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In classical thermodynamic processes the unavoidable presence of irreversibility, quantified by the entropy production, carries two energetic footprints: the reduction of extractable work from the optimal, reversible case, and the generation of a surplus of heat that is irreversibly dissipated to the environment. Recently it has been shown that in the quantum regime an additional quantum irreversibility occurs that is linked to decoherence into the energy basis. Here we employ quantum trajectories to construct distributions for classical heat and quantum heat exchanges, and show that the heat footprint of quantum irreversibility differs markedly from the classical case. We also quantify how quantum irreversibility reduces the amount of work that can be extracted from a state with coherences. Our results show that decoherence leads to both entropic and energetic footprints which both play an important role in the optimization of controlled quantum operations at low temperature.
In classical thermodynamics irreversibility occurs whenever a non-thermal system is brought into contact with a thermal environment. Using quantum trajectories the authors here establish two energetic footprints of quantum irreversible processes, and find that while quantum irreversibility leads to the occurrence of a quantum heat and a reduction of work production, the two are not linked in the same manner as the classical laws of thermodynamics would dictate.
Estimating global mean sea-level rise and its uncertainties by 2100 and 2300 from an expert survey
(2020)
Sea-level rise projections and knowledge of their uncertainties are vital to make informed mitigation and adaptation decisions. To elicit projections from members of the scientific community regarding future global mean sea-level (GMSL) rise, we repeated a survey originally conducted five years ago. Under Representative Concentration Pathway (RCP) 2.6, 106 experts projected a likely (central 66% probability) GMSL rise of 0.30-0.65 m by 2100, and 0.54-2.15 m by 2300, relative to 1986-2005. Under RCP 8.5, the same experts projected a likely GMSL rise of 0.63-1.32 m by 2100, and 1.67-5.61 m by 2300. Expert projections for 2100 are similar to those from the original survey, although the projection for 2300 has extended tails and is higher than the original survey. Experts give a likelihood of 42% (original survey) and 45% (current survey) that under the high-emissions scenario GMSL rise will exceed the upper bound (0.98 m) of the likely range estimated by the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, which is considered to have an exceedance likelihood of 17%. Responses to open-ended questions suggest that the increases in upper-end estimates and uncertainties arose from recent influential studies about the impact of marine ice cliff instability on the meltwater contribution to GMSL rise from the Antarctic Ice Sheet.
Landscapes in high northern latitudes are assumed to be highly sensitive to future global change, but the rates and long-term trajectories of changes are rather uncertain. In the boreal zone, fires are an important factor in climate-vegetation interactions and biogeochemical cycles. Fire regimes are characterized by small, frequent, low-intensity fires within summergreen boreal forests dominated by larch, whereas evergreen boreal forests dominated by spruce and pine burn large areas less frequently but at higher intensities. Here, we explore the potential of the monosaccharide anhydrides (MA) levoglucosan, mannosan and galactosan to serve as proxies of low-intensity biomass burning in glacial-to-interglacial lake sediments from the high northern latitudes. We use sediments from Lake El'gygytgyn (cores PG 1351 and ICDP 5011-1), located in the far north-east of Russia, and study glacial and interglacial samples of the last 430 kyr (marine isotope stages 5e, 6, 7e, 8, 11c and 12) that had different climate and biome configurations. Combined with pollen and non-pollen palynomorph records from the same samples, we assess how far the modern relationships between fire, climate and vegetation persisted during the past, on orbital to centennial timescales. We find that MAs attached to particulates were well-preserved in up to 430 kyr old sediments with higher influxes from low-intensity biomass burning in interglacials compared to glacials. MA influxes significantly increase when summergreen boreal forest spreads closer to the lake, whereas they decrease when tundra-steppe environments and, especially, Sphagnum peatlands spread. This suggests that low-temperature fires are a typical characteristic of Siberian larch forests also on long timescales. The results also suggest that low-intensity fires would be reduced by vegetation shifts towards very dry environments due to reduced biomass availability, as well as by shifts towards peatlands, which limits fuel dryness. In addition, we observed very low MA ratios, which we interpret as high contributions of galactosan and mannosan from biomass sources other than those currently monitored, such as the moss-lichen mats in the understorey of the summergreen boreal forest. Overall, sedimentary MAs can provide a powerful proxy for fire regime reconstructions and extend our knowledge of long-term natural fire-climate-vegetation feedbacks in the high northern latitudes.
Landscapes in high northern latitudes are assumed to be highly sensitive to future global change, but the rates and long-term trajectories of changes are rather uncertain. In the boreal zone, fires are an important factor in climate-vegetation interactions and biogeochemical cycles. Fire regimes are characterized by small, frequent, low-intensity fires within summergreen boreal forests dominated by larch, whereas evergreen boreal forests dominated by spruce and pine burn large areas less frequently but at higher intensities. Here, we explore the potential of the monosaccharide anhydrides (MA) levoglucosan, mannosan and galactosan to serve as proxies of low-intensity biomass burning in glacial-to-interglacial lake sediments from the high northern latitudes. We use sediments from Lake El'gygytgyn (cores PG 1351 and ICDP 5011-1), located in the far north-east of Russia, and study glacial and interglacial samples of the last 430 kyr (marine isotope stages 5e, 6, 7e, 8, 11c and 12) that had different climate and biome configurations. Combined with pollen and non-pollen palynomorph records from the same samples, we assess how far the modern relationships between fire, climate and vegetation persisted during the past, on orbital to centennial timescales. We find that MAs attached to particulates were well-preserved in up to 430 kyr old sediments with higher influxes from low-intensity biomass burning in interglacials compared to glacials. MA influxes significantly increase when summergreen boreal forest spreads closer to the lake, whereas they decrease when tundra-steppe environments and, especially, Sphagnum peatlands spread. This suggests that low-temperature fires are a typical characteristic of Siberian larch forests also on long timescales. The results also suggest that low-intensity fires would be reduced by vegetation shifts towards very dry environments due to reduced biomass availability, as well as by shifts towards peatlands, which limits fuel dryness. In addition, we observed very low MA ratios, which we interpret as high contributions of galactosan and mannosan from biomass sources other than those currently monitored, such as the moss-lichen mats in the understorey of the summergreen boreal forest. Overall, sedimentary MAs can provide a powerful proxy for fire regime reconstructions and extend our knowledge of long-term natural fire-climate-vegetation feedbacks in the high northern latitudes.
Identification of a super-functional Tfh-like subpopulation in murine lupus by pattern perception
(2020)
Dysregulated cytokine expression by T cells plays a pivotal role in the pathogenesis of autoimmune diseases. However, the identification of the corresponding pathogenic subpopulations is a challenge, since a distinction between physiological variation and a new quality in the expression of protein markers requires combinatorial evaluation. Here, we were able to identify a super-functional follicular helper T cell (Tfh)-like subpopulation in lupus-prone NZBxW mice with our binning approach "pattern recognition of immune cells (PRI)". PRI uncovered a subpopulation of IL-21(+) IFN-gamma(high) PD-1(low) CD40L(high) CXCR5(-) Bcl-6(-) T cells specifically expanded in diseased mice. In addition, these cells express high levels of TNF-alpha and IL-2, and provide B cell help for IgG production in an IL-21 and CD40L dependent manner. This super-functional T cell subset might be a superior driver of autoimmune processes due to a polyfunctional and high cytokine expression combined with Tfh-like properties.
