Showing papers by "Utrecht University published in 2015"
TL;DR: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations, and has reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-generation sequencing, deep exome sequencing, and dense microarray genotyping.
Abstract: The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
12,661 citations
Mohammad H. Forouzanfar1, Lily Alexander, H. Ross Anderson, Victoria F Bachman1 +733 more•Institutions (289)
TL;DR: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) as discussed by the authors provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.
5,668 citations
TL;DR: In the Global Burden of Disease Study 2013 (GBD 2013) as mentioned in this paper, the authors estimated the quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013.
4,510 citations
University of Helsinki1, Semmelweis University2, Hungarian Academy of Sciences3, University of Szeged4, University of Palermo5, Institute of Molecular Pathology and Immunology of the University of Porto6, University of Porto7, Autonomous University of Barcelona8, Instituto de Biologia Molecular e Celular9, Ikerbasque10, Harvard University11, University of Duisburg-Essen12, Salk Institute for Biological Studies13, Paracelsus Private Medical University of Salzburg14, University of Colorado Denver15, Bilkent University16, Middle East Technical University17, Statens Serum Institut18, University of Southern Denmark19, Ghent University Hospital20, Oslo University Hospital21, University of Belgrade22, University of Ljubljana23, University of Mainz24, Finnish Red Cross25, University of Gothenburg26, Latvian Biomedical Research and Study centre27, University of Applied Sciences and Arts Northwestern Switzerland FHNW28, University of Valencia29, Centro Nacional de Investigaciones Cardiovasculares30, University of Freiburg31, Utrecht University32, Trinity College, Dublin33, University of Barcelona34, Catalan Institution for Research and Advanced Studies35, International University Of Catalonia36, Aarhus University Hospital37
TL;DR: A comprehensive overview of the current understanding of the physiological roles of EVs is provided, drawing on the unique EV expertise of academia-based scientists, clinicians and industry based in 27 European countries, the United States and Australia.
Abstract: In the past decade, extracellular vesicles (EVs) have been recognized as potent vehicles of intercellular communication, both in prokaryotes and eukaryotes. This is due to their capacity to transfer proteins, lipids and nucleic acids, thereby influencing various physiological and pathological functions of both recipient and parent cells. While intensive investigation has targeted the role of EVs in different pathological processes, for example, in cancer and autoimmune diseases, the EV-mediated maintenance of homeostasis and the regulation of physiological functions have remained less explored. Here, we provide a comprehensive overview of the current understanding of the physiological roles of EVs, which has been written by crowd-sourcing, drawing on the unique EV expertise of academia-based scientists, clinicians and industry based in 27 European countries, the United States and Australia. This review is intended to be of relevance to both researchers already working on EV biology and to newcomers who will encounter this universal cell biological system. Therefore, here we address the molecular contents and functions of EVs in various tissues and body fluids from cell systems to organs. We also review the physiological mechanisms of EVs in bacteria, lower eukaryotes and plants to highlight the functional uniformity of this emerging communication system.
3,690 citations
TL;DR: In virtually all medical domains, diagnostic and prognostic multivariable prediction models are being developed, validated, updated, and implemented with the aim to assist doctors and individuals in estimating probabilities and potentially influence their decision making.
Abstract: The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) Statement includes a 22-item checklist, which aims to improve the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. This explanation and elaboration document describes the rationale; clarifies the meaning of each item; and discusses why transparent reporting is important, with a view to assessing risk of bias and clinical usefulness of the prediction model. Each checklist item of the TRIPOD Statement is explained in detail and accompanied by published examples of good reporting. The document also provides a valuable reference of issues to consider when designing, conducting, and analyzing prediction model studies. To aid the editorial process and help peer reviewers and, ultimately, readers and systematic reviewers of prediction model studies, it is recommended that authors include a completed checklist in their submission. The TRIPOD checklist can also be downloaded from www.tripod-statement.org.
2,982 citations
TL;DR: The SQUEEZE method is documents as an alternative means of addressing the solvent disorder issue and conveniently interfaces with the 2014 version of the least-squares refinement program SHELXL, and many twinned structures containing disordered solvents are now also treatable by SQUEEze.
