Showing papers by "Ghent University published in 2019"
TL;DR: In this paper, the burden of infections caused by antibiotic-resistant bacteria of public health concern in countries of the EU and European Economic Area (EEA) in 2015, measured in number of cases, attributable deaths, and disability-adjusted life-years (DALYs).
Abstract: Summary Background Infections due to antibiotic-resistant bacteria are threatening modern health care. However, estimating their incidence, complications, and attributable mortality is challenging. We aimed to estimate the burden of infections caused by antibiotic-resistant bacteria of public health concern in countries of the EU and European Economic Area (EEA) in 2015, measured in number of cases, attributable deaths, and disability-adjusted life-years (DALYs). Methods We estimated the incidence of infections with 16 antibiotic resistance–bacterium combinations from European Antimicrobial Resistance Surveillance Network (EARS-Net) 2015 data that was country-corrected for population coverage. We multiplied the number of bloodstream infections (BSIs) by a conversion factor derived from the European Centre for Disease Prevention and Control point prevalence survey of health-care-associated infections in European acute care hospitals in 2011–12 to estimate the number of non-BSIs. We developed disease outcome models for five types of infection on the basis of systematic reviews of the literature. Findings From EARS-Net data collected between Jan 1, 2015, and Dec 31, 2015, we estimated 671 689 (95% uncertainty interval [UI] 583 148–763 966) infections with antibiotic-resistant bacteria, of which 63·5% (426 277 of 671 689) were associated with health care. These infections accounted for an estimated 33 110 (28 480–38 430) attributable deaths and 874 541 (768 837–989 068) DALYs. The burden for the EU and EEA was highest in infants (aged Interpretation Our results present the health burden of five types of infection with antibiotic-resistant bacteria expressed, for the first time, in DALYs. The estimated burden of infections with antibiotic-resistant bacteria in the EU and EEA is substantial compared with that of other infectious diseases, and has increased since 2007. Our burden estimates provide useful information for public health decision-makers prioritising interventions for infectious diseases. Funding European Centre for Disease Prevention and Control.
1,746 citations
TL;DR: The identification of FDA-approved drugs as ferroptosis inducers creates high expectations for the potential of ferroPTosis to be a new promising way to kill therapy-resistant cancers.
1,106 citations
TL;DR: The in-depth comprehension of each of these lethal subroutines and their intercellular consequences may uncover novel therapeutic targets for the avoidance of pathogenic cell loss.
Abstract: Cells may die from accidental cell death (ACD) or regulated cell death (RCD). ACD is a biologically uncontrolled process, whereas RCD involves tightly structured signaling cascades and molecularly defined effector mechanisms. A growing number of novel non-apoptotic forms of RCD have been identified and are increasingly being implicated in various human pathologies. Here, we critically review the current state of the art regarding non-apoptotic types of RCD, including necroptosis, pyroptosis, ferroptosis, entotic cell death, netotic cell death, parthanatos, lysosome-dependent cell death, autophagy-dependent cell death, alkaliptosis and oxeiptosis. The in-depth comprehension of each of these lethal subroutines and their intercellular consequences may uncover novel therapeutic targets for the avoidance of pathogenic cell loss.
1,071 citations
TL;DR: The authors comprehensively benchmark the accuracy, scalability, stability and usability of 45 single-cell trajectory inference methods and develop a set of guidelines to help users select the best method for their dataset.
Abstract: Trajectory inference approaches analyze genome-wide omics data from thousands of single cells and computationally infer the order of these cells along developmental trajectories. Although more than 70 trajectory inference tools have already been developed, it is challenging to compare their performance because the input they require and output models they produce vary substantially. Here, we benchmark 45 of these methods on 110 real and 229 synthetic datasets for cellular ordering, topology, scalability and usability. Our results highlight the complementarity of existing tools, and that the choice of method should depend mostly on the dataset dimensions and trajectory topology. Based on these results, we develop a set of guidelines to help users select the best method for their dataset. Our freely available data and evaluation pipeline ( https://benchmark.dynverse.org ) will aid in the development of improved tools designed to analyze increasingly large and complex single-cell datasets.
