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The "Lomonosov" space project is lead by Lomonosov Moscow State University in collaboration with the following key partners: Joint Institute for Nuclear Research, Russia, University of California, Los Angeles (USA), University of Pueblo (Mexico), Sungkyunkwan University (Republic of Korea) and with Russian space industry organi-zations to study some of extreme phenomena in space related to astrophysics, astroparticle physics, space physics, and space biology. The primary goals of this experiment are to study:
-Ultra-high energy cosmic rays (UHECR) in the energy range of the Greizen-ZatsepinKuzmin (GZK) cutoff;
-Ultraviolet (UV) transient luminous events in the upper atmosphere;
-Multi-wavelength study of gamma-ray bursts in visible, UV, gamma, and X-rays;
-Energetic trapped and precipitated radiation (electrons and protons) at low-Earth orbit (LEO) in connection with global geomagnetic disturbances;
-Multicomponent radiation doses along the orbit of spacecraft under different geomagnetic conditions and testing of space segments of optical observations of space-debris and other space objects;
-Instrumental vestibular-sensor conflict of zero-gravity phenomena during space flight.
This paper is directed towards the general description of both scientific goals of the project and scientific equipment on board the satellite. The following papers of this issue are devoted to detailed descriptions of scientific instruments.
Background: With increasing age neuromuscular deficits (e.g., sarcopenia) may result in impaired physical performance and an increased risk for falls. Prominent intrinsic fall-risk factors are age-related decreases in balance and strength / power performance as well as cognitive decline. Additional studies are needed to develop specifically tailored exercise programs for older adults that can easily be implemented into clinical practice. Thus, the objective of the present trial is to assess the effects of a fall prevention program that was developed by an interdisciplinary expert panel on measures of balance, strength / power, body composition, cognition, psychosocial well-being, and falls self-efficacy in healthy older adults. Additionally, the time-related effects of detraining are tested.
Methods/Design: Healthy old people (n = 54) between the age of 65 to 80 years will participate in this trial. The testing protocol comprises tests for the assessment of static / dynamic steady-state balance (i.e., Sharpened Romberg Test, instrumented gait analysis), proactive balance (i.e., Functional Reach Test; Timed Up and Go Test), reactive balance (i.e., perturbation test during bipedal stance; Push and Release Test), strength (i.e., hand grip strength test; Chair Stand Test), and power (i.e., Stair Climb Power Test; countermovement jump). Further, body composition will be analysed using a bioelectrical impedance analysis system. In addition, questionnaires for the assessment of psychosocial (i.e., World Health Organisation Quality of Life Assessment-Bref), cognitive (i.e., Mini Mental State Examination), and fall risk determinants (i.e., Fall Efficacy Scale -International) will be included in the study protocol. Participants will be randomized into two intervention groups or the control / waiting group. After baseline measures, participants in the intervention groups will conduct a 12-week balance and strength / power exercise intervention 3 times per week, with each training session lasting 30 min. (actual training time). One intervention group will complete an extensive supervised training program, while the other intervention group will complete a short version (` 3 times 3') that is home-based and controlled by weekly phone calls. Post-tests will be conducted right after the intervention period. Additionally, detraining effects will be measured 12 weeks after program cessation. The control group / waiting group will not participate in any specific intervention during the experimental period, but will receive the extensive supervised program after the experimental period.
Discussion: It is expected that particularly the supervised combination of balance and strength / power training will improve performance in variables of balance, strength / power, body composition, cognitive function, psychosocial well-being, and falls self-efficacy of older adults. In addition, information regarding fall risk assessment, dose-response-relations, detraining effects, and supervision of training will be provided. Further, training-induced health-relevant changes, such as improved performance in activities of daily living, cognitive function, and quality of life, as well as a reduced risk for falls may help to lower costs in the health care system. Finally, practitioners, therapists, and instructors will be provided with a scientifically evaluated feasible, safe, and easy-to-administer exercise program for fall prevention.
Abiotic stresses cause oxidative damage in plants. Here, we demonstrate that foliar application of an extract from the seaweed Ascophyllum nodosum, SuperFifty (SF), largely prevents paraquat (PQ)-induced oxidative stress in Arabidopsis thaliana. While PQ-stressed plants develop necrotic lesions, plants pre-treated with SF (i.e., primed plants) were unaffected by PQ. Transcriptome analysis revealed induction of reactive oxygen species (ROS) marker genes, genes involved in ROS-induced programmed cell death, and autophagy-related genes after PQ treatment. These changes did not occur in PQ-stressed plants primed with SF. In contrast, upregulation of several carbohydrate metabolism genes, growth, and hormone signaling as well as antioxidant-related genes were specific to SF-primed plants. Metabolomic analyses revealed accumulation of the stress-protective metabolite maltose and the tricarboxylic acid cycle intermediates fumarate and malate in SF-primed plants. Lipidome analysis indicated that those lipids associated with oxidative stress-induced cell death and chloroplast degradation, such as triacylglycerols (TAGs), declined upon SF priming. Our study demonstrated that SF confers tolerance to PQ-induced oxidative stress in A. thaliana, an effect achieved by modulating a range of processes at the transcriptomic, metabolic, and lipid levels.
Flooding is assessed as the most important natural hazard in Europe, causing thousands of deaths, affecting millions of people and accounting for large economic losses in the past decade. Little is known about the damage processes associated with extreme rainfall in cities, due to a lack of accurate, comparable and consistent damage data. The objective of this study is to investigate the impacts of extreme rainfall on residential buildings and how affected households coped with these impacts in terms of precautionary and emergency actions. Analyses are based on a unique dataset of damage characteristics and a wide range of potential damage explaining variables at the household level, collected through computer-aided telephone interviews (CATI) and an online survey. Exploratory data analyses based on a total of 859 completed questionnaires in the cities of Munster (Germany) and Amsterdam (the Netherlands) revealed that the uptake of emergency measures is related to characteristics of the hazardous event. In case of high water levels, more efforts are made to reduce damage, while emergency response that aims to prevent damage is less likely to be effective. The difference in magnitude of the events in Munster and Amsterdam, in terms of rainfall intensity and water depth, is probably also the most important cause for the differences between the cities in terms of the suffered financial losses. Factors that significantly contributed to damage in at least one of the case studies are water contamination, the presence of a basement in the building and people's awareness of the upcoming event. Moreover, this study confirms conclusions by previous studies that people's experience with damaging events positively correlates with precautionary behaviour. For improving future damage data acquisition, we recommend the inclusion of cell phones in a CATI survey to avoid biased sampling towards certain age groups.
Accurate time series representation of paleoclimatic proxy records is challenging because such records involve dating errors in addition to proxy measurement errors. Rigorous attention is rarely given to age uncertainties in paleoclimatic research, although the latter can severely bias the results of proxy record analysis. Here, we introduce a Bayesian approach to represent layer-counted proxy records - such as ice cores, sediments, corals, or tree rings - as sequences of probability distributions on absolute, error-free time axes. The method accounts for both proxy measurement errors and uncertainties arising from layer-counting-based dating of the records. An application to oxygen isotope ratios from the North Greenland Ice Core Project (NGRIP) record reveals that the counting errors, although seemingly small, lead to substantial uncertainties in the final representation of the oxygen isotope ratios. In particular, for the older parts of the NGRIP record, our results show that the total uncertainty originating from dating errors has been seriously underestimated. Our method is next applied to deriving the overall uncertainties of the Suigetsu radiocarbon comparison curve, which was recently obtained from varved sediment cores at Lake Suigetsu, Japan. This curve provides the only terrestrial radiocarbon comparison for the time interval 12.5-52.8 kyr BP. The uncertainties derived here can be readily employed to obtain complete error estimates for arbitrary radiometrically dated proxy records of this recent part of the last glacial interval.
The Net Reclassification Improvement (NRI) has become a popular metric for evaluating improvement in disease prediction models through the past years. The concept is relatively straightforward but usage and interpretation has been different across studies. While no thresholds exist for evaluating the degree of improvement, many studies have relied solely on the significance of the NRI estimate. However, recent studies recommend that statistical testing with the NRI should be avoided. We propose using confidence ellipses around the estimated values of event and non-event NRIs which might provide the best measure of variability around the point estimates. Our developments are illustrated using practical examples from EPIC-Potsdam study.
Background
High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods.
Methods
We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort.
Results
We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis.
Conclusions
We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods.
Past climatic change can be reconstructed from sedimentary archives by a number of proxies. However, few methods exist to directly estimate hydrological changes and even fewer result in quantitative data, impeding our understanding of the timing, magnitude and mechanisms of hydrological changes.
Here we present a novel approach based on delta H-2 values of sedimentary lipid biomarkers in combination with plant physiological modeling to extract quantitative information on past changes in relative humidity. Our initial application to an annually laminated lacustrine sediment sequence from western Europe deposited during the Younger Dryas cold period revealed relative humidity changes of up to 15% over sub-centennial timescales, leading to major ecosystem changes, in agreement with palynological data from the region. We show that by combining organic geochemical methods and mechanistic plant physiological models on well characterized lacustrine archives it is possible to extract quantitative ecohydrological parameters from sedimentary lipid biomarker delta H-2 data.
A flexible approach to assess fluorescence decay functions in complex energy transfer systems
(2015)
Background: Time-correlated Forster resonance energy transfer (FRET) probes molecular distances with greater accuracy than intensity-based calculation of FRET efficiency and provides a powerful tool to study biomolecular structure and dynamics. Moreover, time-correlated photon count measurements bear additional information on the variety of donor surroundings allowing more detailed differentiation between distinct structural geometries which are typically inaccessible to general fitting solutions.
Results: Here we develop a new approach based on Monte Carlo simulations of time-correlated FRET events to estimate the time-correlated single photon counts (TCSPC) histograms in complex systems. This simulation solution assesses the full statistics of time-correlated photon counts and distance distributions of fluorescently labeled biomolecules. The simulations are consistent with the theoretical predictions of the dye behavior in FRET systems with defined dye distances and measurements of randomly distributed dye solutions. We validate the simulation results using a highly heterogeneous aggregation system and explore the conditions to use this tool in complex systems.
Conclusion: This approach is powerful in distinguishing distance distributions in a wide variety of experimental setups, thus providing a versatile tool to accurately distinguish between different structural assemblies in highly complex systems.
The outermost cell layer of plants, the epidermis, and its outer (lateral) membrane domain facing the environment are continuously challenged by biotic and abiotic stresses. Therefore, the epidermis and the outer membrane domain provide important selective and protective barriers. However, only a small number of specifically outer membrane-localized proteins are known. Similarly, molecular mechanisms underlying the trafficking and the polar placement of outer membrane domain proteins require further exploration. Here, we demonstrate that ACTIN7 (ACT7) mediates trafficking of the PENETRATION3 (PEN3) outer membrane protein from the trans-Golgi network (TGN) to the plasma membrane in the root epidermis of Arabidopsis (Arabidopsis thaliana) and that actin function contributes to PEN3 endocytic recycling. In contrast to such generic ACT7-dependent trafficking from the TGN, the EXOCYST84b (EXO84b) tethering factor mediates PEN3 outer-membrane polarity. Moreover, precise EXO84b placement at the outer membrane domain itself requires ACT7 function. Hence, our results uncover spatially and mechanistically distinct requirements for ACT7 function during outer lateral membrane cargo trafficking and polarity establishment. They further identify an exocyst tethering complex mediator of outer lateral membrane cargo polarity.
Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making.
Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop-and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
Liverwort Blasia pusilla L. recruits soil nitrogen-fixing cyanobacteria of genus Nostoc as symbiotic partners. In this work we compared Nostoc community composition inside the plants and in the soil around them from two distant locations in Northern Norway. STRR fingerprinting and 16S rDNA phylogeny reconstruction showed a remarkable local diversity among isolates assigned to several Nostoc clades. An extensive web of negative allelopathic interactions was recorded at an agricultural site, but not at the undisturbed natural site. The cell extracts of the cyanobacteria did not show antimicrobial activities, but four isolates were shown to be cytotoxic to human cells. The secondary metabolite profiles of the isolates were mapped by MALDI-TOF MS, and the most prominent ions were further analyzed by Q-TOF for MS/MS aided identification. Symbiotic isolates produced a great variety of small peptide-like substances, most of which lack any record in the databases. Among identified compounds we found microcystin and nodularin variants toxic to eukaryotic cells. Microcystin producing chemotypes were dominating as symbiotic recruits but not in the free-living community. In addition, we were able to identify several novel aeruginosins and banyaside-like compounds, as well as nostocyclopeptides and nosperin.
A comprehensive hydrometeorological dataset is presented spanning the period 1 January 201131 December 2014 to improve the understanding of the hydrological processes leading to flash floods and the relation between rainfall, runoff, erosion and sediment transport in a mesoscale catchment (Auzon, 116 km(2)) of the Mediterranean region. Badlands are present in the Auzon catchment and well connected to high-gradient channels of bedrock rivers which promotes the transfer of suspended solids downstream. The number of observed variables, the various sensors involved (both in situ and remote) and the space-time resolution (similar to km(2), similar to min) of this comprehensive dataset make it a unique contribution to research communities focused on hydrometeorology, surface hydrology and erosion. Given that rainfall is highly variable in space and time in this region, the observation system enables assessment of the hydrological response to rainfall fields. Indeed, (i) rainfall data are provided by rain gauges (both a research network of 21 rain gauges with a 5 min time step and an operational network of 10 rain gauges with a 5 min or 1 h time step), S-band Doppler dual-polarization radars (1 km(2), 5 min resolution), disdrometers (16 sensors working at 30 s or 1 min time step) and Micro Rain Radars (5 sensors, 100m height resolution). Additionally, during the special observation period (SOP-1) of the HyMeX (Hydrological Cycle in the Mediterranean Experiment) project, two X-band radars provided precipitation measurements at very fine spatial and temporal scales (1 ha, 5 min). (ii) Other meteorological data are taken from the operational surface weather observation stations of Meteo-France (including 2m air temperature, atmospheric pressure, 2 m relative humidity, 10m wind speed and direction, global radiation) at the hourly time resolution (six stations in the region of interest). (iii) The monitoring of surface hydrology and suspended sediment is multi-scale and based on nested catchments. Three hydrometric stations estimate water discharge at a 2-10 min time resolution. Two of these stations also measure additional physico-chemical variables (turbidity, temperature, conductivity) and water samples are collected automatically during floods, allowing further geochemical characterization of water and suspended solids. Two experimental plots monitor overland flow and erosion at 1 min time resolution on a hillslope with vineyard. A network of 11 sensors installed in the intermittent hydrographic network continuously measures water level and water temperature in headwater subcatchments (from 0.17 to 116 km(2)) at a time resolution of 2-5 min. A network of soil moisture sensors enables the continuous measurement of soil volumetric water content at 20 min time resolution at 9 sites. Additionally, concomitant observations (soil moisture measurements and stream gauging) were performed during floods between 2012 and 2014. Finally, this dataset is considered appropriate for understanding the rainfall variability in time and space at fine scales, improving areal rainfall estimations and progressing in distributed hydrological and erosion modelling.
