flowering trait, the standard MSAP method using isoschizomers Hpa II / Msp I, and a newly modified MSAP method using isoschizomers Tfi I / Pfe I which detected DNA methylation at CG, CHG, CHH sites were used in two early flowering lines, EF4 lines 1 (P2) and EF4 lines 2 (P3), and control lines (P1). A significant reduction in the number of fully-methylated bands was detected in P2 and P3 when compared to P1 using the novel MSAP method. In the standard MSAP, the symmetric CG and CHG methylation was maintained over generations in the early flowering lines based on the clustering in P2 and P3, while the novel MSAP approach revealed the asymmetric CHH methylation pattern was not maintained over generations. This study provides evidence of stable selection of phenotypic traits, particularly the early flowering phenotype through both meiosis and mitosis, which is meaningful to both breeding programs and commercial horticulture. The maintenance in CG and CHG methylation over generations suggests the early flowering phenotype might be related to DNA methylation alterations at the CG or CHG sites. Finally, this work provides a new approach for studying the role of epigenetics on complex quantitative trait improvement in strawberry, as well as providing a tool to expand phenotypic diversity and expedite potential new horticulture cultivar releases through either seed or vegetative propagation.

Gut microbiota can have important effects on host health, but explanatory factors and pathways that determine gut microbial composition can differ among host lineages. In mammals, host phylogeny is one of the main drivers of gut microbiota, a result of vertical transfer of microbiota during birth. In birds, it is less clear what the drivers might be, but both phylogeny and environmental factors may play a role. We investigated host and environmental factors that underlie variation in gut microbiota composition in eight species of migratory shorebirds. We characterized bacterial communities from 375 fecal samples collected from adults of eight shorebird species captured at a network of nine breeding sites in the Arctic and sub-Arctic ecoregions of North America, by sequencing the V4 region of the bacterial 16S ribosomal RNA gene. Firmicutes (55.4%), Proteobacteria (13.8%), Fusobacteria (10.2%), and Bacteroidetes (8.1%) dominated the gut microbiota of adult shorebirds. Breeding location was the main driver of variation in gut microbiota of breeding shorebirds (R-2 = 11.6%), followed by shorebird host species (R-2 = 1.8%), and sampling year (R-2 = 0.9%), but most variation remained unexplained. Site variation resulted from differences in the core bacterial taxa, whereas rare, lowabundance bacteria drove host species variation. Our study is the first to highlight a greater importance of local environment than phylogeny as a driver of gut microbiota composition in wild, migratory birds under natural conditions. Avian Health Program grants from the U.S. Fish and Wildlife Service [2013-02]; National Science FoundationNational Science Foundation (NSF) [DDIG-1501479]; Arctic Landscape Conservation Cooperative; U.S. Fish and Wildlife ServiceUS Fish & Wildlife Service; Division of Biology at the Kansas State University; Kansas State University Open Access Publishing Fund This work was funded by the Avian Health Program grants from the U.S. Fish and Wildlife Service (to JS and RL, and 2013-02 to KG and RL), a Doctoral Dissertation Improvement Grant from the National Science Foundation (DDIG-1501479 to KG), the Arctic Landscape Conservation Cooperative, the U.S. Fish and Wildlife Service, and the Division of Biology at the Kansas State University. Publication of this article was funded in part by the Kansas State University Open Access Publishing Fund.