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The history of the Messiah in Judaism is a history of disappointed hopes. Again and again, there were salvation fi gures to whom this role was ascribed. But redemption from occupation and foreign rule, exile, oppression and persecution failed to materialize. Therefore, the expectation of the Messiah fell to the periphery of Jewish theology. This article examinesin what ways the messianic concept plays a role in modern times and what it contributes to describing the relationship between God and humanity in Judaism. The author intends to show the development from the abandonment of a personal Messiah towards the affi rmation of the prophets’ hope for a universal messianic age in which the duty of all people to participate in the healing of the world becomes central. What becomes also clear is: The messiah idea cannot be a bridge between Christianity and Judaism.
Trade-offs between traits are present across different levels of biological systems and ultimately reflect constraints imposed by physicochemical laws and the structure of underlying biochemical networks. Yet, mechanistic explanation of how trade-offs between molecular traits arise and how they relate to optimization of fitness-related traits remains elusive. Here, we introduce the concept of relative flux trade-offs and propose a constraint-based approach, termed FluTOr, to identify metabolic reactions whose fluxes are in relative trade-off with respect to an optimized fitness-related cellular task, like growth. We then employed FluTOr to identify relative flux trade-offs in the genome-scale metabolic networks of Escherichia coli, Saccharomyces cerevisiae, and Arabidopsis thaliana. For the metabolic models of E. coli and S. cerevisiae we showed that: (i) the identified relative flux trade-offs depend on the carbon source used and that (ii) reactions that participated in relative trade-offs in both species were implicated in cofactor biosynthesis. In contrast to the two microorganisms, the relative flux trade-offs for the metabolic model of A. thaliana did not depend on the available nitrogen sources, reflecting the differences in the underlying metabolic network as well as the considered environments. Lastly, the established connection between relative flux trade-offs allowed us to identify overexpression targets that can be used to optimize fitness-related traits. Altogether, our computational approach and findings demonstrate how relative flux trade-offs can shape optimization of metabolic tasks, important in biotechnological applications.
Formal constraints on crossing dependencies have played a large role in research on the formal complexity of natural language grammars and parsing. Here we ask whether the apparent evidence for constraints on crossing dependencies in treebanks might arise because of independent constraints on trees, such as low arity and dependency length minimization. We address this question using two sets of experiments. In Experiment 1, we compare the distribution of formal properties of crossing dependencies, such as gap degree, between real trees and baseline trees matched for rate of crossing dependencies and various other properties. In Experiment 2, we model whether two dependencies cross, given certain psycholinguistic properties of the dependencies. We find surprisingly weak evidence for constraints originating from the mild context-sensitivity literature (gap degree and well-nestedness) beyond what can be explained by constraints on rate of crossing dependencies, topological properties of the trees, and dependency length. However, measures that have emerged from the parsing literature (e.g., edge degree, end-point crossings, and heads' depth difference) differ strongly between real and random trees. Modeling results show that cognitive metrics relating to information locality and working-memory limitations affect whether two dependencies cross or not, but they do not fully explain the distribution of crossing dependencies in natural languages. Together these results suggest that crossing constraints are better characterized by processing pressures than by mildly context-sensitive constraints.
Otter shrew mitogenomes (Afrotheria, Potamogalidae) reconstructed from historical museum skins
(2022)
African otter shrews (Potamogalidae) are Afrotherian mammals adapted to a semi-aquatic lifestyle. Given their rareness, genetic data on otter shrews are limited. By applying laboratory methods tuned for the recovery of archival DNA and an iterative mapping approach, we reconstructed whole mitochondrial genomes of the Giant (Potamogale velox) and Ruwenzori pygmy otter shrew (Micropotamogale ruwenzorii) from historical museum skins. Phylogenetic analyses are consistent with previous reports in recovering a sister relationship between African otter shrews and Malagasy tenrecs. The long branches separating both lineages, however, support their recognition as separate families.
Critical role of parasite-mediated energy pathway on community response to nutrient enrichment
(2022)
Parasites form an integral part of food webs, however, they are often ignored in classic food web theory or limited to the investigation of trophic transmission pathways. Specifically, direct consumption of parasites by nonhost predators is rarely considered, while it can contribute substantially to energy flow in food webs. In aquatic systems, chytrids constitute a major group of fungal parasites whose free-living infective stages (zoospores) form a highly nutritional food source to zooplankton. Thereby, the consumption of zoospores can create an energy pathway from otherwise inedible phytoplankton to zooplankton ( "mycoloop "). This parasite-mediated energy pathway might be of special importance during phytoplankton blooms dominated by inedible or toxic primary producers like cyanobacteria, which are on the rise with eutrophication and global warming. We theoretically investigated community dynamics and energy transfer in a food web consisting of an edible nonhost and an inedible host phytoplankton species, a parasitic fungus, and a zooplankton species grazing on edible phytoplankton and fungi. Food web dynamics were investigated along a nutrient gradient contrasting nonadaptive zooplankton species representative for filter feeders like cladocerans and zooplankton with the ability to actively adapt their feeding preferences like many copepod species. Overall, the importance of the mycoloop for zooplankton increases with nutrient availability. This increase is smooth for nonadaptive consumers. For adaptive consumers, we observe an abrupt shift from an almost exclusive preference for edible phytoplankton at low nutrient levels to a strong preference for parasitic fungi at high nutrient levels. The model predicts that parasitic fungi could contribute up to 50% of the zooplankton diet in nutrient-rich environments, which agrees with empirical observations on zooplankton gut content from eutrophic systems during blooms of inedible diatoms or cyanobacteria. Our findings highlight the role of parasite-mediated energy pathways for predictions of energy flow and community composition under current and future environmental change.
The acquisition of clitics still remains a highly controversial issue in Greek acquisition literature despite the bulk of studies performed.
Object clitics have been shown to be early acquired by monolingual children in terms of production rates, whereas only highly proficient bilingual children achieve target-like performance.
Crucially, errors in gender marking are persistent for monolingual and bilingual children even when adult-like production rates are achieved.
This study aims to readdress the acquisition of clitics in an innovative way, by entering the variable of gender in an experimental design targeting to assess production and processing by bilingual and monolingual children.
Moreover, we examined the role of language proficiency (in terms of general verbal intelligence and syntactic production abilities). The groups had comparable performance in both tasks (in terms of correct responses and error distribution in production and reaction times in comprehension).
However, verbal intelligence had an effect on the performance of the monolingual but not of the bilingual group in the production task, and bilingual children were overall slower in the comprehension task. Syntactic production abilities did not have any effect. We argue that gender marking affects clitic processing, and we discuss the implications of our findings for bilingual acquisition.
Large agricultural streams receive excessive inputs of nitrogen.
However, quantifying the role of these streams in nitrogen processing remains limited because continuous direct measurements of the interacting and highly time-varying nitrogen processing pathways in larger streams and rivers are very complex.
Therefore, we employed a monitoring-driven modelling approach with high-frequency in situ data and the river water quality model Water Quality Analysis Simulation Program (WASP) 7.5.2 in the 27.4 km reach of the sixth-order agricultural stream called Lower Bode (central Germany) for a 5-year period (2014-2018).