Abstract: The completion of a crystal structure determination is often hampered by the presence of embedded solvent molecules or ions that are seriously disordered. Their contribution to the calculated structure factors in the least-squares refinement of a crystal structure has to be included in some way. Traditionally, an atomistic solvent disorder model is attempted. Such an approach is generally to be preferred, but it does not always lead to a satisfactory result and may even be impossible in cases where channels in the structure are filled with continuous electron density. This paper documents the SQUEEZE method as an alternative means of addressing the solvent disorder issue. It conveniently interfaces with the 2014 version of the least-squares refinement program SHELXL [Sheldrick (2015). Acta Cryst. C71. In the press] and other refinement programs that accept externally provided fixed contributions to the calculated structure factors. The PLATON SQUEEZE tool calculates the solvent contribution to the structure factors by back-Fourier transformation of the electron density found in the solvent-accessible region of a phase-optimized difference electron-density map. The actual least-squares structure refinement is delegated to, for example, SHELXL. The current versions of PLATON SQUEEZE and SHELXL now address several of the unnecessary complications with the earlier implementation of the SQUEEZE procedure that were a necessity because least-squares refinement with the now superseded SHELXL97 program did not allow for the input of fixed externally provided contributions to the structure-factor calculation. It is no longer necessary to subtract the solvent contribution temporarily from the observed intensities to be able to use SHELXL for the least-squares refinement, since that program now accepts the solvent contribution from an external file (.fab file) if the ABIN instruction is used. In addition, many twinned structures containing disordered solvents are now also treatable by SQUEEZE. The details of a SQUEEZE calculation are now automatically included in the CIF archive file, along with the unmerged reflection data. The current implementation of the SQUEEZE procedure is described, and discussed and illustrated with three examples. Two of them are based on the reflection data of published structures and one on synthetic reflection data generated for a published structure.
2,712 citations
Northern Arizona University1, University of Alaska Fairbanks2, University of Florida3, Alfred Wegener Institute for Polar and Marine Research4, United States Geological Survey5, Oak Ridge National Laboratory6, Stockholm University7, Lawrence Berkeley National Laboratory8, National Center for Atmospheric Research9, Woods Hole Research Center10, University of Alberta11, Tyumen State Oil and Gas University12, University of Guelph13, University of New Hampshire14, Utrecht University15
TL;DR: In this paper, the authors find that current evidence suggests a gradual and prolonged release of greenhouse gas emissions in a warming climate and present a research strategy with which to target poorly understood aspects of permafrost carbon dynamics.
Abstract: Large quantities of organic carbon are stored in frozen soils (permafrost) within Arctic and sub-Arctic regions. A warming climate can induce environmental changes that accelerate the microbial breakdown of organic carbon and the release of the greenhouse gases carbon dioxide and methane. This feedback can accelerate climate change, but the magnitude and timing of greenhouse gas emission from these regions and their impact on climate change remain uncertain. Here we find that current evidence suggests a gradual and prolonged release of greenhouse gas emissions in a warming climate and present a research strategy with which to target poorly understood aspects of permafrost carbon dynamics.
2,282 citations
University of Amsterdam1, Utrecht University2, University of Virginia3, Brown University4, Bond University5, University of Sydney6, Ottawa Hospital Research Institute7, University of Ottawa8, University of California, San Francisco9, VU University Medical Center10, Beth Israel Deaconess Medical Center11, Boston Children's Hospital12, Northwestern University13, University of Oxford14, Paris Descartes University15
TL;DR: STARD 2015 is presented, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study, which incorporates recent evidence about sources of bias and variability in diagnostic accuracy.
Abstract: Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting Diagnostic Accuracy (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.
2,116 citations
TL;DR: The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used, and is best used in conjunction with the TRIPod explanation and elaboration document.
Abstract: Prediction models are developed to aid health-care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health-care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).
1,973 citations
University of Washington1, University of Maryland, Baltimore2, Harvard University3, Broad Institute4, Mayo Clinic5, Yale University6, Washington University in St. Louis7, University of Michigan8, University of Texas Health Science Center at Houston9, Louisiana State University10, University of North Carolina at Charlotte11, Wellcome Trust12, University of Texas MD Anderson Cancer Center13, Boston College14, Yeshiva University15, Bilkent University16, University of California, San Diego17, National Institutes of Health18, Leiden University19, Baylor College of Medicine20, Cornell University21, Utrecht University22, University of Oxford23, Icahn School of Medicine at Mount Sinai24, Kyoto University25, Virginia Commonwealth University26, Heidelberg University27, Ewha Womans University28
TL;DR: In this paper, the authors describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which are constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations.
Abstract: Structural variants are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight structural variant classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype blocks in 26 human populations. Analysing this set, we identify numerous gene-intersecting structural variants exhibiting population stratification and describe naturally occurring homozygous gene knockouts that suggest the dispensability of a variety of human genes. We demonstrate that structural variants are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of structural variant complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex structural variants with multiple breakpoints likely to have formed through individual mutational events. Our catalogue will enhance future studies into structural variant demography, functional impact and disease association.
1,971 citations
19 Nov 2015
TL;DR: The first description in the English language of the constellation of findings now known to be due to this chromosomal difference was made in the 1960s in children with DiGeorge syndrome, who presented with the clinical triad of immunodeficiency, hypoparathyroidism and congenital heart disease as mentioned in this paper.