In a recent paper, the Lefschetz number for endomorphisms (modulo trace class operators) of sequences of trace class curvature was introduced. We show that this is a well defined, canonical extension of the classical Lefschetz number and establish the homotopy invariance of this number. Moreover, we apply the results to show that the Lefschetz fixed point formula holds for geometric quasiendomorphisms of elliptic quasicomplexes.
Background: Medical training is very demanding and associated with a high prevalence of psychological distress. Compared to the general population, medical students are at a greater risk of developing a psychological disorder. Various attempts of stress management training in medical school have achieved positive results on minimizing psychological distress; however, there are often limitations. Therefore, the use of a rigorous scientific method is needed. The present study protocol describes a randomized controlled trial to examine the effectiveness of a specifically developed mindfulness-based stress prevention training for medical students that includes selected elements of cognitive behavioral strategies (MediMind).
Methods/Design: This study protocol presents a prospective randomized controlled trial, involving four assessment time points: baseline, post-intervention, one-year follow-up and five-year follow-up. The aims include evaluating the effect on stress, coping, psychological morbidity and personality traits with validated measures. Participants are allocated randomly to one of three conditions: MediMind, Autogenic Training or control group. Eligible participants are medical or dental students in the second or eighth semester of a German university. They form a population of approximately 420 students in each academic term. A final total sample size of 126 (at five-year follow-up) is targeted. The trainings (MediMind and Autogenic Training) comprise five weekly sessions lasting 90 minutes each. MediMind will be offered to participants of the control group once the five-year follow-up is completed. The allotment is randomized with a stratified allocation ratio by course of studies, semester, and gender. After descriptive statistics have been evaluated, inferential statistical analysis will be carried out with a repeated measures ANOVA-design with interactions between time and group. Effect sizes will be calculated using partial η-square values.
Discussion: Potential limitations of this study are voluntary participation and the risk of attrition, especially concerning participants that are allocated to the control group. Strengths are the study design, namely random allocation, follow-up assessment, the use of control groups and inclusion of participants at different stages of medical training with the possibility of differential analysis.
We show that self-consistent partial synchrony in globally coupled oscillatory ensembles is a general phenomenon. We analyze in detail appearance and stability properties of this state in possibly the simplest setup of a biharmonic Kuramoto-Daido phase model as well as demonstrate the effect in limit-cycle relaxational Rayleigh oscillators. Such a regime extends the notion of splay state from a uniform distribution of phases to an oscillating one. Suitable collective observables such as the Kuramoto order parameter allow detecting the presence of an inhomogeneous distribution. The characteristic and most peculiar property of self-consistent partial synchrony is the difference between the frequency of single units and that of the macroscopic field.
The unusual mix of morphological traits displayed by extinct South American native ungulates (SANUs) confounded both Charles Darwin, who first discovered them, and Richard Owen, who tried to resolve their relationships. Here we report an almost complete mitochondrial genome for the litoptern Macrauchenia. Our dated phylogenetic tree places Macrauchenia as sister to Perissodactyla, but close to the radiation of major lineages within Laurasiatheria. This position is consistent with a divergence estimate of B66Ma (95% credibility interval, 56.64-77.83 Ma) obtained for the split between Macrauchenia and other Panperissodactyla. Combined with their morphological distinctiveness, this evidence supports the positioning of Litopterna (possibly in company with other SANU groups) as a separate order within Laurasiatheria. We also show that, when using strict criteria, extinct taxa marked by deep divergence times and a lack of close living relatives may still be amenable to palaeogenomic analysis through iterative mapping against more distant relatives.
A model analysis of mechanisms for radial microtubular patterns at root hair initiation sites
(2016)
Plant cells have two main modes of growth generating anisotropic structures. Diffuse growth where whole cell walls extend in specific directions, guided by anisotropically positioned cellulose fibers, and tip growth, with inhomogeneous addition of new cell wall material at the tip of the structure. Cells are known to regulate these processes via molecular signals and the cytoskeleton. Mechanical stress has been proposed to provide an input to the positioning of the cellulose fibers via cortical microtubules in diffuse growth. In particular, a stress feedback model predicts a circumferential pattern of fibers surrounding apical tissues and growing primordia, guided by the anisotropic curvature in such tissues. In contrast, during the initiation of tip growing root hairs, a star-like radial pattern has recently been observed. Here, we use detailed finite element models to analyze how a change in mechanical properties at the root hair initiation site can lead to star-like stress patterns in order to understand whether a stress-based feedback model can also explain the microtubule patterns seen during root hair initiation. We show that two independent mechanisms, individually or combined, can be sufficient to generate radial patterns. In the first, new material is added locally at the position of the root hair. In the second, increased tension in the initiation area provides a mechanism. Finally, we describe how a molecular model of Rho-of-plant (ROP) GTPases activation driven by auxin can position a patch of activated ROP protein basally along a 2D root epidermal cell plasma membrane, paving the way for models where mechanical and molecular mechanisms cooperate in the initial placement and outgrowth of root hairs.
The knowledge of the contemporary in situ stress state is a key issue for safe and sustainable subsurface engineering. However, information on the orientation and magnitudes of the stress state is limited and often not available for the areas of interest. Therefore 3-D geomechanical-numerical modelling is used to estimate the in situ stress state and the distance of faults from failure for application in subsurface engineering. The main challenge in this approach is to bridge the gap in scale between the widely scattered data used for calibration of the model and the high resolution in the target area required for the application. We present a multi-stage 3-D geomechanical-numerical approach which provides a state-of-the-art model of the stress field for a reservoir-scale area from widely scattered data records. Therefore, we first use a large-scale regional model which is calibrated by available stress data and provides the full 3-D stress tensor at discrete points in the entire model volume. The modelled stress state is used subsequently for the calibration of a smaller-scale model located within the large-scale model in an area without any observed stress data records. We exemplify this approach with two-stages for the area around Munich in the German Molasse Basin. As an example of application, we estimate the scalar values for slip tendency and fracture potential from the model results as measures for the criticality of fault reactivation in the reservoir-scale model. The modelling results show that variations due to uncertainties in the input data are mainly introduced by the uncertain material properties and missing S-Hmax magnitude estimates needed for a more reliable model calibration. This leads to the conclusion that at this stage the model's reliability depends only on the amount and quality of available stress information rather than on the modelling technique itself or on local details of the model geometry. Any improvements in modelling and increases in model reliability can only be achieved using more high-quality data for calibration.
Background: Cysteine is a component in organic compounds including glutathione that have been implicated in the adaptation of plants to stresses. O-acetylserine (thiol) lyase (OAS-TL) catalyses the final step of cysteine biosynthesis. OAS-TL enzyme isoforms are localised in the cytoplasm, the plastids and mitochondria but the contribution of individual OAS-TL isoforms to plant sulphur metabolism has not yet been fully clarified.
Results: The seedling lethal phenotype of the Arabidopsis onset of leaf death3-1 (old3-1) mutant is due to a point mutation in the OAS-A1 gene, encoding the cytosolic OAS-TL. The mutation causes a single amino acid substitution from Gly(162) to Glu(162), abolishing old3-1 OAS-TL activity in vitro. The old3-1 mutation segregates as a monogenic semidominant trait when backcrossed to its wild type accession Landsberg erecta (Ler-0) and the Di-2 accession. Consistent with its semi-dominant behaviour, wild type Ler-0 plants transformed with the mutated old3-1 gene, displayed the early leaf death phenotype. However, the old3-1 mutation segregates in an 11: 4: 1 (wild type: semi-dominant: mutant) ratio when backcrossed to the Colombia-0 and Wassilewskija accessions. Thus, the early leaf death phenotype depends on two semi-dominant loci. The second locus that determines the old3-1 early leaf death phenotype is referred to as odd-ler (for old3 determinant in the Ler accession) and is located on chromosome 3. The early leaf death phenotype is temperature dependent and is associated with increased expression of defence-response and oxidative-stress marker genes. Independent of the presence of the odd-ler gene, OAS-A1 is involved in maintaining sulphur and thiol levels and is required for resistance against cadmium stress.
Conclusions: The cytosolic OAS-TL is involved in maintaining organic sulphur levels. The old3-1 mutation causes genome-dependent and independent phenotypes and uncovers a novel function for the mutated OAS-TL in cell death regulation.
The polar and subtropical jet streams are strong upper-level winds with a crucial influence on weather throughout the Northern Hemisphere midlatitudes. In particular, the polar jet is located between cold arctic air to the north and warmer subtropical air to the south. Strongly meandering states therefore often lead to extreme surface weather.
Some algorithms exist which can detect the 2-D (latitude and longitude) jets' core around the hemisphere, but all of them use a minimal threshold to determine the subtropical and polar jet stream. This is particularly problematic for the polar jet stream, whose wind velocities can change rapidly from very weak to very high values and vice versa.
We develop a network-based scheme using Dijkstra's shortest-path algorithm to detect the polar and subtropical jet stream core. This algorithm not only considers the commonly used wind strength for core detection but also takes wind direction and climatological latitudinal position into account. Furthermore, it distinguishes between polar and subtropical jet, and between separate and merged jet states.
The parameter values of the detection scheme are optimized using simulated annealing and a skill function that accounts for the zonal-mean jet stream position (Rikus, 2015). After the successful optimization process, we apply our scheme to reanalysis data covering 1979-2015 and calculate seasonal-mean probabilistic maps and trends in wind strength and position of jet streams.
We present longitudinally defined probability distributions of the positions for both jets for all on the Northern Hemisphere seasons. This shows that winter is characterized by two well-separated jets over Europe and Asia (ca. 20 degrees W to 140 degrees E). In contrast, summer normally has a single merged jet over the western hemisphere but can have both merged and separated jet states in the eastern hemisphere.
With this algorithm it is possible to investigate the position of the jets' cores around the hemisphere and it is therefore very suitable to analyze jet stream patterns in observations and models, enabling more advanced model-validation.
The DNA origami technique has great potential for the development of brighter and more sensitive reporters for fluorescence based detection schemes such as a microbead-based assay in diagnostic applications. The nanostructures can be programmed to include multiple dye molecules to enhance the measured signal as well as multiple probe strands to increase the binding strength of the target oligonucleotide to these nanostructures. Here we present a proof-of-concept study to quantify short oligonucleotides by developing a novel DNA origami based reporter system, combined with planar microbead assays. Analysis of the assays using the VideoScan digital imaging platform showed DNA origami to be a more suitable reporter candidate for quantification of the target oligonucleotides at lower concentrations than a conventional reporter that consists of one dye molecule attached to a single stranded DNA. Efforts have been made to conduct multiplexed analysis of different targets as well as to enhance fluorescence signals obtained from the reporters. We therefore believe that the quantification of short oligonucleotides that exist in low copy numbers is achieved in a better way with the DNA origami nanostructures as reporters.
The use of monoclonal antibodies is ubiquitous in science and biomedicine but the generation and validation process of antibodies is nevertheless complicated and time-consuming. To address these issues we developed a novel selective technology based on an artificial cell surface construct by which secreted antibodies were connected to the corresponding hybridoma cell when they possess the desired antigen-specificity. Further the system enables the selection of desired isotypes and the screening for potential cross-reactivities in the same context. For the design of the construct we combined the transmembrane domain of the EGF-receptor with a hemagglutinin epitope and a biotin acceptor peptide and performed a transposon-mediated transfection of myeloma cell lines. The stably transfected myeloma cell line was used for the generation of hybridoma cells and an antigen- and isotype-specific screening method was established. The system has been validated for globular protein antigens as well as for haptens and enables a fast and early stage selection and validation of monoclonal antibodies in one step.
Background: For omics experiments, detailed characterisation of experimental material with respect to its genetic features, its cultivation history and its treatment history is a requirement for analyses by bioinformatics tools and for publication needs. Furthermore, meta-analysis of several experiments in systems biology based approaches make it necessary to store this information in a standardised manner, preferentially in relational databases. In the Golm Plant Database System, we devised a data management system based on a classical Laboratory Information Management System combined with web-based user interfaces for data entry and retrieval to collect this information in an academic environment.
Results: The database system contains modules representing the genetic features of the germplasm, the experimental conditions and the sampling details. In the germplasm module, genetically identical lines of biological material are generated by defined workflows, starting with the import workflow, followed by further workflows like genetic modification (transformation), vegetative or sexual reproduction. The latter workflows link lines and thus create pedigrees. For experiments, plant objects are generated from plant lines and united in so-called cultures, to which the cultivation conditions are linked. Materials and methods for each cultivation step are stored in a separate ACCESS database of the plant cultivation unit. For all cultures and thus every plant object, each cultivation site and the culture's arrival time at a site are logged by a barcode-scanner based system. Thus, for each plant object, all site-related parameters, e. g. automatically logged climate data, are available. These life history data and genetic information for the plant objects are linked to analytical results by the sampling module, which links sample components to plant object identifiers. This workflow uses controlled vocabulary for organs and treatments. Unique names generated by the system and barcode labels facilitate identification and management of the material. Web pages are provided as user interfaces to facilitate maintaining the system in an environment with many desktop computers and a rapidly changing user community. Web based search tools are the basis for joint use of the material by all researchers of the institute.
Conclusion: The Golm Plant Database system, which is based on a relational database, collects the genetic and environmental information on plant material during its production or experimental use at the Max-Planck-Institute of Molecular Plant Physiology. It thus provides information according to the MIAME standard for the component 'Sample' in a highly standardised format. The Plant Database system thus facilitates collaborative work and allows efficient queries in data analysis for systems biology research.
Processes driving the production, transformation and transport of methane (CH4) in wetland ecosystems are highly complex. We present a simple calculation algorithm to separate open-water CH4 fluxes measured with automatic chambers into diffusion- and ebullition-derived components. This helps to reveal underlying dynamics, to identify potential environmental drivers and, thus, to calculate reliable CH4 emission estimates. The flux separation is based on identification of ebullition-related sudden concentration changes during single measurements. Therefore, a variable ebullition filter is applied, using the lower and upper quartile and the interquartile range (IQR). Automation of data processing is achieved by using an established R script, adjusted for the purpose of CH4 flux calculation. The algorithm was validated by performing a laboratory experiment and tested using flux measurement data (July to September 2013) from a former fen grassland site, which converted into a shallow lake as a result of rewetting. Ebullition and diffusion contributed equally (46 and 55 %) to total CH4 emissions, which is comparable to ratios given in the literature. Moreover, the separation algorithm revealed a concealed shift in the diurnal trend of diffusive fluxes throughout the measurement period. The water temperature gradient was identified as one of the major drivers of diffusive CH4 emissions, whereas no significant driver was found in the case of erratic CH4 ebullition events.