Paired high-frequency sensor data (15 min interval) of discharge, nitrate, dissolved oxygen, and chlorophyll a at upstream and downstream stations were used as model boundaries and for setting model constraints.
The WASP model simulated 15 min intervals of discharge, nitrate, and dissolved oxygen with Nash-Sutcliffe efficiency values higher than 0.9 for calibration and validation, enabling the calculation of gross and net dissolved inorganic nitrogen uptake and pathway rates on a daily, seasonal, and multiannual scale.
Results showed daily net uptake rate of dissolved inorganic nitrogen ranged from -17.4 to 553.9 mgNm(-2)d(-1). The highest daily net uptake could reach almost 30 % of the total input loading, which occurred at extreme low flow in summer 2018.
The growing season (spring and summer) accounted for 91 % of the average net annual uptake of dissolved inorganic nitrogen in the measured period. In spring, both the DIN gross and net uptake were dominated by the phytoplankton uptake pathway. In summer, benthic algae assimilation dominated the gross uptake of dissolved inorganic nitrogen.
Conversely, the reach became a net source of dissolved inorganic nitrogen with negative daily net uptake values in autumn and winter, mainly because the release from benthic algae surpassed uptake processes.
Over the 5 years, average gross and net uptake rates of dissolved inorganic nitrogen were 124.1 and 56.8 mgNm(-2)d(-1), which accounted for only 2.7 % and 1.2 % of the total loadings in the Lower Bode, respectively. The 5-year average gross DIN uptake decreased from assimilation by benthic algae through assimilation by phytoplankton to denitrification.
Our study highlights the value of combining river water quality modelling with high-frequency data to obtain a reliable budget of instream dissolved inorganic nitrogen processing which facilitates our ability to manage nitrogen in aquatic systems.
This study provides a methodology that can be applied to any large stream to quantify nitrogen processing pathway dynamics and complete our understanding of nitrogen cycling.
Temperature impacts on hate speech online: evidence from 4 billion geolocated tweets from the USA
(2022)
Background - A link between weather and aggression in the offline world has been established across a variety of societal settings. Simultaneously, the rapid digitalisation of nearly every aspect of everyday life has led to a high frequency of interpersonal conflicts online. Hate speech online has become a prevalent problem that has been shown to aggravate mental health conditions, especially among young people and marginalised groups.
We examine the effect of temperature on the occurrence of hate speech on the social media platform Twitter and interpret the results in the context of the interlinkage between climate change, human behaviour, and mental health.
Methods - In this quantitative empirical study, we used a supervised machine learning approach to identify hate speech in a dataset containing around 4 billion geolocated tweets from 773 cities across the USA between May 1, 2014 and May 1, 2020.
We statistically evaluated the changes in daily hate tweets against changes in local temperature, isolating the temperature influence from confounding factors using binned panel-regression models.
Findings - The prevalence of hate tweets was lowest at moderate temperatures (12 to 21?) and marked increases in the number of hate tweets were observed at hotter and colder temperatures, reaching up to 12middot5% (95% CI 8middot0-16middot5) for cold temperature extremes (-6 to -3?) and up to 22middot0% (95% CI 20middot5-23middot5) for hot temperature extremes (42 to 45?). Outside of the moderate temperature range, the hate tweets also increased as a proportion of total tweeting activity. The quasi-quadratic shape of the temperature-hate tweet curve was robust across varying climate zones, income quartiles, religious and political beliefs, and both city-level and state-level aggregations.
However, temperature ranges with the lowest prevalence of hate tweets were centred around the local temperature mean and the magnitude of the increases in hate tweets for hot and cold temperatures varied across the climate zones.
Interpretation - Our results highlight hate speech online as a potential channel through which temperature alters interpersonal conflict and societal aggression. We provide empirical evidence that hot and cold temperatures can aggravate aggressive tendencies online. The prevalence of the results across climatic and socioeconomic subgroups points to limitations in the ability of humans to adapt to temperature extremes.
Soil microbial communities are crucial for plant growth and are already depleted by anthropogenic activities.
The application of microbial transplants provides a strategy to restore beneficial soil traits, but less is known about the microbiota of traditional inoculants used in biodynamic agriculture.
In this study, we used amplicon sequencing and quantitative PCR to decipher microbial communities of composts, biodynamic manures, and plant preparations from Austria and France.
In addition, we investigated the effect of extracts derived from biodynamic manure and compost on the rhizosphere microbiome of apple trees. Microbiota abundance, composition, and diversity of biodynamic manures, plant preparations, and composts were distinct. Microbial abundances ranged between 1010-1011 (bacterial 16S rRNA genes) and 109-1011 (fungal ITS genes). The bacterial diversity was significantly higher in biodynamic manures compared to compost without discernible differences in abundance. Fungal diversity was not significantly different while abundance was increased in biodynamic manures. The microbial communities of biodynamic manures and plant preparations were specific for each production site, but all contain potentially plant-beneficial bacterial genera.
When applied in apple orchards, biodynamic preparations (extracts) had the non-significant effect of reducing bacterial and fungal abundance in apple rhizosphere (4 months post-application), while increasing fungal and lowering bacterial Shannon diversity.
One to four months after inoculation, individual taxa indicated differential abundance. We observed the reduction of the pathogenic fungus Alternaria, and the enrichment of potentially beneficial bacterial genera such as Pseudomonas.
Our study paves way for the science-based adaptation of empirically developed biodynamic formulations under different farming practices to restore the vitality of agricultural soils.
Patient monitoring technology has been used to guide therapy and alert staff when a vital sign leaves a predefined range in the intensive care unit (ICU) for decades. However, large amounts of technically false or clinically irrelevant alarms provoke alarm fatigue in staff leading to desensitisation towards critical alarms.
With this systematic review, we are following the Preferred Reporting Items for Systematic Reviews (PRISMA) checklist in order to summarise scientific efforts that aimed to develop IT systems to reduce alarm fatigue in ICUs. 69 peer-reviewed publications were included. The majority of publications targeted the avoidance of technically false alarms, while the remainder focused on prediction of patient deterioration or alarm presentation.
The investigated alarm types were mostly associated with heart rate or arrhythmia, followed by arterial blood pressure, oxygen saturation, and respiratory rate.
Most publications focused on the development of software solutions, some on wearables, smartphones, or headmounted displays for delivering alarms to staff.
The most commonly used statistical models were tree-based. In conclusion, we found strong evidence that alarm fatigue can be alleviated by IT-based solutions.
However, future efforts should focus more on the avoidance of clinically non-actionable alarms which could be accelerated by improving the data availability.
It is often claimed that the entropy of a network's degree distribution is a proxy for its robustness. Here, we clarify the link between degree distribution entropy and giant component robustness to node removal by showing that the former merely sets a lower bound to the latter for randomly configured networks when no other network characteristics are specified. Furthermore, we show that, for networks of fixed expected degree that follow degree distributions of the same form, the degree distribution entropy is not indicative of robustness. By contrast, we show that the remaining degree entropy and robustness have a positive monotonic relationship and give an analytic expression for the remaining degree entropy of the log-normal distribution. We also show that degree-degree correlations are not by themselves indicative of a network's robustness for real networks. We propose an adjustment to how mutual information is measured which better encapsulates structural properties related to robustness.
