• Other research productsclose
• Other ORP type close
• Wellcome Trust close
• English close
• NARCIS close

Cardiotoxicity is a severe side effect of drugs that induce structural or electrophysiological changes in heart muscle cells. As a result, the heart undergoes failure and potentially lethal arrhythmias. It is still a major reason for drug failure in preclinical and clinical phases of drug discovery. Current methods for predicting cardiotoxicity are based on guidelines that combine electrophysiological analysis of cell lines expressing ion channels ectopically in vitro with animal models and clinical trials. Although no new cases of drugs linked to lethal arrhythmias have been reported since the introduction of these guidelines in 2005, their limited predictive power likely means that potentially valuable drugs may not reach clinical practice. Human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) are now emerging as potentially more predictive alternatives, particularly for the early phases of preclinical research. However, these cells are phenotypically immature and culture and assay methods not standardized, which could be a hurdle to the development of predictive computational models and their implementation into the drug discovery pipeline, in contrast to the ambitions of the comprehensive pro-arrhythmia in vitro assay (CiPA) initiative. Here, we review present and future preclinical cardiotoxicity screening and suggest possible hPSC-CM-based strategies that may help to move the field forward. Coordinated efforts by basic scientists, companies and hPSC banks to standardize experimental conditions for generating reliable and reproducible safety indices will be helpful not only for cardiotoxicity prediction but also for precision medicine. Linked Articles: This article is part of a themed section on New Insights into Cardiotoxicity Caused by Chemotherapeutic Agents. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.21/issuetoc.

In the past 50 years, variants in the major histocompatibility complex (MHC) locus, also known as the human leukocyte antigen (HLA), have been reported as major risk factors for complex diseases. Recent advances, including large genetic screens, imputation, and analyses of non-additive and epistatic effects, have contributed to a better understanding of the shared and specific roles of MHC variants in different diseases. We review these advances and discuss the relationships between MHC variants involved in autoimmune and infectious diseases. Further work in this area will help to distinguish between alternative hypotheses for the role of pathogens in autoimmune disease development.

The clinical demand for mutation detection within multiple genes from a single tumour sample requires molecular diagnostic laboratories to develop rapid, high-throughput, highly sensitive, accurate and parallel testing within tight budget constraints. To meet this demand, many laboratories employ next-generation sequencing (NGS) based on small amplicons. Building on existing publications and general guidance for the clinical use of NGS and learnings from germline testing, the following guidelines establish consensus standards for somatic diagnostic testing, specifically for identifying and reporting mutations in solid tumours. These guidelines cover the testing strategy, implementation of testing within clinical service, sample requirements, data analysis and reporting of results. In conjunction with appropriate staff training and international standards for laboratory testing, these consensus standards for the use of NGS in molecular pathology of solid tumours will assist laboratories in implementing NGS in clinical services.

Climate change will alter the conditions that underlie economies. Slow onset changes such as shifting rainfall patterns, increasing temperatures, and coastal intrusion will affect both global as well as national and subnational markets, while rapid onset events such as high intensity storms and flooding will increase disruption and drive economic loss. These impacts are changing the conditions under which economies deliver goods and services. The resulting structural shift in the economy has already started to drive investment in new business models, technologies, and infrastructure, as well as the upgrading/climate proofing and relocation of existing infrastructure. These investments are taking place against a background of unprecedented uncertainty accompanying climate change and its immediate physical impacts, as well as the more indirect consequences that might ensue. This uncertainty and lack of historical precedent, coupled with other market imperfections, inhibit private financial flows for adaptation from reaching the required volumes. Much of the discussion on adaptation finance to date has focused on public spending. However, it is clear that a large share of the required adaptation measures, as well as the corresponding financing needs, will need to be provided by private sector actors. This report finds that substantial investment in adaptation and resilience is already occurring in the private sector, financed by private capital. This investment is being undertaken within private enterprises of varying scales in response to the shifting market conditions driven by climate change. Understanding how this investment occurs, what drives it and how it is financed, is a low-cost entrance for governments and policy makers seeking to increase levels of adaptation. The ultimate aim of this report is to analyse the role of public actors in order to inform the way in which public finance and policy can be used to catalyse private investments in adaptation. The report focuses on the barriers inhibiting private financial flows for adaptation and how these barriers may be removed by public intervention.