We propose a novel way to measure and analyze networks of drainage divides from digital elevation models. We developed an algorithm that extracts drainage divides based on the drainage basin boundaries defined by a stream network. In contrast to streams, there is no straightforward approach to order and classify divides, although it is intuitive that some divides are more important than others. A meaningful way of ordering divides is the average distance one would have to travel down on either side of a divide to reach a common stream location. However, because measuring these distances is computationally expensive and prone to edge effects, we instead sort divide segments based on their tree-like network structure, starting from endpoints at river confluences. The sorted nature of the network allows for assigning distances to points along the divides, which can be shown to scale with the average distance downslope to the common stream location. Furthermore, because divide segments tend to have characteristic lengths, an ordering scheme in which divide orders increase by 1 at junctions mimics these distances. We applied our new algorithm to the Big Tujunga catchment in the San Gabriel Mountains of southern California and studied the morphology of the drainage divide network. Our results show that topographic metrics, like the downstream flow distance to a stream and hillslope relief, attain characteristic values that depend on the drainage area threshold used to derive the stream network. Portions along the divide network that have lower than average relief or are closer than average to streams are often distinctly asymmetric in shape, suggesting that these divides are unstable. Our new and automated approach thus helps to objectively extract and analyze divide networks from digital elevation models.
Xanthomonas phaseoli pv. manihotis (Xpm) is the causal agent of cassava bacterial blight, the most important bacterial disease in this crop. There is a paucity of knowledge about the metabolism of Xanthomonas and its relevance in the pathogenic process, with the exception of the elucidation of the xanthan biosynthesis route. Here we report the reconstruction of the genome-scale model of Xpm metabolism and the insights it provides into plant-pathogen interactions. The model, iXpm1556, displayed 1,556 reactions, 1,527 compounds, and 890 genes. Metabolic maps of central amino acid and carbohydrate metabolism, as well as xanthan biosynthesis of Xpm, were reconstructed using Escher (https://escher.github.io/) to guide the curation process and for further analyses. The model was constrained using the RNA-seq data of a mutant of Xpm for quorum sensing (QS), and these data were used to construct context-specific models (CSMs) of the metabolism of the two strains (wild type and QS mutant). The CSMs and flux balance analysis were used to get insights into pathogenicity, xanthan biosynthesis, and QS mechanisms. Between the CSMs, 653 reactions were shared; unique reactions belong to purine, pyrimidine, and amino acid metabolism. Alternative objective functions were used to demonstrate a trade-off between xanthan biosynthesis and growth and the re-allocation of resources in the process of biosynthesis. Important features altered by QS included carbohydrate metabolism, NAD(P)(+) balance, and fatty acid elongation. In this work, we modeled the xanthan biosynthesis and the QS process and their impact on the metabolism of the bacterium. This model will be useful for researchers studying host-pathogen interactions and will provide insights into the mechanisms of infection used by this and other Xanthomonas species.
The remarkable progress of metal halide perovskites in photovoltaics has led to the power conversion efficiency approaching 26%. However, practical applications of perovskite-based solar cells are challenged by the stability issues, of which the most critical one is photo-induced degradation. Bare CH3NH3PbI3 perovskite films are known to decompose rapidly, with methylammonium and iodine as volatile species and residual solid PbI2 and metallic Pb, under vacuum under white light illumination, on the timescale of minutes. We find, in agreement with previous work, that the degradation is non-uniform and proceeds predominantly from the surface, and that illumination under N-2 and ambient air (relative humidity 20%) does not induce substantial degradation even after several hours. Yet, in all cases the release of iodine from the perovskite surface is directly identified by X-ray photoelectron spectroscopy. This goes in hand with a loss of organic cations and the formation of metallic Pb. When CH3NH3PbI3 films are covered with a few nm thick organic capping layer, either charge selective or non-selective, the rapid photodecomposition process under ultrahigh vacuum is reduced by more than one order of magnitude, and becomes similar in timescale to that under N-2 or air. We conclude that the light-induced decomposition reaction of CH3NH3PbI3, leading to volatile methylammonium and iodine, is largely reversible as long as these products are restrained from leaving the surface. This is readily achieved by ambient atmospheric pressure, as well as a thin organic capping layer even under ultrahigh vacuum. In addition to explaining the impact of gas pressure on the stability of this perovskite, our results indicate that covalently "locking" the position of perovskite components at the surface or an interface should enhance the overall photostability.
Recent findings suggest a role of oxytocin on the tendency to spontaneously mimic the emotional facial expressions of others. Oxytocin-related increases of facial mimicry, however, seem to be dependent on contextual factors. Given previous literature showing that people preferentially mimic emotional expressions of individuals associated with high (vs. low) rewards, we examined whether the reward value of the mimicked agent is one factor influencing the oxytocin effects on facial mimicry. To test this hypothesis, 60 male adults received 24 IU of either intranasal oxytocin or placebo in a double-blind, between-subject experiment. Next, the value of male neutral faces was manipulated using an associative learning task with monetary rewards. After the reward associations were learned, participants watched videos of the same faces displaying happy and angry expressions. Facial reactions to the emotional expressions were measured with electromyography. We found that participants judged as more pleasant the face identities associated with high reward values than with low reward values. However, happy expressions by low rewarding faces were more spontaneously mimicked than high rewarding faces. Contrary to our expectations, we did not find a significant direct effect of intranasal oxytocin on facial mimicry, nor on the reward-driven modulation of mimicry. Our results support the notion that mimicry is a complex process that depends on contextual factors, but failed to provide conclusive evidence of a role of oxytocin on the modulation of facial mimicry.
When running a lab we do not think about calamities, since they are rare events for which we cannot plan while we are busy with the day-to-day management and intellectual challenges of a research lab. No lab team can be prepared for something like a pandemic such as COVID-19, which has led to shuttered labs around the globe. But many other types of crises can also arise that labs may have to weather during their lifetime. What can researchers do to make a lab more resilient in the face of such exterior forces? What systems or behaviors could we adjust in 'normal' times that promote lab success, and increase the chances that the lab will stay on its trajectory? We offer 10 rules, based on our current experiences as a lab group adapting to crisis.
Objective:
The Indonesia Basic Health Research 2018 indicates that Indonesian children are still among the shortest in the world. When referred to World Health Organization Child Growth Standards (WHOCGS), the prevalence of stunting reaches up to 43% in several Indonesian districts. Indonesian National Growth Reference Charts (INGRC) were established in order to better distinguish between healthy short children and children with growth disorders. We analyzed height and weight measurements of healthy Indonesian children using INGRC and WHOCGS.
Methods:
6972 boys and 5800 girls (n = 12,772), aged 0-59 months old, from Bandung District were measured. Z-scores of length/height and body mass index were calculated based on INGRC and WHOCGS.
