Showing papers by "Norwegian University of Science and Technology published in 2019"

The Gene Ontology Resource: 20 years and still GOing strong

Abstract: The Gene Ontology resource (GO; http://geneontology.org) provides structured, computable knowledge regarding the functions of genes and gene products. Founded in 1998, GO has become widely adopted in the life sciences, and its contents are under continual improvement, both in quantity and in quality. Here, we report the major developments of the GO resource during the past two years. Each monthly release of the GO resource is now packaged and given a unique identifier (DOI), enabling GO-based analyses on a specific release to be reproduced in the future. The molecular function ontology has been refactored to better represent the overall activities of gene products, with a focus on transcription regulator activities. Quality assurance efforts have been ramped up to address potentially out-of-date or inaccurate annotations. New evidence codes for high-throughput experiments now enable users to filter out annotations obtained from these sources. GO-CAM, a new framework for representing gene function that is more expressive than standard GO annotations, has been released, and users can now explore the growing repository of these models. We also provide the ‘GO ribbon’ widget for visualizing GO annotations to a gene; the widget can be easily embedded in any web page.

Contrasting Computational Models of Mate Preference Integration Across 45 Countries

Abstract: Humans express a wide array of ideal mate preferences. Around the world, people desire romantic partners who are intelligent, healthy, kind, physically attractive, wealthy, and more. In order for these ideal preferences to guide the choice of actual romantic partners, human mating psychology must possess a means to integrate information across these many preference dimensions into summaries of the overall mate value of their potential mates. Here we explore the computational design of this mate preference integration process using a large sample of n = 14,487 people from 45 countries around the world. We combine this large cross-cultural sample with agent-based models to compare eight hypothesized models of human mating markets. Across cultures, people higher in mate value appear to experience greater power of choice on the mating market in that they set higher ideal standards, better fulfill their preferences in choice, and pair with higher mate value partners. Furthermore, we find that this cross-culturally universal pattern of mate choice is most consistent with a Euclidean model of mate preference integration.

Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk.

Abstract: Alzheimer's disease (AD) is highly heritable and recent studies have identified over 20 disease-associated genomic loci. Yet these only explain a small proportion of the genetic variance, indicating that undiscovered loci remain. Here, we performed a large genome-wide association study of clinically diagnosed AD and AD-by-proxy (71,880 cases, 383,378 controls). AD-by-proxy, based on parental diagnoses, showed strong genetic correlation with AD (rg = 0.81). Meta-analysis identified 29 risk loci, implicating 215 potential causative genes. Associated genes are strongly expressed in immune-related tissues and cell types (spleen, liver, and microglia). Gene-set analyses indicate biological mechanisms involved in lipid-related processes and degradation of amyloid precursor proteins. We show strong genetic correlations with multiple health-related outcomes, and Mendelian randomization results suggest a protective effect of cognitive ability on AD risk. These results are a step forward in identifying the genetic factors that contribute to AD risk and add novel insights into the neurobiology of AD.

Are We Speaking the Same Language? Recommendations for a Definition and Categorization Framework for Plastic Debris.

Abstract: The accumulation of plastic litter in natural environments is a global issue. Concerns over potential negative impacts on the economy, wildlife, and human health provide strong incentives for improving the sustainable use of plastics. Despite the many voices raised on the issue, we lack a consensus on how to define and categorize plastic debris. This is evident for microplastics, where inconsistent size classes are used and where the materials to be included are under debate. While this is inherent in an emerging research field, an ambiguous terminology results in confusion and miscommunication that may compromise progress in research and mitigation measures. Therefore, we need to be explicit on what exactly we consider plastic debris. Thus, we critically discuss the advantages and disadvantages of a unified terminology, propose a definition and categorization framework, and highlight areas of uncertainty. Going beyond size classes, our framework includes physicochemical properties (polymer composition, solid state, solubility) as defining criteria and size, shape, color, and origin as classifiers for categorization. Acknowledging the rapid evolution of our knowledge on plastic pollution, our framework will promote consensus building within the scientific and regulatory community based on a solid scientific foundation.

Genome-wide association study identifies 30 loci associated with bipolar disorder

Abstract: Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder.