While the acquisition and curation of heterogeneous data in a single repository presents a technical challenge in itself, the ingestion of data into the CENDARI repository also opens up the possibility to process and index them through data extraction, entity recognition, semantic enhancement and other transformations. In this way the CENDARI project was able to act as a bridge between cultural heritage institutions and historical researchers, insofar as it drew together holdings from a broad range of institutions and enabled the browsing of this heterogeneous content within a single search space. This document describes a broad range of ways in which the CENDARI project acquired data from cultural heritage institutions as well as the necessary technical background. In exemplifying diverse data creation or acquisition strategies, multiple formats and technical solutions, assets and drawbacks of a repository, this “White Book” aims at providing guidance and advice as well as best practices for archivists and cultural heritage institutions collaborating or planning to collaborate with infrastructure projects.

This deliverable relates to the work carried out under task T8.3, “Research Impact Services”. The task’s focus is on the development of pilots with selected National funding agencies and infrastructure initiatives in order to serve them with the OpenAIRE research impact suite of services. A major service that OpenAIRE provides is the linking of research results to funding. Aside from importing the links from the repositories and journals, OpenAIRE designs, develops and enhances mining algorithms that identify and extract funding information from the text of scientific publications. With the help of NOADs we have initiated bi-lateral, often informal, collaborations with national funding agencies to facilitate mining extraction on their data. This is an on-going activity throughout the duration of the project. Currently the national funding agencies that we are working with are: FCT (Portugal), ARC (Australia), NHMRC (Australia), NSF & NIH (USA), SFI (Ireland), “Ministry of Science Education and Sport” & "Croatian Science Foundation” (Croatia), NWO (Netherlands), and DFG (Germany). This deliverable describes the nature of the data of the identified National funding agencies, as well as their export technologies, and provides the specification of the general-purpose OpenAIRE services required to support research impact measurements.

Background: Recent genome-wide association studies have identified multiple loci that are associated with an increased risk of developing coronary artery disease (CAD). The impact of these loci on the disease severity and prognosis of ischemic heart failure due to CAD is currently unknown. Methods: We undertook association analysis of 7 single nucleotide polymorphism (rs599839, rs17465637, rs2972147, rs6922269, rs1333049, rs501120, and rs17228212) at 7 well established CAD risk loci (1p13.3, 1q41, 2q36.3, 6q25.1, 9p21.3, 10q11.21, and 15q22.33, respectively) in 3,320 subjects diagnosed with systolic heart failure of ischemic aetiology and participating in the COntrolled ROsuvastatin multiNAtional Trial in Heart Failure (CORONA) trial. The primary outcome was the composite of time to first event of cardiovascular death, non-fatal myocardial infarction and non-fatal stroke, secondary outcomes included mortality and hospitalization due to worsening heart failure. Results: None of the 7 loci were significantly associated with the primary composite endpoint of the CORONA trial (death from cardiovascular cases, nonfatal myocardial infarction, and nonfatal stroke). However, the 1p13.3 locus (rs599839) showed evidence for association with all-cause mortality (after adjustment for covariates; HR 0.74, 95% CI [0.61 to 0.90]; P = 0.0025) and we confirmed the 1p13.3 locus (rs599839) to be associated with lipid parameters (total cholesterol (P = 1.1x10(-4)), low-density lipoprotein levels (P = 3.5 x 10(-7)) and apolipoprotein B (P = 2.2 x 10(-10))). Conclusion: Genetic variants strongly associated with CAD risk are not associated with the severity and outcome of ischemic heart failure. The observed association of the 1p13.3 locus with all-cause mortality requires confirmation in further studies.