Contour scanning and process gas type are process parameters typically considered achieving second order effects compared to first order factors such as laser power and scanning speed.
The present work highlights that contour scanning is crucial to ensure geometrical accuracy and thereby the high performance under uniaxial compression of complex Alloy 718 lattice structures.
Studies of X-ray computed tomography visualizations of as-built and compression-strained structures reveal the continuous and smooth bending and compression of the walls, and the earlier onset of internal contact appearance in the denser lattices printed with contour. In contrast, the effect of addition of He to the Ar process gas appears to have limited influence on the mechanical response of the lattices and their microstructure as characterized by electron backscattered diffraction.
However, the addition of He proved to significantly enhance the cooling rate and to reduce the amount of the generated spatters as evidenced by in situ monitoring of the process emissions, which is very promising for the process stability and powder reusability during laser powder bed fusion.
Understanding the assembly mechanism and function of membrane proteins is a fundamental problem in biochemical research. Among the membrane proteins, G protein-coupled receptors (GPCRs) represent the largest class in the human body and have long been considered to function as monomers.
Nowadays, the oligomeric assembly of GPCRs is widely accepted, although the functional importance and therapeutic intervention remain largely unexplored. This is partly due to difficulties in the heterologous production of membrane proteins.
Cell-free protein synthesis (CFPS) with its endogenous endoplasmic reticulum-derived structures has proven as a technique to address this issue.
In this study, we investigate for the first time the conceptual CFPS of a heteromeric GPCR, the gamma-aminobutyric acid receptor type B (GABA(B)), from its protomers BR1 and BR2 using a eukaryotic cell-free lysate. Using a fluorescence-based proximity ligation assay, we provide evidence for colocalization and thus suggesting heterodimerization.
We prove the heterodimeric assembly by a bioluminescence resonance energy transfer saturation assay providing the manufacturability of a heterodimeric GPCR by CFPS. Additionally, we show the binding of a fluorescent orthosteric antagonist, demonstrating the feasibility of combining the CFPS of GPCRs with pharmacological applications.
These results provide a simple and powerful experimental platform for the synthesis of heteromeric GPCRs and open new perspectives for the modelling of protein-protein interactions.
Accordingly, the presented technology enables the targeting of protein assemblies as a new interface for pharmacological intervention in disease-relevant dimers.
Landslide hazard models aim at mitigating landslide impact by providing probabilistic forecasting, and the accuracy of these models hinges on landslide databases for model training and testing.
Landslide databases at times lack information on the underlying triggering mechanism, making these inventories almost unusable in hazard models.
We developed a Python-based unique library, Landsifier, that contains three different machine-Learning frameworks for assessing the likely triggering mechanisms of individual landslides or entire inventories based on landslide geometry.
Two of these methods only use the 2D landslide planforms, and the third utilizes the 3D shape of landslides relying on an underlying digital elevation model (DEM). The base method extracts geometric properties of landslide polygons as a feature space for the shallow learner - random forest (RF).
An alternative method relies on landslide planform images as an input for the deep learning algorithm - convolutional neural network (CNN).
The last framework extracts topological properties of 3D landslides through topological data analysis (TDA) and then feeds these properties as a feature space to the random forest classifier.
We tested all three interchangeable methods on several inventories with known triggers spread over the Japanese archipelago. To demonstrate the effectiveness of developed methods, we used two testing configurations.
The first configuration merges all the available data for the k-fold cross-validation, whereas the second configuration excludes one inventory during the training phase to use as the sole testing inventory.
Our geometric-feature-based method performs satisfactorily, with classification accuracies varying between 67 % and 92 %. We have introduced a more straightforward but data-intensive CNN alternative, as it inputs only landslide images without manual feature selection.
CNN eases the scripting process without losing classification accuracy. Using topological features from 3D landslides (extracted through TDA) in the RF classifier improves classification accuracy by 12 % on average.
TDA also requires less training data. However, the landscape autocorrelation could easily bias TDA-based classification. Finally, we implemented the three methods on an inventory without any triggering information to showcase a real-world application.
Over the past years, NGS has become a crucial workhorse for open-view pathogen diagnostics.
Yet, long turnaround times result from using massively parallel high-throughput technologies as the analysis can only be performed after sequencing has finished. The interpretation of results can further be challenged by contaminations, clinically irrelevant sequences, and the sheer amount and complexity of the data.
We implemented PathoLive, a real-time diagnostics pipeline for the detection of pathogens from clinical samples hours before sequencing has finished.
Based on real-time alignment with HiLive2, mappings are scored with respect to common contaminations, low-entropy areas, and sequences of widespread, non-pathogenic organisms.
The results are visualized using an interactive taxonomic tree that provides an easily interpretable overview of the relevance of hits. For a human plasma sample that was spiked in vitro with six pathogenic viruses, all agents were clearly detected after only 40 of 200 sequencing cycles.
For a real-world sample from Sudan, the results correctly indicated the presence of Crimean-Congo hemorrhagic fever virus. In a second real-world dataset from the 2019 SARS-CoV-2 outbreak in Wuhan, we found the presence of a SARS coronavirus as the most relevant hit without the novel virus reference genome being included in the database.
For all samples, clinically irrelevant hits were correctly de-emphasized.
Our approach is valuable to obtain fast and accurate NGS-based pathogen identifications and correctly prioritize and visualize them based on their clinical significance: PathoLive is open source and available on GitLab and BioConda.
This joint experimental-theoretical work focuses on molecular and photophysical properties of the spiropyran-containing amphiphilic molecule in organic and aqueous solutions.
Being dissolved in tested organic solvents, the system demonstrates positive photochromism, i.e., upon UV stimulus the colorless spiropyran form is transformed into colorful merocyanine isomer.
However, the aqueous solution of the amphiphile possesses a negative photochromism: the orange-red merocyanine form becomes thermodynamically more stable in water, and both UV and vis stimuli lead to the partial or complete photobleaching of the solution.
The explanation of this phenomenon is given on the basis of density functional theory calculations and classical modeling including thermodynamic integration.
The simulations reveal that stabilization of merocyanine in water proceeds with the energy of ca. 70 kJ mol-1, and that the Helmholtz free energy of hydration of merocyanine form is 100 kJ mol-1 lower as compared to the behavior of SP isomer in water.
The explanation of such a difference lies in the molecular properties of the merocyanine: after ring-opening reaction this molecule transforms into a zwitterionic form, as evidenced by the electrostatic potential plotted around the opened form.
The presence of three charged groups on the periphery of a flat conjugated backbone stimulates the self-assembly of merocyanine molecules in water, ending up with the formation of elongated associates with stack-like building blocks, as shown in molecular dynamics simulations of the aqueous solution with the concentration above critical micelle concentration.