In recent decades, the Greenland Ice Sheet has been losing mass and has thereby contributed to global sea-level rise. The rate of ice loss is highly relevant for coastal protection worldwide. The ice loss is likely to increase under future warming. Beyond a critical temperature threshold, a meltdown of the Greenland Ice Sheet is induced by the self-enforcing feedback between its lowering surface elevation and its increasing surface mass loss: the more ice that is lost, the lower the ice surface and the warmer the surface air temperature, which fosters further melting and ice loss. The computation of this rate so far relies on complex numerical models which are the appropriate tools for capturing the complexity of the problem. By contrast we aim here at gaining a conceptual understanding by deriving a purposefully simple equation for the self-enforcing feedback which is then used to estimate the melt time for different levels of warming using three observable characteristics of the ice sheet itself and its surroundings. The analysis is purely conceptual in nature. It is missing important processes like ice dynamics for it to be useful for applications to sea-level rise on centennial timescales, but if the volume loss is dominated by the feedback, the resulting logarithmic equation unifies existing numerical simulations and shows that the melt time depends strongly on the level of warming with a critical slow-down near the threshold: the median time to lose 10% of the present-day ice volume varies between about 3500 years for a temperature level of 0.5 degrees C above the threshold and 500 years for 5 degrees C. Unless future observations show a significantly higher melting sensitivity than currently observed, a complete meltdown is unlikely within the next 2000 years without significant ice-dynamical contributions.
Modern 3D geovisualization systems (3DGeoVSs) are complex and evolving systems that are required to be adaptable and leverage distributed resources, including massive geodata. This article focuses on 3DGeoVSs built based on the principles of service-oriented architectures, standards and image-based representations (SSI) to address practically relevant challenges and potentials. Such systems facilitate resource sharing and agile and efficient system construction and change in an interoperable manner, while exploiting images as efficient, decoupled and interoperable representations. The software architecture of a 3DGeoVS and its underlying visualization model have strong effects on the system's quality attributes and support various system life cycle activities. This article contributes a software reference architecture (SRA) for 3DGeoVSs based on SSI that can be used to design, describe and analyze concrete software architectures with the intended primary benefit of an increase in effectiveness and efficiency in such activities. The SRA integrates existing, proven technology and novel contributions in a unique manner. As the foundation for the SRA, we propose the generalized visualization pipeline model that generalizes and overcomes expressiveness limitations of the prevalent visualization pipeline model. To facilitate exploiting image-based representations (IReps), the SRA integrates approaches for the representation, provisioning and styling of and interaction with IReps. Five applications of the SRA provide proofs of concept for the general applicability and utility of the SRA. A qualitative evaluation indicates the overall suitability of the SRA, its applications and the general approach of building 3DGeoVSs based on SSI.
In this combined theoretical and experimental study we report a full analysis of the resonant inelastic X-ray scattering (RIXS) spectra of H2O, D2O and HDO. We demonstrate that electronically-elastic RIXS has an inherent capability to map the potential energy surface and to perform vibrational analysis of the electronic ground state in multimode systems. We show that the control and selection of vibrational excitation can be performed by tuning the X-ray frequency across core-excited molecular bands and that this is clearly reflected in the RIXS spectra. Using high level ab initio electronic structure and quantum nuclear wave packet calculations together with high resolution RIXS measurements, we discuss in detail the mode coupling, mode localization and anharmonicity in the studied systems.
We present XMM-Newton and Chandra observations of the born-again planetary nebula A 30. These X-ray observations reveal a bright unresolved source at the position of the central star whose X-ray luminosity exceeds by far the model expectations for photospheric emission and for shocks within the stellar wind. We suggest that a “born-again hot bubble” may be responsible for this X-ray emission. Diffuse X-ray emission associated with the petal-like features and one of the H-poor knots seen in the optical is also found. The weakened emission of carbon lines in the spectrum of the diffuse emission can be interpreted as the dilution of stellar wind by mass-loading or as the detection of material ejected during a very late thermal pulse.
Identifying abrupt transitions is a key question in various disciplines. Existing transition detection methods, however, do not rigorously account for time series uncertainties, often neglecting them altogether or assuming them to be independent and qualitatively similar. Here, we introduce a novel approach suited to handle uncertainties by representing the time series as a time-ordered sequence of probability density functions. We show how to detect abrupt transitions in such a sequence using the community structure of networks representing probabilities of recurrence. Using our approach, we detect transitions in global stock indices related to well-known periods of politico-economic volatility. We further uncover transitions in the El Nino-Southern Oscillation which coincide with periods of phase locking with the Pacific Decadal Oscillation. Finally, we provide for the first time an 'uncertainty-aware' framework which validates the hypothesis that ice-rafting events in the North Atlantic during the Holocene were synchronous with a weakened Asian summer monsoon.
Abstract gringo
(2015)
This paper defines the syntax and semantics of the input language of the ASP grounder gringo. The definition covers several constructs that were not discussed in earlier work on the semantics of that language, including intervals, pools, division of integers, aggregates with non-numeric values, and lparse-style aggregate expressions. The definition is abstract in the sense that it disregards some details related to representing programs by strings of ASCII characters. It serves as a specification for gringo from Version 4.5 on.
Landscape evolution models (LEMs) allow the study of earth surface responses to changing climatic and tectonic forcings. While much effort has been devoted to the development of LEMs that simulate a wide range of processes, the numerical accuracy of these models has received less attention. Most LEMs use first-order accurate numerical methods that suffer from substantial numerical diffusion. Numerical diffusion particularly affects the solution of the advection equation and thus the simulation of retreating landforms such as cliffs and river knickpoints. This has potential consequences for the integrated response of the simulated landscape. Here we test a higher-order flux-limiting finite volume method that is total variation diminishing (TVD-FVM) to solve the partial differential equations of river incision and tectonic displacement. We show that using the TVD-FVM to simulate river incision significantly influences the evolution of simulated landscapes and the spatial and temporal variability of catchment-wide erosion rates. Furthermore, a two-dimensional TVD-FVM accurately simulates the evolution of landscapes affected by lateral tectonic displacement, a process whose simulation was hitherto largely limited to LEMs with flexible spatial discretization. We implement the scheme in TTLEM (TopoToolbox Landscape Evolution Model), a spatially explicit, raster-based LEM for the study of fluvially eroding landscapes in TopoToolbox 2.
Background
Riociguat is the first of a new class of drugs, the soluble guanylate cyclase (sGC) stimulators. Riociguat has a dual mode of action: it sensitizes sGC to the body’s own NO and can also increase sGC activity in the absence of NO. The NO-sGC-pathway is impaired in many cardiovascular diseases such as heart failure, pulmonary hypertension and diabetic nephropathy (DN). DN leads to high cardiovascular morbidity and mortality. There is still a high unmet medical need. The urinary albumin excretion rate is a predictive biomarker for these clinical events. Therefore, we investigated the effect of riociguat, alone and in combination with the angiotensin II receptor antagonist (ARB) telmisartan on the progression of DN in diabetic eNOS knock out mice, a new model closely resembling human pathology.
Methods
Seventy-six male eNOS knockout C57BL/6J mice were divided into 4 groups after receiving intraperitoneal high-dose streptozotocin: telmisartan (1 mg/kg), riociguat (3 mg/kg), riociguat+telmisartan (3 and 1 mg/kg), and vehicle. Fourteen mice were used as non-diabetic controls. After 12 weeks, urine and blood were obtained and blood pressure measured. Glucose concentrations were highly increased and similar in all diabetic groups.
Results
Riociguat, alone (105.2 ± 2.5 mmHg; mean±SEM; n = 14) and in combination with telmisartan (105.0 ± 3.2 mmHg; n = 12), significantly reduced blood pressure versus diabetic controls (117.1 ± 2.2 mmHg; n = 14; p = 0.002 and p = 0.004, respectively), whereas telmisartan alone (111.2 ± 2.6 mmHg) showed a modest blood pressure lowering trend (p = 0.071; n = 14). The effects of single treatment with either riociguat (97.1 ± 15.7 µg/d; n = 13) or telmisartan (97.8 ± 26.4 µg/d; n = 14) did not significantly lower albumin excretion on its own (p = 0.067 and p = 0.101, respectively). However, the combined treatment led to significantly lower urinary albumin excretion (47.3 ± 9.6 µg/d; n = 12) compared to diabetic controls (170.8 ± 34.2 µg/d; n = 13; p = 0.004), and reached levels similar to non-diabetic controls (31.4 ± 10.1 µg/d, n = 12).
Conclusion
Riociguat significantly reduced urinary albumin excretion in diabetic eNOS knock out mice that were refractory to treatment with ARB’s alone. Patients with diabetic nephropathy refractory to treatment with ARB’s have the worst prognosis among all patients with diabetic nephropathy. Our data indicate that additional stimulation of sGC on top of standard treatment with ARB`s may offer a new therapeutic approach for patients with diabetic nephropathy resistant to ARB treatment.
Plant cultivation and processing may impact nutrient and phytochemical content of vegetables. The present study aimed at determining the influence of cultivation and processing on the health promoting capacity of African nightshade (Solanum scabrum Mill.) leaves, an indigenous vegetable, rich in nutrients and phytochemicals. Anti-genotoxicity against the human liver carcinogen aflatoxin B1 (AFB1) as determined by the comet assay and radical oxygen species (ROS) scavenging capacity of ethanolic and aqueous extracts were investigated in human derived liver (HepG2) cells. ROS scavenging activity was assessed using electron paramagnetic spin resonance and quantification of ARE/Nrf2 mediated gene expression. The cultivation was done under different environmental conditions. The processing included fermentation and cooking; postharvest ultraviolet irradiation (UV-C) treatment was also investigated. Overall, S. scabrum extracts showed strong health promoting potential, the highest potential was observed with the fermented extract, which showed a 60% reduction of AFB1 induced DNA damage and a 38% reduction in FeSO4 induced oxidative stress. The content of total polyphenols, carotenoids and chlorophylls was indeed affected by cultivation and processing. Based on the present in vitro findings consumption of S. scabrum leaves could be further encouraged, preferentially after cooking or fermentation of the plant.
In the aftermath of the severe flooding in Central Europe in August 2002, a number of changes in flood policies were launched in Germany and other European countries, aiming at improved risk management. The question arises as to whether these changes have already had an impact on the residents' ability to cope with floods, and whether flood-affected private households are now better prepared than they were in 2002. Therefore, computer-aided telephone interviews with private households in Germany that suffered from property damage due to flooding in 2005, 2006, 2010 or 2011 were performed and analysed with respect to flood awareness, precaution, preparedness and recovery. The data were compared to a similar investigation conducted after the flood in 2002.
After the flood in 2002, the level of private precautions taken increased considerably. One contributing factor is the fact that, in general, a larger proportion of people knew that they were at risk of flooding. The best level of precaution was found before the flood events in 2006 and 2011. The main reason for this might be that residents had more experience with flooding than residents affected in 2005 or 2010. Yet, overall, flood experience and knowledge did not necessarily result in building retrofitting or flood-proofing measures, which are considered as mitigating damages most effectively. Hence, investments still need to be stimulated in order to reduce future damage more efficiently.
Early warning and emergency responses were substantially influenced by flood characteristics. In contrast to flood-affected people in 2006 or 2011, people affected by flooding in 2005 or 2010 had to deal with shorter lead times and therefore had less time to take emergency measures. Yet, the lower level of emergency measures taken also resulted from the people's lack of flood experience and insufficient knowledge of how to protect themselves. Overall, it was noticeable that these residents suffered from higher losses. Therefore, it is important to further improve early warning systems and communication channels, particularly in hilly areas with rapid-onset flooding.
Air pollution is the number one environmental cause of premature deaths in Europe. Despite extensive regulations, air pollution remains a challenge, especially in urban areas. For studying summertime air quality in the Berlin-Brandenburg region of Germany, the Weather Research and Forecasting Model with Chemistry (WRF-Chem) is set up and evaluated against meteorological and air quality observations from monitoring stations as well as from a field campaign conducted in 2014. The objective is to assess which resolution and level of detail in the input data is needed for simulating urban background air pollutant concentrations and their spatial distribution in the Berlin-Brandenburg area. The model setup includes three nested domains with horizontal resolutions of 15, 3 and 1 km and anthropogenic emissions from the TNO-MACC III inventory. We use RADM2 chemistry and the MADE/SORGAM aerosol scheme. Three sensitivity simulations are conducted updating input parameters to the single-layer urban canopy model based on structural data for Berlin, specifying land use classes on a sub-grid scale (mosaic option) and downscaling the original emissions to a resolution of ca. 1 km x 1 km for Berlin based on proxy data including traffic density and population density. The results show that the model simulates meteorology well, though urban 2m temperature and urban wind speeds are biased high and nighttime mixing layer height is biased low in the base run with the settings described above. We show that the simulation of urban meteorology can be improved when specifying the input parameters to the urban model, and to a lesser extent when using the mosaic option. On average, ozone is simulated reasonably well, but maximum daily 8 h mean concentrations are underestimated, which is consistent with the results from previous modelling studies using the RADM2 chemical mechanism. Particulate matter is underestimated, which is partly due to an underestimation of secondary organic aerosols. NOx (NO + NO2) concentrations are simulated reasonably well on average, but nighttime concentrations are overestimated due to the model's underestimation of the mixing layer height, and urban daytime concentrations are underestimated. The daytime underestimation is improved when using downscaled, and thus locally higher emissions, suggesting that part of this bias is due to deficiencies in the emission input data and their resolution. The results further demonstrate that a horizontal resolution of 3 km improves the results and spatial representativeness of the model compared to a horizontal resolution of 15 km. With the input data (land use classes, emissions) at the level of detail of the base run of this study, we find that a horizontal resolution of 1 km does not improve the results compared to a resolution of 3 km. However, our results suggest that a 1 km horizontal model resolution could enable a detailed simulation of local pollution patterns in the Berlin-Brandenburg region if the urban land use classes, together with the respective input parameters to the urban canopy model, are specified with a higher level of detail and if urban emissions of higher spatial resolution are used.
