AIM To evaluate whether the introduction of the 2015 Guidelines for CardiopulmonaryResuscitation were associated with a change in outcomes after out-of-hospital cardiac arrest (OHCA). METHODS Patients with OHCA were divided into adults (≥ 18 years) and pediatric cases ( less then 18 years). An interrupted time-series analysis was used to compare survival before (pre-guidelines January 1st, 2013 and October 31st, 2015) and after (post-guidelines May 1st, 2016 and December 31st, 2018) introduction of the 2015 guidelines. We fitted a regression model after dividing the time-period into segments with separate intercept and slope estimates. RESULTS We included 309,499 adults and 8,668 children with OHCA. There was no difference in the change in survival to hospital discharge with a favorable functional outcome per year between the two periods for adults (slope difference -0.07% [95%CI -0.30 to 0.16], p = 0.55) and pediatric cases (slope difference -0.01% [95%CI -1.35 to 1.32], p = 0.98). Likewise, we found no immediate change in survival to hospital discharge with a favorable functional outcome between the two periods for adults (0.20% (95%CI -0.21 to 0.61], p = 0.33) and pediatric cases (-1.08 [95%CI -3.44 to 1.27], p = 0.37). CONCLUSION Publication of the 2015 Guidelines for Cardiopulmonary Resuscitation was not associated with an increase in survival to hospital discharge with a favorable functional outcome after OHCA. Outcomes for OHCA have not improved the last 6 years in the United States. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2020. For permissions please email journals.permissions@oup.com.Colonization of new habitats often reduces population sizes and may result in the accumulation of deleterious mutations by genetic drift. Compared to the genomic basis for adaptation to new environments, genome-wide analysis of deleterious mutations in isolated populations remains limited. In the present study, we investigated the accumulation of deleterious mutations in five endangered freshwater populations of threespine stickleback (Gasterosteus aculeatus) in the central part of the mainland of Japan. Using whole genome resequencing data, we first conducted phylogenomic analysis and confirmed at least two independent freshwater colonization events in the central mainland from ancestral marine ecotypes. Next, analyses of single nucleotide polymorphisms (SNPs) showed a substantial reduction of heterozygosity in freshwater populations compared to marine populations. Reduction in heterozygosity was more apparent at the center of each chromosome than the peripheries and on X-chromosomes compared to autosomes. Third, bioinformatic analysis of deleterious mutations showed increased accumulation of putatively deleterious mutations in the landlocked freshwater populations compared to marine populations. For the majority of populations examined, the frequencies of putatively deleterious mutations were higher on X-chromosomes than on autosomes. The inter-population comparison indicated that the majority of putatively deleterious mutations may have accumulated independently. Thus, whole genome resequencing of endangered populations can help to estimate the accumulation of deleterious mutations and inform us of which populations are the most severely endangered. Furthermore, analysis of variation among chromosomes can give insights into whether any particular chromosomes are likely to accumulate deleterious mutations. © The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.MOTIVATION Developing methods to efficiently analyze 3D point cloud data of plant architectures remains challenging for many phenotyping applications. Here, we describe a tool that tackles four core phenotyping tasks classification of cloud points into stem and lamina points; graph skeletonization of the stem points; segmentation of individual lamina; and whole leaf labeling. These four tasks are critical for numerous downstream phenotyping goals, such as quantifying plant biomass, performing morphological analyses of plant shapes, and uncovering genotype to phenotype relationships. The P3D tool provides an intuitive graphical user interface, a fast 3D rendering engine for visualizing plants with millions of cloud points, and several graph-theoretic and machine learning algorithms for 3D architecture analyses. AVAILABILITY AND IMPLEMENTATION P3D is open-source and implemented in C ++. Source code and Windows installer are freely available at https//github.com/iziamtso/P3D/. © The Author(s) (2020). Published by Oxford University Press. All rights reserved. For Permissions, please email journals.permissions@oup.com.SUMMARY ScaffoldGraph (SG) is an open-source Python library and command-line tool for the generation and analysis of molecular scaffold networks and trees, with the capability of processing large sets of input molecules. With the increase in high-throughput screening (HTS) data, scaffold graphs have proven useful for the navigation and analysis of chemical space, being used for visualisation, clustering, scaffold-diversity analysis and active-series identification. Built on RDKit and NetworkX, SG integrates scaffold graph analysis into the growing scientific/cheminformatics Python stack, increasing the flexibility and extendibility of the tool compared to existing software. AVAILABILITY AND IMPLEMENTATION SG is freely available and released under the MIT license at https//github.com/UCLCheminformatics/ScaffoldGraph. © The Author(s) (2020). Published by Oxford University Press. All rights reserved. For Permissions, please email journals.permissions@oup.com.AIMS An in-depth understanding of the prognostic value of patient-reported outcomes (PRO) is essential to facilitate person-centred care in heart failure (HF). This study aimed to clarify the prognostic role of subjective mental and physical health status in patients with HF. https://www.selleckchem.com/products/sn-001.html METHODS AND RESULTS Patients with HF were identified from the DenHeart Survey (n = 1,499) and PRO data were obtained at hospital discharge, including the EuroQol five-dimensional questionnaire (EQ-5D), the HeartQoL and the Hospital Anxiety and Depression Scale (HADS). Clinical baseline data were obtained from medical records and linked to nationwide registries with patient-level data on sociodemographics and healthcare contacts. Outcomes were all-cause and cardiovascular (CV) mortality, CV events and HF hospitalisation with one- and three-year follow-up.Analysing the PRO data on a continuous scale, a worse score in the following were associated with risk of all-cause and CV mortality after one year the HeartQoL (adjusted HRs 1.91, 95% CI1.