Results:
Under 5-year-old Indonesian children raised in Bandung are short and slim. Mean height z-scores of boys is -2.03 [standard deviation (SD) 1.31], mean height z-scores of girls is -2.03 (SD 1.31) when referred to WHOCGS indicating that over 50 % of these children are stunted. Bandung children are heterogeneous, with substantial subpopulations of tall children. Depending on the growth reference used, between 9% and 15% of them are wasted. Wasted children are on average half a SD taller than their peers.
Conclusion:
WHOCGS seriously overestimates the true prevalence of undernutrition in Indonesian children. The present investigation fails to support evidence of undernutrition at a prevalence similar to the over 50% prevalence of stunting (WHOCGS) versus 13.3% (INGRC). We suggest refraining from using WHOCGS, and instead applying INGRC that closely mirror height and weight increments in Bandung children. INGRC appear superior for practical and clinical purposes, such as detecting growth and developmental disorders.
Biofilms are complex, sessile microbial communities that are problematic in clinical settings due to their association with survival and pathogenicity of bacteria. The biofilm formation supporting conditions for zoonotic serovars of Salmonella and avian pathogenic E. coli (APEC) from poultry have not been well studied yet. Clinical isolates of zoonotic Salmonella and APEC from poultry were evaluated for biofilm formation in four media at 37 degrees C and 40 degrees C after incubation of 48 and 72 hrs. The biofilms formed in 96 well plates were visualized and quantified with a new module of Aklides system using fluorescence microscope coupled with automated VideoScan Technology. After 72 hrs, brain heart infusion at 40 degrees C and Rappaport-Vassiliadis Soya broth at 37 degrees C were found most suitable for APEC and Salmonella biofilm formations respectively. The new information will be useful for further biofilm associated studies particularly for evaluation of antibiofilm compounds and contribute in infection control. (C) 2020 PVJ. All rights reserved
Plant proteins have become increasingly important for ecological reasons. Rapeseed is a novel source of plant proteins with high biological value, but its metabolic impact in humans is largely unknown. A randomized, controlled intervention study including 20 healthy subjects was conducted in a crossover design. All participants received a test meal without additional protein or with 28 g of rapeseed protein isolate or soy protein isolate (control). Venous blood samples were collected over a 360-min period to analyze metabolites; satiety was assessed using a visual analog scale. Postprandial levels of lipids, urea, and amino acids increased following the intake of both protein isolates. The postprandial insulin response was lower after consumption of the rapeseed protein than after intake of the soy protein (p< 0.05), whereas the postmeal responses of glucose, lipids, interleukin-6, minerals, and urea were comparable between the two protein isolates. Interestingly, the rapeseed protein exerted stronger effects on postprandial satiety than the soy protein (p< 0.05). The postmeal metabolism following rapeseed protein intake is comparable with that of soy protein. The favorable effect of rapeseed protein on postprandial insulin and satiety makes it a valuable plant protein for human nutrition.
Background:
Many felid species are of high conservation concern, and with increasing human disturbance the situation is worsening. Small isolated populations are at risk of genetic impoverishment decreasing within-species biodiversity. Movement is known to be a key behavioural trait that shapes both demographic and genetic dynamics and affects population survival. However, we have limited knowledge on how different manifestations of movement behaviour translate to population processes. In this study, we aimed to 1) understand the potential effects of movement behaviour on the genetic diversity of small felid populations in heterogeneous landscapes, while 2) presenting a simulation tool that can help inform conservation practitioners following, or considering, population management actions targeting the risk of genetic impoverishment.
Methods:
We developed a spatially explicit individual-based population model including neutral genetic markers for felids and applied this to the example of Eurasian lynx. Using a neutral landscape approach, we simulated reintroductions into a three-patch system, comprising two breeding patches separated by a larger patch of differing landscape heterogeneity, and tested for the effects of various behavioural movement syndromes and founder population sizes. We explored a range of movement syndromes by simulating populations with various movement model parametrisations that range from 'shy' to 'bold' movement behaviour.
Results:
We find that movement syndromes can lead to a higher loss of genetic diversity and an increase in between population genetic structure for both "bold" and "shy" movement behaviours, depending on landscape conditions, with larger decreases in genetic diversity and larger increases in genetic differentiation associated with bold movement syndromes, where the first colonisers quickly reproduce and subsequently dominate the gene pool. In addition, we underline the fact that a larger founder population can offset the genetic losses associated with subpopulation isolation and gene pool dominance. Conclusions We identified a movement syndrome trade-off for population genetic variation, whereby bold-explorers could be saviours - by connecting populations and promoting panmixia, or sinks - by increasing genetic losses via a 'founder takes all' effect, whereas shy-stayers maintain a more gradual genetic drift due to their more cautious behaviour. Simulations should incorporate movement behaviour to provide better projections of long-term population viability and within-species biodiversity, which includes genetic diversity. Simulations incorporating demographics and genetics have great potential for informing conservation management actions, such as population reintroductions or reinforcements. Here, we present such a simulation tool for solitary felids.
Laser-induced breakdown spectroscopy (LIBS) analysers are becoming increasingly common for material classification purposes. However, to achieve good classification accuracy, mostly noncompact units are used based on their stability and reproducibility. In addition, computational algorithms that require significant hardware resources are commonly applied. For performing measurement campaigns in hard-to-access environments, such as mining sites, there is a need for compact, portable, or even handheld devices capable of reaching high measurement accuracy. The optics and hardware of small (i.e., handheld) devices are limited by space and power consumption and require a compromise of the achievable spectral quality. As long as the size of such a device is a major constraint, the software is the primary field for improvement. In this study, we propose a novel combination of handheld LIBS with non-negative tensor factorisation to investigate its classification capabilities of copper minerals. The proposed approach is based on the extraction of source spectra for each mineral (with the use of tensor methods) and their labelling based on the percentage contribution within the dataset. These latent spectra are then used in a regression model for validation purposes. The application of such an approach leads to an increase in the classification score by approximately 5% compared to that obtained using commonly used classifiers such as support vector machines, linear discriminant analysis, and the k-nearest neighbours algorithm.
Marine sponges host highly diverse but specific bacterial communities that provide essential functions for the sponge holobiont, including antimicrobial defense. Here, we characterized the bacterial microbiome of the marine sponge Haliclona cnidata that has been in culture in an artificial marine aquarium system. We tested the hypotheses (1) that the long-term aquarium cultured sponge H. cnidata is tightly associated with a typical sponge bacterial microbiota and (2) that the symbiotic Bacteria sustain bioactivity under harmful environmental conditions to facilitate holobiont survival by preventing pathogen invasion. Microscopic and phylogenetic analyses of the bacterial microbiota revealed that H. cnidata represents a high microbial abundance (HMA) sponge with a temporally stable bacterial community that significantly shifts with changing aquarium conditions. A 4-week incubation experiment was performed in small closed aquarium systems with antibiotic and/or light exclusion treatments to reduce the total bacterial and photosynthetically active sponge-associated microbiota to a treatment-specific resilient community. While the holobiont was severely affected by the experimental treatment (i.e., bleaching of the sponge, reduced bacterial abundance, shifted bacterial community composition), the biological defense and bacterial community interactions (i.e., quorum sensing activity) remained intact. 16S rRNA gene amplicon sequencing revealed a resilient community of 105 bacterial taxa, which remained in the treated sponges. These 105 taxa accounted for a relative abundance of 72-83% of the bacterial sponge microbiota of non-treated sponge fragments that have been cultured under the same conditions. We conclude that a sponge-specific resilient community stays biologically active under harmful environmental conditions, facilitating the resilience of the holobiont. In H. cnidata, bacteria are located in bacteriocytes, which may have contributed to the observed phenomenon.