All you can feed
(2020)
The laboratory mouse is the most common used mammalian research model in biomedical research. Usually these animals are maintained in germ-free, gnotobiotic, or specific-pathogen-free facilities. In these facilities, skilled staff takes care of the animals and scientists usually don’t pay much attention about the formulation and quality of diets the animals receive during normal breeding and keeping. However, mice have specific nutritional requirements that must be met to guarantee their potential to grow, reproduce and to respond to pathogens or diverse environmental stress situations evoked by handling and experimental interventions. Nowadays, mouse diets for research purposes are commercially manufactured in an industrial process, in which the safety of food products is addressed through the analysis and control of all biological and chemical materials used for the different diet formulations. Similar to human food, mouse diets must be prepared under good sanitary conditions and truthfully labeled to provide information of all ingredients. This is mandatory to guarantee reproducibility of animal studies. In this review, we summarize some information on mice research diets and general aspects of mouse nutrition including nutrient requirements of mice, leading manufacturers of diets, origin of nutrient compounds, and processing of feedstuffs for mice including dietary coloring, autoclaving and irradiation. Furthermore, we provide some critical views on the potential pitfalls that might result from faulty comparisons of grain-based diets with purified diets in the research data production resulting from confounding nutritional factors.
All's well that ends well
(2012)
The transition from cell proliferation to cell expansion is critical for determining leaf size. Andriankaja et al. (2012) demonstrate that in leaves of dicotyledonous plants, a basal proliferation zone is maintained for several days before abruptly disappearing, and that chloroplast differentiation is required to trigger the onset of cell expansion.
Background: Flooding during seasonal monsoons affects millions of hectares of rice-cultivated areas across Asia. Submerged rice plants die within a week due to lack of oxygen, light and excessive elongation growth to escape the water. Submergence tolerance was first reported in an aus-type rice landrace, FR13A, and the ethylene-responsive transcription factor (TF) gene SUB1A-1 was identified as the major tolerance gene. Intolerant rice varieties generally lack
the SUB1A gene but some intermediate tolerant varieties, such as IR64, carry the allelic variant SUB1A-2. Differential effects of the two alleles have so far not been addressed. As a first step, we have therefore quantified and compared the expression of nearly 2500 rice TF genes between IR64 and its derived tolerant near isogenic line IR64-Sub1, which carries the SUB1A-1 allele. Gene expression was studied in internodes, where the main difference in expression between
the two alleles was previously shown.
Results: Nineteen and twenty-six TF genes were identified that responded to submergence in IR64 and IR64-Sub1,
respectively. Only one gene was found to be submergence-responsive in both, suggesting different regulatory pathways under submergence in the two genotypes. These differentially expressed genes (DEGs) mainly included MYB, NAC, TIFY and Zn-finger TFs, and most genes were downregulated upon submergence. In IR64, but not in IR64-Sub1,
SUB1B and SUB1C, which are also present in the Sub1 locus, were identified as submergence responsive. Four TFs were not submergence responsive but exhibited constitutive, genotype-specific differential expression. Most of the identified submergence responsive DEGs are associated with regulatory hormonal pathways, i.e. gibberellins (GA), abscisic acid (ABA), and jasmonic acid (JA), apart from ethylene. An in-silico promoter analysis of the two genotypes revealed the
presence of allele-specific single nucleotide polymorphisms, giving rise to ABRE, DRE/CRT, CARE and Site II cis-elements, which can partly explain the observed differential TF gene expression.
Conclusion: This study identified new gene targets with the potential to further enhance submergence tolerance in rice and provides insights into novel aspects of SUB1A-mediated tolerance.
Inventories of individually delineated landslides are a key to understanding landslide physics and mitigating their impact. They permit assessment of area–frequency distributions and landslide volumes, and testing of statistical correlations between landslides and physical parameters such as topographic gradient or seismic strong motion. Amalgamation, i.e. the mapping of several adjacent landslides as a single polygon, can lead to potentially severe distortion of the statistics of these inventories. This problem can be especially severe in data sets produced by automated mapping. We present five inventories of earthquake-induced landslides mapped with different materials and techniques and affected by varying degrees of amalgamation. Errors on the total landslide volume and power-law exponent of the area–frequency distribution, resulting from amalgamation, may be up to 200 and 50%, respectively. We present an algorithm based on image and digital elevation model (DEM) analysis, for automatic identification of amalgamated polygons. On a set of about 2000 polygons larger than 1000 m2, tracing landslides triggered by the 1994 Northridge earthquake, the algorithm performs well, with only 2.7–3.6% incorrectly amalgamated landslides missed and 3.9–4.8% correct polygons incorrectly identified as amalgams. This algorithm can be used broadly to check landslide inventories and allow faster correction by automating the identification of amalgamation.
Extreme weather resilience has been defined as being based on three pillars: resistance (the ability to lower impacts), recovery (the ability to bounce back), and adaptive capacity (the ability to learn and improve). These resilience pillars are important both before and after the occurrence of extreme weather events. Extreme weather insurance can influence these pillars of resilience depending on how particular insurance mechanisms are structured. We explore how the lessons learnt from the current best insurance practices can improve resilience to extreme weather events. We employ an extensive inventory of private property and agricultural crop insurance mechanisms to conduct a multi-criteria analysis of insurance market outcomes. We draw conclusions regarding the patterns in the best practice from six European countries to increase resilience. We suggest that requirements to buy a bundle extreme weather event insurance with general insurance packages are strengthened and supported with structures to financing losses through public-private partnerships. Moreover, support for low income households through income vouchers could be provided. Similarly, for the agricultural sector we propose moving towards comprehensive crop yield insurance linked to general agricultural subsidies. In both cases a nationally representative body can coordinate the various stakeholders into acting in concert.
The intangible impacts of floods on welfare are not well investigated, even though they are important aspects of welfare. Moreover, flooding has gender based impacts on welfare. These differing impacts create a gender based flood risk resilience gap. We study the intangible impacts of flood risk on the subjective well-being of residents in central Vietnam. The measurement of intangible impacts through subjective well-being is a growing field within flood risk research. We find an initial drop in welfare through subjective well-being across genders when a flood is experienced. Male respondents tended to recover their welfare losses by around 80% within 5 years while female respondents were associated with a welfare recovery of around 70%. A monetization of the impacts floods have on an individual’s subjective well-being shows that for the average female respondent, between 41% to 86% of annual income would be required to compensate subjective well-being losses after 5 years of experiencing a flood. The corresponding value for males is 30% to 57% of annual income. This shows that the intangible impacts of flood risk are important (across genders) and need to be integrated into flood (or climate) risk assessments to develop more socially appropriate risk management strategies.
Introduction
Genes involved in body weight regulation that were previously investigated in genome-wide association studies (GWAS) and in animal models were target-enriched followed by massive parallel next generation sequencing.
Methods
We enriched and re-sequenced continuous genomic regions comprising FTO, MC4R, TMEM18, SDCCAG8, TKNS, MSRA and TBC1D1 in a screening sample of 196 extremely obese children and adolescents with age and sex specific body mass index (BMI) >= 99th percentile and 176 lean adults (BMI <= 15th percentile). 22 variants were confirmed by Sanger sequencing. Genotyping was performed in up to 705 independent obesity trios (extremely obese child and both parents), 243 extremely obese cases and 261 lean adults.
Results and Conclusion
We detected 20 different non-synonymous variants, one frame shift and one nonsense mutation in the 7 continuous genomic regions in study groups of different weight extremes. For SNP Arg695Cys (rs58983546) in TBC1D1 we detected nominal association with obesity (p(TDT) = 0.03 in 705 trios). Eleven of the variants were rare, thus were only detected heterozygously in up to ten individual(s) of the complete screening sample of 372 individuals. Two of them (in FTO and MSRA) were found in lean individuals, nine in extremely obese. In silico analyses of the 11 variants did not reveal functional implications for the mutations. Concordant with our hypothesis we detected a rare variant that potentially leads to loss of FTO function in a lean individual. For TBC1D1, in contrary to our hypothesis, the loss of function variant (Arg443Stop) was found in an obese individual. Functional in vitro studies are warranted.
The course timetabling problem can be generally defined as the task of assigning a number of lectures to a limited set of timeslots and rooms, subject to a given set of hard and soft constraints. The modeling language for course timetabling is required to be expressive enough to specify a wide variety of soft constraints and objective functions. Furthermore, the resulting encoding is required to be extensible for capturing new constraints and for switching them between hard and soft, and to be flexible enough to deal with different formulations. In this paper, we propose to make effective use of ASP as a modeling language for course timetabling. We show that our ASP-based approach can naturally satisfy the above requirements, through an ASP encoding of the curriculum-based course timetabling problem proposed in the third track of the second international timetabling competition (ITC-2007). Our encoding is compact and human-readable, since each constraint is individually expressed by either one or two rules. Each hard constraint is expressed by using integrity constraints and aggregates of ASP. Each soft constraint S is expressed by rules in which the head is the form of penalty (S, V, C), and a violation V and its penalty cost C are detected and calculated respectively in the body. We carried out experiments on four different benchmark sets with five different formulations. We succeeded either in improving the bounds or producing the same bounds for many combinations of problem instances and formulations, compared with the previous best known bounds.
Antibodies against spike proteins of influenza are used as a tool for characterization of viruses and therapeutic approaches. However, development, production and quality control of antibodies is expensive and time consuming. To circumvent these difficulties, three peptides were derived from complementarity determining regions of an antibody heavy chain against influenza A spike glycoprotein. Their binding properties were studied experimentally, and by molecular dynamics simulations. Two peptide candidates showed binding to influenza A/Aichi/2/68 H3N2. One of them, termed PeB, with the highest affinity prevented binding to and infection of target cells in the micromolar region without any cytotoxic effect. PeB matches best the conserved receptor binding site of hemagglutinin. PeB bound also to other medical relevant influenza strains, such as human-pathogenic A/California/7/2009 H1N1, and avian-pathogenic A/MuteSwan/Rostock/R901/2006 H7N1. Strategies to improve the affinity and to adapt specificity are discussed and exemplified by a double amino acid substituted peptide, obtained by substitutional analysis. The peptides and their derivatives are of great potential for drug development as well as biosensing.
Background: Malaria is an old life-threatening parasitic disease that is still affecting many people, mainly children living in sub-Saharan Africa. Availability of effective antimalarial drugs played a significant role in the treatment and control of malaria. However, recent information on the emergence of P. falciparum parasites resistant to one of the artemisinin-based combination therapies suggests the need for discovery of new drug molecules. Therefore, this study aimed to evaluate the antiplasmodial activity of extracts, fractions and isolated compound from medicinal plants traditionally used in the treatment of malaria in Tanzania.
Methods: Dry powdered plant materials were extracted by cold macerations using different solvents. Norcaesalpin D was isolated by column chromatography from dichloromethane root extract of Caesalpinia bonducella and its structure was assigned based on the spectral data. Crude extracts, fractions and isolated compound were evaluated for antiplasmodial activity against chloroquine-sensitive P. falciparum (3D7), chloroquine-resistant P. falciparum (Dd2, K1) and artemisinin-resistant P. falciparum (IPC 5202 Battambang, IPC 4912 Mondolkiri) strains using the parasite lactate dehydrogenase assay.
Results: The results indicated that extracts of Erythrina schliebenii, Holarrhena pubescens, Dissotis melleri and C. bonducella exhibited antiplasmodial activity against Dd2 parasites. Ethanolic root extract of E. schliebenii had an IC50 of 1.87 mu g/mL while methanolic and ethanolic root extracts of H. pubescens exhibited an IC50 = 2.05 mu g/mL and IC50 = 2.43 mu g/mL, respectively. Fractions from H. pubescens and C. bonducella roots were found to be highly active against K1, Dd2 and artemisinin-resistant parasites. Norcaesalpin D from C. bonducella root extract was active with IC50 of 0.98, 1.85 and 2.13 mu g/mL against 3D7, Dd2 and IPC 4912-Mondolkiri parasites, respectively.
Conclusions: Antiplasmodial activity of norcaesalpin D and extracts of E. schliebenii, H. pubescens, D. melleri and C. bonducella reported in this study requires further attention for the discovery of antimalarial lead compounds for future drug development.
Background
Antiphospholipid antibodies (aPL) can be detected in asymptomatic carriers and infectious patients. The aim was to investigate whether a novel line immunoassay (LIA) differentiates between antiphospholipid syndrome (APS) and asymptomatic aPL+ carriers or patients with infectious diseases (infectious diseases controls (IDC)).
Methods
Sixty-one patients with APS (56 primary, 22/56 with obstetric events only, and 5 secondary), 146 controls including 24 aPL+ asymptomatic carriers and 73 IDC were tested on a novel hydrophobic solid phase coated with cardiolipin (CL), phosphatic acid, phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylinositol, phosphatidylserine, beta2-glycoprotein I (β2GPI), prothrombin, and annexin V. Samples were also tested by anti-CL and anti-β2GPI ELISAs and for lupus anticoagulant activity. Human monoclonal antibodies (humoAbs) against human β2GPI or PL alone were tested on the same LIA substrates in the absence or presence of human serum, purified human β2GPI or after CL-micelle absorption.
Results
Comparison of LIA with the aPL-classification assays revealed good agreement for IgG/IgM aß2GPI and aCL. Anti-CL and anti-ß2GPI IgG/IgM reactivity assessed by LIA was significantly higher in patients with APS versus healthy controls and IDCs, as detected by ELISA. IgG binding to CL and ß2GPI in the LIA was significantly lower in aPL+ carriers and Venereal Disease Research Laboratory test (VDRL) + samples than in patients with APS. HumoAb against domain 1 recognized β2GPI bound to the LIA-matrix and in anionic phospholipid (PL) complexes. Absorption with CL micelles abolished the reactivity of a PL-specific humoAb but did not affect the binding of anti-β2GPI humoAbs.
Conclusions
The LIA and ELISA have good agreement in detecting aPL in APS, but the LIA differentiates patients with APS from infectious patients and asymptomatic carriers, likely through the exposure of domain 1.
Arboreal epiphytes (plants residing in forest canopies) are present across all major climate zones and play important roles in forest biogeochemistry. The substantial water storage capacity per unit area of the epiphyte “bucket” is a key attribute underlying their capability to influence forest hydrological processes and their related mass and energy flows. It is commonly assumed that the epiphyte bucket remains saturated, or near-saturated, most of the time; thus, epiphytes (particularly vascular epiphytes) can store little precipitation, limiting their impact on the forest canopy water budget. We present evidence that contradicts this common assumption from (i) an examination of past research; (ii) new datasets on vascular epiphyte and epi-soil water relations at a tropical montane cloud forest (Monteverde, Costa Rica); and (iii) a global evaluation of non-vascular epiphyte saturation state using a process-based vegetation model, LiBry. All analyses found that the external and internal water storage capacity of epiphyte communities is highly dynamic and frequently available to intercept precipitation. Globally, non-vascular epiphytes spend <20% of their time near saturation and regionally, including the humid tropics, model results found that non-vascular epiphytes spend ~1/3 of their time in the dry state (0–10% of water storage capacity). Even data from Costa Rican cloud forest sites found the epiphyte community was saturated only 1/3 of the time and that internal leaf water storage was temporally dynamic enough to aid in precipitation interception. Analysis of the epi-soils associated with epiphytes further revealed the extent to which the epiphyte bucket emptied—as even the canopy soils were often <50% saturated (29–53% of all days observed). Results clearly show that the epiphyte bucket is more dynamic than currently assumed, meriting further research on epiphyte roles in precipitation interception, redistribution to the surface and chemical composition of “net” precipitation waters reaching the surface.