Our quantitative evaluation of the hydrophilicity switching in spiropyran/merocyanine containing surfactants may prompt the search for new systems, including colloidal and polymeric ones, aiming at remote tuning of their morphology, which could give new promising shapes and patterns for the needs of modern nanotechnology.
Noble metal nanostructures are known to confine photon energies to their dimensions with resonant oscillations of their conduction electrons, leading to the ultrahigh enhancement of electromagnetic fields in numerous spectroscopic methods.
Of all the possible plasmonic nanomaterials, silver offers the most intriguing properties, such as best field enhancements and tunable resonances in visible-to-near infrared regions.
This review highlights the recent developments in silver nanostructured substrates for plasmonic sensing with the main emphasis on surface plasmon resonance (SPR) and surface-enhanced Raman spectroscopy (SERS) over the past decade.
The main focus is on the synthesis of silver nanostructured substrates via physical vapor deposition and chemical synthesis routes and their applications in each sensing regime.
A comprehensive review of recent literature on various possible silver nanostructures prepared through these methodologies is discussed and critically reviewed for various planar and optical fiber-based substrates.
Paleogenomes reveal a complex evolutionary history of late Pleistocene bison in Northeastern China
(2022)
Steppe bison are a typical representative of the Mid-Late Pleistocene steppes of the northern hemisphere.
Despite the abundance of fossil remains, many questions related to their genetic diversity, population structure and dispersal route are still elusive.
Here, we present both near-complete and partial mitochondrial genomes, as well as a partial nuclear genome from fossil bison samples excavated from Late Pleistocene strata in northeastern China.
Maximum-likelihood and Bayesian trees both suggest the bison clade are divided into three maternal haplogroups (A, B and C), and Chinese individuals fall in two of them. Bayesian analysis shows that the split between haplogroup C and the ancestor of haplogroups A and B dates at 326 ky BP (95% HPD: 397-264 ky BP).
In addition, our nuclear phylogenomic tree also supports a basal position for the individual carrying haplogroup C. Admixture analyses suggest that CADG467 (haplogroup C) has a similar genetic structure to steppe bison from Siberia (haplogroup B).
Our new findings indicate that the genetic diversity of Pleistocene bison was probably even higher than previously thought and that northeastern Chinese populations of several mammalian species, including Pleistocene bison, were genetically distinct.
A special class of English words with tense vowel/diphthong nuclei and liquid codas receive variable syllable count judgments (one and over-one syllables).
Tilsen and Cohn (2016) showed that differences in judgments correlate with differences in production, supporting their hypothesis that meta-phonological judgments and speech motor control share a common representation.
In the present study, we further propose that syllable count judgments are related to subsegmental representation in the rime, and are independent of acoustic duration.
We test the hypothesis by comparing English and German, chosen for their similar word structures and vowel length contrast, and their crucial difference in the gestural specification of coda liquids.
In English, coda liquids have an earlier vocalic gesture relative to the consonantal one, while in German, both gestures are simultaneous.
We stipulated that sesquisyllabic (over-one) judgments are related to the count of sequentially-timed vocalic gestures in the rime. The difference in the coda liquid composition between the two languages predicts that sesquisyllables should not emerge in German.
Our predictions were confirmed by the results of parallel production (acoustic) and syllable count judgment experiments in English and German.
We propose a model accounting for these results, and we discuss its typological implications and its limitations.
During a survey of aquatic fungi from Anzali Lagoon in Iran, several fungal specimens were isolated from freshwater habitats. Morphological evidence and comparing sequencing based on rDNA (ITS and LSU) and protein-coding genes (TEF1 and TUB2) showed that some isolates belong to undescribed fungal species.
These isolates belong to Arthrobotrys and Sarocladium, two ascomycetes genera. Arthrobotrys hyrcanus, sp. nov., differs from closely related species such as A. dianchiensis by its larger conidia and septation of primary conidia. Sarocladium pseudokiliense, sp. nov., was similar to S. kiliense, but distinguished by its conidial shape and the absence of adelophialides and chlamydospores.
Morphological descriptions, illustrations and multilocus phylogenetic analysis for both new species are provided.
Devising optimal interventions for constraining stochastic systems is a challenging endeavor that has to confront the interplay between randomness and dynamical nonlinearity.
Existing intervention methods that employ stochastic path sampling scale poorly with increasing system dimension and are slow to converge.
Here we propose a generally applicable and practically feasible methodology that computes the optimal interventions in a noniterative scheme.
We formulate the optimal dynamical adjustments in terms of deterministically sampled probability flows approximated by an interacting particle system.
Applied to several biologically inspired models, we demonstrate that our method provides the necessary optimal controls in settings with terminal, transient, or generalized collective state constraints and arbitrary system dynamics.
Unspecific peroxygenases (UPOs, EC 1.11.2.1) are fungal enzymes that catalyze the oxyfunctionalization of non-activated hydrocarbons, making them valuable biocatalysts. Despite the increasing interest in UPOs that has led to the identification of thousands of putative UPO genes, only a few of these have been successfully expressed and characterized.
There is currently no universal expression system in place to explore their full potential. Cell-free protein synthesis has proven to be a sophisticated technique for the synthesis of difficult-to-express proteins.
In this work, we aimed to establish an insect-based cell-free protein synthesis (CFPS) platform to produce UPOs. CFPS relies on translationally active cell lysates rather than living cells.
The system parameters can thus be directly manipulated without having to account for cell viability, thereby making it highly adaptable.
The insect-based lysate contains translocationally active, ER-derived vesicles, called microsomes.
These microsomes have been shown to allow efficient translocation of proteins into their lumen, promoting post-translational modifications such as disulfide bridge formation and N-glycosylations.
In this study the ability of a redox optimized, vesicle-based, eukaryotic CFPS system to synthesize functional UPOs was explored. The influence of different reaction parameters as well as the influence of translocation on enzyme activity was evaluated for a short UPO from Marasmius rotula and a long UPO from Agrocybe aegerita.
The capability of the CFPS system described here was demonstrated by the successful synthesis of a novel UPO from Podospora anserina, thus qualifying CFPS as a promising tool for the identification and evaluation of novel UPOs and variants thereof.
Quantifying the influence of pollen aging on the adhesive
properties of Hypochaeris radicata pollen
(2022)
Simple Summary Pollination is the transfer of pollen from a plant's male part (anther) to the corresponding female part (stigma). It is a fundamental biological process that ensures plant reproduction. Most studies investigate pollination from a biological perspective, but the underlying physical processes are poorly understood. Many plants rely on insects to transport pollen and the forces with which pollen adhere to insects and floral surfaces are fundamental for successful pollination.
We quantified pollen adhesion by measuring the forces necessary to detach Hypochaeris radicata (catsear, a common insect-pollinated plant) pollen from glass and studied for the first time how the adhesion forces change with pollen aging.
Our results show that newly formed adhesion bonds between H. radicata pollen and glass are stronger for fresh pollen than for old ones. On the other hand, when H. radicata pollen age in contact with glass, the adhesion between pollen and glass strengthens over time. These effects are probably caused by the viscous liquid covering most pollen (pollenkitt) changing its viscoelastic properties as it dries.