Smart cancer nanomedicine

Abstract: Nanomedicines are extensively employed in cancer therapy. We here propose four strategic directions to improve nanomedicine translation and exploitation. (1) Patient stratification has become common practice in oncology drug development. Accordingly, probes and protocols for patient stratification are urgently needed in cancer nanomedicine, to identify individuals suitable for inclusion in clinical trials. (2) Rational drug selection is crucial for clinical and commercial success. Opportunistic choices based on drug availability should be replaced by investments in modular (pro)drug and nanocarrier design. (3) Combination therapies are the mainstay of clinical cancer care. Nanomedicines synergize with pharmacological and physical co-treatments, and should be increasingly integrated in multimodal combination therapy regimens. (4) Immunotherapy is revolutionizing the treatment of cancer. Nanomedicines can modulate the behaviour of myeloid and lymphoid cells, thereby empowering anticancer immunity and immunotherapy efficacy. Alone and especially together, these four directions will fuel and foster the development of successful cancer nanomedicine therapies.

Standards for distribution models in biodiversity assessments

Abstract: Demand for models in biodiversity assessments is rising, but which models are adequate for the task? We propose a set of best-practice standards and detailed guidelines enabling scoring of studies based on species distribution models for use in biodiversity assessments. We reviewed and scored 400 modeling studies over the past 20 years using the proposed standards and guidelines. We detected low model adequacy overall, but with a marked tendency of improvement over time in model building and, to a lesser degree, in biological data and model evaluation. We argue that implementation of agreed-upon standards for models in biodiversity assessments would promote transparency and repeatability, eventually leading to higher quality of the models and the inferences used in assessments. We encourage broad community participation toward the expansion and ongoing development of the proposed standards and guidelines.

Twenty-three unsolved problems in hydrology (UPH)–a community perspective

Abstract: This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come.

Grand challenges in the science of wind energy

Abstract: Harvested by advanced technical systems honed over decades of research and development, wind energy has become a mainstream energy resource. However, continued innovation is needed to realize the potential of wind to serve the global demand for clean energy. Here, we outline three interdependent, cross-disciplinary grand challenges underpinning this research endeavor. The first is the need for a deeper understanding of the physics of atmospheric flow in the critical zone of plant operation. The second involves science and engineering of the largest dynamic, rotating machines in the world. The third encompasses optimization and control of fleets of wind plants working synergistically within the electricity grid. Addressing these challenges could enable wind power to provide as much as half of our global electricity needs and perhaps beyond.

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Abstract: Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities1,2. This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity3,4,5,6. Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017—and more than 80% in some low- and middle-income regions—was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing—and in some countries reversal—of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.

Chitosan as a Wound Dressing Starting Material: Antimicrobial Properties and Mode of Action

Abstract: Fighting bacterial resistance is one of the concerns in modern days, as antibiotics remain the main resource of bacterial control. Data shows that for every antibiotic developed, there is a microorganism that becomes resistant to it. Natural polymers, as the source of antibacterial agents, offer a new way to fight bacterial infection. The advantage over conventional synthetic antibiotics is that natural antimicrobial agents are biocompatible, non-toxic, and inexpensive. Chitosan is one of the natural polymers that represent a very promising source for the development of antimicrobial agents. In addition, chitosan is biodegradable, non-toxic, and most importantly, promotes wound healing, features that makes it suitable as a starting material for wound dressings. This paper reviews the antimicrobial properties of chitosan and describes the mechanisms of action toward microbial cells as well as the interactions with mammalian cells in terms of wound healing process. Finally, the applications of chitosan as a wound-dressing material are discussed along with the current status of chitosan-based wound dressings existing on the market.

Relevance of nano- and microplastics for freshwater ecosystems: A critical review

Abstract: The current paper critically reviews the state-of-the-science on (1) microplastics (MP) types and particle concentrations in freshwater ecosystems, (2) MP and nanoplastics (NP) uptake and tissue translocation, (3) MP/NP-induced effects in freshwater organisms, and (4) capabilities of MP/NP to modulate the toxicity of environmental chemicals. The reviewed literature as well as new data on MP and NP concentrations in the river Elbe and on particle uptake into human cells indicate an environmental relevance of small particles in the low nano- and micrometer range higher than that of larger MP.

Omega-3 Long-Chain Polyunsaturated Fatty Acids, EPA and DHA: Bridging the Gap between Supply and Demand.