The oldest ice core records are obtained from the East Antarctic Plateau. Water isotopes are key proxies to reconstructing past climatic conditions over the ice sheet and at the evaporation source. The accuracy of climate reconstructions depends on knowledge of all processes affecting water vapour, precipitation and snow isotopic compositions. Fractionation processes are well understood and can be integrated in trajectory-based Rayleigh distillation and isotope-enabled climate models. However, a quantitative understanding of processes potentially altering snow isotopic composition after deposition is still missing. In low-accumulation sites, such as those found in East Antarctica, these poorly constrained processes are likely to play a significant role and limit the interpretability of an ice core's isotopic composition.
By combining observations of isotopic composition in vapour, precipitation, surface snow and buried snow from Dome C, a deep ice core site on the East Antarctic Plateau, we found indications of a seasonal impact of metamorphism on the surface snow isotopic signal when compared to the initial precipitation. Particularly in summer, exchanges of water molecules between vapour and snow are driven by the diurnal sublimation-condensation cycles. Overall, we observe in between precipitation events modification of the surface snow isotopic composition. Using high-resolution water isotopic composition profiles from snow pits at five Antarctic sites with different accumulation rates, we identified common patterns which cannot be attributed to the seasonal variability of precipitation. These differences in the precipitation, surface snow and buried snow isotopic composition provide evidence of post-deposition processes affecting ice core records in low-accumulation areas.
Biomembranes are constantly remodeled and in cells, these processes are controlled and modulated by an assortment of membrane proteins. Here, it is shown that such remodeling can also be induced by photoresponsive molecules. The morphological control of giant vesicles in the presence of a water-soluble ortho-tetrafluoroazobenzene photoswitch (F-azo) is demonstrated and it is shown that the shape transformations are based on an increase in membrane area and generation of spontaneous curvature. The vesicles exhibit budding and the buds can be retracted by using light of a different wavelength. In the presence of F-azo, the membrane area can increase by more than 5% as assessed from vesicle electrodeformation. To elucidate the underlying molecular mechanism and the partitioning of F-azo in the membrane, molecular dynamics simulations are employed. Comparison with theoretically calculated shapes reveals that the budded shapes are governed by curvature elasticity, that the spontaneous curvature can be decomposed into a local and a nonlocal contribution, and that the local spontaneous curvature is about 1/(2.5 mu m). The results show that exo- and endocytotic events can be controlled by light and that these photoinduced processes provide an attractive method to change membrane area and morphology.
ASP modulo CSP
(2012)
We present the hybrid ASP solver clingcon, combining the simple modeling language and the high performance Boolean solving capacities of Answer Set Programming (ASP) with techniques for using non-Boolean constraints from the area of Constraint Programming (CP). The new clingcon system features an extended syntax supporting global constraints and optimize statements for constraint variables. The major technical innovation improves the interaction between ASP and CP solver through elaborated learning techniques based on irreducible inconsistent sets. A broad empirical evaluation shows that these techniques yield a performance improvement of an order of magnitude.
aspeed
(2015)
Although Boolean Constraint Technology has made tremendous progress over the last decade, the efficacy of state-of-the-art solvers is known to vary considerably across different types of problem instances, and is known to depend strongly on algorithm parameters. This problem was addressed by means of a simple, yet effective approach using handmade, uniform, and unordered schedules of multiple solvers in ppfolio, which showed very impressive performance in the 2011 Satisfiability Testing (SAT) Competition. Inspired by this, we take advantage of the modeling and solving capacities of Answer Set Programming (ASP) to automatically determine more refined, that is, nonuniform and ordered solver schedules from the existing benchmarking data. We begin by formulating the determination of such schedules as multi-criteria optimization problems and provide corresponding ASP encodings. The resulting encodings are easily customizable for different settings, and the computation of optimum schedules can mostly be done in the blink of an eye, even when dealing with large runtime data sets stemming from many solvers on hundreds to thousands of instances. Also, the fact that our approach can be customized easily enabled us to swiftly adapt it to generate parallel schedules for multi-processor machines.
Losses due to floods have dramatically increased over the past decades, and losses of companies, comprising direct and indirect losses, have a large share of the total economic losses. Thus, there is an urgent need to gain more quantitative knowledge about flood losses, particularly losses caused by business interruption, in order to mitigate the economic loss of companies. However, business interruption caused by floods is rarely assessed because of a lack of sufficiently detailed data. A survey was undertaken to explore processes influencing business interruption, which collected information on 557 companies affected by the severe flood in June 2013 in Germany. Based on this data set, the study aims to assess the business interruption of directly affected companies by means of a Random Forests model. Variables that influence the duration and costs of business interruption were identified by the variable importance measures of Random Forests. Additionally, Random Forest-based models were developed and tested for their capacity to estimate business interruption duration and associated costs. The water level was found to be the most important variable influencing the duration of business interruption. Other important variables, relating to the estimation of business interruption duration, are the warning time, perceived danger of flood recurrence and inundation duration. In contrast, the amount of business interruption costs is strongly influenced by the size of the company, as assessed by the number of employees, emergency measures undertaken by the company and the fraction of customers within a 50 km radius. These results provide useful information and methods for companies to mitigate their losses from business interruption. However, the heterogeneity of companies is relatively high, and sector-specific analyses were not possible due to the small sample size. Therefore, further sector-specific analyses on the basis of more flood loss data of companies are recommended.
Assimilation of pseudo-tree-ring-width observations into an atmospheric general circulation model
(2017)
Paleoclimate data assimilation (DA) is a promising technique to systematically combine the information from climate model simulations and proxy records. Here, we investigate the assimilation of tree-ring-width (TRW) chronologies into an atmospheric global climate model using ensemble Kalman filter (EnKF) techniques and a process-based tree-growth forward model as an observation operator. Our results, within a perfect-model experiment setting, indicate that the "online DA" approach did not outperform the "off-line" one, despite its considerable additional implementation complexity. On the other hand, it was observed that the nonlinear response of tree growth to surface temperature and soil moisture does deteriorate the operation of the time-averaged EnKF methodology. Moreover, for the first time we show that this skill loss appears significantly sensitive to the structure of the growth rate function, used to represent the principle of limiting factors (PLF) within the forward model. In general, our experiments showed that the error reduction achieved by assimilating pseudo-TRW chronologies is modulated by the magnitude of the yearly internal variability in themodel. This result might help the dendrochronology community to optimize their sampling efforts.
German football stadiums are well known for their atmosphere. It is often described as ‘electrifying,’ or ‘cracking.’ This article focuses on this atmosphere. Using a phenomenological approach, it explores how this emotionality can be understood and how geography matters while attending a match. Atmosphere in this context is conceptualized based on work by as a mood-charged space, neither object- nor subject-centered, but rather a medium of perception which cannot not exist. Based on qualitative research done in the home stadium of Hertha BSC in the German Bundesliga, this article shows that the bodily sensations experienced by spectators during a visit to the stadium are synchronized with events on the pitch and with the more or less imposing scenery. The analysis of in situ diaries reveals that spectators experience a comprehensive sense of collectivity. The study presents evidence that the occurrence of these bodily sensations is strongly connected with different aspects of spatiality. This includes sensations of constriction and expansion within the body, an awareness of one’s location within the stadium, the influence of the immediate surroundings and cognitive here/there and inside/outside distinctions.
Building biological models by inferring functional dependencies from experimental data is an important issue in Molecular Biology. To relieve the biologist from this traditionally manual process, various approaches have been proposed to increase the degree of automation. However, available approaches often yield a single model only, rely on specific assumptions, and/or use dedicated, heuristic algorithms that are intolerant to changing circumstances or requirements in the view of the rapid progress made in Biotechnology. Our aim is to provide a declarative solution to the problem by appeal to Answer Set Programming (ASP) overcoming these difficulties. We build upon an existing approach to Automatic Network Reconstruction proposed by part of the authors. This approach has firm mathematical foundations and is well suited for ASP due to its combinatorial flavor providing a characterization of all models explaining a set of experiments. The usage of ASP has several benefits over the existing heuristic algorithms. First, it is declarative and thus transparent for biological experts. Second, it is elaboration tolerant and thus allows for an easy exploration and incorporation of biological constraints. Third, it allows for exploring the entire space of possible models. Finally, our approach offers an excellent performance, matching existing, special-purpose systems.
Great megathrust earthquakes arise from the sudden release of energy accumulated during centuries of interseismic plate convergence. The moment deficit (energy available for future earthquakes) is commonly inferred by integrating the rate of interseismic plate locking over the time since the previous great earthquake. But accurate integration requires knowledge of how interseismic plate locking changes decades after earthquakes, measurements not available for most great earthquakes. Here we reconstruct the post-earthquake history of plate locking at Guafo Island, above the seismogenic zone of the giant 1960 (M-w = 9.5) Chile earthquake, through forward modeling of land-level changes inferred from aerial imagery (since 1974) and measured by GPS (since 1994). We find that interseismic locking increased to similar to 70% in the decade following the 1960 earthquake and then gradually to 100% by 2005. Our findings illustrate the transient evolution of plate locking in Chile, and suggest a similarly complex evolution elsewhere, with implications for the time- and magnitude-dependent probability of future events.
Bayesian Data Assimilation to Support Informed Decision Making in Individualized Chemotherapy
(2020)
An essential component of therapeutic drug/biomarker monitoring (TDM) is to combine patient data with prior knowledge for model-based predictions of therapy outcomes. Current Bayesian forecasting tools typically rely only on the most probable model parameters (maximum a posteriori (MAP) estimate). This MAP-based approach, however, does neither necessarily predict the most probable outcome nor does it quantify the risks of treatment inefficacy or toxicity. Bayesian data assimilation (DA) methods overcome these limitations by providing a comprehensive uncertainty quantification. We compare DA methods with MAP-based approaches and show how probabilistic statements about key markers related to chemotherapy-induced neutropenia can be leveraged for more informative decision support in individualized chemotherapy. Sequential Bayesian DA proved to be most computationally efficient for handling interoccasion variability and integrating TDM data. For new digital monitoring devices enabling more frequent data collection, these features will be of critical importance to improve patient care decisions in various therapeutic areas.
The transmission of wildlife zoonoses to humans depends, amongst others, on complex interactions of host population ecology and pathogen dynamics within host populations. In Europe, the Puumala virus (PUUV) causes nephropathia epidemica in humans. In this study we investigated complex interrelations within the epidemic system of PUUV and its rodent host, the bank vole (Myodes glareolus). We suggest that beech fructification and bank vole abundance are both decisive factors affecting human PUUV infections. While rodent host dynamics are expected to be directly linked to human PUUV infections, beech fructification is a rather indirect predictor by serving as food source for PUUV rodent hosts. Furthermore, we examined the dependence of bank vole abundance on beech fructification. We analysed a 12-year (2001-2012) time series of the parameters: beech fructification (as food resource for the PUUV host), bank vole abundance and human incidences from 7 Federal States of Germany. For the first time, we could show the direct interrelation between these three parameters involved in human PUUV epidemics and we were able to demonstrate on a large scale that human PUUV infections are highly correlated with bank vole abundance in the present year, as well as beech fructification in the previous year. By using beech fructification and bank vole abundance as predictors in one model we significantly improved the degree of explanation of human PUUV incidence. Federal State was included as random factor because human PUUV incidence varies considerably among states. Surprisingly, the effect of rodent abundance on human PUUV infections is less strong compared to the indirect effect of beech fructification. Our findings are useful to facilitate the development of predictive models for host population dynamics and the related PUUV infection risk for humans and can be used for plant protection and human health protection purposes.
Bio-jETI
(2008)
Background: With Bio-jETI, we introduce a service platform for interdisciplinary work on biological application domains and illustrate its use in a concrete application concerning statistical data processing in R and xcms for an LC/MS analysis of FAAH gene knockout.
Methods: Bio-jETI uses the jABC environment for service-oriented modeling and design as a graphical process modeling tool and the jETI service integration technology for remote tool execution.
Conclusions: As a service definition and provisioning platform, Bio-jETI has the potential to become a core technology in interdisciplinary service orchestration and technology transfer. Domain experts, like biologists not trained in computer science, directly define complex service orchestrations as process models and use efficient and complex bioinformatics tools in a simple and intuitive way.
Background: For heterogeneous tissues, such as blood, measurements of gene expression are confounded by relative proportions of cell types involved. Conclusions have to rely on estimation of gene expression signals for homogeneous cell populations, e.g. by applying micro-dissection, fluorescence activated cell sorting, or in-silico deconfounding. We studied feasibility and validity of a non-negative matrix decomposition algorithm using experimental gene expression data for blood and sorted cells from the same donor samples. Our objective was to optimize the algorithm regarding detection of differentially expressed genes and to enable its use for classification in the difficult scenario of reversely regulated genes. This would be of importance for the identification of candidate biomarkers in heterogeneous tissues.
Results: Experimental data and simulation studies involving noise parameters estimated from these data revealed that for valid detection of differential gene expression, quantile normalization and use of non-log data are optimal. We demonstrate the feasibility of predicting proportions of constituting cell types from gene expression data of single samples, as a prerequisite for a deconfounding-based classification approach. Classification cross-validation errors with and without using deconfounding results are reported as well as sample-size dependencies. Implementation of the algorithm, simulation and analysis scripts are available.
Conclusions: The deconfounding algorithm without decorrelation using quantile normalization on non-log data is proposed for biomarkers that are difficult to detect, and for cases where confounding by varying proportions of cell types is the suspected reason. In this case, a deconfounding ranking approach can be used as a powerful alternative to, or complement of, other statistical learning approaches to define candidate biomarkers for molecular diagnosis and prediction in biomedicine, in realistically noisy conditions and with moderate sample sizes.
The large variety of atmospheric circulation systems affecting the eastern Asian climate is reflected by the complex Asian vegetation distribution. Particularly in the transition zones of these circulation systems, vegetation is supposed to be very sensitive to climate change. Since proxy records are scarce, hitherto a mechanistic understanding of the past spatio-temporal climate-vegetation relationship is lacking. To assess the Holocene vegetation change and to obtain an ensemble of potential mid-Holocene biome distributions for eastern Asia, we forced the diagnostic biome model BIOME4 with climate anomalies of different transient Holocene climate simulations performed in coupled atmosphere-ocean(-vegetation) models. The simulated biome changes are compared with pollen-based biome records for different key regions.