Although pollination is one of the most crucial biological processes that ensures plant reproduction, its mechanisms are poorly understood. Especially in insect-mediated pollination, a pollen undergoes several attachment and detachment cycles when being transferred from anther to insect and from insect to stigma. The influence of the properties of pollen, insect and floral surfaces on the adhesion forces that mediate pollen transfer have been poorly studied.
Here, we investigate the adhesive properties of Hypochaeris radicata pollen and their dependence on pollen aging by quantifying the pull-off forces from glass slides using centrifugation and atomic force microscopy. We found that the properties of the pollenkitt-the viscous, lipid liquid on the surface of most pollen grains-influences the forces necessary to detach a pollen from hydrophilic surfaces.
Our results show that aged H. radicata pollen form weaker adhesions to hydrophilic glass than fresh ones. On the other hand, when a pollen grain ages in contact with glass, the adhesion between the two surfaces increases over time.
This study shows for the first time the pollen aging effect on the pollination mechanism.
Volatile organic compounds (VOCs) are involved in microbial interspecies communication and in the mode of action of various antagonistic interactions. They are important for balancing host-microbe interactions and provide the basis for developing biological control strategies to control plant pathogens.
We studied the interactions between the bacterial antagonist Serratia plymuthica HRO-C48 and three fungal plant pathogens Rhizoctonia solani, Leptosphaeria maculans and Verticillium longisporum. Significant differences in fungal growth inhibition by the Serratia-emitted VOCs in pairwise dual culture assays and changes in the transcriptome of the bacterium and in the volatilomes of both interacting partners were observed. Even though the rate of fungal growth inhibition by Serratia was variable, the confrontation of the bacterium with the VOCs of all three fungi changed the levels of expression of the genes involved in stress response, biofilm formation, and the production of antimicrobial VOCs. Pairwise interacting microorganisms switched between defense (downregulation of gene expression) and attack (upregulation of gene expression and metabolism followed by growth inhibition of the interacting partner) modes, subject to the combinations of microorganisms that were interacting.
In the attack mode HRO-C48 significantly inhibited the growth of R. solani while simultaneously boosting its own metabolism; by contrast, its metabolism was downregulated when HRO-C48 went into a defense mode that was induced by the L. maculans and V. longisporum VOCs. L. maculans growth was slightly reduced by the one bacterial VOC methyl acetate that induced a strong downregulation of expression of genes involved in almost all metabolic functions in S. plymuthica.
Similarly, the interaction between S. plymuthica and V. longisporum resulted in an insignificant growth reduction of the fungus and repressed the rate of bacterial metabolism on the transcriptional level, accompanied by an intense volatile dialogue. Overall, our results indicate that VOCs substantially contribute to the highly break species-specific interactions between pathogens and their natural antagonists and thus deserving of increased consideration for pathogen control.
Floodplain wetlands are critical for sustaining various ecological and hydrological functions in a riverine environment. Severe anthropogenic alterations and human occupation of floodplains have threatened these wetlands in several parts of the world. A major handicap in designing sustainable restoration and monitoring strategies for these wetlands is the lack of scientific process-based understanding and information on the basin-scale controls of their degradation. Here, we offer a novel approach to integrate the connectivity of the wetlands with the surrounding landscape along with other attributes such as stream density, hydrometeorological parameters, and groundwater dynamics to explain their degradation and then to prioritise them for restoration and monitoring.
We hypothesise that the best possible connectivity scenario for the existence of a wetland would be if (a) the wetland has a high connectivity with its upslope area, and (b) the wetland has a low connectivity with its downslope region.
The first condition ensures the flow of water into the wetland and the second condition allows longer water residence time in the wetland. Accordingly, we define four connectivity-based wetland health scenarios-good, no impact, bad, and worst.
We have implemented the proposed method in 3226 wetlands in the Ramganga Basin in north India. Further, we have applied specific selection criteria, such as distance from the nearest stream and stream density, to prioritise the wetlands for restoration and monitoring.
We conclude that the connectivity analysis offers a quick process-based assessment of wetlands' health status and serves as an important criterion to prioritise the wetlands for developing appropriate management strategies.
Dark field scattering microscopy can create large hyperspectral data sets that contain a wealth of information on the properties and the molecular environment of noble metal nanoparticles.
For a quick screening of samples of microscopic dimensions that contain many different types of plasmonic nanostructures, we propose a multivariate analysis of data sets of thousands to several hundreds of thousands of scattering spectra.
By using non-negative matrix factorization for decomposing the spectra, components are identified that represent individual plasmon resonances and relative contributions of these resonances to particular microscopic focal volumes in the mapping data sets. Using data from silver and gold nanoparticles in the presence of different molecules, including gold nanoparticle-protein agglomerates or silver nanoparticles forming aggregates in the presence of acrylamide, plasmonic properties are observed that differ from those of the original nanoparticles.
For the case of acrylamide, we show that the plasmon resonances of the silver nanoparticles are ideally suited to support surface enhanced Raman scattering (SERS) and the two-photon excited process of surface enhanced hyper Raman scattering (SEHRS). Both vibrational tools give complementary information on the in situ formed polyacrylamide and the molecular composition at the nanoparticle surface.
In this increasingly data-rich world, visual recordings of human behavior are often unable to be shared due to concerns about privacy.
Consequently, data sharing in fields such as behavioral science, multimodal communication, and human movement research is often limited.
In addition, in legal and other non-scientific contexts, privacy-related concerns may preclude the sharing of video recordings and thus remove the rich multimodal context that humans recruit to communicate.
Minimizing the risk of identity exposure while preserving critical behavioral information would maximize utility of public resources (e.g., research grants) and time invested in audio-visual research.
Here we present an open-source computer vision tool that masks the identities of humans while maintaining rich information about communicative body movements. Furthermore, this masking tool can be easily applied to many videos, leveraging computational tools to augment the reproducibility and accessibility of behavioral research.
The tool is designed for researchers and practitioners engaged in kinematic and affective research. Application areas include teaching/education, communication and human movement research, CCTV, and legal contexts.
Objective:
Hypertension has long been recognized as one of the most important predisposing factors for cardiovascular diseases and mortality.
In recent years, machine learning methods have shown potential in diagnostic and predictive approaches in chronic diseases.
Electronic health records (EHRs) have emerged as a reliable source of longitudinal data. The aim of this study is to predict the onset of hypertension using modern deep learning (DL) architectures, specifically long short-term memory (LSTM) networks, and longitudinal EHRs.
Materials and Methods:
We compare this approach to the best performing models reported from previous works, particularly XGboost, applied to aggregated features.
Our work is based on data from 233 895 adult patients from a large health system in the United States. We divided our population into 2 distinct longitudinal datasets based on the diagnosis date.
To ensure generalization to unseen data, we trained our models on the first dataset (dataset A "train and validation") using cross-validation, and then applied the models to a second dataset (dataset B "test") to assess their performance.