Fairy circles are striking regularly sized and spaced, bare circles surrounded by Stipagrostis grasses that occur over thousands of square kilometres in Namibia. The mechanisms explaining their origin, shape, persistence and regularity remain controversial. One hypothesis for the formation of vegetation rings is based on the centrifugal expansion of a single individual grass plant, via clonal growth and die-back in the centre. Clonality could explain FC origin, shape and long-term persistence as well as their regularity, if one clone competes with adjacent clones. Here, we show that for virtually all tested fairy circles the periphery is not exclusively made up of genetically identical grasses, but these peripheral grasses belong to more than one unrelated genet. These results do not support a clonal explanation for fairy circles. Lack of clonality implies that a biological reason for their origin, shape and regularity must emerge from competition between near neighbor individuals within each fairy circle. Such lack of clonality also suggests a mismatch between longevity of fairy circles versus their constituent plants. Furthermore, our findings of lack of clonality have implications for some models of spatial patterning of fairy circles that are based on self-organization. Christian Kappel et al. examine the genetic composition of fairy circles, regular circular patterns of grasses in the Namib Desert, using ddRAD-seq. They find that these grasses are made up of multiple unrelated genets rather than genetically identical grasses, suggesting non-clonality.
The transfer of Microcystis aeruginosa from freshwater to estuaries has been described worldwide and salinity is reported as the main factor controlling the expansion of M. aeruginosa to coastal environments. Analyzing the expression levels of targeted genes and employing both targeted and non-targeted metabolomic approaches, this study investigated the effect of a sudden salt increase on the physiological and metabolic responses of two toxic M. aeruginosa strains separately isolated from fresh and brackish waters, respectively, PCC 7820 and 7806. Supported by differences in gene expressions and metabolic profiles, salt tolerance was found to be strain specific. An increase in salinity decreased the growth of M. aeruginosa with a lesser impact on the brackish strain. The production of intracellular microcystin variants in response to salt stress correlated well to the growth rate for both strains. Furthermore, the release of microcystins into the surrounding medium only occurred at the highest salinity treatment when cell lysis occurred. This study suggests that the physiological responses of M. aeruginosa involve the accumulation of common metabolites but that the intraspecific salt tolerance is based on the accumulation of specific metabolites. While one of these was determined to be sucrose, many others remain to be identified. Taken together, these results provide evidence that M. aeruginosa is relatively salt tolerant in the mesohaline zone and microcystin (MC) release only occurs when the capacity of the cells to deal with salt increase is exceeded.
Barite scales in geothermal installations are a highly unwanted effect of circulating deep saline fluids. They build up in the reservoir if supersaturated fluids are re-injected, leading to irreversible loss of injectivity. A model is presented for calculating the total expected barite precipitation. To determine the related injectivity decline over time, the spatial precipitation distribution in the subsurface near the injection well is assessed by modelling barite growth kinetics in a radially diverging Darcy flow domain. Flow and reservoir properties as well as fluid chemistry are chosen to represent reservoirs subject to geothermal exploration located in the North German Basin (NGB) and the Upper Rhine Graben (URG) in Germany. Fluids encountered at similar depths are hotter in the URG, while they are more saline in the NGB. The associated scaling amount normalised to flow rate is similar for both regions. The predicted injectivity decline after 10 years, on the other hand, is far greater for the NGB (64%) compared to the URG (24%), due to the temperature- and salinity-dependent precipitation rate. The systems in the NGB are at higher risk. Finally, a lightweight score is developed for approximating the injectivity loss using the Damkohler number, flow rate and total barite scaling potential. This formula can be easily applied to geothermal installations without running complex reactive transport simulations.
In this paper, we present the convergence rate analysis of the modified Landweber method under logarithmic source condition for nonlinear ill-posed problems. The regularization parameter is chosen according to the discrepancy principle. The reconstructions of the shape of an unknown domain for an inverse potential problem by using the modified Landweber method are exhibited.
Glacial-cycle simulations of the Antarctic Ice Sheet with the Parallel Ice Sheet Model (PISM)
(2020)
The Parallel Ice Sheet Model (PISM) is applied to the Antarctic Ice Sheet over the last two glacial cycles (approximate to 210 000 years) with a resolution of 16 km. An ensemble of 256 model runs is analyzed in which four relevant model parameters have been systematically varied using full-factorial parameter sampling. Parameters and plausible parameter ranges have been identified in a companion paper (Albrecht et al., 2020) and are associated with ice dynamics, climatic forcing, basal sliding and bed deformation and represent distinct classes of model uncertainties. The model is scored against both modern and geologic data, including reconstructed grounding-line locations, elevation-age data, ice thickness, surface velocities and uplift rates. An aggregated score is computed for each ensemble member that measures the overall model-data misfit, including measurement uncertainty in terms of a Gaussian error model (Briggs and Tarasov, 2013). The statistical method used to analyze the ensemble simulation results follows closely the simple averaging method described in Pollard et al. (2016).
This analysis reveals clusters of best-fit parameter combinations, and hence a likely range of relevant model and boundary parameters, rather than individual best-fit parameters. The ensemble of reconstructed histories of Antarctic Ice Sheet volumes provides a score-weighted likely range of sea-level contributions since the Last Glacial Maximum (LGM) of 9.4 +/- 4.1m (or 6.5 +/- 2.0 x 10(6) km(3)), which is at the upper range of most previous studies. The last deglaciation occurs in all ensemble simulations after around 12 000 years before present and hence after the meltwater pulse 1A (MWP1a). Our ensemble analysis also provides an estimate of parametric uncertainty bounds for the present-day state that can be used for PISM projections of future sea-level contributions from the Antarctic Ice Sheet.
Environmental protection efforts can only be effective in the long term with a reliable quantification of pollutant gas emissions as a first step to mitigation. Measurement and analysis strategies must permit the accurate extrapolation of emission values. We systematically analyzed the added value of applying modern machine learning methods in the process of monitoring emissions from naturally ventilated livestock buildings to the atmosphere. We considered almost 40 weeks of hourly emission values from a naturally ventilated dairy cattle barn in Northern Germany. We compared model predictions using 27 different scenarios of temporal sampling, multiple measures of model accuracy, and eight different regression approaches. The error of the predicted emission values with the tested measurement protocols was, on average, well below 20%. The sensitivity of the prediction to the selected training dataset was worse for the ordinary multilinear regression. Gradient boosting and random forests provided the most accurate and robust emission value predictions, accompanied by the second-smallest model errors. Most of the highly ranked scenarios involved six measurement periods, while the scenario with the best overall performance was: One measurement period in summer and three in the transition periods, each lasting for 14 days.