928 citations
TL;DR: Insight is provided into the endogenous immune system of the central nervous system during development, homeostasis and disease, and may also provide new targets for the treatment of neurodegenerative and neuroinflammatory pathologies.
Abstract: Microglia have critical roles not only in neural development and homeostasis, but also in neurodegenerative and neuroinflammatory diseases of the central nervous system1-4. These highly diverse and specialized functions may be executed by subsets of microglia that already exist in situ, or by specific subsets of microglia that develop from a homogeneous pool of cells on demand. However, little is known about the presence of spatially and temporally restricted subclasses of microglia in the central nervous system during development or disease. Here we combine massively parallel single-cell analysis, single-molecule fluorescence in situ hybridization, advanced immunohistochemistry and computational modelling to comprehensively characterize subclasses of microglia in multiple regions of the central nervous system during development and disease. Single-cell analysis of tissues of the central nervous system during homeostasis in mice revealed specific time- and region-dependent subtypes of microglia. Demyelinating and neurodegenerative diseases evoked context-dependent subtypes of microglia with distinct molecular hallmarks and diverse cellular kinetics. Corresponding clusters of microglia were also identified in healthy human brains, and the brains of patients with multiple sclerosis. Our data provide insights into the endogenous immune system of the central nervous system during development, homeostasis and disease, and may also provide new targets for the treatment of neurodegenerative and neuroinflammatory pathologies.
755 citations
TL;DR: These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community providing the theory and key practical aspects offlow cytometry enabling immunologists to avoid the common errors that often undermine immunological data.
Abstract: These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer-reviewed by leading experts in the field, making this an essential research companion.
698 citations
Australian National University1, University of Melbourne2, Ghent University3, Pontifical Catholic University of Chile4, University of Pamplona5, University of Puerto Rico6, State University of Campinas7, Florida International University8, Spanish National Research Council9, Imperial College London10, University of Los Andes11, Alexander von Humboldt Biological Resources Research Institute12, Zoological Society of London13, North-West University14, Smithsonian Institution15, Colorado State University16, Universidad San Francisco de Quito17, Museum für Naturkunde18, Massey University19, University of Maryland, College Park20, University of Florida21, University of the Republic22, Cornell University23, Georgia Institute of Technology24, National Autonomous University of Mexico25, University of Pittsburgh26, Instituto Politécnico Nacional27, Andrés Bello National University28, University of Nevada, Reno29, Zoo Miami30, Natural History Museum31
TL;DR: A global, quantitative assessment of the amphibian chytridiomycosis panzootic demonstrates its role in the decline of at least 501 amphibian species over the past half-century and represents the greatest recorded loss of biodiversity attributable to a disease.
Abstract: Anthropogenic trade and development have broken down dispersal barriers, facilitating the spread of diseases that threaten Earth's biodiversity. We present a global, quantitative assessment of the amphibian chytridiomycosis panzootic, one of the most impactful examples of disease spread, and demonstrate its role in the decline of at least 501 amphibian species over the past half-century, including 90 presumed extinctions. The effects of chytridiomycosis have been greatest in large-bodied, range-restricted anurans in wet climates in the Americas and Australia. Declines peaked in the 1980s, and only 12% of declined species show signs of recovery, whereas 39% are experiencing ongoing decline. There is risk of further chytridiomycosis outbreaks in new areas. The chytridiomycosis panzootic represents the greatest recorded loss of biodiversity attributable to a disease.
680 citations
Karolinska Institutet1, Ghent University2, Eastern Virginia Medical School3, Université de Montréal4, Katholieke Universiteit Leuven5, Regeneron6, University of Pittsburgh7, University of Barcelona8, University of Pennsylvania9, Brigham and Women's Hospital10, Royal Brisbane and Women's Hospital11, St Thomas' Hospital12, Charité13, Humanitas University14, University of Pisa15, University of South Florida16, University of Amsterdam17, University of Fukui18
TL;DR: Dupilumab significantly improved the coprimary endpoints in both studies and was added to standard of care in adults with severe CRSwNP despite previous treatment with systemic corticosteroids, surgery, or both.