We also experimented with 2 different time-windows before the onset of hypertension and evaluated the impact on model performance.
Results:
With the LSTM network, we were able to achieve an area under the receiver operating characteristic curve value of 0.98 in the "train and validation" dataset A and 0.94 in the "test" dataset B for a prediction time window of 1 year. Lipid disorders, type 2 diabetes, and renal disorders are found to be associated with incident hypertension.
Conclusion:
These findings show that DL models based on temporal EHR data can improve the identification of patients at high risk of hypertension and corresponding driving factors. In the long term, this work may support identifying individuals who are at high risk for developing hypertension and facilitate earlier intervention to prevent the future development of hypertension.
The mechanisms underlying increased dual-task costs in the comparison of modality compatible stimulus -response mappings (e.g., visual-manual, auditory-vocal) and modality incompatible mappings (e.g., visual -vocal, auditory-manual) remain elusive.
To investigate whether additional control mechanisms are at work in simultaneously processing two modality incompatible mappings, we applied a transfer logic between both types of dual-task mappings in the context of a mental fatigue induction.
We expected an increase in dual-task costs for both modality mappings after a fatigue induction with modality compatible tasks. In contrast, we expected an additional, selective increase in modality incompatible dual-task costs after a fatigue induction with modality incompatible tasks.
We tested a group of 45young individuals (19-30 years) in an online pre-post design, in which participants were assigned to one of three groups. The two fatigue groups completed a 90-min time-on -task intervention with a dual task comprising either compatible or incompatible modality mappings.
The third group paused for 90 min as a passive control group. Pre and post-session contained single and dual tasks in both modality mappings for all participants. In addition to behavioral performance measurements, seven subjective items (effort, focus, subjective fatigue, motivation, frustration, mental and physical capacity) were analyzed.
Mean dual-task performance during and after the intervention indicated a practice effect instead of the presumed fatigue effect for all three groups. The modality incompatible intervention group showed a selective performance improvement for the modality incompatible mapping but no transfer to the modality compatible dual task. In contrast, the compatible intervention group showed moderately improved performance in both modality map-pings.
Still, participants reported increased subjective fatigue and reduced motivation after the fatigue inter-vention.
This dynamic interplay of training and fatigue effects suggests that high control demands were involved in the prolonged performance of a modality incompatible dual task, which are separable from modality compatible dual-task demands.
Hepatobiliary involvement is a hallmark in cystic fibrosis (CF), as the causative CF Transmembrane Conductance Regulator (CFTR) defect is expressed in the biliary tree. However, bile acid (BA) compositions in regard to pancreatic insufficiency, which is present at an early stage in about 85% of CF patients, have not been satisfactorily understood.
We assess the pattern of serum BAs in people with CF (pwCF) without CFTR modulator therapy in regard to pancreatic insufficiency and the CFTR genotype.
In 47 pwCF, 10 free and 12 taurine- and glycine-conjugated BAs in serum were prospectively assessed.
Findings were related to genotype, pancreatic insufficiency prevalence (PIP)-score, and hepatic involvement indicated by serum liver enzymes, as well as clinical and ultrasound criteria for CF-related liver disease.
Serum concentrations of total primary BAs and free cholic acid (CA) were significantly higher in pwCF with higher PIP-scores (p = 0.025, p = 0.009, respectively). Higher total BAs were seen in pwCF with PIP-scores >= 0.88 (p = 0.033) and with pancreatic insufficiency (p = 0.034).
Free CA was higher in patients with CF-related liver involvement without cirrhosis, compared to pwCF without liver disease (2.3-fold, p = 0.036). pwCF with severe CFTR genotypes, as assessed by the PIP-score, reveals more toxic BA compositions in serum. Subsequent studies assessing changes in BA homeostasis during new highly effective CFTR-modulating therapies are of high interest.
A circular, single-contig Methanobacterium sp. metagenome-assembled genome (MAG) was recovered from high-CO2 enrichments inoculated with drill core material from the tectonic Eger Rift terrestrial subsurface.
Annotation of the recovered MAG highlighted putative methanogenesis genes, providing valuable information on archaeal activity in the deep biosphere.
The Gram-negative bacterium Paenalcaligenes niemegkensis NGK35(T) was isolated from plastic debris in an abandoned landfill.
It has the ability to grow on polyethylene and hexadecane as the sole carbon sources. Here, we report the corresponding draft genome, which contains 3.66 Mbp and is characterized by a G+C content of 52.1%.
International migration patterns, at the global level, can to a large extent be explained through economic factors in origin and destination countries.
On the other hand, it has been shown that global climate change is likely to affect economic development over the coming decades.
Here, we demonstrate how these future climate impacts on national income levels could alter the global migration landscape.
Using an empirically calibrated global migration model, we investigate two separate mechanisms. The first is through destination-country income, which has been shown consistently to have a positive effect on immigration.
As countries' income levels relative to each other are projected to change in the future both due to different rates of economic growth and due to different levels of climate change impacts, the relative distribution of immigration across destination countries also changes as a result, all else being equal.
Second, emigration rates have been found to have a complex, inverted U-shaped dependence on origin-country income.
Given the available migration flow data, it is unclear whether this dependence-found in spatio-temporal panel data-also pertains to changes in a given migration flow over time. If it does, then climate change will additionally affect migration patterns through origin countries' emigration rates, as the relative and absolute positions of countries on the migration "hump" change.
We illustrate these different possibilities, and the corresponding effects of 3 degrees C global warming (above pre-industrial) on global migration patterns, using climate model projections and two different methods for estimating climate change effects on macroeconomic development.
We present the extension of the Kalmag model, proposed as a candidate for IGRF-13, to the twentieth century.
The dataset serving its derivation has been complemented by new measurements coming from satellites, ground-based observatories and land, marine and airborne surveys.
As its predecessor, this version is derived from a combination of a Kalman filter and a smoothing algorithm, providing mean models and associated uncertainties. These quantities permit a precise estimation of locations where mean solutions can be considered as reliable or not.
The temporal resolution of the core field and the secular variation was set to 0.1 year over the 122 years the model is spanning.
Nevertheless, it can be shown through ensembles a posteriori sampled, that this resolution can be effectively achieved only by a limited amount of spatial scales and during certain time periods.
Unsurprisingly, highest accuracy in both space and time of the core field and the secular variation is achieved during the CHAMP and Swarm era. In this version of Kalmag, a particular effort was made for resolving the small-scale lithospheric field.
Under specific statistical assumptions, the latter was modeled up to spherical harmonic degree and order 1000, and signal from both satellite and survey measurements contributed to its development.
External and induced fields were jointly estimated with the rest of the model. We show that their large scales could be accurately extracted from direct measurements whenever the latter exhibit a sufficiently high temporal coverage.
Temporally resolving these fields down to 3 hours during the CHAMP and Swarm missions, gave us access to the link between induced and magnetospheric fields. In particular, the period dependence of the driving signal on the induced one could be directly observed.
The model is available through various physical and statistical quantities on a dedicated website at https://ionocovar.agnld.uni-potsdam.de/Kalmag/.