Abstract: The omega-3 (n-3) long-chain polyunsaturated fatty acids (LC-PUFA), eicosapentaenoic (EPA, 20:5n-3) and docosahexaenoic (DHA, 22:6n-3) acids, are well accepted as being essential components of a healthy, balanced diet, having beneficial effects on development and in mitigating a range of pathological conditions. However, their global supply from all the traditional sources of these nutrients is insufficient to satisfy human nutritional requirements. For two decades there has been considerable research carried out into all possible alternatives to the main sources of n-3 LC-PUFA, marine fish oil and fishmeal, driven largely by the aquaculture sector, as both the major user and provider of EPA and DHA. In the last few years these efforts have focused increasingly on the development of entirely new supplies of n-3 LC-PUFA produced de novo. Recently, this has resulted in various new sources of EPA and/or DHA that are already available or likely to available in the near future. In this short review, we briefly summaries the current gap between supply and demand of EPA and DHA for human requirements, the role of aquaculture in providing n-3 LC-PUFA to human consumers, the range of potential novel sources, and suggest how these new products could be used effectively. We conclude that all the new sources have potentially important roles to play in increasing the supply of n-3 LC-PUFA so that they are available more widely and in higher concentrations providing more options and opportunities for human consumers to obtain sufficient EPA and DHA to support more healthy, balanced diets.

Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment

Abstract: With big data analytics growing rapidly in popularity, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. Drawing on the resource‐based view, the dynamic capabilities view, and on recent literature on big data analytics, this study examines the indirect relationship between a big data analytics capability (BDAC) and two types of innovation capabilities: incremental and radical. The study extends existing research by proposing that BDACs enable firms to generate insight that can help strengthen their dynamic capabilities, which in turn positively impact incremental and radical innovation capabilities. To test their proposed research model, the authors used survey data from 175 chief information officers and IT managers working in Greek firms. By means of partial least squares structural equation modelling, the results confirm the authors’ assumptions regarding the indirect effect that BDACs have on innovation capabilities. Specifically, they find that dynamic capabilities fully mediate the effect on both incremental and radical innovation capabilities. In addition, under conditions of high environmental heterogeneity, the impact of BDACs on dynamic capabilities and, in sequence, incremental innovation capability is enhanced, while under conditions of high environmental dynamism the effect of dynamic capabilities on incremental innovation capabilities is amplified.

Agricultural and forestry trade drives large share of tropical deforestation emissions

Abstract: Deforestation, the second largest source of anthropogenic greenhouse gas emissions, is largely driven by expanding forestry and agriculture. However, despite agricultural expansion being increasingly driven by foreign demand, the links between deforestation and foreign demand for agricultural commodities have only been partially mapped. Here we present a pan-tropical quantification of carbon emissions from deforestation associated with the expansion of agriculture and forest plantations, and trace embodied emissions through global supply chains to consumers. We find that in the period 2010–2014, expansion of agriculture and tree plantations into forests across the tropics was associated with net emissions of approximately 2.6 gigatonnes carbon dioxide per year. Cattle and oilseed products account for over half of these emissions. Europe and China are major importers, and for many developed countries, deforestation emissions embodied in imports rival or exceed emissions from domestic agriculture. Depending on the trade model used, 29–39% of deforestation-related emissions were driven by international trade. This is substantially higher than the share of fossil carbon emissions embodied in trade, indicating that efforts to reduce greenhouse gas emissions from land-use change need to consider the role of international demand in driving deforestation. Additionally, we find that deforestation emissions are similar to, or larger than, other emissions in the carbon footprint of key forest-risk commodities. Similarly, deforestation emissions constitute a substantial share (˜15%) of the total carbon footprint of food consumption in EU countries. This highlights the need for consumption-based accounts to include emissions from deforestation, and for the implementation of policy measures that cross these international supply-chains if deforestation emissions are to be effectively reduced.

Climate as a risk factor for armed conflict

Abstract: Research findings on the relationship between climate and conflict are diverse and contested. Here we assess the current understanding of the relationship between climate and conflict, based on the structured judgments of experts from diverse disciplines. These experts agree that climate has affected organized armed conflict within countries. However, other drivers, such as low socioeconomic development and low capabilities of the state, are judged to be substantially more influential, and the mechanisms of climate–conflict linkages remain a key uncertainty. Intensifying climate change is estimated to increase future risks of conflict. Climate has affected organized armed conflict within countries, and intensifying climate change is estimated to increase future risks of conflict, although other drivers are substantially more influential and the mechanisms of climate–conflict linkages remain uncertain.