Multiple sclerosis (MS) is a chronic, inflammatory, autoimmune disease of the central nervous system (CNS) which is associated with lower life expectancy and disability. The experimental antigen-induced encephalomyelitis (EAE) in mice is a useful animal model of MS, which allows exploring the etiopathogenetic mechanisms and testing novel potential therapeutic drugs. A new therapeutic paradigm for the treatment of MS was introduced in 2010 through the sphingosine 1-phosphate (S1P) analogue fingolimod (FTY720, Gilenya(R)), which acts as a functional S1P(1) antagonist on T lymphocytes to deplete these cells from the blood. In this study, we synthesized two novel structures, ST-1893 and ST-1894, which are derived from fingolimod and chemically feature a morpholine ring in the polar head group. These compounds showed a selective S1P(1) activation profile and a sustained S1P(1) internalization in cultures of S1P(1)-overexpressing Chinese hamster ovary (CHO)-K1 cells, consistent with a functional antagonism. In vivo, both compounds induced a profound lymphopenia in mice. Finally, these substances showed efficacy in the EAE model, where they reduced clinical symptoms of the disease, and, on the molecular level, they reduced the T-cell infiltration and several inflammatory mediators in the brain and spinal cord. In summary, these data suggest that S1P(1)-selective compounds may have an advantage over fingolimod and siponimod, not only in MS but also in other autoimmune diseases.
This study, based on new and high quality in situ observations, quantifies for the first time, the individual contributions of light-absorbing aerosols (black carbon (BC), brown carbon (BrC) and dust) to aerosol absorption over the Indo-Gangetic Plain (IGP) and the Himalayan foothill region, a relatively poorly studied region with several sensitive ecosystems of global importance, as well as highly vulnerable populations. The annual and seasonal average single scattering albedo (SSA) over Kathmandu is the lowest of all the locations. The SSA over Kathmandu is < 0.89 during all seasons, which confirms the dominance of light-absorbing carbonaceous aerosols from local and regional sources over Kathmandu. It is observed here that the SSA decreases with increasing elevation, confirming the dominance of light absorbing carbonaceous aerosols at higher elevations. In contrast, the SSA over the IGP does not exhibit a pronounced spatial variation. BC dominates (>= 75%) the aerosol absorption over the IGP and the Himalayan foothills throughout the year. Higher BC concentration at elevated locations in the Himalayas leads to lower SSA at elevated locations in the Himalayas. The contribution of dust to aerosol absorption is higher throughout the year over the IGP than over the Himalayan foothills. The aerosol absorption over South Asia is very high, exceeding available observations over East Asia, and also exceeds previous model estimates. This quantification will be valuable as observational constraints to help improve regional simulations of climate change, impacts on the glaciers and the hydrological cycle, and will help to direct the focus towards BC as the main contributor to aerosol-induced warming in the region.
During the period 750-600 Ma ago, prior to the final break-up of the supercontinent Rodinia, the crust of both the North American Craton and Baltica was intruded by significant amounts of rift-related magmas originating from the mantle. In the Proterozoic crust of Southern Norway, the 580 Ma old Fen carbonatite-ultramafic complex is a representative of this type of rocks. In this paper, we report the occurrence of an ultramafic lamprophyre dyke which possibly is linked to the Fen complex, although Ar-40/Ar-39 data from phenocrystic phlogopite from the dyke gave an age of 686 +/- 9 Ma. The lamprophyre dyke was recently discovered in one of the Kongsberg silver mines at Vinoren, Norway. Whole rock geochemistry, geochronological and mineralogical data from the ultramafic lamprophyre dyke are presented aiming to elucidate its origin and possible geodynamic setting. From the whole-rock composition of the Vinoren dyke, the rock could be recognized as transitional between carbonatite and kimberlite-II (orangeite). From its diagnostic mineralogy, the rock is classified as aillikite. The compositions and xenocrystic nature of several of the major and accessory minerals from the Vinoren aillikite are characteristic for diamondiferous rocks (kimberlites/lamproites/UML): Phlogopite with kinoshitalite-rich rims, chromite-spinel-ulvospinel series, Mg- and Mn-rich ilmenites, rutile and lucasite-(Ce). We suggest that the aillikite melt formed during partial melting of a MARID (mica-amphibole-rutile-ilmenite-diopside)-like source under CO2 fluxing. The pre-rifting geodynamic setting of the Vinoren aillikite before the Rodinia supercontinent breakup suggests a relatively thick SCLM (Subcontinental Lithospheric Mantle) during this stage and might indicate a diamond-bearing source for the parental melt. This is in contrast to the about 100 Ma younger Fen complex, which were derived from a thin SCLM.
A simple experimental setup for temperature dependent mass spectrometric measurements has been constructed. It consists of a heated sample chamber and a mass spectrometer and allows for measurements under inert gas and ambient air. Based on initial measurements on two extruded polystyrene (XPS) samples a methodology for the data analysis has been developed. With this methodology the outgassing temperature of volatile compounds, which were used as blowing agents, has been identified. Furthermore, the composition of the blowing agents has been analyzed by temperature dependent mass spectra. The results indicate the use of ambient air in one material and a mixture of the banned blowing agents R142b and R22, both hydrochlorofluorocarbons (HCFC), in the other material. The here described methodology provides an easy to use approach to identify such compounds, for example as part of environmental or quality control.
Biogenic greenhouse gas emissions, e.g., of methane (CH4) and carbon dioxide (CO2) from inland waters, contribute substantially to global warming. In aquatic systems, dissolved greenhouse gases are highly heterogeneous in both space and time. To better understand the biological and physical processes that affect sources and sinks of both CH4 and CO2, their dissolved concentrations need to be measured with high spatial and temporal resolution. To achieve this goal, we developed the Fast-Response Automated Gas Equilibrator (FaRAGE) for real-time in situ measurement of dissolved CH4 and CO2 concentrations at the water surface and in the water column. FaRAGE can achieve an exceptionally short response time (t(95%) = 12 s when including the response time of the gas analyzer) while retaining an equilibration ratio of 62.6% and a measurement accuracy of 0.5% for CH4. A similar performance was observed for dissolved CO2 (t(95%) = 10 s, equilibration ratio 67.1 %). An equilibration ratio as high as 91.8% can be reached at the cost of a slightly increased response time (16 s). The FaRAGE is capable of continuously measuring dissolved CO2 and CH4 concentrations in the nM-to-submM (10(-9)-10(-3) mol L-1) range with a detection limit of subnM (10(-10) mol L-1), when coupling with a cavity ring-down greenhouse gas analyzer (Picarro GasScouter). FaRAGE allows for the possibility of mapping dissolved concentration in a "quasi" three-dimensional manner in lakes and provides an inexpensive alternative to other commercial gas equilibrators. It is simple to operate and suitable for continuous monitoring with a strong tolerance for suspended particles. While the FaRAGE is developed for inland waters, it can be also applied to ocean waters by tuning the gas-water mixing ratio. The FaRAGE is easily adapted to suit other gas analyzers expanding the range of potential applications, including nitrous oxide and isotopic composition of the gases.
