Showing papers by "Aarhus University published in 2022"

Portability of 245 polygenic scores when derived from the UK Biobank and applied to 9 ancestry groups from the same cohort

Abstract: The low portability of polygenic scores (PGSs) across global populations is a major concern that must be addressed before PGSs can be used for everyone in the clinic. Indeed, prediction accuracy has been shown to decay as a function of the genetic distance between the training and test cohorts. However, such cohorts differ not only in their genetic distance but also in their geographical distance and their data collection and assaying, conflating multiple factors. In this study, we examine the extent to which PGSs are transferable between ancestries by deriving polygenic scores for 245 curated traits from the UK Biobank data and applying them in nine ancestry groups from the same cohort. By restricting both training and testing to the UK Biobank data, we reduce the risk of environmental and genotyping confounding from using different cohorts. We define the nine ancestry groups at a sub-continental level, based on a simple, robust, and effective method that we introduce here. We then apply two different predictive methods to derive polygenic scores for all 245 phenotypes and show a systematic and dramatic reduction in portability of PGSs trained using Northwestern European individuals and applied to nine ancestry groups. These analyses demonstrate that prediction already drops off within European ancestries and reduces globally in proportion to genetic distance. Altogether, our study provides unique and robust insights into the PGS portability problem.

Prosocial behavior and altruism: A review of concepts and definitions.

Abstract: The field of prosociality is flourishing, yet researchers disagree about how to define prosocial behavior and often neglect defining it altogether. In this review, we provide an overview about the breadth of definitions of prosocial behavior and the related concept of altruism. Common to almost all definitions is an emphasis on the promotion of welfare in agents other than the actor. However, definitions of the two concepts differ in terms of whether they emphasize intentions and motives, costs and benefits, and the societal context. In order to improve on the conceptual ambiguity surrounding the study of prosociality, we urge researchers to provide definitions, to use operationalizations that match their definitions, and to acknowledge the diversity of prosocial behavior.

Prosocial behavior and altruism: A review of concepts and definitions

Abstract: The field of prosociality is flourishing, yet researchers disagree about how to define prosocial behavior and often neglect defining it altogether. In this review, we provide an overview about the breadth of definitions of prosocial behavior and the related concept of altruism. Common to almost all definitions is an emphasis on the promotion of welfare in agents other than the actor. However, definitions of the two concepts differ in terms of whether they emphasize intentions and motives, costs and benefits, and the societal context. In order to improve on the conceptual ambiguity surrounding the study of prosociality, we urge researchers to provide definitions, to use operationalizations that match their definitions, and to acknowledge the diversity of prosocial behavior.

Single‐cell RNA sequencing technologies and applications: A brief overview

Abstract: Single-cell RNA sequencing (scRNA-seq) technology has become the state-of-the-art approach for unravelling the heterogeneity and complexity of RNA transcripts within individual cells, as well as revealing the composition of different cell types and functions within highly organized tissues/organs/organisms. Since its first discovery in 2009, studies based on scRNA-seq provide massive information across different fields making exciting new discoveries in better understanding the composition and interaction of cells within humans, model animals and plants. In this review, we provide a concise overview about the scRNA-seq technology, experimental and computational procedures for transforming the biological and molecular processes into computational and statistical data. We also provide an explanation of the key technological steps in implementing the technology. We highlight a few examples on how scRNA-seq can provide unique information for better understanding health and diseases. One important application of the scRNA-seq technology is to build a better and high-resolution catalogue of cells in all living organism, commonly known as atlas, which is key resource to better understand and provide a solution in treating diseases. While great promises have been demonstrated with the technology in all areas, we further highlight a few remaining challenges to be overcome and its great potentials in transforming current protocols in disease diagnosis and treatment.