676 citations
TL;DR: An overview of the known mechanisms that regulate sensitivity to ferroptosis in cancer cells and how the modulation of metabolic pathways controlling ferroPTosis might reshape the tumour niche, leading to an immunosuppressive microenvironment that promotes tumour growth and progression is provided.
Abstract: Ferroptosis is a recently recognized cell death modality that is morphologically, biochemically and genetically distinct from other forms of cell death and that has emerged to play an important role in cancer biology. Recent discoveries have highlighted the metabolic plasticity of cancer cells and have provided intriguing insights into how metabolic rewiring is a critical event for the persistence, dedifferentiation and expansion of cancer cells. In some cases, this metabolic reprogramming has been linked to an acquired sensitivity to ferroptosis, thus opening up new opportunities to treat therapy-insensitive tumours. However, it is not yet clear what metabolic determinants are critical for therapeutic resistance and evasion of immune surveillance. Therefore, a better understanding of the processes that regulate ferroptosis sensitivity should ultimately aid in the discovery of novel therapeutic strategies to improve cancer treatment. In this Perspectives article, we provide an overview of the known mechanisms that regulate sensitivity to ferroptosis in cancer cells and how the modulation of metabolic pathways controlling ferroptosis might reshape the tumour niche, leading to an immunosuppressive microenvironment that promotes tumour growth and progression.
625 citations
Ghent University1, University of California, San Diego2, Leiden University3, Dresden University of Technology4, Stanford University5, University of Maryland, College Park6, Indiana University7, University of Cambridge8, Cardiff University9, University of Western Ontario10, Monash University, Clayton campus11, University of Toronto12, University of Vermont13, University of Oregon14, University of Tasmania15, University of Oslo16, Utrecht University17, Katholieke Universiteit Leuven18, Yale University19, Vanderbilt University20, University of Amsterdam21, Anglia Ruskin University22, Indian Institute of Science23, Queen's University24, King's College London25, Michigan State University26, University of Iowa27, Trinity College, Dublin28
TL;DR: The goal is to facilitate a more accurate use of the stop-signal task and provide user-friendly open-source resources intended to inform statistical-power considerations, facilitate the correct implementation of the task, and assist in proper data analysis.
Abstract: Response inhibition is essential for navigating everyday life. Its derailment is considered integral to numerous neurological and psychiatric disorders, and more generally, to a wide range of behavioral and health problems. Response-inhibition efficiency furthermore correlates with treatment outcome in some of these conditions. The stop-signal task is an essential tool to determine how quickly response inhibition is implemented. Despite its apparent simplicity, there are many features (ranging from task design to data analysis) that vary across studies in ways that can easily compromise the validity of the obtained results. Our goal is to facilitate a more accurate use of the stop-signal task. To this end, we provide 12 easy-to-implement consensus recommendations and point out the problems that can arise when they are not followed. Furthermore, we provide user-friendly open-source resources intended to inform statistical-power considerations, facilitate the correct implementation of the task, and assist in proper data analysis.
617 citations
TL;DR: Current understanding of caspase biology is reviewed with a prime focus on the inflammatory caspases and important topics for future experimentation are outlined.
TL;DR: The results provide a framework for understanding host–macrophage interactions in both the healthy and diseased brain and identify IRF8 as a master regulator that drives the maturation and diversity of brain macrophages.
Abstract: While the roles of parenchymal microglia in brain homeostasis and disease are fairly clear, other brain-resident myeloid cells remain less well understood. By dissecting border regions and combining single-cell RNA-sequencing with high-dimensional cytometry, bulk RNA-sequencing, fate-mapping and microscopy, we reveal the diversity of non-parenchymal brain macrophages. Border-associated macrophages (BAMs) residing in the dura mater, subdural meninges and choroid plexus consisted of distinct subsets with tissue-specific transcriptional signatures, and their cellular composition changed during postnatal development. BAMs exhibited a mixed ontogeny, and subsets displayed distinct self-renewal capacity following depletion and repopulation. Single-cell and fate-mapping analysis both suggested that there is a unique microglial subset residing on the apical surface of the choroid plexus epithelium. Finally, gene network analysis and conditional deletion revealed IRF8 as a master regulator that drives the maturation and diversity of brain macrophages. Our results provide a framework for understanding host-macrophage interactions in both the healthy and diseased brain.