Abstract: 22q11.2 deletion syndrome (22q11.2DS) is the most common chromosomal microdeletion disorder, estimated to result mainly from de novo non-homologous meiotic recombination events occurring in approximately 1 in every 1,000 fetuses. The first description in the English language of the constellation of findings now known to be due to this chromosomal difference was made in the 1960s in children with DiGeorge syndrome, who presented with the clinical triad of immunodeficiency, hypoparathyroidism and congenital heart disease. The syndrome is now known to have a heterogeneous presentation that includes multiple additional congenital anomalies and later-onset conditions, such as palatal, gastrointestinal and renal abnormalities, autoimmune disease, variable cognitive delays, behavioural phenotypes and psychiatric illness - all far extending the original description of DiGeorge syndrome. Management requires a multidisciplinary approach involving paediatrics, general medicine, surgery, psychiatry, psychology, interventional therapies (physical, occupational, speech, language and behavioural) and genetic counselling. Although common, lack of recognition of the condition and/or lack of familiarity with genetic testing methods, together with the wide variability of clinical presentation, delays diagnosis. Early diagnosis, preferably prenatally or neonatally, could improve outcomes, thus stressing the importance of universal screening. Equally important, 22q11.2DS has become a model for understanding rare and frequent congenital anomalies, medical conditions, psychiatric and developmental disorders, and may provide a platform to better understand these disorders while affording opportunities for translational strategies across the lifespan for both patients with 22q11.2DS and those with these associated features in the general population.
Mohammad H. Forouzanfar1, Lily Alexander1, H. Ross Anderson2, Victoria F Bachman1 +718 more•Institutions (295)
TL;DR: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) as mentioned in this paper provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.
TL;DR: This article presents an alternative model that separates the within-person process from stable between-person differences through the inclusion of random intercepts, and discusses how this model is related to existing structural equation models that include cross-lagged relationships.
Abstract: The cross-lagged panel model (CLPM) is believed by many to overcome the problems associated with the use of cross-lagged correlations as a way to study causal influences in longitudinal panel data. The current article, however, shows that if stability of constructs is to some extent of a trait-like, time-invariant nature, the autoregressive relationships of the CLPM fail to adequately account for this. As a result, the lagged parameters that are obtained with the CLPM do not represent the actual within-person relationships over time, and this may lead to erroneous conclusions regarding the presence, predominance, and sign of causal influences. In this article we present an alternative model that separates the within-person process from stable between-person differences through the inclusion of random intercepts, and we discuss how this model is related to existing structural equation models that include cross-lagged relationships. We derive the analytical relationship between the cross-lagged parameters from the CLPM and the alternative model, and use simulations to demonstrate the spurious results that may arise when using the CLPM to analyze data that include stable, trait-like individual differences. We also present a modeling strategy to avoid this pitfall and illustrate this using an empirical data set. The implications for both existing and future cross-lagged panel research are discussed.
Beth Israel Deaconess Medical Center1, University of Pennsylvania2, UCL Institute of Neurology3, University of Bremen4, Utrecht University5, University of Michigan6, University of Texas Southwestern Medical Center7, University of Toronto8, Sunnybrook Research Institute9, University of Manchester10, Erasmus University Rotterdam11, Leiden University Medical Center12, University of California, Los Angeles13, University of California, San Diego14, Stanford University15
TL;DR: This review provides a summary statement of recommended implementations of arterial spin labeling (ASL) for clinical applications and describes the major considerations and trade‐offs in implementing an ASL protocol and provides specific recommendations for a standard approach.
Abstract: This review provides a summary statement of recommended implementations of arterial spin labeling (ASL) for clinical applications. It is a consensus of the ISMRM Perfusion Study Group and the European ASL in Dementia consortium, both of whom met to reach this consensus in October 2012 in Amsterdam. Although ASL continues to undergo rapid technical development, we believe that current ASL methods are robust and ready to provide useful clinical information, and that a consensus statement on recommended implementations will help the clinical community to adopt a standardized approach. In this review, we describe the major considerations and trade-offs in implementing an ASL protocol and provide specific recommendations for a standard approach. Our conclusion is that as an optimal default implementation, we recommend pseudo-continuous labeling, background suppression, a segmented three-dimensional readout without vascular crushing gradients, and calculation and presentation of both label/control difference images and cerebral blood flow in absolute units using a simplified model.
TL;DR: The nature of the prediction in diagnosis is estimating the probability that a specific outcome or disease is present (or absent) within an individual, at this point in timethat is, the moment of prediction (T= 0), and prognostic prediction involves a longitudinal relationship.
Abstract: Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).
Christopher J L Murray1, Ryan M Barber, Kyle J Foreman2, Ayse Abbasoglu Ozgoren +608 more•Institutions (251)
TL;DR: Patterns of the epidemiological transition with a composite indicator of sociodemographic status, which was constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population, were quantified.