Editorial
(2020)
Aerosol emissions from human activities are extensive and changing rapidly over Asia. Model simulations and satellite observations indicate a dipole pattern in aerosol emissions and loading between South Asia and East Asia, two of the most heavily polluted regions of the world. We examine the previously unexplored diverging trends in the existing dipole pattern of aerosols between East and South Asia using the high quality, two-decade long ground-based time series of observations of aerosol properties from the Aerosol Robotic Network (AERONET), from satellites (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)), and from model simulations (Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The data cover the period since 2001 for Kanpur (South Asia) and Beijing (East Asia), two locations taken as being broadly representative of the respective regions. Since 2010 a dipole in aerosol optical depth (AOD) is maintained, but the trend is reversed-the decrease in AOD over Beijing (East Asia) is rapid since 2010, being 17% less in current decade compared to first decade of twenty-first century, while the AOD over South Asia increased by 12% during the same period. Furthermore, we find that the aerosol composition is also changing over time. The single scattering albedo (SSA), a measure of aerosol's absorption capacity and related to aerosol composition, is slightly higher over Beijing than Kanpur, and has increased from 0.91 in 2002 to 0.93 in 2017 over Beijing and from 0.89 to 0.92 during the same period over Kanpur, confirming that aerosols in this region have on an average become more scattering in nature. These changes have led to a notable decrease in aerosol-induced atmospheric heating rate (HR) over both regions between the two decades, decreasing considerably more over East Asia (- 31%) than over South Asia (- 9%). The annual mean HR is lower now, it is still large (>= 0.6 K per day), which has significant climate implications. The seasonal trends in AOD, SSA and HR are more pronounced than their respective annual trends over both regions. The seasonal trends are caused mainly by the increase/decrease in anthropogenic aerosol emissions (sulfate, black carbon and organic carbon) while the natural aerosols (dust and sea salt) did not change significantly over South and East Asia during the last two decades. The MERRA-2 model is able to simulate the observed trends in AODs well but not the magnitude, while it also did not simulate the SSA values or trends well. These robust findings based on observations of key aerosol parameters and previously unrecognized diverging trends over South and East Asia need to be accounted for in current state-of-the-art climate models to ensure accurate quantification of the complex and evolving impact of aerosols on the regional climate over Asia.
Corona and the climate
(2020)
Compound natural hazards likeEl Ninoevents cause high damage to society, which to manage requires reliable risk assessments. Damage modelling is a prerequisite for quantitative risk estimations, yet many procedures still rely on expert knowledge, and empirical studies investigating damage from compound natural hazards hardly exist. A nationwide building survey in Peru after theEl Ninoevent 2017 - which caused intense rainfall, ponding water, flash floods and landslides - enables us to apply data-mining methods for statistical groundwork, using explanatory features generated from remote sensing products and open data. We separate regions of different dominant characteristics through unsupervised clustering, and investigate feature importance rankings for classifying damage via supervised machine learning. Besides the expected effect of precipitation, the classification algorithms select the topographic wetness index as most important feature, especially in low elevation areas. The slope length and steepness factor ranks high for mountains and canyons. Partial dependence plots further hint at amplified vulnerability in rural areas. An example of an empirical damage probability map, developed with a random forest model, is provided to demonstrate the technical feasibility.
We describe a new, original approach to the modelling of the Earth's magnetic field. The overall objective of this study is to reliably render fast variations of the core field and its secular variation. This method combines a sequential modelling approach, a Kalman filter, and a correlation-based modelling step. Sources that most significantly contribute to the field measured at the surface of the Earth are modelled. Their separation is based on strong prior information on their spatial and temporal behaviours. We obtain a time series of model distributions which display behaviours similar to those of recent models based on more classic approaches, particularly at large temporal and spatial scales. Interesting new features and periodicities are visible in our models at smaller time and spatial scales. An important aspect of our method is to yield reliable error bars for all model parameters. These errors, however, are only as reliable as the description of the different sources and the prior information used are realistic. Finally, we used a slightly different version of our method to produce candidate models for the thirteenth edition of the International Geomagnetic Reference Field.
To construct a coherent multi-modal percept, vertebrate brains extract low-level features (such as spatial and temporal frequencies) from incoming sensory signals. However, because frequency processing is lateralized with the right hemisphere favouring low frequencies while the left favours higher frequencies, this introduces asymmetries between the hemispheres. Here, we describe how this lateralization shapes the development of several cognitive domains, ranging from visuo-spatial and numerical cognition to language, social cognition, and even aesthetic appreciation, and leads to the emergence of asymmetries in behaviour. We discuss the neuropsychological and educational implications of these emergent asymmetries and suggest future research approaches.
Carbon nanodots revised
(2020)
Luminescent compounds obtained from the thermal reaction of citric acid and urea have been studied and utilized in different applications in the past few years. The identified reaction products range from carbon nitrides over graphitic carbon to distinct molecular fluorophores. On the other hand, the solid, non-fluorescent reaction product produced at higher temperatures has been found to be a valuable precursor for the CO2-laser-assisted carbonization reaction in carbon laser-patterning. This work addresses the question of structural identification of both, the fluorescent and non-fluorescent reaction products obtained in the thermal reaction of citric acid and urea. The reaction products produced during autoclave-microwave reactions in the melt were thoroughly investigated as a function of the reaction temperature and the reaction products were subsequently separated by a series of solvent extractions and column chromatography. The evolution of a green molecular fluorophore, namely HPPT, was confirmed and a full characterization study on its structure and photophysical properties was conducted. The additional blue fluorescence is attributed to oligomeric ureas, which was confirmed by complementary optical and structural characterization. These two components form strong hydrogen-bond networks which eventually react to form solid, semi-crystalline particles with a size of similar to 7 nm and an elemental composition of 46% C, 22% N, and 29% O. The structural features and properties of all three main components were investigated in a comprehensive characterization study.
Social epigenomics is a new field of research that studies how the social environment shapes the epigenome and how in turn the epigenome modulates behavior. We focus on describing known gene-environment interactions (GEIs) and epigenetic mechanisms in different mammalian social systems. To illustrate how epigenetic mechanisms integrate GEls, we highlight examples where epigenetic mechanisms are associated with social behaviors and with their maintenance through neuroendocrine, locomotor, and metabolic responses. We discuss future research trajectories and open questions for the emerging field of social epigenomics in nonmodel and naturally occurring social systems. Finally, we outline the technological advances that aid the study of epigenetic mechanisms in the establishment of GEIs and vice versa.