TL;DR: A classification framework to understand what indicators measure is proposed and none of the analysed indicators focuses on the preservation of functions.
Abstract: Circular Economy (CE) is a growing topic, especially in the European Union, that promotes the responsible and cyclical use of resources possibly contributing to sustainable development. CE is an umbrella concept incorporating different meanings. Despite the unclear concept, CE is turned into defined action plans supported by specific indicators. To understand what indicators used in CE measure specifically, we propose a classification framework to categorise indicators according to reasoning on what (CE strategies) and how (measurement scope). Despite different types, CE strategies can be grouped according to their attempt to preserve functions, products, components, materials, or embodied energy; additionally, indicators can measure the linear economy as a reference scenario. The measurement scope shows how indicators account for technological cycles with or without a Life Cycle Thinking (LCT) approach; or their effects on environmental, social, or economic dimensions. To illustrate the classification framework, we selected quantitative micro scale indicators from literature and macro scale indicators from the European Union 'CE monitoring framework'. The framework illustration shows that most of the indicators focus on the preservation of materials, with strategies such as recycling. However, micro scale indicators can also focus on other CE strategies considering LCT approach, while the European indicators mostly account for materials often without taking LCT into account. Furthermore, none of the available indicators can assess the preservation of functions instead of products, with strategies such as sharing platforms, schemes for product redundancy, or multifunctionality. Finally, the framework illustration suggests that a set of indicators should be used to assess CE instead of a single indicator.
European Society of Cardiology1, National Institutes of Health2, Ghent University3, Karolinska Institutet4, University Medical Center Utrecht5, University of Lausanne6, Vilnius University7, Charles University in Prague8, Hospital Universitario La Paz9, National University of Ireland, Galway10, Kazakh National Medical University11, Erasmus University Rotterdam12, University of Sarajevo13, Shupyk National Medical Academy of Postgraduate Education14, University of Latvia15, University of Ljubljana16, Ljubljana University Medical Centre17, University of Würzburg18, Assiut University19, Jagiellonian University Medical College20, University Hospital Centre Zagreb21, Kyrgyz State Medical Academy22, University of Zagreb23, Hacettepe University24, National and Kapodistrian University of Athens25, University of Banja Luka26
TL;DR: A large majority of coronary patients have unhealthy lifestyles in terms of smoking, diet and sedentary behaviour, which adversely impacts major cardiovascular risk factors, and a majority did not achieve their blood pressure, low-density lipoprotein cholesterol and glucose targets.
Abstract: AimsThe aim of this study was to determine whether the Joint European Societies guidelines on secondary cardiovascular prevention are followed in everyday practice.DesignA cross-sectional ESC-EORP ...
TL;DR: The cytokine networks driving asthma are reviewed, placing these in cellular context and incorporating insights from cytokine-targeting therapies in the clinic, to argue that the development of new and improved therapeutics will require understanding the diverse mechanisms underlying the spectrum of asthma pathologies.
TL;DR: It is shown that the expression of enzymatically inactive CASP8(C362S) causes embryonic lethality in mice by inducing necroptosis and pyroptosis, and prevents tissue damage during embryonic development and adulthood in mice.