TL;DR: Bychkov and Rashba as discussed by the authors introduced a simple form of spin-orbit coupling to explain the peculiarities of electron spin resonance in two-dimensional semiconductors, which has inspired a vast number of predictions, discoveries and innovative concepts far beyond semiconductor devices.
Abstract: In 1984, Bychkov and Rashba introduced a simple form of spin-orbit coupling to explain the peculiarities of electron spin resonance in two-dimensional semiconductors. Over the past 30 years, Rashba spin-orbit coupling has inspired a vast number of predictions, discoveries and innovative concepts far beyond semiconductors. The past decade has been particularly creative, with the realizations of manipulating spin orientation by moving electrons in space, controlling electron trajectories using spin as a steering wheel, and the discovery of new topological classes of materials. This progress has reinvigorated the interest of physicists and materials scientists in the development of inversion asymmetric structures, ranging from layered graphene-like materials to cold atoms. This Review discusses relevant recent and ongoing realizations of Rashba physics in condensed matter.
Royal Netherlands Academy of Arts and Sciences1, Lustgarten Foundation2, Cold Spring Harbor Laboratory3, Stony Brook University4, Watson School of Biological Sciences5, University Medical Center Utrecht6, Utrecht University7, Memorial Sloan Kettering Cancer Center8, Johns Hopkins University School of Medicine9
TL;DR: Comprehensive transcriptional and proteomic analyses of murine pancreatic organoids revealed genes and pathways altered during disease progression that demonstrate that organoids are a facile model system to discover characteristics of this deadly malignancy.
TL;DR: These data show that lumacaftor in combination with ivacaftors provided a benefit for patients with cystic fibrosis homozygous for the Phe508del CFTR mutation.
Abstract: A total of 1108 patients underwent randomization and received study drug. The mean baseline FEV 1 was 61% of the predicted value. In both studies, there were significant improvements in the primary end point in both lumacaftor–ivacaftor dose groups; the difference between active treatment and placebo with respect to the mean absolute improvement in the percentage of predicted FEV 1 ranged from 2.6 to 4.0 percentage points (P<0.001), which corresponded to a mean relative treatment difference of 4.3 to 6.7% (P<0.001). Pooled analyses showed that the rate of pulmonary exacerbations was 30 to 39% lower in the lumacaftor–ivacaftor groups than in the placebo group; the rate of events leading to hospitalization or the use of intravenous antibiotics was lower in the lumacaftor–ivacaftor groups as well. The incidence of adverse events was generally similar in the lumacaftor–ivacaftor and placebo groups. The rate of discontinuation due to an adverse event was 4.2% among patients who received lumacaftor–ivacaftor versus 1.6% among those who received placebo. CONCLUSIONS These data show that lumacaftor in combination with ivacaftor provided a benefit for patients with cystic fibrosis homozygous for the Phe508del CFTR mutation. (Funded by Vertex Pharmaceuticals and others; TRAFFIC and TRANSPORT ClinicalTrials.gov numbers, NCT01807923 and NCT01807949.)
TL;DR: Large-scale molecular surveys have provided novel insights into the diversity, spatial and temporal dynamics of mycorrhizal fungal communities, and network theory makes it possible to analyze interactions between plant-fungal partners as complex underground multi-species networks.
Abstract: Almost all land plants form symbiotic associations with mycorrhizal fungi. These below-ground fungi play a key role in terrestrial ecosystems as they regulate nutrient and carbon cycles, and influence soil structure and ecosystem multifunctionality. Up to 80% of plant N and P is provided by mycorrhizal fungi and many plant species depend on these symbionts for growth and survival. Estimates suggest that there are c. 50 000 fungal species that form mycorrhizal associations with c. 250 000 plant species. The development of high-throughput molecular tools has helped us to better understand the biology, evolution, and biodiversity of mycorrhizal associations. Nuclear genome assemblies and gene annotations of 33 mycorrhizal fungal species are now available providing fascinating opportunities to deepen our understanding of the mycorrhizal lifestyle, the metabolic capabilities of these plant symbionts, the molecular dialogue between symbionts, and evolutionary adaptations across a range of mycorrhizal associations. Large-scale molecular surveys have provided novel insights into the diversity, spatial and temporal dynamics of mycorrhizal fungal communities. At the ecological level, network theory makes it possible to analyze interactions between plant-fungal partners as complex underground multi-species networks. Our analysis suggests that nestedness, modularity and specificity of mycorrhizal networks vary and depend on mycorrhizal type. Mechanistic models explaining partner choice, resource exchange, and coevolution in mycorrhizal associations have been developed and are being tested. This review ends with major frontiers for further research.