In all simulations, substantial biome shifts during the last 6000 years are confined to the high northern latitudes and the monsoon-westerly wind transition zone, but the temporal evolution and amplitude of change strongly depend on the climate forcing. Large parts of the southern tundra are replaced by taiga during the mid-Holocene due to a warmer growing season and the boreal treeline in northern Asia is shifted northward by approx. 4 degrees in the ensemble mean, ranging from 1.5 to 6 degrees in the individual simulations, respectively. This simulated treeline shift is in agreement with pollen-based reconstructions from northern Siberia. The desert fraction in the transition zone is reduced by 21% during the mid-Holocene compared to pre-industrial due to enhanced precipitation. The desert-steppe margin is shifted westward by 5 degrees (1-9 degrees in the individual simulations). The forest biomes are expanded north-westward by 2 degrees, ranging from 0 to 4 degrees in the single simulations. These results corroborate pollen-based reconstructions indicating an extended forest area in north-central China during the mid-Holocene. According to the model, the forest-to-non-forest and steppe-to-desert changes in the climate transition zones are spatially not uniform and not linear since the mid-Holocene.
Multi-color fluorescence imaging experiments of wave forming Dictyostelium cells have revealed that actin waves separate two domains of the cell cortex that differ in their actin structure and phosphoinositide composition. We propose a bistable model of actin dynamics to account for these experimental observation. The model is based on the simplifying assumption that the actin cytoskeleton is composed of two distinct network types, a dendritic and a bundled network. The two structurally different states that were observed in experiments correspond to the stable fixed points in the bistable regime of this model. Each fixed point is dominated by one of the two network types. The experimentally observed actin waves can be considered as trigger waves that propagate transitions between the two stable fixed points.
The synthesis, structure, and photocatalytic water splitting performance of two new titania (TiO 2 )/gold(Au)/Bombyx mori silk hybrid materials are reported. All materials are monoliths with diameters of up to ca. 4.5 cm. The materials are macroscopically homogeneous and porous with surface areas between 170 and 210 m 2/g. The diameter of the TiO 2 nanoparticles (NPs) – mainly anatase with a minor fraction of brookite – and the Au NPs are on the order of 5 and 7–18 nm, respectively. Addition of poly(ethylene oxide) to the reaction mixture enables pore size tuning, thus providing access to different materials with different photocatalytic activities. Water splitting experiments using a sunlight simulator and a Xe lamp show that the new hybrid materials are effective water splitting catalysts and produce up to 30 mmol of hydrogen per 24 h. Overall the article demonstrates that the combination of a renewable and robust scaffold such as B. mori silk with a photoactive material provides a promising approach to new monolithic photocatalysts that can easily be recycled and show great potential for application in lightweight devices for green fuel production.
Brief communication
(2015)
Accelerating climate change and increased economic and environmental interests in permafrost-affected regions have resulted in an acute need for more directed permafrost research. In June 2014, 88 early career researchers convened to identify future priorities for permafrost research. This multidisciplinary forum concluded that five research topics deserve greatest attention: permafrost landscape dynamics, permafrost thermal modeling, integration of traditional knowledge, spatial distribution of ground ice, and engineering issues. These topics underline the need for integrated research across a spectrum of permafrost-related domains and constitute a contribution to the Third International Conference on Arctic Research Planning (ICARP III).
Brief communication
(2016)
In March 2015, a new international blueprint for disaster risk reduction (DRR) was adopted in Sendai, Japan, at the end of the Third UN World Conference on Disaster Risk Reduction (WCDRR, 14-18 March 2015). We review and discuss the agreed commitments and targets, as well as the negotiation leading the Sendai Framework for DRR (SF-DRR) and discuss briefly its implication for the later UN-led negotiations on sustainable development goals and climate change.
Background: Rodents of the genus Rattus are among the most pervasive and successful invasive species, causing major vicissitudes in native ecological communities. A broad and flexible generalist diet has been suggested as key to the invasion success of Rattus spp. Here, we use an indirect approach to better understand foraging niche width, plasticity, and overlap within and between introduced Rattus spp. in anthropogenic habitats and natural humid forests of Madagascar.
Results: Based on stable carbon and nitrogen isotope values measured in hair samples of 589 individual rodents, we found that Rattus rattus had an extremely wide foraging niche, encompassing the isotopic space covered by a complete endemic forest-dwelling Malagasy small mammal community. Comparisons of Bayesian standard ellipses, as well as (multivariate) mixed-modeling analyses, revealed that the stable isotope niche of R. rattus tended to change seasonally and differed between natural forests and anthropogenic habitats, indicating plasticity in feeding niches. In co-occurrence, R. rattus and Rattus norvegicus partitioned feeding niches. Isotopic mismatch of signatures of individual R. rattus and the habitat in which they were captured, indicate frequent dispersal movements for this species between natural forest and anthropogenic habitats.
Conclusions: Since R. rattus are known to transmit a number of zoonoses, potentially affecting communities of endemic small mammals, as well as humans, these movements presumably increase transmission potential. Our results suggest that due to their generalist diet and potential movement between natural forest and anthropogenic habitats, Rattus spp. might affect native forest-dependent Malagasy rodents as competitors, predators, and disease vectors. The combination of these effects helps explain the invasion success of Rattus spp. and the detrimental effects of this genus on the endemic Malagasy rodent fauna.
Plants encounter biotic and abiotic stresses many times during their life cycle and this limits their productivity. Moderate heat stress (HS) primes a plant to survive higher temperatures that are lethal in the naive state. Once temperature stress subsides, the memory of the priming event is actively retained for several days preparing the plant to better cope with recurring HS. Recently, chromatin regulation at different levels has been implicated in HS memory. Here, we report that the chromatin protein BRUSHY1 (BRU1)/TONSOKU/MGOUN3 plays a role in the HS memory in Arabidopsis thaliana. BRU1 is also involved in transcriptional gene silencing and DNA damage repair. This corresponds with the functions of its mammalian orthologue TONSOKU-LIKE/NF Kappa BIL2. During HS memory, BRU1 is required to maintain sustained induction of HS memory-associated genes, whereas it is dispensable for the acquisition of thermotolerance. In summary, we report that BRU1 is required for HS memory in A. thaliana, and propose a model where BRU1 mediates the epigenetic inheritance of chromatin states across DNA replication and cell division.
In various biological systems and small scale technological applications particles transiently bind to a cylindrical surface. Upon unbinding the particles diffuse in the vicinal bulk before rebinding to the surface. Such bulk-mediated excursions give rise to an effective surface translation, for which we here derive and discuss the dynamic equations, including additional surface diffusion. We discuss the time evolution of the number of surface-bound particles, the effective surface mean squared displacement, and the surface propagator. In particular, we observe sub- and superdiffusive regimes. A plateau of the surface mean-squared displacement reflects a stalling of the surface diffusion at longer times. Finally, the corresponding first passage problem for the cylindrical geometry is analysed.
Bumps in river profiles
(2017)
The analysis of longitudinal river profiles is an important tool for studying landscape evolution. However, characterizing river profiles based on digital elevation models (DEMs) suffers from errors and artifacts that particularly prevail along valley bottoms. The aim of this study is to characterize uncertainties that arise from the analysis of river profiles derived from different, near-globally available DEMs. We devised new algorithms quantile carving and the CRS algorithm - that rely on quantile regression to enable hydrological correction and the uncertainty quantification of river profiles. We find that globally available DEMs commonly overestimate river elevations in steep topography. The distributions of elevation errors become increasingly wider and right skewed if adjacent hillslope gradients are steep. Our analysis indicates that the AW3D DEM has the highest precision and lowest bias for the analysis of river profiles in mountainous topography. The new 12m resolution TanDEM-X DEM has a very low precision, most likely due to the combined effect of steep valley walls and the presence of water surfaces in valley bottoms. Compared to the conventional approaches of carving and filling, we find that our new approach is able to reduce the elevation bias and errors in longitudinal river profiles.
Mosses are a major component of the arctic vegetation, particularly in wetlands. We present C / N atomic ratio, delta C-13 and delta N-15 data of 400 brown-moss samples belonging to 10 species that were collected along hydrological gradients within polygonal mires located on the southern Taymyr Peninsula and the Lena River delta in northern Siberia. Additionally, n-alkane patterns of six of these species (16 samples) were investigated. The aim of the study is to see whether the inter-and intraspecific differences in C / N, isotopic compositions and n-alkanes are indicative of habitat, particularly with respect to water level. Overall, we find high variability in all investigated parameters for two different moisture-related groups of moss species. The C / N ratios range between 11 and 53 (median: 32) and show large variations at the intraspecific level. However, species preferring a dry habitat (xero-mesophilic mosses) show higher C / N ratios than those preferring a wet habitat (meso-hygrophilic mosses). The delta C-13 values range between 37.0 and 22.5% (median D 27.8 %). The delta N-15 values range between 6.6 and C 1.7%(median D 2.2 %). We find differences in delta C-13 and delta N-15 compositions between both habitat types. For some species of the meso-hygrophilic group, we suggest that a relationship between the individ-ual habitat water level and isotopic composition can be inferred as a function of microbial symbiosis. The n-alkane distribution also shows differences primarily between xeromesophilic and meso-hygrophilic mosses, i. e. having a dominance of n-alkanes with long (n-C29, n-C31 /and intermediate (n-C25 /chain lengths, respectively. Overall, our results reveal that C / N ratios, isotopic signals and n-alkanes of studied brown-moss taxa from polygonal wetlands are characteristic of their habitat.
Background
Serotonin induces fluid secretion from Calliphora salivary glands by the parallel activation of the InsP3/Ca2+ and cAMP signaling pathways. We investigated whether cAMP affects 5-HT-induced Ca2+ signaling and InsP3-induced Ca2+ release from the endoplasmic reticulum (ER).
Results
Increasing intracellular cAMP level by bath application of forskolin, IBMX or cAMP in the continuous presence of threshold 5-HT concentrations converted oscillatory [Ca2+]i changes into a sustained increase. Intraluminal Ca2+ measurements in the ER of ß-escin-permeabilized glands with mag-fura-2 revealed that cAMP augmented InsP3-induced Ca2+ release in a concentration-dependent manner. This indicated that cAMP sensitized the InsP3 receptor Ca2+ channel for InsP3. By using cAMP analogs that activated either protein kinase A (PKA) or Epac and the application of PKA-inhibitors, we found that cAMP-induced augmentation of InsP3-induced Ca2+ release was mediated by PKA not by Epac. Recordings of the transepithelial potential of the glands suggested that cAMP sensitized the InsP3/Ca2+ signaling pathway for 5-HT, because IBMX potentiated Ca2+-dependent Cl- transport activated by a threshold 5-HT concentration.
Conclusion
This report shows, for the first time for an insect system, that cAMP can potentiate InsP3-induced Ca2+ release from the ER in a PKA-dependent manner, and that this crosstalk between cAMP and InsP3/Ca2+ signaling pathways enhances transepithelial electrolyte transport.
To understand past flood changes in the Rhine catchment and in particular the role of anthropogenic climate change in extreme flows, an attribution study relying on a proper GCM (general circulation model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach. This approach assumes a strong link between weather patterns and local climate, and sufficient GCM skill in reproducing weather pattern climatology. These presuppositions are unprecedentedly evaluated here using 111 years of daily climate data from 490 stations in the Rhine basin and comprehensively testing the number of classification parameters and GCM weather pattern characteristics. A classification based on a combination of mean sea level pressure, temperature, and humidity from the ERA20C reanalysis of atmospheric fields over central Europe with 40 weather types was found to be the most appropriate for stratifying six local climate variables. The corresponding skill is quite diverse though, ranging from good for radiation to poor for precipitation. Especially for the latter it was apparent that pressure fields alone cannot sufficiently stratify local variability. To test the skill of the latest generation of GCMs from the CMIP5 ensemble in reproducing the frequency, seasonality, and persistence of the derived weather patterns, output from 15 GCMs is evaluated. Most GCMs are able to capture these characteristics well, but some models showed consistent deviations in all three evaluation criteria and should be excluded from further attribution analysis.
The simultaneous detection of energy, momentum and temporal information in electron spectroscopy is the key aspect to enhance the detection efficiency in order to broaden the range of scientific applications. Employing a novel 60 degrees wide angle acceptance lens system, based on an additional accelerating electron optical element, leads to a significant enhancement in transmission over the previously employed 30 degrees electron lenses. Due to the performance gain, optimized capabilities for time resolved electron spectroscopy and other high transmission applications with pulsed ionizing radiation have been obtained. The energy resolution and transmission have been determined experimentally utilizing BESSY II as a photon source. Four different and complementary lens modes have been characterized. (C) 2017 The Authors. Published by Elsevier B.V.
Ice-rich yedoma-dominated landscapes store con-
siderable amounts of organic carbon (C) and nitrogen (N)
and are vulnerable to degradation under climate warming.
We investigate the C and N pools in two thermokarst-affected
yedoma landscapes – on Sobo-Sise Island and on Bykovsky
Peninsula in the north of eastern Siberia. Soil cores up to 3 m
depth were collected along geomorphic gradients and anal-
ysed for organic C and N contents. A high vertical sampling
density in the profiles allowed the calculation of C and N
stocks for short soil column intervals and enhanced under-
standing of within-core parameter variability. Profile-level C
and N stocks were scaled to the landscape level based on
landform classifications from 5 m resolution, multispectral
RapidEye satellite imagery. Mean landscape C and N storage
in the first metre of soil for Sobo-Sise Island is estimated to
be 20.2 kg C m −2 and 1.8 kg N m −2 and for Bykovsky Penin-
sula 25.9 kg C m −2 and 2.2 kg N m −2 . Radiocarbon dating
demonstrates the Holocene age of thermokarst basin de-
posits but also suggests the presence of thick Holocene-
age cover layers which can reach up to 2 m on top of in-
tact yedoma landforms. Reconstructed sedimentation rates
of 0.10–0.57 mm yr −1 suggest sustained mineral soil accu-
mulation across all investigated landforms. Both yedoma and
thermokarst landforms are characterized by limited accumu-
lation of organic soil layers (peat).
We further estimate that an active layer deepening of
about 100 cm will increase organic C availability in a sea-
sonally thawed state in the two study areas by ∼ 5.8 Tg
(13.2 kg C m −2 ). Our study demonstrates the importance of
increasing the number of C and N storage inventories in ice-
rich yedoma and thermokarst environments in order to ac-
count for high variability of permafrost and thermokarst en-
vironments in pan-permafrost soil C and N pool estimates.