Abstract: Caspase-8 is the initiator caspase of extrinsic apoptosis(1,2) and inhibits necroptosis mediated by RIPK3 and MLKL. Accordingly, caspase-8 deficiency in mice causes embryonic lethality(3), which can be rescued by deletion of either Ripk3 or Mlkl(4-6). Here we show that the expression of enzymatically inactive CASP8(C362S) causes embryonic lethality in mice by inducing necroptosis and pyroptosis. Similar to Casp8(-/-) mice(3,7), Casp8(C362S/C362S) mouse embryos died after endothelial cell necroptosis leading to cardiovascular defects. MLKL deficiency rescued the cardiovascular phenotype but unexpectedly caused perinatal lethality in Casp8(C362S/C362S) mice, indicating that CASP8(C362S) causes necroptosis-independent death at later stages of embryonic development. Specific loss of the catalytic activity of caspase-8 in intestinal epithelial cells induced intestinal inflammation similar to intestinal epithelial cell-specific Casp8 knockout mice(8). Inhibition of necroptosis by additional deletion of Mlkl severely aggravated intestinal inflammation and caused premature lethality in Mlkl knockout mice with specific loss of caspase-8 catalytic activity in intestinal epithelial cells. Expression of CASP8(C362S) triggered the formation of ASC specks, activation of caspase-1 and secretion of IL-1 beta. Both embryonic lethality and premature death were completely rescued in Casp8(C362S/C362S)Mlkl(-/-)Asc(-/-) or Casp8(C362S/C362S)Mlkl(-/-)Casp1(-/-) mice, indicating that the activation of the inflammasome promotes CASP8(C362S)-mediated tissue pathology when necroptosis is blocked. Therefore, caspase-8 represents the molecular switch that controls apoptosis, necroptosis and pyroptosis, and prevents tissue damage during embryonic development and adulthood.
TL;DR: In this paper, the use of methanol as a pure fuel or a blend component for internal combustion engines (ICEs) is discussed, highlighting the differences with fuels such as ethanol and gasoline.
TL;DR: The Multi-Source Weighted Ensemble Precipitation (MSWEP) dataset as discussed by the authors is a gridded precipitation P dataset spanning 1979-2017, which is unique in several aspects: i) full global co...
Abstract: We present Multi-Source Weighted-Ensemble Precipitation, version 2 (MSWEP V2), a gridded precipitation P dataset spanning 1979–2017. MSWEP V2 is unique in several aspects: i) full global co...
TL;DR: Combined measurements of the production and decay rates of the Higgs boson, as well as its couplings to vector bosons and fermions, are presented and constraints are placed on various two Higgs doublet models.
Abstract: Combined measurements of the production and decay rates of the Higgs boson, as well as its couplings to vector bosons and fermions, are presented. The analysis uses the LHC proton–proton collision data set recorded with the CMS detector in 2016 at $\sqrt{s}=13\,\text {Te}\text {V} $ , corresponding to an integrated luminosity of 35.9 ${\,\text {fb}^{-1}} $ . The combination is based on analyses targeting the five main Higgs boson production mechanisms (gluon fusion, vector boson fusion, and associated production with a $\mathrm {W}$ or $\mathrm {Z}$ boson, or a top quark-antiquark pair) and the following decay modes: $\mathrm {H} \rightarrow \gamma \gamma $ , $\mathrm {Z}\mathrm {Z}$ , $\mathrm {W}\mathrm {W}$ , $\mathrm {\tau }\mathrm {\tau }$ , $\mathrm {b} \mathrm {b} $ , and $\mathrm {\mu }\mathrm {\mu }$ . Searches for invisible Higgs boson decays are also considered. The best-fit ratio of the signal yield to the standard model expectation is measured to be $\mu =1.17\pm 0.10$ , assuming a Higgs boson mass of $125.09\,\text {Ge}\text {V} $ . Additional results are given for various assumptions on the scaling behavior of the production and decay modes, including generic parametrizations based on ratios of cross sections and branching fractions or couplings. The results are compatible with the standard model predictions in all parametrizations considered. In addition, constraints are placed on various two Higgs doublet models.
TL;DR: In this review, an overview is given of recent developments of stimuli-responsive bio-based polymeric systems, and several emerging applications of these systems including intelligent drug delivery, responsive food packaging and smart water treatment are discussed.
Abstract: Stimuli-responsive bio-based polymeric systems are gaining considerable attention as intelligent versatile tools that show great potential in various fields. In this review, an overview is given of recent developments of stimuli-responsive bio-based polymeric systems. The characteristics of bio-based polymers in different applications are discussed and the superiority of these advanced stimuli-responsive bio-based polymeric systems is highlighted. Furthermore, several emerging applications of these systems including intelligent drug delivery, responsive food packaging and smart water treatment are discussed and the section of intelligent drug delivery is emphasized in detail. Finally, the respective prospects and limitations inherent to these systems are addressed.