The sensitivity of key hydrologic variables and hydropower generation to climate change in the Lake Malawi and Shire River basins is assessed. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021-2050 and 2071-2100 are used. An annual temperature increase of 1 degrees C decreases mean lake level and outflow by 0.3 m and 17%, respectively, signifying the importance of intensified evaporation for Lake Malawi's water budget. Meanwhile, a +5% (-5%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows in the Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5 degrees C (3.5 degrees C) and -20% (-15%). The study further projects a reduction in annual hydropower production between 1% (RCP8.5) and 2.5% (RCP4.5) during 2021-2050 and between 5% (RCP4.5) and 24% (RCP8.5) during 2071-2100. The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change, e.g., longer low flow periods and/or higher discharge fluctuations, and thus uncertainty in the amount of electricity produced.
The occurrence of refugia beyond the arctic treeline and genetic adaptation therein play a crucial role of largely unknown effect size. While refugia have potential for rapidly colonizing the tundra under global warming, the taxa may be maladapted to the new environmental conditions. Understanding the genetic composition and age of refugia is thus crucial for predicting any migration response.
Here, we genotype 194 larch individuals from an similar to 1.8 km(2)area in northcentral Siberia on the southern Taimyr Peninsula by applying an assay of 16 nuclear microsatellite markers. For estimating the age of clonal individuals, we counted tree rings at sections along branches to establish a lateral growth rate that was then combined with geographic distance.
Findings reveal that the predominant reproduction type is clonal (58.76%) by short distance spreading of ramets. One outlier of clones 1 km apart could have been dispersed by reindeer. In clonal groups and within individuals, we find that somatic mutations accumulate with geographic distance. Clonal groups of two or more individuals are observed. Clonal age estimates regularly suggest individuals as old as 2,200 years, which coincides with a major environmental change that forced a treeline retreat in the region.
We conclude that individuals with clonal growth mode were naturally selected as it lowers the likely risk of extinction under a harsh environment. We discuss this legacy from the past that might now be a maladaptation and hinder expansion under currently strongly increasing temperatures.
The Paris Climate Agreement aims to keep temperature rise well below 2 degrees C. This implies mitigation costs as well as avoided climate damages. Here we show that independent of the normative assumptions of inequality aversion and time preferences, the agreement constitutes the economically optimal policy pathway for the century. To this end we consistently incorporate a damage-cost curve reproducing the observed relation between temperature and economic growth into the integrated assessment model DICE. We thus provide an intertemporally optimizing cost-benefit analysis of this century's climate problem. We account for uncertainties regarding the damage curve, climate sensitivity, socioeconomic future, and mitigation costs. The resulting optimal temperature is robust as can be understood from the generic temperature-dependence of the mitigation costs and the level of damages inferred from the observed temperature-growth relationship. Our results show that the politically motivated Paris Climate Agreement also represents the economically favourable pathway, if carried out properly.
Consensify
(2020)
A standard practise in palaeogenome analysis is the conversion of mapped short read data into pseudohaploid sequences, frequently by selecting a single high-quality nucleotide at random from the stack of mapped reads. This controls for biases due to differential sequencing coverage, but it does not control for differential rates and types of sequencing error, which are frequently large and variable in datasets obtained from ancient samples. These errors have the potential to distort phylogenetic and population clustering analyses, and to mislead tests of admixture using D statistics. We introduce Consensify, a method for generating pseudohaploid sequences, which controls for biases resulting from differential sequencing coverage while greatly reducing error rates. The error correction is derived directly from the data itself, without the requirement for additional genomic resources or simplifying assumptions such as contemporaneous sampling. For phylogenetic and population clustering analysis, we find that Consensify is less affected by artefacts than methods based on single read sampling. For D statistics, Consensify is more resistant to false positives and appears to be less affected by biases resulting from different laboratory protocols than other frequently used methods. Although Consensify is developed with palaeogenomic data in mind, it is applicable for any low to medium coverage short read datasets. We predict that Consensify will be a useful tool for future studies of palaeogenomes.
Soil structure, the complex arrangement of soil into aggregates and pore spaces, is a key feature of soils and soil biota. Among them, filamentous saprobic fungi have well-documented effects on soil aggregation. However, it is unclear what properties, or traits, determine the overall positive effect of fungi on soil aggregation. To achieve progress, it would be helpful to systematically investigate a broad suite of fungal species for their trait expression and the relation of these traits to soil aggregation. Here, we apply a trait-based approach to a set of 15 traits measured under standardized conditions on 31 fungal strains including Ascomycota, Basidiomycota, and Mucoromycota, all isolated from the same soil. We find large differences among these fungi in their ability to aggregate soil, including neutral to positive effects, and we document large differences in trait expression among strains. We identify biomass density, i.e., the density with which a mycelium grows (positive effects), leucine aminopeptidase activity (negative effects) and phylogeny as important factors explaining differences in soil aggregate formation (SAF) among fungal strains; importantly, growth rate was not among the important traits. Our results point to a typical suite of traits characterizing fungi that are good soil aggregators, and our findings illustrate the power of employing a trait-based approach to unravel biological mechanisms underpinning soil aggregation. Such an approach could now be extended also to other soil biota groups. In an applied context of restoration and agriculture, such trait information can inform management, for example to prioritize practices that favor the expression of more desirable fungal traits.
Globally, cardiovascular diseases are the leading cause of death in the aging population. While the clinical pathology of the aging heart is thoroughly characterized, underlying molecular mechanisms are still insufficiently clarified. The aim of the present study was to establish an in vitro model system of cardiomyocyte premature senescence, culturing heart muscle cells derived from neonatal C57Bl/6J mice for 21 days. Premature senescence of neonatal cardiac myocytes was induced by prolonged culture time in an oxygen-rich postnatal environment. Age-related changes in cellular function were determined by senescence-associated beta-galactosidase activity, increasing presence of cell cycle regulators, such as p16, p53, and p21, accumulation of protein aggregates, and restricted proteolysis in terms of decreasing (macro-)autophagy. Furthermore, the culture system was functionally characterized for alterations in cell morphology and contractility. An increase in cellular size associated with induced expression of atrial natriuretic peptides demonstrated a stress-induced hypertrophic phenotype in neonatal cardiomyocytes. Using the recently developed analytical software tool Myocyter, we were able to show a spatiotemporal constraint in spontaneous contraction behavior during cultivation. Within the present study, the 21-day culture of neonatal cardiomyocytes was defined as a functional model system of premature cardiac senescence to study age-related changes in cardiomyocyte contractility and autophagy.
Several large-scale cryosphere elements such as the Arctic summer sea ice, the mountain glaciers, the Greenland and West Antarctic Ice Sheet have changed substantially during the last century due to anthropogenic global warming. However, the impacts of their possible future disintegration on global mean temperature (GMT) and climate feedbacks have not yet been comprehensively evaluated. Here, we quantify this response using an Earth system model of intermediate complexity. Overall, we find a median additional global warming of 0.43 degrees C (interquartile range: 0.39-0.46 degrees C) at a CO2 concentration of 400 ppm. Most of this response (55%) is caused by albedo changes, but lapse rate together with water vapour (30%) and cloud feedbacks (15%) also contribute significantly. While a decay of the ice sheets would occur on centennial to millennial time scales, the Arctic might become ice-free during summer within the 21st century. Our findings imply an additional increase of the GMT on intermediate to long time scales. The disintegration of cryosphere elements such as the Arctic summer sea ice, mountain glaciers, Greenland and West Antarctica is associated with temperature and radiative feedbacks. In this work, the authors quantify these feedbacks and find an additional global warming of 0.43 degrees C.