A new scenario logic for the Paris Agreement long-term temperature goal

Abstract: To understand how global warming can be kept well below 2 degrees Celsius and even 1.5 degrees Celsius, climate policy uses scenarios that describe how society could reduce its greenhouse gas emissions. However, current scenarios have a key weakness: they typically focus on reaching specific climate goals in 2100. This choice may encourage risky pathways that delay action, reach higher-than-acceptable mid-century warming, and rely on net removal of carbon dioxide thereafter to undo their initial shortfall in reductions of emissions. Here we draw on insights from physical science to propose a scenario framework that focuses on capping global warming at a specific maximum level with either temperature stabilization or reversal thereafter. The ambition of climate action until carbon neutrality determines peak warming, and can be followed by a variety of long-term states with different sustainability implications. The approach proposed here closely mirrors the intentions of the United Nations Paris Agreement, and makes questions of intergenerational equity into explicit design choices. Fundamental value judgments about acceptable maximum levels of climate change and future reliance on controversial technologies can be made explicitly in climate scenarios, thereby addressing the intergenerational bias present in the scenario literature.

Adaptive responses of animals to climate change are most likely insufficient

Abstract: Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.

A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels

Abstract: A large array of species distribution model (SDM) approaches has been developed for explaining and predicting the occurrences of individual species or species assemblages. Given the wealth of existing models, it is unclear which models perform best for interpolation or extrapolation of existing data sets, particularly when one is concerned with species assemblages. We compared the predictive performance of 33 variants of 15 widely applied and recently emerged SDMs in the context of multispecies data, including both joint SDMs that model multiple species together, and stacked SDMs that model each species individually combining the predictions afterward. We offer a comprehensive evaluation of these SDM approaches by examining their performance in predicting withheld empirical validation data of different sizes representing five different taxonomic groups, and for prediction tasks related to both interpolation and extrapolation. We measure predictive performance by 12 measures of accuracy, discrimination power, calibration, and precision of predictions, for the biological levels of species occurrence, species richness, and community composition. Our results show large variation among the models in their predictive performance, especially for communities comprising many species that are rare. The results do not reveal any major trade‐offs among measures of model performance; the same models performed generally well in terms of accuracy, discrimination, and calibration, and for the biological levels of individual species, species richness, and community composition. In contrast, the models that gave the most precise predictions were not well calibrated, suggesting that poorly performing models can make overconfident predictions. However, none of the models performed well for all prediction tasks. As a general strategy, we therefore propose that researchers fit a small set of models showing complementary performance, and then apply a cross‐validation procedure involving separate data to establish which of these models performs best for the goal of the study.

Deep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography

Abstract: Delineation of the cardiac structures from 2D echocardiographic images is a common clinical task to establish a diagnosis. Over the past decades, the automation of this task has been the subject of intense research. In this paper, we evaluate how far the state-of-the-art encoder-decoder deep convolutional neural network methods can go at assessing 2D echocardiographic images, i.e segmenting cardiac structures as well as estimating clinical indices, on a dataset especially designed to answer this objective. We therefore introduce the Cardiac Acquisitions for Multi-structure Ultrasound Segmentation (CAMUS) dataset, the largest publicly-available and fully-annotated dataset for the purpose of echocardiographic assessment. The dataset contains two and four-chamber acquisitions from 500 patients with reference measurements from one cardiologist on the full dataset and from three cardiologists on a fold of 50 patients. Results show that encoder-decoder based architectures outperform state-of-the-art non-deep learning methods and faithfully reproduce the expert analysis for the end-diastolic and end-systolic left ventricular volumes, with a mean correlation of 0.95 and an absolute mean error of 9.5 ml. Concerning the ejection fraction of the left ventricle, results are more contrasted with a mean correlation coefficient of 0.80 and an absolute mean error of 5.6 %. Although these results are below the inter-observer scores, they remain slightly worse than the intra-observer's ones. Based on this observation, areas for improvement are defined, which open the door for accurate and fully-automatic analysis of 2D echocardiographic images.

DNA metabarcoding-Need for robust experimental designs to draw sound ecological conclusions.