TL;DR: An overview of key physiologic and biophysical principles related to arterial stiffness, the impact of aortic stiffening on target organs, noninvasive methods for the measurement of arterials stiffness, mechanisms leading to aorti stiffening, therapeutic approaches to reduce it, and clinical applications of arterial stiffening measurements is provided.
TL;DR: The progress of remote sensing with UAVs in drought stress, in weed and pathogen detection, in nutrient status and growth vigor assessment, and in yield prediction is reviewed.
TL;DR: An optimal intake of whole grains, vegetables, fruits, nuts, legumes, dairy, fish, red and processed meat, eggs and SSB showed an important lower risk of CHD, stroke, and HF.
Abstract: Background Despite growing evidence for food-based dietary patterns' potential to reduce cardiovascular disease risk, knowledge about the amounts of food associated with the greatest change in risk of specific cardiovascular outcomes and about the quality of meta-evidence is limited. Therefore, the aim of this meta-analysis was to synthesize the knowledge about the relation between intake of 12 major food groups (whole grains, refined grains, vegetables, fruits, nuts, legumes, eggs, dairy, fish, red meat, processed meat, and sugar-sweetened beverages [SSB]) and the risk of coronary heart disease (CHD), stroke and heart failure (HF). Methods We conducted a systematic search in PubMed and Embase up to March 2017 for prospective studies. Summary risk ratios (RRs) and 95% confidence intervals (95% CI) were estimated using a random effects model for highest versus lowest intake categories, as well as for linear and non-linear relationships. Results Overall, 123 reports were included in the meta-analyses. An inverse association was present for whole grains (RRCHD: 0.95 (95% CI: 0.92-0.98), RRHF: 0.96 (0.95-0.97)), vegetables and fruits (RRCHD: 0.97 (0.96-0.99), and 0.94 (0.90-0.97); RRstroke: 0.92 (0.86-0.98), and 0.90 (0.84-0.97)), nuts (RRCHD: 0.67 (0.43-1.05)), and fish consumption (RRCHD: 0.88 (0.79-0.99), RRstroke: 0.86 (0.75-0.99), and RRHF: 0.80 (0.67-0.95)), while a positive association was present for egg (RRHF: 1.16 (1.03-1.31)), red meat (RRCHD: 1.15 (1.08-1.23), RRstroke: 1.12 (1.06-1.17), RRHF: 1.08 (1.02-1.14)), processed meat (RRCHD: 1.27 (1.09-1.49), RRstroke: 1.17 (1.02-1.34), RRHF: 1.12 (1.05-1.19)), and SSB consumption (RRCHD: 1.17 (1.11-1.23), RRstroke: 1.07 (1.02-1.12), RRHF: 1.08 (1.05-1.12)) in the linear dose-response meta-analysis. There were clear indications for non-linear dose-response relationships between whole grains, fruits, nuts, dairy, and red meat and CHD. Conclusion An optimal intake of whole grains, vegetables, fruits, nuts, legumes, dairy, fish, red and processed meat, eggs and SSB showed an important lower risk of CHD, stroke, and HF.
TL;DR: This paper provides an introduction to the topic of uncertainty in machine learning as well as an overview of attempts so far at handling uncertainty in general and formalizing this distinction in particular.
Abstract: The notion of uncertainty is of major importance in machine learning and constitutes a key element of machine learning methodology. In line with the statistical tradition, uncertainty has long been perceived as almost synonymous with standard probability and probabilistic predictions. Yet, due to the steadily increasing relevance of machine learning for practical applications and related issues such as safety requirements, new problems and challenges have recently been identified by machine learning scholars, and these problems may call for new methodological developments. In particular, this includes the importance of distinguishing between (at least) two different types of uncertainty, often referred to as aleatoric and epistemic. In this paper, we provide an introduction to the topic of uncertainty in machine learning as well as an overview of attempts so far at handling uncertainty in general and formalizing this distinction in particular.