Metal‐Organic Framework Glass Anode with an Exceptional Cycling‐Induced Capacity Enhancement for Lithium‐Ion Batteries

Abstract: Metal-organic frameworks (MOFs) hold great promise as high-energy anode materials for next-generation lithium-ion batteries (LIBs) due to their tunable chemistry, pore structure and abundant reaction sites. However, the pore structure of crystalline MOFs tends to collapse during lithium-ion insertion and extraction, and hence, their electrochemical performances are rather limited. As a critical breakthrough, a MOF glass anode for LIBs has been developed in the present work. In detail, it is fabricated by melt-quenching Cobalt-ZIF-62 (Co(Im)1.75 (bIm)0.25 ) to glass, and then by combining glass with carbon black and binder. The derived anode exhibits high lithium storage capacity (306 mAh g-1 after 1000 cycles at of 2 A g-1 ), outstanding cycling stability, and superior rate performance compared with the crystalline Cobalt-ZIF-62 and the amorphous one prepared by high-energy ball-milling. Importantly, it is found that the Li-ion storage capacity of the MOF glass anode continuously rises with charge-discharge cycling and even tripled after 1000 cycles. Combined spectroscopic and structural analyses, along with density functional theory calculations, reveal the origin of the cycling-induced enhancement of the performances of the MOF glass anode, that is, the increased distortion and local breakage of the CoN coordination bonds making the Li-ion intercalation sites more accessible.

Learning-based object detection and localization for a mobile robot manipulator in SME production

Abstract: Increasing research attention has been attracted to automatic production processes in small and medium-sized enterprises (SMEs) using collaborative robotic systems. In this work, we develop an object detection solution based on deep learning on 3D point clouds for a collaborative mobile robot manipulator to automate SME production. In this solution, a 3D point cloud technology is adopted to measure the shape and depth information of targeted objects in SME production, for instance, name tags production and plug-in charging. Deep learning is then employed to deal with the uncertainty in 3D detection, such as inconsistent light conditions and the irregular distribution and structural ambiguity of point clouds. A 2D camera is employed to calibrate the relative positions of the mobile manipulator to workstations. The mobile robot manipulator is equipped with cameras, an in-house developed adaptive gripper, and a learning-based computer vision system developed in this work. The principle and procedures of the proposed 3D object detection and 2D calibration are presented in detail. The automatic name tags production and plug-in charging experiments are conducted to validate the object detection, localization algorithms, and tools developed and employed in production cases using the mobile robot manipulator.

Trade-off between microbial carbon use efficiency and microbial phosphorus limitation under salinization in a tidal wetland

Abstract: Sea level rise–induced salinization is projected to influence the decomposition of soil carbon (C) in tidal wetlands. Despite evidence showing that microbial metabolism can determine the fate of soil C decomposition, the response of microbial metabolism to salinization in tidal wetlands remains largely unknown. Microbial metabolism is impacted by the microbial metabolic limitation and carbon use efficiency (CUE), which can provide mechanistic insights into soil C decomposition. Here, we measured microbial metabolic limitation, microbial CUE, and extracellular enzyme activities along an estuarine salinity gradient ranging from freshwater (0.1 ± 0.1 mg g−1) to oligohaline (2.1 ± 0.5 mg g−1) in a tidal wetland. Overall, microorganisms were limited by phosphorus (P) in the tidal wetlands, where salinization increased microbial P limitation by 34%. The enhanced microbial P limitation was attributed to increases in soil C:P and belowground biomass, as well as decreases in root C:P with increasing salinity. Microbial CUE decreased from 0.38 to 0.33 as salinity increased, while microbial P limitation was negatively correlated with microbial CUE, representing the trade-off between the two. Furthermore, microbial P limitation was positively associated with C-, nitrogen (N)-, and P-acquiring extracellular enzyme activities, while all these enzyme activities were negatively correlated with microbial CUE. These results illustrate that to balance microbial P limitation with salinization, microorganisms transfer more energy from the microbial CUE to extracellular enzyme production, and this was the mechanism underlying the trade-off. Microorganisms were also limited by C in the tidal wetlands. However, as the increasing belowground biomass alleviated microbial C limitation with salinization, no relationship was observed between microbial C limitation and CUE. Future C and nutrient models aimed to simulate tidal wetland ecosystem responses to salinization will benefit from the inclusion of trade-off between microbial CUE and microbial P limitation for more accurate prediction.