Utrecht University1, Université catholique de Louvain2, Institut national de la recherche agronomique3, Centre national de la recherche scientifique4, Université du Québec à Montréal5, Royal Society for the Protection of Birds6, University of Cambridge7, University of Padua8, University of Sussex9, Natural Resources Canada10, Purdue University11, Helmholtz Centre for Environmental Research - UFZ12, Smithsonian Institution13, University of Neuchâtel14, University of Saskatchewan15, Washington State University16, University of Bergen17, University of Stirling18
TL;DR: In this paper, a review of the global literature explores these risks and show a growing body of evidence that persistent, low concentrations of these insecticides pose serious risks of undesirable environmental impacts.
Abstract: Since their discovery in the late 1980s, neonicotinoid pesticides have become the most widely used class of insecticides worldwide, with large-scale applications ranging from plant protection (crops, vegetables, fruits), veterinary products, and biocides to invertebrate pest control in fish farming. In this review, we address the phenyl-pyrazole fipronil together with neonicotinoids because of similarities in their toxicity, physicochemical profiles, and presence in the environment. Neonicotinoids and fipronil currently account for approximately one third of the world insecticide market; the annual world production of the archetype neonicotinoid, imidacloprid, was estimated to be ca. 20,000 tonnes active substance in 2010. There were several reasons for the initial success of neonicotinoids and fipronil: (1) there was no known pesticide resistance in target pests, mainly because of their recent development, (2) their physicochemical properties included many advantages over previous generations of insecticides (i.e., organophosphates, carbamates, pyrethroids, etc.), and (3) they shared an assumed reduced operator and consumer risk. Due to their systemic nature, they are taken up by the roots or leaves and translocated to all parts of the plant, which, in turn, makes them effectively toxic to herbivorous insects. The toxicity persists for a variable period of time—depending on the plant, its growth stage, and the amount of pesticide applied. A wide variety of applications are available, including the most common prophylactic non-Good Agricultural Practices (GAP) application by seed coating. As a result of their extensive use and physicochemical properties, these substances can be found in all environmental compartments including soil, water, and air. Neonicotinoids and fipronil operate by disrupting neural transmission in the central nervous system of invertebrates. Neonicotinoids mimic the action of neurotransmitters, while fipronil inhibits neuronal receptors. In doing so, they continuously stimulate neurons leading ultimately to death of target invertebrates. Like virtually all insecticides, they can also have lethal and sublethal impacts on non-target organisms, including insect predators and vertebrates. Furthermore, a range of synergistic effects with other stressors have been documented. Here, we review extensively their metabolic pathways, showing how they form both compound-specific and common metabolites which can themselves be toxic. These may result in prolonged toxicity. Considering their wide commercial expansion, mode of action, the systemic properties in plants, persistence and environmental fate, coupled with limited information about the toxicity profiles of these compounds and their metabolites, neonicotinoids and fipronil may entail significant risks to the environment. A global evaluation of the potential collateral effects of their use is therefore timely. The present paper and subsequent chapters in this review of the global literature explore these risks and show a growing body of evidence that persistent, low concentrations of these insecticides pose serious risks of undesirable environmental impacts.
Utrecht University1, University of Florida2, Australian National University3, University of Zurich4, Technical University of Denmark5, Institute of Tropical Medicine Antwerp6, Boston Children's Hospital7, University of Kelaniya8, Université catholique de Louvain9, World Health Organization10, Centers for Disease Control and Prevention11
TL;DR: The Foodborne Disease Burden Epidemiology Reference Group (FERG) reports their first estimates of the incidence, mortality, and disease burden due to 31 foodborne hazards, finding that the global burden of FBD is comparable to those of the major infectious diseases, HIV/AIDS, malaria and tuberculosis.
Abstract: Illness and death from diseases caused by contaminated food are a constant threat to public health and a significant impediment to socio-economic development worldwide. To measure the global and regional burden of foodborne disease (FBD), the World Health Organization (WHO) established the Foodborne Disease Burden Epidemiology Reference Group (FERG), which here reports their first estimates of the incidence, mortality, and disease burden due to 31 foodborne hazards. We find that the global burden of FBD is comparable to those of the major infectious diseases, HIV/AIDS, malaria and tuberculosis. The most frequent causes of foodborne illness were diarrheal disease agents, particularly norovirus and Campylobacter spp. Diarrheal disease agents, especially non-typhoidal Salmonella enterica, were also responsible for the majority of deaths due to FBD. Other major causes of FBD deaths were Salmonella Typhi, Taenia solium and hepatitis A virus. The global burden of FBD caused by the 31 hazards in 2010 was 33 million Disability Adjusted Life Years (DALYs); children under five years old bore 40% of this burden. The 14 subregions, defined on the basis of child and adult mortality, had considerably different burdens of FBD, with the greatest falling on the subregions in Africa, followed by the subregions in South-East Asia and the Eastern Mediterranean D subregion. Some hazards, such as non-typhoidal S. enterica, were important causes of FBD in all regions of the world, whereas others, such as certain parasitic helminths, were highly localised. Thus, the burden of FBD is borne particularly by children under five years old-although they represent only 9% of the global population-and people living in low-income regions of the world. These estimates are conservative, i.e., underestimates rather than overestimates; further studies are needed to address the data gaps and limitations of the study. Nevertheless, all stakeholders can contribute to improvements in food safety throughout the food chain by incorporating these estimates into policy development at national and international levels.