Time and angle-resolved time-of-flight electron spectroscopy for functional materials science
(2022)
Electron spectroscopy with the unprecedented transmission of angle-resolved time-of-flight detection, in combination with pulsed X-ray sources, brings new impetus to functional materials science.
We showcase recent developments towards chemical sensitivity from electron spectroscopy for chemical analysis and structural information from photoelectron diffraction using the phase transition properties of 1T-TaS2.
Our development platform is the SurfaceDynamics instrument located at the Femtoslicing facility at BESSY II, where femtosecond and picosecond X-ray pulses can be generated and extracted.
The scientific potential is put into perspective to the current rapidly developing pulsed X-ray source capabilities from Lasers and Free-Electron Lasers.
Faults and fractures can be permeable pathways for focused fluid flow in structurally controlled ore-forming hydrothermal systems.
However, quantifying their role in fluid flow on the scale of several kilometers with numerical models typically requires high-resolution meshes.
This study introduces a modified numerical representation of m-scale fault zones using lower-dimensional elements (here, one-dimensional [1D] elements in a 2D domain) to resolve structurally controlled fluid flow with coarser mesh resolutions and apply the method to magmatic-hydrothermal ore-forming systems.
We modeled horizontal and vertical structure-controlled magmatic-hydrothermal deposits to understand the role of permeability and structure connectivity on ore deposition.
The simulation results of vertically extended porphyry copper systems show that ore deposition can occur along permeable vertical structures where ascending, overpressured magmatic fluids are cooled by downflowing ambient fluids. Structure permeability and fault location control the distribution of ore grades.
In highly permeable structures, the mineralization can span up to 3 km vertically, resulting in heat-pipe mechanisms that promote the ascent of a magmatic vapor phase to an overlying structurally controlled epithermal system.
Simulations for the formation of subhorizontal vein-type deposits suggest that the major control on fluid flow and metal deposition along horizontal structures is the absence of vertical structures above the injection location but their presence at greater distances.
Using a dynamic permeability model mimicking crack-seal mechanisms within the structures leads to a pulsating behavior of fracture-controlled hydrothermal systems and prevents the inflow of ambient fluids under overpressured conditions.
Floods affect more people than any other natural hazard; thus flood warning and disaster management are of utmost importance.
However, the operational hydrological forecasts do not provide information about affected areas and impact but only discharge and water levels at gauges.
We show that a simple hydrodynamic model operating with readily available data is able to provide highly localized information on the expected flood extent and impacts, with simulation times enabling operational flood warning.
We demonstrate that such an impact forecast would have indicated the deadly potential of the 2021 flood in western Germany with sufficient lead time.
This study aimed to validate the Norwegian version of the Basic Psychological Need Satisfaction and Frustration Scale (BPNSFS) and to examine its relations with indicators of well-being and ill-being. Additionally, despite the vast number of studies employing the BPNSFS, norms related to the BPNSFS are currently lacking.
Therefore, we also aimed to provide normative data for this scale. Data were collected among a representative sample of 326 participants (M age = 42.90 years, SD = 14.76; range 18-70) in Norway, of which 49.7% was female.
Results yielded evidence for a six-factor structure (i.e., combining satisfaction/frustration with the type of need) and showed the subscales to be highly reliable. Subsequent structural equation modeling showed that both need satisfaction and need frustration related strongly to vitality, life satisfaction, and internalizing symptoms, but in opposite ways. Norm scores were provided, thereby differentiating between women and men and different age groups.
These findings support the use of the Norwegian BPNSFS and provide researchers and professionals with normative data on the most widely used tool to assess individuals' satisfaction and frustration of the basic psychological needs for autonomy, competence, and relatedness.
In this work we present windlidar data for the research village Ny-Alesund located on Svalbard in the European Arctic (78.923 degrees N, 11.928 degrees F) from 2013 to 2021.
The data have a resolution of 50 m and 10 min with an overlapping height of about 150 m.
The maximum range depends on the meteorologic situation. Up to 1000 m altitude the data availability is better than 71%.
We found that the highest wind speeds occur in November and December, the lowest ones in June and July, up to 500 m altitude the wind is channelled strongly in ESE to NW direction parallel to the fjord axis and the synoptic conditions above 1000 m altitude already dominate.
While the fraction of windy days (v > 10 m/s) varies significantly from month to month, there is no overall trend of the wind visible in our data set.
We define gusts and jets by the requirement of wind maxima v > 2 m/s above and below a wind maximum. In total, more than 24,000 of these events were identified (corresponding to 6% of the time), of which 223 lasted for at least 100 min ("Long Jets"). All of these events are fairly equally distributed over the months relatively to the available data.
Further, gusts and jets follow different distributions (in terms of altitude or depths) and occur more frequently for synoptic flow from roughly a southerly direction. Jets do not show a clear correlation between occurrence and synoptic flow. Gusts and jets are not related to cloud cover.
We conclude that the atmosphere from 400 m to 1000 m above Ny-Alesund is dominated by a turbulent wind shear zone, which connects the micrometeorology in the atmospheric boundary layer (ABL) with the synoptic flow.
Climate change heavily threatens forest ecosystems worldwide and there is urgent need to understand what controls tree survival and forests stability.
There is evidence that biodiversity can enhance ecosystem stability (Loreau and de Mazancourt in Ecol Lett 16:106-115, 2013; McCann in Nature 405:228-233, 2000), however it remains largely unclear whether this also holds for climate change and what aspects of biodiversity might be most important.
Here we apply machine learning to outputs of a flexible-trait Dynamic Global Vegetation Model to unravel the effects of enhanced functional tree trait diversity and its sub-components on climate-change resistance of temperate forests (http://www.pik-potsdam.de/similar to billing/video/Forest_Resistance_LPJmLFIT.mp4).
We find that functional tree trait diversity enhances forest resistance. We explain this with 1. stronger complementarity effects (similar to 25% importance) especially improving the survival of trees in the understorey of up to +16.8% (+/- 1.6%) and 2. environmental and competitive filtering of trees better adapted to future climate (40-87% importance).
We conclude that forests containing functionally diverse trees better resist and adapt to future conditions.
In this context, we especially highlight the role of functionally diverse understorey trees as they provide the fundament for better survival of young trees and filtering of resistant tree individuals in the future.
The most profound consequences of the presence of Ca-Mg carbonates (CaCO3-MgCO3) in the Earth's upper mantle may be to lower the melting temperatures of the mantle and control the melt composition.
Low-degree partial melting of a carbonate-bearing mantle produces CO2-rich, silica-poor melts compositionally imposed by the melting relations of carbonates.
Thus, understanding the melting relations in the CaCO3-MgCO3 system facilitates the interpretation of natural carbonate-bearing silicate systems.
We report the melting relations of the CaCO3-MgCO3 system and the partition coefficient of trace elements between carbonates and carbonate melt from experiments at high pressure (6 and 9 GPa) and temperature (1300-1800 degrees C) using a rocking multi-anvil press. In the absence of water, Ca-Mg carbonates are stable along geothermal gradients typical of subducting slabs.