TL;DR: Examining lignins in different species reveals the extent to which evolution and natural variation have resulted in the incorporation of 'non-traditional' phenolic monomers, including phenolics from beyond the monolignol biosynthetic pathway.
TL;DR: Vesiclepedia is a web-based compendium of RNA, proteins, lipids and metabolites that are identified in EVs from both published and unpublished studies aiding biomedical scientists in assessing the quality of the EV preparation and the corresponding data obtained.
Abstract: Extracellular vesicles (EVs) are membranous vesicles that are released by both prokaryotic and eukaryotic cells into the extracellular microenvironment. EVs can be categorised as exosomes, ectosomes or shedding microvesicles and apoptotic bodies based on the mode of biogenesis. EVs contain biologically active cargo of nucleic acids, proteins, lipids and metabolites that can be altered based on the precise state of the cell. Vesiclepedia (http://www.microvesicles.org) is a web-based compendium of RNA, proteins, lipids and metabolites that are identified in EVs from both published and unpublished studies. Currently, Vesiclepedia contains data obtained from 1254 EV studies, 38 146 RNA entries, 349 988 protein entries and 639 lipid/metabolite entries. Vesiclepedia is publicly available and allows users to query and download EV cargo based on different search criteria. The mode of EV isolation and characterization, the biophysical and molecular properties and EV-METRIC are listed in the database aiding biomedical scientists in assessing the quality of the EV preparation and the corresponding data obtained. In addition, FunRich-based Vesiclepedia plugin is incorporated aiding users in data analysis.
TL;DR: This critical review discusses in detail the synthesis, characterization, computational work and applications of mixed-metal MOFs.
Abstract: Mixed-metal MOFs are metal–organic frameworks that contain at least 2 different metal ions as nodes of their frameworks. They are prepared relatively easily by either a one-pot synthesis with a synthesis mixture containing the different metals, or by a post-synthetic ion-exchange method by soaking a monometallic MOF in a concentrated solution of a different (but compatible) metal-ion. More difficult is the accurate characterization of these materials. Is the formed product a mixture of monometallic MOFs or indeed a MOF with different metallic nodes? Are the metals randomly distributed or do they form domains? What is the oxidation state of the metals? How do the metals mutually influence each other, and impact the material's performance? Advanced characterization techniques are required e.g. X-ray absorption spectroscopy, magnetic resonance and electron microscopy. Computational tools at multiple scales are also often applied. In almost every case, a judicious choice of several techniques is required to unambiguously characterize the mixed-metal MOF. Although still in their infancy, several applications are emerging for mixed-metal MOFs, that improve on conventional monometallic MOFs. In the field of gas sorption and storage, especially the stability and affinity towards the target gases can be largely improved by introducing a second metal ion. In the case of flexible MOFs, the breathing behavior, and in particular the pressure at which the MOF opens, can be tailored. In heterogeneous catalysis, new cascade and tandem reactions become possible, with particular focus on reactions where the two metals in close proximity truly form a mixed-metal transition state. The bimetallic MOF should have a clear benefit over a mixture of the respective monometallic MOFs, and bimetallic enzymes can be a huge source of inspiration in this field. Another very promising application lies in the fields of luminescence and sensing. By tuning the lanthanide metals in mixed-metal lanthanide MOFs and by using the organic linkers as antennae, novel smart materials can be developed, acting as sensors and as thermochromic thermometers. Of course there are also still open challenges, as also mixed-metal MOFs do not escape the typical drawbacks of MOFs, such as low stability in moisture and possible metal leaching in liquids. The ease of synthesis of mixed-metal MOFs is a large bonus. In this critical review, we discuss in detail the synthesis, characterization, computational work and applications of mixed-metal MOFs.