TL;DR: Conditions allowing long-term expansion of adult bile duct-derived bipotent progenitor cells from human liver opens up experimental avenues for disease modeling, toxicology studies, regenerative medicine, and gene therapy.
TL;DR: RaceID, an algorithm for rare cell type identification in complex populations of single cells, is developed and it is demonstrated that this algorithm can resolve cell types represented by only a single cell in a population of randomly sampled organoid cells.
Abstract: Understanding the development and function of an organ requires the characterization of all of its cell types. Traditional methods for visualizing and isolating subpopulations of cells are based on messenger RNA or protein expression of only a few known marker genes. The unequivocal identification of a specific marker gene, however, poses a major challenge, particularly if this cell type is rare. Identifying rare cell types, such as stem cells, short-lived progenitors, cancer stem cells, or circulating tumour cells, is crucial to acquire a better understanding of normal or diseased tissue biology. To address this challenge we first sequenced the transcriptome of hundreds of randomly selected cells from mouse intestinal organoids, cultured self-organizing epithelial structures that contain all cell lineages of the mammalian intestine. Organoid buds, like intestinal crypts, harbour stem cells that continuously differentiate into a variety of cell types, occurring at widely different abundances. Since available computational methods can only resolve more abundant cell types, we developed RaceID, an algorithm for rare cell type identification in complex populations of single cells. We demonstrate that this algorithm can resolve cell types represented by only a single cell in a population of randomly sampled organoid cells. We use this algorithm to identify Reg4 as a novel marker for enteroendocrine cells, a rare population of hormone-producing intestinal cells. Next, we use Reg4 expression to enrich for these rare cells and investigate the heterogeneity within this population. RaceID confirmed the existence of known enteroendocrine lineages, and moreover discovered novel subtypes, which we subsequently validated in vivo. Having validated RaceID we then applied the algorithm to ex vivo-isolated Lgr5-positive stem cells and their direct progeny. We find that Lgr5-positive cells represent a homogenous abundant population of stem cells mixed with a rare population of Lgr5-positive secretory cells. We envision broad applicability of our method for discovering rare cell types and the corresponding marker genes in healthy and diseased organs.
Australian National University1, Technical University of Denmark2, Johns Hopkins University3, Food and Agriculture Organization4, University of Otago5, Ghent University6, Institute of Tropical Medicine Antwerp7, Université catholique de Louvain8, University of Wisconsin-Madison9, Public Health Agency of Canada10, Centers for Disease Control and Prevention11, University of the Witwatersrand12, University of Zurich13, Utrecht University14, University of Florida15
TL;DR: Although it is known that diarrheal diseases are a major burden in children, this first global and regional estimates of the disease burden of the most important foodborne bacterial, protozoal, and viral diseases demonstrated for the first time the importance of contaminated food as a cause.
Abstract: BACKGROUND: Foodborne diseases are important worldwide, resulting in considerable morbidity and mortality. To our knowledge, we present the first global and regional estimates of the disease burden of the most important foodborne bacterial, protozoal, and viral diseases. METHODS AND FINDINGS: We synthesized data on the number of foodborne illnesses, sequelae, deaths, and Disability Adjusted Life Years (DALYs), for all diseases with sufficient data to support global and regional estimates, by age and region. The data sources included varied by pathogen and included systematic reviews, cohort studies, surveillance studies and other burden of disease assessments. We sought relevant data circa 2010, and included sources from 1990-2012. The number of studies per pathogen ranged from as few as 5 studies for bacterial intoxications through to 494 studies for diarrheal pathogens. To estimate mortality for Mycobacterium bovis infections and morbidity and mortality for invasive non-typhoidal Salmonella enterica infections, we excluded cases attributed to HIV infection. We excluded stillbirths in our estimates. We estimate that the 22 diseases included in our study resulted in two billion (95% uncertainty interval [UI] 1.5-2.9 billion) cases, over one million (95% UI 0.89-1.4 million) deaths, and 78.7 million (95% UI 65.0-97.7 million) DALYs in 2010. To estimate the burden due to contaminated food, we then applied proportions of infections that were estimated to be foodborne from a global expert elicitation. Waterborne transmission of disease was not included. We estimate that 29% (95% UI 23-36%) of cases caused by diseases in our study, or 582 million (95% UI 401-922 million), were transmitted by contaminated food, resulting in 25.2 million (95% UI 17.5-37.0 million) DALYs. Norovirus was the leading cause of foodborne illness causing 125 million (95% UI 70-251 million) cases, while Campylobacter spp. caused 96 million (95% UI 52-177 million) foodborne illnesses. Of all foodborne diseases, diarrheal and invasive infections due to non-typhoidal S. enterica infections resulted in the highest burden, causing 4.07 million (95% UI 2.49-6.27 million) DALYs. Regionally, DALYs per 100,000 population were highest in the African region followed by the South East Asian region. Considerable burden of foodborne disease is borne by children less than five years of age. Major limitations of our study include data gaps, particularly in middle- and high-mortality countries, and uncertainty around the proportion of diseases that were foodborne. CONCLUSIONS: Foodborne diseases result in a large disease burden, particularly in children. Although it is known that diarrheal diseases are a major burden in children, we have demonstrated for the first time the importance of contaminated food as a cause. There is a need to focus food safety interventions on preventing foodborne diseases, particularly in low- and middle-income settings.