PURPOSE. Graves' orbitopathy (GO) is an autoimmune orbital disorder associated with Graves' disease caused by thyrotropin receptor autoantibodies. Orbital fibroblasts (OFs) and CD40 play a key role in disease pathogenesis. The bioactive lipid sphingosine-1-phosphate (S1P) has been implicated in promoting adipogenesis, fibrosis, and inflammation in OFs. We investigated the role of CD40 signaling in inducing S1P activity in orbital inflammation.
METHODS. OFs and T cells were derived from GO patients and healthy control (Ctl) persons. S1P abundance in orbital tissues was evaluated by immunofluorescence. OFs were stimulated with CD40 ligand and S1P levels were determined by ELISA. Further, activities of acid sphingomyelinase (ASM), acid ceramidase, and sphingosine kinase were measured by ultraperformance liquid chromatography. Sphingosine and ceramide contents were analyzed by mass spectrometry. Finally, the role for S1P in T-cell attraction was investigated by T-cell migration assays.
RESULTS. GO orbital tissue showed elevated amounts of S1P as compared to control samples. Stimulation of CD40 induced S1P expression in GO-derived OFs, while Ctl-OFs remained unaffected. A significant increase of ASM and sphingosine kinase activities, as well as lipid formation, was observed in GO-derived OFs. Migration assay of T cells in the presence of SphK inhibitor revealed that S1P released by GO-OFs attracted T cells for migration.
CONCLUSIONS. The results demonstrated that CD40 ligand stimulates GO fibroblast to produce S1P, which is a driving force for T-cell migration. The results support the use of S1P receptor signaling modulators in GO management.
Cell-free protein synthesis as a novel tool for directed glycoengineering of active erythropoietin
(2018)
As one of the most complex post-translational modification, glycosylation is widely involved in cell adhesion, cell proliferation and immune response. Nevertheless glycoproteins with an identical polypeptide backbone mostly differ in their glycosylation patterns. Due to this heterogeneity, the mapping of different glycosylation patterns to their associated function is nearly impossible. In the last years, glycoengineering tools including cell line engineering, chemoenzymatic remodeling and site-specific glycosylation have attracted increasing interest. The therapeutic hormone erythropoietin (EPO) has been investigated in particular by various groups to establish a production process resulting in a defined glycosylation pattern. However commercially available recombinant human EPO shows batch-to-batch variations in its glycoforms. Therefore we present an alternative method for the synthesis of active glycosylated EPO with an engineered O-glycosylation site by combining eukaryotic cell-free protein synthesis and site-directed incorporation of non-canonical amino acids with subsequent chemoselective modifications.
The connection between the macroscopic description of collective chaos and the underlying microscopic dynamics is thoroughly analysed in mean-field models of one-dimensional oscillators. We investigate to what extent infinitesimal perturbations of the microscopic configurations can provide information also on the stability of the corresponding macroscopic phase. In ensembles of identical one-dimensional dynamical units, it is possible to represent the microscopic configurations so as to make transparent their connection with the macroscopic world. As a result, we find evidence of an intermediate, mesoscopic, range of distances, over which the instability is neither controlled by the microscopic equations nor by the macroscopic ones. We examine a whole series of indicators, ranging from the usual microscopic Lyapunov exponents, to the collective ones, including finite-amplitude exponents. A system of pulse-coupled oscillators is also briefly reviewed as an example of non-identical phase oscillators where collective chaos spontaneously emerges.
Exosomes are small membrane vesicles released by different cell types, including hepatocytes, that play important roles in intercellular communication. We have previously demonstrated that hepatocyte-derived exosomes contain the synthetic machinery to form sphingosine-1-phosphate (S1P) in target hepatocytes resulting in proliferation and liver regeneration after ischemia/reperfusion (I/R) injury. We also demonstrated that the chemokine receptors, CXCR1 and CXCR2, regulate liver recovery and regeneration after I/R injury. In the current study, we sought to determine if the regulatory effects of CXCR1 and CXCR2 on liver recovery and regeneration might occur via altered release of hepatocyte exosomes. We found that hepatocyte release of exosomes was dependent upon CXCR1 and CXCR2. CXCR1-deficient hepatocytes produced fewer exosomes, whereas CXCR2-deficient hepatocytes produced more exosomes compared to their wild-type controls. In CXCR2-deficient hepatocytes, there was increased activity of neutral sphingomyelinase (Nsm) and intracellular ceramide. CXCR1-deficient hepatocytes had no alterations in Nsm activity or ceramide production. Interestingly, exosomes from CXCR1-deficient hepatocytes had no effect on hepatocyte proliferation, due to a lack of neutral ceramidase and sphingosine kinase. The data demonstrate that CXCR1 and CXCR2 regulate hepatocyte exosome release. The mechanism utilized by CXCR1 remains elusive, but CXCR2 appears to modulate Nsm activity and resultant production of ceramide to control exosome release. CXCR1 is required for packaging of enzymes into exosomes that mediate their hepatocyte proliferative effect.
Necrotrophic as well as saprophytic small-spored Altemaria (A.) species are annually responsible for major losses of agricultural products, such as cereal crops, associated with the contamination of food and feedstuff with potential health-endangering Altemaria toxins. Knowledge of the metabolic capabilities of different species-groups to form mycotoxins is of importance for a reliable risk assessment. 93 Altemaria strains belonging to the four species groups Alternaria tenuissima, A. arborescens, A. altemata, and A. infectoria were isolated from winter wheat kernels harvested from fields in Germany and Russia and incubated under equal conditions. Chemical analysis by means of an HPLC-MS/MS multi-Alternaria-toxin-method showed that 95% of all strains were able to form at least one of the targeted 17 non-host specific Altemaria toxins. Simultaneous production of up to 15 (modified) Altemaria toxins by members of the A. tenuissima, A. arborescens, A. altemata species-groups and up to seven toxins by A. infectoria strains was demonstrated. Overall tenuazonic acid was the most extensively formed mycotoxin followed by alternariol and alternariol mono methylether, whereas altertoxin I was the most frequently detected toxin. Sulfoconjugated modifications of alternariol, alternariol mono methylether, altenuisol and altenuene were frequently determined. Unknown perylene quinone derivatives were additionally detected. Strains of the species-group A. infectoria could be segregated from strains of the other three species-groups due to significantly lower toxin levels and the specific production of infectopyrone. Apart from infectopyrone, alterperylenol was also frequently produced by 95% of the A. infectoria strains. Neither by the concentration nor by the composition of the targeted Altemaria toxins a differentiation between the species-groups A. altemata, A. tenuissima and A. arborescens was possible.
The nitric oxide (NO)/soluble guanylate cyclase (sGC)/cyclic guanosine monophasphate (cGMP)-signalling pathway is impaired under oxidative stress conditions due to oxidation and subsequent loss of the prosthetic sGC heme group as observed in particular in chronic renal failure. Thus, the pool of heme free sGC is increased under pathological conditions. sGC activators such as cinaciguat selectively activate the heme free form of sGC and target the disease associated enzyme. In this study, a therapeutic effect of long-term activation of heme free sGC by the sGC activator cinaciguat was investigated in an experimental model of salt-sensitive hypertension, a condition that is associated with increased oxidative stress, heme loss from sGC and development of chronic renal failure. For that purpose Dahl/ss rats, which develop severe hypertension upon high salt intake, were fed a high salt diet (8% NaCl) containing either placebo or cinaciguat for 21 weeks. Cinaciguat markedly improved survival and ameliorated the salt-induced increase in blood pressure upon treatment with cinaciguat compared to placebo. Renal function was significantly improved in the cinaciguat group compared to the placebo group as indicated by a significantly improved glomerular filtration rate and reduced urinary protein excretion. This was due to anti-fibrotic and antiinflammatory effects of the cinaciguat treatment. Taken together, this is the first study showing that long-term activation of heme free sGC leads to renal protection in an experimental model of hypertension and chronic kidney disease. These results underline the promising potential of cinaciguat to treat renal diseases by targeting the disease associated heme free form of sGC.
claspfolio 2
(2014)
Building on the award-winning, portfolio-based ASP solver claspfolio, we present claspfolio 2, a modular and open solver architecture that integrates several different portfolio-based algorithm selection approaches and techniques. The claspfolio 2 solver framework supports various feature generators, solver selection approaches, solver portfolios, as well as solver-schedule-based pre-solving techniques. The default configuration of claspfolio 2 relies on a light-weight version of the ASP solver clasp to generate static and dynamic instance features. The flexible open design of claspfolio 2 is a distinguishing factor even beyond ASP. As such, it provides a unique framework for comparing and combining existing portfolio-based algorithm selection approaches and techniques in a single, unified framework. Taking advantage of this, we conducted an extensive experimental study to assess the impact of different feature sets, selection approaches and base solver portfolios. In addition to gaining substantial insights into the utility of the various approaches and techniques, we identified a default configuration of claspfolio 2 that achieves substantial performance gains not only over clasp's default configuration and the earlier version of claspfolio, but also over manually tuned configurations of clasp.
During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007–2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash–Sutcliffe efficiency of 0.72 and a Kling–Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.
Climate change increases riverine carbon outgassing, while export to the ocean remains uncertain
(2016)
Any regular interaction of land and river during flooding affects carbon pools within the terrestrial system, riverine carbon and carbon exported from the system. In the Amazon basin carbon fluxes are considerably influenced by annual flooding, during which terrigenous organic material is imported to the river. The Amazon basin therefore represents an excellent example of a tightly coupled terrestrial-riverine system. The processes of generation, conversion and transport of organic carbon in such a coupled terrigenous-riverine system strongly interact and are climate-sensitive, yet their functioning is rarely considered in Earth system models and their response to climate change is still largely unknown. To quantify regional and global carbon budgets and climate change effects on carbon pools and carbon fluxes, it is important to account for the coupling between the land, the river, the ocean and the atmosphere. We developed the RIVerine Carbon Model (RivCM), which is directly coupled to the well-established dynamic vegetation and hydrology model LPJmL, in order to account for this large-scale coupling. We evaluate RivCM with observational data and show that some of the values are reproduced quite well by the model, while we see large deviations for other variables. This is mainly caused by some simplifications we assumed. Our evaluation shows that it is possible to reproduce large-scale carbon transport across a river system but that this involves large uncertainties. Acknowledging these uncertainties, we estimate the potential changes in riverine carbon by applying RivCM for climate forcing from five climate models and three CO2 emission scenarios (Special Report on Emissions Scenarios, SRES). We find that climate change causes a doubling of riverine organic carbon in the southern and western basin while reducing it by 20% in the eastern and northern parts. In contrast, the amount of riverine inorganic carbon shows a 2- to 3-fold increase in the entire basin, independent of the SRES scenario. The export of carbon to the atmosphere increases as well, with an average of about 30 %. In contrast, changes in future export of organic carbon to the Atlantic Ocean depend on the SRES scenario and are projected to either decrease by about 8.9% (SRES A1B) or increase by about 9.1% (SRES A2). Such changes in the terrigenous-riverine system could have local and regional impacts on the carbon budget of the whole Amazon basin and parts of the Atlantic Ocean. Changes in riverine carbon could lead to a shift in the riverine nutrient supply and pH, while changes in the exported carbon to the ocean lead to changes in the supply of organic material that acts as a food source in the Atlantic. On larger scales the increased outgassing of CO2 could turn the Amazon basin from a sink of carbon to a considerable source. Therefore, we propose that the coupling of terrestrial and riverine carbon budgets should be included in subsequent analysis of the future regional carbon budget.
Climate impacts on transocean dispersal and habitat in gray whales from the Pleistocene to 2100
(2015)
Arctic animals face dramatic habitat alteration due to ongoing climate change. Understanding how such species have responded to past glacial cycles can help us forecast their response to today's changing climate. Gray whales are among those marine species likely to be strongly affected by Arctic climate change, but a thorough analysis of past climate impacts on this species has been complicated by lack of information about an extinct population in the Atlantic. While little is known about the history of Atlantic gray whales or their relationship to the extant Pacific population, the extirpation of the Atlantic population during historical times has been attributed to whaling. We used a combination of ancient and modern DNA, radiocarbon dating and predictive habitat modelling to better understand the distribution of gray whales during the Pleistocene and Holocene. Our results reveal that dispersal between the Pacific and Atlantic was climate dependent and occurred both during the Pleistocene prior to the last glacial period and the early Holocene immediately following the opening of the Bering Strait. Genetic diversity in the Atlantic declined over an extended interval that predates the period of intensive commercial whaling, indicating this decline may have been precipitated by Holocene climate or other ecological causes. These first genetic data for Atlantic gray whales, particularly when combined with predictive habitat models for the year 2100, suggest that two recent sightings of gray whales in the Atlantic may represent the beginning of the expansion of this species' habitat beyond its currently realized range.
By using 3-year global positioning system (GPS)measurements from December 2013 to November 2016, we provide in this study a detailed survey on the climatology of the GPS signal loss of Swarm onboard receivers. Our results show that the GPS signal losses prefer to occur at both low latitudes between ±5 and ±20 ◦ magnetic latitude (MLAT) and high latitudes above 60 ◦ MLAT in both hemispheres. These events at all latitudes are observed mainly during equinoxes and December solstice months, while totally absent during June solstice months. At low latitudes the GPS signal losses are caused by the equatorial plasma irregularities shortly after sunset, and at high latitude they are also highly related to the large density gradients associated with ionospheric irregularities. Additionally, the high-latitude events are more often observed in the Southern Hemisphere, occurring mainly at the cusp region and along nightside auroral latitudes. The signal losses mainly happen for those GPS rays with elevation angles less than 20 ◦ , and more commonly occur when the line of sight between GPS and Swarm satellites is aligned with the shell structure of plasma irregularities. Our results also confirm that the capability of the Swarm receiver has been improved after the bandwidth of the phase-locked loop (PLL) widened, but the updates cannot radically avoid the interruption in tracking GPS satellites caused by the ionospheric plasma irregularities. Additionally, after the PLL bandwidth increased larger than 0.5 Hz, some unexpected signal losses are observed even at middle latitudes, which are not related to the ionospheric plasma irregularities. Our results suggest that rather than 1.0 Hz, a PLL bandwidth of 0.5 Hz is a more suitable value for the Swarm receiver.