Abstract: Zinger, Lucie; Bonin, Aurélie; Alsos, Inger G; Bálint, Miklós; Bik, Holly; Boyer, Frédéric; Chariton, Anthony A; Creer, Simon; Coissac, Eric; Deagle, Bruce E; De Barba, Marta; Dickie, Ian A; Dumbrell, Alex J; Ficetola, Gentile Francesco; Fierer, Noah; Fumagalli, Luca; Gilbert, M Thomas P; Jarman, Simon; Jumpponen, Ari; Kauserud, Håvard; Orlando, Ludovic; Pansu, Johan; Pawlowski, Jan; Tedersoo, Leho; Thomsen, Philip Francis; Willerslev, Eske; Taberlet, Pierre

Large-scale ruminant genome sequencing provides insights into their evolution and distinct traits.

Abstract: The ruminants are one of the most successful mammalian lineages, exhibiting morphological and habitat diversity and containing several key livestock species. To better understand their evolution, we generated and analyzed de novo assembled genomes of 44 ruminant species, representing all six Ruminantia families. We used these genomes to create a time-calibrated phylogeny to resolve topological controversies, overcoming the challenges of incomplete lineage sorting. Population dynamic analyses show that population declines commenced between 100,000 and 50,000 years ago, which is concomitant with expansion in human populations. We also reveal genes and regulatory elements that possibly contribute to the evolution of the digestive system, cranial appendages, immune system, metabolism, body size, cursorial locomotion, and dentition of the ruminants.

Brain Imaging of the Cortex in ADHD: A Coordinated Analysis of Large-Scale Clinical and Population-Based Samples

Abstract: OBJECTIVE: Neuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies. METHODS: Cortical thickness and surface area (based on the Desikan-Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707). RESULTS: In the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen's d=-0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample. CONCLUSIONS: Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis.

Plasma protein patterns as comprehensive indicators of health.

Abstract: Proteins are effector molecules that mediate the functions of genes1,2 and modulate comorbidities3–10, behaviors and drug treatments11. They represent an enormous potential resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatment. However, the concept of using plasma proteins for individualized health assessment across many health conditions simultaneously has not been tested. Here, we show that plasma protein expression patterns strongly encode for multiple different health states, future disease risks and lifestyle behaviors. We developed and validated protein-phenotype models for 11 different health indicators: liver fat, kidney filtration, percentage body fat, visceral fat mass, lean body mass, cardiopulmonary fitness, physical activity, alcohol consumption, cigarette smoking, diabetes risk and primary cardiovascular event risk. The analyses were prospectively planned, documented and executed at scale on archived samples and clinical data, with a total of ~85 million protein measurements in 16,894 participants. Our proof-of-concept study demonstrates that protein expression patterns reliably encode for many different health issues, and that large-scale protein scanning12–16 coupled with machine learning is viable for the development and future simultaneous delivery of multiple measures of health. We anticipate that, with further validation and the addition of more protein-phenotype models, this approach could enable a single-source, individualized so-called liquid health check. Large-scale aptamer-based scanning of plasma proteins coupled with machine learning demonstrates proof-of-concept and feasibility of an individualized health check using a single blood sample.

Increasing impacts of land use on biodiversity and carbon sequestration driven by population and economic growth

Abstract: Biodiversity and ecosystem service losses driven by land-use change are expected to intensify as a growing and more affluent global population requires more agricultural and forestry products, and teleconnections in the global economy lead to increasing remote environmental responsibility. By combining global biophysical and economic models, we show that, between the years 2000 and 2011, overall population and economic growth resulted in increasing total impacts on bird diversity and carbon sequestration globally, despite a reduction of land-use impacts per unit of gross domestic product (GDP). The exceptions were North America and Western Europe, where there was a reduction of forestry and agriculture impacts on nature accentuated by the 2007-2008 financial crisis. Biodiversity losses occurred predominantly in Central and Southern America, Africa and Asia with international trade an important and growing driver. In 2011, 33% of Central and Southern America and 26% of Africa's biodiversity impacts were driven by consumption in other world regions. Overall, cattle farming is the major driver of biodiversity loss, but oil seed production showed the largest increases in biodiversity impacts. Forestry activities exerted the highest impact on carbon sequestration, and also showed the largest increase in the 2000-2011 period. Our results suggest that to address the biodiversity crisis, governments should take an equitable approach recognizing remote responsibility, and promote a shift of economic development towards activities with low biodiversity impacts.