TL;DR: The authors in this article reviewed the entrepreneurial ecosystem literature and its shortcomings, and provided a novel synthesis including a causal scheme of how the framework and sy... and a causal depth and evidence base is rather limited.
Abstract: Regional policies for entrepreneurship are currently going through a transition from increasing the quantity of entrepreneurship to increasing the quality of entrepreneurship. The next step will be the transition from entrepreneurship policy towards policy for an entrepreneurial economy. The entrepreneurial ecosystem approach has been heralded as a new framework accommodating these transitions. This approach starts with the entrepreneurial actor, but emphasizes the context of productive entrepreneurship. Entrepreneurship is not only the output of the system, entrepreneurs are important players themselves in creating the ecosystem and keeping it healthy. This research briefing reviews the entrepreneurial ecosystem literature and its shortcomings, and provides a novel synthesis. The entrepreneurial ecosystem approach speaks directly to practitioners, but its causal depth and evidence base is rather limited. This article provides a novel synthesis including a causal scheme of how the framework and sy...
Paracelsus Private Medical University of Salzburg1, University of Duisburg-Essen2, Semmelweis University3, University of Turin4, Institut Gustave Roussy5, Brown University6, Pontifical Catholic University of Chile7, University of Barcelona8, Trinity College, Dublin9, Istituto Superiore di Sanità10, Ikerbasque11, Pohang University of Science and Technology12, University of Louisville13, Ghent University Hospital14, La Trobe University15, Harvard University16, National University of Singapore17, Maastricht University18, University of Mainz19, University of Cambridge20, Utrecht University21, Agency for Science, Technology and Research22, University of Gothenburg23, University of Valencia24, University of Freiburg25, Aalborg University26, National Research Council27, Paul Ehrlich Institute28, German Red Cross29, University of Oxford30, Karolinska Institutet31
TL;DR: In this paper, the authors summarize recent developments and the current knowledge of extracellular vesicles (EVs) and discuss safety and regulatory requirements that must be considered for pharmaceutical manufacturing and clinical application.
Abstract: Extracellular vesicles (EVs), such as exosomes and microvesicles, are released by different cell types and participate in physiological and pathophysiological processes. EVs mediate intercellular communication as cell-derived extracellular signalling organelles that transmit specific information from their cell of origin to their target cells. As a result of these properties, EVs of defined cell types may serve as novel tools for various therapeutic approaches, including (a) anti-tumour therapy, (b) pathogen vaccination, (c) immune-modulatory and regenerative therapies and (d) drug delivery. The translation of EVs into clinical therapies requires the categorization of EV-based therapeutics in compliance with existing regulatory frameworks. As the classification defines subsequent requirements for manufacturing, quality control and clinical investigation, it is of major importance to define whether EVs are considered the active drug components or primarily serve as drug delivery vehicles. For an effective and particularly safe translation of EV-based therapies into clinical practice, a high level of cooperation between researchers, clinicians and competent authorities is essential. In this position statement, basic and clinical scientists, as members of the International Society for Extracellular Vesicles (ISEV) and of the European Cooperation in Science and Technology (COST) program of the European Union, namely European Network on Microvesicles and Exosomes in Health and Disease (ME-HaD), summarize recent developments and the current knowledge of EV-based therapies. Aspects of safety and regulatory requirements that must be considered for pharmaceutical manufacturing and clinical application are highlighted. Production and quality control processes are discussed. Strategies to promote the therapeutic application of EVs in future clinical studies are addressed.