Centre national de la recherche scientifique1, IFREMER2, ETH Zurich3, University of Bern4, Cardiff University5, Université Paris-Saclay6, University of Bordeaux7, Federal Fluminense University8, Leibniz Institute for Baltic Sea Research9, University of St Andrews10, University of New Hampshire11, Oregon State University12, École pratique des hautes études13, Royal Holloway, University of London14, University of Nantes15, Hofstra University16, Lamont–Doherty Earth Observatory17, Uppsala University18, Woods Hole Oceanographic Institution19, University of Edinburgh20, Geological Survey of Denmark and Greenland21, Instituto Geológico y Minero de España22, University of Connecticut23, Georgia Institute of Technology24, University of Colorado Boulder25, University of the Algarve26, British Antarctic Survey27, VU University Amsterdam28, University of Bremen29, Max Planck Society30, Thermo Fisher Scientific31, University of Cambridge32, University of Paris33, University College London34, Ghent University35, Aix-Marseille University36, Autonomous University of Barcelona37, University of California, Santa Barbara38, Utrecht University39
TL;DR: This is the first set of consistently dated marine sediment cores enabling paleoclimate scientists to evaluate leads/lags between circulation and climate changes over vast regions of the Atlantic Ocean.
Abstract: Rapid changes in ocean circulation and climate have been observed in marine-sediment and ice cores over the last glacial period and deglaciation, highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing. To date, these rapid changes in climate and ocean circulation are still not fully explained. One obstacle hindering progress in our understanding of the interactions between past ocean circulation and climate changes is the difficulty of accurately dating marine cores. Here, we present a set of 92 marine sediment cores from the Atlantic Ocean for which we have established age-depth models that are consistent with the Greenland GICC05 ice core chronology, and computed the associated dating uncertainties, using a new deposition modeling technique. This is the first set of consistently dated marine sediment cores enabling paleoclimate scientists to evaluate leads/lags between circulation and climate changes over vast regions of the Atlantic Ocean. Moreover, this data set is of direct use in paleoclimate modeling studies.
TL;DR: The goal of the perspective is not to present a convincing answer to these questions, but to assess the scientific progress to date, while highlighting new and innovative avenues to keep advancing the understanding in the future.
Abstract: Droughts and heatwaves cause agricultural loss, forest mortality, and drinking water scarcity, especially when they occur simultaneously as combined events. Their predicted increase in recurrence and intensity poses serious threats to future food security. Still today, the knowledge of how droughts and heatwaves start and evolve remains limited, and so does our understanding of how climate change may affect them. Droughts and heatwaves have been suggested to intensify and propagate via land-atmosphere feedbacks. However, a global capacity to observe these processes is still lacking, and climate and forecast models are immature when it comes to representing the influences of land on temperature and rainfall. Key open questions remain in our goal to uncover the real importance of these feedbacks: What is the impact of the extreme meteorological conditions on ecosystem evaporation? How do these anomalies regulate the atmospheric boundary layer state (event self-intensification) and contribute to the inflow of heat and moisture to other regions (event self-propagation)? Can this knowledge on the role of land feedbacks, when available, be exploited to develop geo-engineering mitigation strategies that prevent these events from aggravating during their early stages? The goal of our perspective is not to present a convincing answer to these questions, but to assess the scientific progress to date, while highlighting new and innovative avenues to keep advancing our understanding in the future.
TL;DR: A specialized metabolic network expressed in the roots of A. thaliana that consists of functionally divergent triterpene biosynthetic gene clusters connected by scattered genes outside the clusters that encode promiscuous acyltransferases and alcohol dehydrogenases is elucidated.
Abstract: Plant specialized metabolites have ecological functions, yet the presence of numerous uncharacterized biosynthetic genes in plant genomes suggests that many molecules remain unknown. We discovered a triterpene biosynthetic network in the roots of the small mustard plant Arabidopsis thaliana. Collectively, we have elucidated and reconstituted three divergent pathways for the biosynthesis of root triterpenes, namely thalianin (seven steps), thalianyl medium-chain fatty acid esters (three steps), and arabidin (five steps). A. thaliana mutants disrupted in the biosynthesis of these compounds have altered root microbiota. In vitro bioassays with purified compounds reveal selective growth modulation activities of pathway metabolites toward root microbiota members and their biochemical transformation and utilization by bacteria, supporting a role for this biosynthetic network in shaping an Arabidopsis-specific root microbial community.