Advances in air quality research – current and emerging challenges

Abstract: Abstract. This review provides a community's perspective on air quality research focusing mainly on developments over the past decade. The article provides perspectives on current and future challenges as well as research needs for selected key topics. While this paper is not an exhaustive review of all research areas in the field of air quality, we have selected key topics that we feel are important from air quality research and policy perspectives. After providing a short historical overview, this review focuses on improvements in characterizing sources and emissions of air pollution, new air quality observations and instrumentation, advances in air quality prediction and forecasting, understanding interactions of air quality with meteorology and climate, exposure and health assessment, and air quality management and policy. In conducting the review, specific objectives were (i) to address current developments that push the boundaries of air quality research forward, (ii) to highlight the emerging prominent gaps of knowledge in air quality research, and (iii) to make recommendations to guide the direction for future research within the wider community. This review also identifies areas of particular importance for air quality policy. The original concept of this review was borne at the International Conference on Air Quality 2020 (held online due to the COVID 19 restrictions during 18–26 May 2020), but the article incorporates a wider landscape of research literature within the field of air quality science. On air pollution emissions the review highlights, in particular, the need to reduce uncertainties in emissions from diffuse sources, particulate matter chemical components, shipping emissions, and the importance of considering both indoor and outdoor sources. There is a growing need to have integrated air pollution and related observations from both ground-based and remote sensing instruments, including in particular those on satellites. The research should also capitalize on the growing area of low-cost sensors, while ensuring a quality of the measurements which are regulated by guidelines. Connecting various physical scales in air quality modelling is still a continual issue, with cities being affected by air pollution gradients at local scales and by long-range transport. At the same time, one should allow for the impacts from climate change on a longer timescale. Earth system modelling offers considerable potential by providing a consistent framework for treating scales and processes, especially where there are significant feedbacks, such as those related to aerosols, chemistry, and meteorology. Assessment of exposure to air pollution should consider the impacts of both indoor and outdoor emissions, as well as application of more sophisticated, dynamic modelling approaches to predict concentrations of air pollutants in both environments. With particulate matter being one of the most important pollutants for health, research is indicating the urgent need to understand, in particular, the role of particle number and chemical components in terms of health impact, which in turn requires improved emission inventories and models for predicting high-resolution distributions of these metrics over cities. The review also examines how air pollution management needs to adapt to the above-mentioned new challenges and briefly considers the implications from the COVID-19 pandemic for air quality. Finally, we provide recommendations for air quality research and support for policy.

Automatic sleep staging of EEG signals: recent development, challenges, and future directions

Abstract: Abstract Modern deep learning holds a great potential to transform clinical studies of human sleep. Teaching a machine to carry out routine tasks would be a tremendous reduction in workload for clinicians. Sleep staging, a fundamental step in sleep practice, is a suitable task for this and will be the focus in this article. Recently, automatic sleep-staging systems have been trained to mimic manual scoring, leading to similar performance to human sleep experts, at least on scoring of healthy subjects. Despite tremendous progress, we have not seen automatic sleep scoring adopted widely in clinical environments. This review aims to provide the shared view of the authors on the most recent state-of-the-art developments in automatic sleep staging, the challenges that still need to be addressed, and the future directions needed for automatic sleep scoring to achieve clinical value.

Generating alternative fuel and bioplastics from medical plastic waste and waste frying oil using microwave co-pyrolysis combined with microbial fermentation

Abstract: In the present study, microwave co-pyrolysis (MCP) was used to simultaneously convert medical plastic waste (MPW) and waste frying oil (WFO) into liquid oil products. The MCP process demonstrated a faster heating rate (24 °C/min) and shorter process time (20 min) compared to conventional pyrolysis techniques converting MPW and WFO into liquid oil (≥80 wt%). The MCP reduced the oxygen content from 25.7 to 9.82 wt% in liquid oil encompassing light aliphatic hydrocarbons ranging from C10 to C28, generating a novel sustainable liquid fuel. The liquid having a high carbon content (approximately 77.1 wt%) and low carbon to nitrogen ratio (27.9) is a suitable energy feedstock for polyhydroxyalkanoate (PHA) bioplastic production in the form of poly3-hydroxybutyrate [P(3HB)]. The liquid oil acted as an energy source for the growth of Bacillus sp. During microbial fermentation, yielding approximately 11% (w/w) P(3HB). Bioplastics are biodegradable, biocompatible with humans and non-toxic to marine organisms, representing a valuable additive in the production of cosmetics, detergents, and as medical scaffolds for tissue engineering. The results indicate the promising upcycling of waste products by this approach through pyrolytic biorefinery into value-added fuel and bioplastic products, being important for the future sustainable production of renewable resources.