Closing yield gaps
(2015)
Global food production needs to be increased by 60-110% between 2005 and 2050 to meet growing food and feed demand. Intensification and/or expansion of agriculture are the two main options available to meet the growing crop demands. Land conversion to expand cultivated land increases GHG emissions and impacts biodiversity and ecosystem services. Closing yield gaps to attain potential yields may be a viable option to increase the global crop production. Traditional methods of agricultural intensification often have negative externalities. Therefore, there is a need to explore location-specific methods of sustainable agricultural intensification. We identified regions where the achievement of potential crop calorie production on currently cultivated land will meet the present and future food demand based on scenario analyses considering population growth and changes in dietary habits. By closing yield gaps in the current irrigated and rain-fed cultivated land, about 24% and 80% more crop calories can respectively be produced compared to 2000. Most countries will reach food self-sufficiency or improve their current food self-sufficiency levels if potential crop production levels are achieved. As a novel approach, we defined specific input and agricultural management strategies required to achieve the potential production by overcoming biophysical and socioeconomic constraints causing yield gaps. The management strategies include: fertilizers, pesticides, advanced soil management, land improvement, management strategies coping with weather induced yield variability, and improving market accessibility. Finally, we estimated the required fertilizers (N, P2O5, and K2O) to attain the potential yields. Globally, N-fertilizer application needs to increase by 45-73%, P2O5-fertilizer by 22-46%, and K2O-fertilizer by 2-3 times compared to the year 2010 to attain potential crop production. The sustainability of such agricultural intensification largely depends on the way management strategies for closing yield gaps are chosen and implemented.
The clumping of massive star winds is an established paradigm, which is confirmed by multiple lines of evidence and is supported by stellar wind theory. We use the results from time-dependent hydrodynamical models of the instability in the line-driven wind of a massive supergiant star to derive the time-dependent accretion rate on to a compact object in the Bondi-Hoyle-Lyttleton approximation. The strong density and velocity fluctuations in the wind result in strong variability of the synthetic X-ray light curves. Photoionization of inhomogeneous winds is different from the photoinization of smooth winds. The degree of ionization is affected by the wind clumping. The wind clumping must also be taken into account when comparing the observed and model spectra of the photoionized stellar wind.
We propose a novel cluster-based reduced-order modelling (CROM) strategy for unsteady flows. CROM combines the cluster analysis pioneered in Gunzburger's group (Burkardt, Gunzburger & Lee, Comput. Meth. Appl. Mech. Engng, vol. 196, 2006a, pp. 337-355) and transition matrix models introduced in fluid dynamics in Eckhardt's group (Schneider, Eckhardt & Vollmer, Phys. Rev. E, vol. 75, 2007, art. 066313). CROM constitutes a potential alternative to POD models and generalises the Ulam-Galerkin method classically used in dynamical systems to determine a finite-rank approximation of the Perron-Frobenius operator. The proposed strategy processes a time-resolved sequence of flow snapshots in two steps. First, the snapshot data are clustered into a small number of representative states, called centroids, in the state space. These centroids partition the state space in complementary non-overlapping regions (centroidal Voronoi cells). Departing from the standard algorithm, the probabilities of the clusters are determined, and the states are sorted by analysis of the transition matrix. Second, the transitions between the states are dynamically modelled using a Markov process. Physical mechanisms are then distilled by a refined analysis of the Markov process, e. g. using finite-time Lyapunov exponent (FTLE) and entropic methods. This CROM framework is applied to the Lorenz attractor (as illustrative example), to velocity fields of the spatially evolving incompressible mixing layer and the three-dimensional turbulent wake of a bluff body. For these examples, CROM is shown to identify non-trivial quasi-attractors and transition processes in an unsupervised manner. CROM has numerous potential applications for the systematic identification of physical mechanisms of complex dynamics, for comparison of flow evolution models, for the identification of precursors to desirable and undesirable events, and for flow control applications exploiting nonlinear actuation dynamics.
Cocoa Bean Proteins
(2019)
The protein fractions of cocoa have been implicated influencing both the bioactive potential and sensory properties of cocoa and cocoa products. The objective of the present review is to show the impact of different stages of cultivation and processing with regard to the changes induced in the protein fractions. Special focus has been laid on the major seed storage proteins throughout the different stages of processing. The study starts with classical introduction of the extraction and the characterization methods used, while addressing classification approaches of cocoa proteins evolved during the timeline. The changes in protein composition during ripening and maturation of cocoa seeds, together with the possible modifications during the post-harvest processing (fermentation, drying, and roasting), have been documented. Finally, the bioactive potential arising directly or indirectly from cocoa proteins has been elucidated. The “state of the art” suggests that exploration of other potentially bioactive components in cocoa needs to be undertaken, while considering the complexity of reaction products occurring during the roasting phase of the post-harvest processing. Finally, the utilization of partially processed cocoa beans (e.g., fermented, conciliatory thermal treatment) can be recommended, providing a large reservoir of bioactive potentials arising from the protein components that could be instrumented in functionalizing foods.
We show that the codifference is a useful tool in studying the ergodicity breaking and non-Gaussianity properties of stochastic time series. While the codifference is a measure of dependence that was previously studied mainly in the context of stable processes, we here extend its range of applicability to random-parameter and diffusing-diffusivity models which are important in contemporary physics, biology and financial engineering. We prove that the codifference detects forms of dependence and ergodicity breaking which are not visible from analysing the covariance and correlation functions. We also discuss a related measure of dispersion, which is a nonlinear analogue of the mean squared displacement.
Based on niche theory, closely related and morphologically similar species are not predicted to coexist due to overlap in resource and habitat use. Local assemblages of bats often contain cryptic taxa, which co-occur despite notable similarities in morphology and ecology. We measured in two different habitat types on Madagascar levels of stable carbon and nitrogen isotopes in hair (n = 103) and faeces (n = 57) of cryptic Vespertilionidae taxa to indirectly examine whether fine-grained trophic niche differentiation explains their coexistence. In the dry deciduous forest (Kirindy), six sympatric species ranged over 6.0% in delta N-15, i.e. two trophic levels, and 4.2% in delta C-13 with a community mean of 11.3% in delta N-15 and - 21.0% in delta C-13. In the mesic forest (Antsahabe), three sympatric species ranged over one trophic level (delta N-15: 2.4%, delta C-13: 1.0%) with a community mean of 8.0% delta N-15 and - 21.7% in delta C-13. Multivariate analyses and residual permutation of Euclidian distances in delta C-13- delta N-15 bi-plots revealed in both communities distinct stable isotope signatures and species separation for the hair samples among coexisting Vespertilionidae. Intraspecific variation in faecal and hair stable isotopes did not indicate that seasonal migration might relax competition and thereby facilitate the local co-occurrence of sympatric taxa.
The performance of hybridization capture combined with next-generation sequencing (NGS) has seen limited investigation with samples from hot and arid regions until now. We applied hybridization capture and shotgun sequencing to recover DNA sequences from bone specimens of ancient-domestic dromedary (Camelus dromedarius) and its extinct ancestor, the wild dromedary from Jordan, Syria, Turkey and the Arabian Peninsula, respectively. Our results show that hybridization capture increased the percentage of mitochondrial DNA (mtDNA) recovery by an average 187-fold and in some cases yielded virtually complete mitochondrial (mt) genomes at multifold coverage in a single capture experiment. Furthermore, we tested the effect of hybridization temperature and time by using a touchdown approach on a limited number of samples. We observed no significant difference in the number of unique dromedary mtDNA reads retrieved with the standard capture compared to the touchdown method. In total, we obtained 14 partial mitochondrial genomes from ancient-domestic dromedaries with 17-95% length coverage and 1.27-47.1-fold read depths for the covered regions. Using whole-genome shotgun sequencing, we successfully recovered endogenous dromedary nuclear DNA (nuDNA) from domestic and wild dromedary specimens with 1-1.06-fold read depths for covered regions. Our results highlight that despite recent methodological advances, obtaining ancient DNA (aDNA) from specimens recovered from hot, arid environments is still problematic. Hybridization protocols require specific optimization, and samples at the limit of DNA preservation need multiple replications of DNA extraction and hybridization capture as has been shown previously for Middle Pleistocene specimens.
Solving problems combining task and motion planning requires searching across a symbolic search space and a geometric search space. Because of the semantic gap between symbolic and geometric representations, symbolic sequences of actions are not guaranteed to be geometrically feasible. This compels us to search in the combined search space, in which frequent backtracks between symbolic and geometric levels make the search inefficient. We address this problem by guiding symbolic search with rich information extracted from the geometric level through culprit detection mechanisms.
Small scale distribution of insect root herbivores may promote plant species diversity by creating patches of different herbivore pressure. However, determinants of small scale distribution of insect root herbivores, and impact of land use intensity on their small scale distribution are largely unknown. We sampled insect root herbivores and measured vegetation parameters and soil water content along transects in grasslands of different management intensity in three regions in Germany. We calculated community-weighted mean plant traits to test whether the functional plant community composition determines the small scale distribution of insect root herbivores. To analyze spatial patterns in plant species and trait composition and insect root herbivore abundance we computed Mantel correlograms. Insect root herbivores mainly comprised click beetle (Coleoptera, Elateridae) larvae (43%) in the investigated grasslands. Total insect root herbivore numbers were positively related to community-weighted mean traits indicating high plant growth rates and biomass (specific leaf area, reproductive-and vegetative plant height), and negatively related to plant traits indicating poor tissue quality (leaf C/N ratio). Generalist Elaterid larvae, when analyzed independently, were also positively related to high plant growth rates and furthermore to root dry mass, but were not related to tissue quality. Insect root herbivore numbers were not related to plant cover, plant species richness and soil water content. Plant species composition and to a lesser extent plant trait composition displayed spatial autocorrelation, which was not influenced by land use intensity. Insect root herbivore abundance was not spatially autocorrelated. We conclude that in semi-natural grasslands with a high share of generalist insect root herbivores, insect root herbivores affiliate with large, fast growing plants, presumably because of availability of high quantities of food. Affiliation of insect root herbivores with large, fast growing plants may counteract dominance of those species, thus promoting plant diversity.
Fractures serve as highly conductive preferential flow paths for fluids in rocks, which are difficult to exactly reconstruct in numerical models. Especially, in low-conductive rocks, fractures are often the only pathways for advection of solutes and heat. The presented study compares the results from hydraulic and tracer tomography applied to invert a theoretical discrete fracture network (DFN) that is based on data from synthetic cross-well testing. For hydraulic tomography, pressure pulses in various injection intervals are induced and the pressure responses in the monitoring intervals of a nearby observation well are recorded. For tracer tomography, a conservative tracer is injected in different well levels and the depth-dependent breakthrough of the tracer is monitored. A recently introduced transdimensional Bayesian inversion procedure is applied for both tomographical methods, which adjusts the fracture positions, orientations, and numbers based on given geometrical fracture statistics. The used Metropolis-Hastings-Green algorithm is refined by the simultaneous estimation of the measurement error’s variance, that is, the measurement noise. Based on the presented application to invert the two-dimensional cross-section between source and the receiver well, the hydraulic tomography reveals itself to be more suitable for reconstructing the original DFN. This is based on a probabilistic representation of the inverted results by means of fracture probabilities.
Winter storms are the most costly natural hazard for European residential property. We compare four distinct storm damage functions with respect to their forecast accuracy and variability, with particular regard to the most severe winter storms. The analysis focuses on daily loss estimates under differing spatial aggregation, ranging from district to country level. We discuss the broad and heavily skewed distribution of insured losses posing difficulties for both the calibration and the evaluation of damage functions. From theoretical considerations, we provide a synthesis between the frequently discussed cubic wind–damage relationship and recent studies that report much steeper damage functions for European winter storms. The performance of the storm loss models is evaluated for two sources of wind gust data, direct observations by the German Weather Service and ERA-Interim reanalysis data. While the choice of gust data has little impact on the evaluation of German storm loss, spatially resolved coefficients of variation reveal dependence between model and data choice. The comparison shows that the probabilistic models by Heneka et al. (2006) and Prahl et al. (2012) both provide accurate loss predictions for moderate to extreme losses, with generally small coefficients of variation. We favour the latter model in terms of model applicability. Application of the versatile deterministic model by Klawa and Ulbrich (2003) should be restricted to extreme loss, for which it shows the least bias and errors comparable to the probabilistic model by Prahl et al. (2012).
Preference handling and optimization are indispensable means for addressing nontrivial applications in Answer Set Programming (ASP). However, their implementation becomes difficult whenever they bring about a significant increase in computational complexity. As a consequence, existing ASP systems do not offer complex optimization capacities, supporting, for instance, inclusion-based minimization or Pareto efficiency. Rather, such complex criteria are typically addressed by resorting to dedicated modeling techniques, like saturation. Unlike the ease of common ASP modeling, however, these techniques are rather involved and hardly usable by ASP laymen. We address this problem by developing a general implementation technique by means of meta-prpogramming, thus reusing existing ASP systems to capture various forms of qualitative preferences among answer sets. In this way, complex preferences and optimization capacities become readily available for ASP applications.
The isotopic composition of water in ice sheets is extensively used to infer past climate changes. In low-accumulation regions their interpretation is, however, challenged by poorly constrained effects that may influence the initial isotope signal during and after deposition of the snow. This is reflected in snow-pit isotope data from Kohnen Station, Antarctica, which exhibit a seasonal cycle but also strong interannual variations that contradict local temperature observations. These inconsistencies persist even after averaging many profiles and are thus not explained by local stratigraphic noise. Previous studies have suggested that post-depositional processes may significantly influence the isotopic composition of East Antarctic firn. Here, we investigate the importance of post-depositional processes within the open-porous firn (greater than or similar to 10 cm depth) at Kohnen Station by separating spatial from temporal variability. To this end, we analyse 22 isotope profiles obtained from two snow trenches and examine the temporal isotope modifications by comparing the new data with published trench data extracted 2 years earlier. The initial isotope profiles undergo changes over time due to downward advection, firn diffusion and densification in magnitudes consistent with independent estimates. Beyond that, we find further modifications of the original isotope record to be unlikely or small in magnitude (<< 1 parts per thousand RMSD). These results show that the discrepancy between local temperatures and isotopes most likely originates from spatially coherent processes prior to or during deposition, such as precipitation intermittency or systematic isotope modifications acting on drifting or loose surface snow.
The size of plant organs, such as leaves and flowers, is determined by an interaction of genotype and environmental influences. Organ growth occurs through the two successive processes of cell proliferation followed by cell expansion. A number of genes influencing either or both of these processes and thus contributing to the control of final organ size have been identified in the last decade. Although the overall picture of the genetic regulation of organ size remains fragmentary, two transcription factor/microRNA-based genetic pathways are emerging in the control of cell proliferation. However, despite this progress, fundamental questions remain unanswered, such as the problem of how the size of a growing organ could be monitored to determine the appropriate time for terminating growth. While genetic analysis will undoubtedly continue to advance our knowledge about size control in plants, a deeper understanding of this and other basic questions will require including advanced live-imaging and mathematical modeling, as impressively demonstrated by some recent examples. This should ultimately allow the comparison of the mechanisms underlying size control in plants and in animals to extract common principles and lineage-specific solutions.