Overnutrition contributes to insulin resistance, obesity and metabolic stress, initiating a loss of functional beta-cells and diabetes development. Whether these damaging effects are amplified in advanced age is barely investigated. Therefore, New Zealand Obese (NZO) mice, a well-established model for the investigation of human obesity-associated type 2 diabetes, were fed a metabolically challenging diet with a high-fat, carbohydrate restricted period followed by a carbohydrate intervention in young as well as advanced age. Interestingly, while young NZO mice developed massive hyperglycemia in response to carbohydrate feeding, leading to beta-cell dysfunction and cell death, aged counterparts compensated the increased insulin demand by persistent beta-cell function and beta-cell mass expansion. Beta-cell loss in young NZO islets was linked to increased expression of thioredoxin-interacting protein (TXNIP), presumably initiating an apoptosis-signaling cascade via caspase-3 activation. In contrast, islets of aged NZOs exhibited a sustained redox balance without changes in TXNIP expression, associated with higher proliferative potential by cell cycle activation. These findings support the relevance of a maintained proliferative potential and redox homeostasis for preserving islet functionality under metabolic stress, with the peculiarity that this adaptive response emerged with advanced age in diabetesprone NZO mice.
Background:
Cyberhate is a growing form of online aggression against a person or a group based on race, ethnicity, nationality, sexual orientation, gender, religion, or disability. The present study aims to examine psychometric properties of the Coping with Cyberhate Questionnaire, the prevalence of coping strategies in Spanish adolescents, differences in coping strategies based in sex, age, and victim status, and the association between coping with cyberhate and adolescents' mental well-being.
Method:
The sample consisted of 1,005 adolescents between 12 and 18 years old (Mage = 14.28 years, SD = 1.63; 51.9% girls) who completed self-report measures on coping strategies, victimization status, and mental well-being.
Results:
The results of confirmatory factor analyses showed a structure for the Coping with Cyberhate Questionnaire composed of six factors, namely Distal advice, Assertiveness, Helplessness/Selfblame, Close support, Technical coping, and Retaliation. It demonstrated acceptable internal consistency. The three most frequently endorsed coping strategies were Technical coping, Close support, and Assertiveness. In addition, lower Helplessness/Self-blame, and higher Close-support, Assertiveness, and Distal advice were significantly related to adolescents' better mental well-being.
Conclusion:
Prevention programs that educate adolescents about how to deal with cyberhate are needed.
Projected changes in compound flood hazard from riverine and coastal floods in northwestern Europe
(2020)
Compound flooding in coastal regions, that is, the simultaneous or successive occurrence of high sea levels and high river flows, is expected to increase in a warmer world. To date, however, there is no robust evidence on projected changes in compound flooding for northwestern Europe. We combine projected storm surges and river floods with probabilistic, localized relative sea-level rise (SLR) scenarios to assess the future compound flood hazard over northwestern coastal Europe in the high (RCP8.5) emission scenario. We use high-resolution, dynamically downscaled regional climate models (RCM) to drive a storm surge model and a hydrological model, and analyze the joint occurrence of high coastal water levels and associated river peaks in a multivariate copula-based approach. The RCM-forced multimodel mean reasonably represents the observed spatial pattern of the dependence strength between annual maxima surge and peak river discharge, although substantial discrepancies exist between observed and simulated dependence strength. All models overestimate the dependence strength, possibly due to limitations in model parameterizations. This bias affects compound flood hazard estimates and requires further investigation. While our results suggest decreasing compound flood hazard over the majority of sites by 2050s (2040-2069) compared to the reference period (1985-2005), an increase in projected compound flood hazard is limited to around 34% of the sites. Further, we show the substantial role of SLR, a driver of compound floods, which has frequently been neglected. Our findings highlight the need to be aware of the limitations of the current generation of Earth system models in simulating coastal compound floods.
The smell of hunger
(2020)
When individuals exchange helpful acts reciprocally, increasing the benefit of the receiver can enhance its propensity to return a favour, as pay-offs are typically correlated in iterated interactions. Therefore, reciprocally cooperating animals should consider the relative benefit for the receiver when deciding to help a conspecific. Norway rats (Rattus norvegicus) exchange food reciprocally and thereby take into account both the cost of helping and the potential benefit to the receiver. By using a variant of the sequential iterated prisoner's dilemma paradigm, we show that rats may determine the need of another individual by olfactory cues alone. In an experimental food-exchange task, test subjects were provided with odour cues from hungry or satiated conspecifics located in a different room. Our results show that wild-type Norway rats provide help to a stooge quicker when they receive odour cues from a hungry rather than from a satiated conspecific. Using chemical analysis by gas chromatography-mass spectrometry (GC-MS), we identify seven volatile organic compounds that differ in their abundance between hungry and satiated rats. Combined, this "smell of hunger" can apparently serve as a reliable cue of need in reciprocal cooperation, which supports the hypothesis of honest signalling.
The Flood Damage Database HOWAS 21 contains object-specific flood damage data resulting from fluvial, pluvial and groundwater flooding. The datasets incorporate various variables of flood hazard, exposure, vulnerability and direct tangible damage at properties from several economic sectors. The main purpose of development of HOWAS 21 was to support forensic flood analysis and the derivation of flood damage models. HOWAS 21 was first developed for Germany and currently almost exclusively contains datasets from Germany. However, its scope has recently been enlarged with the aim to serve as an international flood damage database; e.g. its web application is now available in German and English. This paper presents the recent advancements of HOWAS 21 and highlights exemplary analyses to demonstrate the use of HOWAS 21 flood damage data. The data applications indicate a large potential of the database for fostering a better understanding and estimation of the consequences of flooding.
Hazelnuts are rarely cultivated in Germany, although they are a valuable source for macro- and micronutrients and can thus contribute to a healthy diet. Near the present, 15 varieties were cultivated in Thuringia, Germany, as a pilot study for further research. The aim of our study was to evaluate the micro- and macronutrient composition of representative, randomly mixed samples of the 15 different hazelnut cultivars. Protein, fat, and fiber contents were determined using established methods. Fatty acids, tocopherols, minerals, trace elements, and ultra-trace elements were analyzed using gas chromatography, high-performance liquid chromatography, and inductively coupled plasma triple quadrupole mass-spectrometry, respectively. We found that the different hazelnut varieties contained valuable amounts of fat, protein, dietary fiber, minerals, trace elements, and alpha-tocopherol, however, in different quantities. The variations in nutrient composition were independent of growth conditions, which were identical for all hazelnut varieties. Therefore, each hazelnut cultivar has its specific nutrient profile.