TL;DR: The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used, and is best used in conjunction with the TRIPod explanation and elaboration document.
Abstract: Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).
University of Minnesota1, Leipzig University2, University College Dublin3, Centre national de la recherche scientifique4, University of Zurich5, University of Bayreuth6, Iowa State University7, Martin Luther University of Halle-Wittenberg8, University of Jena9, Swansea University10, United States Department of Agriculture11, Utrecht University12, University of Oxford13, University of Greifswald14, Sewanee: The University of the South15, University of Bern16, Technische Universität München17, Yokohama National University18, Columbia University19, University of Western Sydney20, Colorado State University21, University of California, Santa Barbara22, Virginia Tech23, Wageningen University and Research Centre24
TL;DR: Biodiversity mainly stabilizes ecosystem productivity, and productivity-dependent ecosystem services, by increasing resistance to climate events, and restoration of biodiversity to increase it, mainly by changing the resistance of ecosystem productivity toClimate events.
Abstract: It remains unclear whether biodiversity buffers ecosystems against climate extremes, which are becoming increasingly frequent worldwide1. Early results suggested that the ecosystem productivity of diverse grassland plant communities was more resistant, changing less during drought, and more resilient, recovering more quickly after drought, than that of depauperate communities2. However, subsequent experimental tests produced mixed results3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13. Here we use data from 46 experiments that manipulated grassland plant diversity to test whether biodiversity provides resistance during and resilience after climate events. We show that biodiversity increased ecosystem resistance for a broad range of climate events, including wet or dry, moderate or extreme, and brief or prolonged events. Across all studies and climate events, the productivity of low-diversity communities with one or two species changed by approximately 50% during climate events, whereas that of high-diversity communities with 16–32 species was more resistant, changing by only approximately 25%. By a year after each climate event, ecosystem productivity had often fully recovered, or overshot, normal levels of productivity in both high- and low-diversity communities, leading to no detectable dependence of ecosystem resilience on biodiversity. Our results suggest that biodiversity mainly stabilizes ecosystem productivity, and productivity-dependent ecosystem services, by increasing resistance to climate events. Anthropogenic environmental changes that drive biodiversity loss thus seem likely to decrease ecosystem stability14, and restoration of biodiversity to increase it, mainly by changing the resistance of ecosystem productivity to climate events.
TL;DR: There is strong evidence that soils, waterways, and plants in agricultural environments and neighboring areas are contaminated with variable levels of neonicotinoids or fipronil mixtures and their metabolites, and this provides multiple routes for chronic exposure of nontarget animals.
Abstract: Systemic insecticides are applied to plants using a wide variety of methods, ranging from foliar sprays to seed treatments and soil drenches. Neonicotinoids and fipronil are among the most widely used pesticides in the world. Their popularity is largely due to their high toxicity to invertebrates, the ease and flexibility with which they can be applied, their long persistence, and their systemic nature, which ensures that they spread to all parts of the target crop. However, these properties also increase the probability of environmental contamination and exposure of nontarget organisms. Environmental contamination occurs via a number of routes including dust generated during drilling of dressed seeds, contamination and accumulation in arable soils and soil water, runoff into waterways, and uptake of pesticides by nontarget plants via their roots or dust deposition on leaves. Persistence in soils, waterways, and nontarget plants is variable but can be prolonged; for example, the half-lives of neonicotinoids in soils can exceed 1,000 days, so they can accumulate when used repeatedly. Similarly, they can persist in woody plants for periods exceeding 1 year. Breakdown results in toxic metabolites, though concentrations of these in the environment are rarely measured. Overall, there is strong evidence that soils, waterways, and plants in agricultural environments and neighboring areas are contaminated with variable levels of neonicotinoids or fipronil mixtures and their metabolites (soil, parts per billion (ppb)-parts per million (ppm) range; water, parts per trillion (ppt)-ppb range; and plants, ppb-ppm range). This provides multiple routes for chronic (and acute in some cases) exposure of nontarget animals. For example, pollinators are exposed through direct contact with dust during drilling; consumption of pollen, nectar, or guttation drops from seed-treated crops, water, and consumption of contaminated pollen and nectar from wild flowers and trees growing near-treated crops. Studies of food stores in honeybee colonies from across the globe demonstrate that colonies are routinely and chronically exposed to neonicotinoids, fipronil, and their metabolites (generally in the 1–100 ppb range), mixed with other pesticides some of which are known to act synergistically with neonicotinoids. Other nontarget organisms, particularly those inhabiting soils, aquatic habitats, or herbivorous insects feeding on noncrop plants in farmland, will also inevitably receive exposure, although data are generally lacking for these groups. We summarize the current state of knowledge regarding the environmental fate of these compounds by outlining what is known about the chemical properties of these compounds, and placing these properties in the context of modern agricultural practices.