Ca-Mg carbonates ( similar to Mg0.1-0.9Ca0.9-0.1CO3) partially melt beneath mid-ocean ridges and in plume settings. Ca-Mg carbonates melt incongruently, forming periclase crystals and carbonate melt between 4 and 9 GPa.
Furthermore, we show that the rare earth element (REE) signature of Group-I kimberlites, namely strong REE fractionation and depletion of heavy REE relative to the primitive mantle, is resembled by carbonate melt in equilibrium with Ca-bearing magnesite and periclase at 6 and 9 GPa.
This suggests that the dolomite-magnesite join of the CaCO3-MgCO3 system might be useful to approximate the REE signature of carbonate-rich melts parental to kimberlites.
Non-alcoholic fatty liver disease (NAFLD) is characterized by excessive lipid accumulation in the liver.
Various mechanisms such as an increased uptake in fatty acids or de novo synthesis contribute to the development of steatosis and progression to more severe stages. Furthermore, it has been shown that impaired lipophagy, the degradation of lipids by autophagic processes, contributes to NAFLD.
Through an unbiased lipidome analysis of mouse livers in a genetic model of impaired lipophagy, we aimed to determine the resulting alterations in the lipidome. Observed changes overlap with those of the human disease.
Overall, the entire lipid content and in particular the triacylglycerol concentration increased under conditions of impaired lipophagy.
In addition, we detected a reduction in long-chain polyunsaturated fatty acids (PUFAs) and an increased ratio of n-6 PUFAs to n-3 PUFAs, which was due to the depletion of n-3 PUFAs.
Although the abundance of major phospholipid classes was reduced, the ratio of phosphatidylcholines to phosphatidylethanolamines was not affected. In conclusion, this study demonstrates that impaired lipophagy contributes to the pathology of NAFLD and is associated with an altered lipid profile.
However, the lipid pattern does not appear to be specific for lipophagic alterations, as it resembles mainly that described in relation to fatty liver disease.
The development of interface technologies is driven by the goal of making interaction more positive through natural action-control mappings.
In Virtual Reality (VR), the entire body is potentially involved for interaction, using such mappings with a maximum of degrees of freedom. The downside is the increase in interaction complexity, which can dramatically influence interface design.
A cognitive perspective on detailed aspects of interaction patterns is lacking in common interface design guidelines, although it can be helpful to make this complexity controllable and, thus, make interaction behavior predictable.
In the present study, the distinction between grounding, embodiment, and situatedness (the GES framework) is applied to organize aspects of interactions and to compare them with each other.
In two experiments, zooming into or out of emotional pictures through changes of arm span was examined in VR. There are qualitatively different aspects during such an interaction: i) perceptual aspects caused by zooming are fundamental for human behavior (Grounding: closer objects appear bigger) and ii) aspects of gestures correspond to the physical characteristics of the agents (Embodiment: little distance of hands signals little or, in contrast, "creating more detail").
The GES-framework sets aspects of Grounding against aspects of Embodiment, thus allowing to predict human behavior regarding these qualitatively different aspects.
For the zooming procedure, the study shows that Grounding can overrule Embodiment in interaction design.
Thus, we propose GES as a cognitive framework that can help to inform interaction guidelines for user interface design in VR.
kappa-casein (kappa-CN) is one of the key components in bovine milk, playing a unique role in the structuration of casein micelles.
It contains in its chemical structure up to sixteen amino acid residues (mainly serine and threonine) susceptible to modifications, including glycosylation and phosphorylation, which may further be formed during milk processing.
In this study, changes in post-translational modification (PTM) of kappa-CN during bovine milk fermentation were investigated. One-to-five-day fermented milk samples were produced.
A traditional bottom-up proteomics approach was used to establish a multiple-reaction monitoring (MRM) method for relative quantification of kappa-CN PTM. Endoproteinase Glu-C was found to efficiently digest the kappa-CN molecule.
The developed LC-MS method was validated by performing assessments of linearity, precision, repeatability, reproducibility, limit of detection (LOD), and limit of quantification (LOQ).
Among the yielded peptides, four of them containing serine and threonine residues were identified and the unmodified as well as the modified variants of each of them were relatively quantified. These peptides were (1) IPTINTIASGEPTSTTE ([140, 158]), (2) STVATLE ([162, 168]), (3) DSPE ([169, 172]), and (4) INTVQVTSTAV ([180, 190]). Distribution analysis between unmodified and modified peptides revealed that over 50% of kappa-CN was found in one of its modified forms in milk.
The fermentation process further significantly altered the composition between unmodified/modified kappa-CN, with glycoslaytion being predominant compared to phosphorylation (p < 0.01).
Further method development towards alpha and beta-CN fractions and their PTM behavior would be an asset to better understand the changes undergone by milk proteins and the micellar structure during fermentation.
Rhizophagus irregularis is one of the most extensively studied arbuscular mycorrhizal fungi (AMF) that forms symbioses with and improves the performance of many crops. Lack of transformation protocol for R. irregularis renders it challenging to investigate molecular mechanisms that shape the physiology and interactions of this AMF with plants.
Here, we used all published genomics, transcriptomics, and metabolomics resources to gain insights into the metabolic functionalities of R. irregularis by reconstructing its high-quality genome-scale metabolic network that considers enzyme constraints. Extensive validation tests with the enzyme-constrained metabolic model demonstrated that it can be used to (i) accurately predict increased growth of R. irregularis on myristate with minimal medium; (ii) integrate enzyme abundances and carbon source concentrations that yield growth predictions with high and significant Spearman correlation (rS = 0.74) to measured hyphal dry weight; and (iii) simulate growth rate increases with tighter association of this AMF with the host plant across three fungal structures.
Based on the validated model and system-level analyses that integrate data from transcriptomics studies, we predicted that differences in flux distributions between intraradical mycelium and arbuscles are linked to changes in amino acid and cofactor biosynthesis.
Therefore, our results demonstrated that the enzyme-constrained metabolic model can be employed to pinpoint mechanisms driving developmental and physiological responses of R. irregularis to different environmental cues.
In conclusion, this model can serve as a template for other AMF and paves the way to identify metabolic engineering strategies to modulate fungal metabolic traits that directly affect plant performance.
IMPORTANCE Mounting evidence points to the benefits of the symbiotic interactions between the arbuscular mycorrhiza fungus Rhizophagus irregularis and crops; however, the molecular mechanisms underlying the physiological responses of this fungus to different host plants and environments remain largely unknown.
We present a manually curated, enzyme-constrained, genome-scale metabolic model of R. irregularis that can accurately predict experimentally observed phenotypes.
We show that this high-quality model provides an entry point into better understanding the metabolic and physiological responses of this fungus to changing environments due to the availability of different nutrients.
The model can be used to design metabolic engineering strategies to tailor R. irregularis metabolism toward improving the performance of host plants.
In plants, the trehalose biosynthetic pathway plays key roles in the regulation of carbon allocation and stress adaptation.
Engineering of the pathway holds great promise to increase the stress resilience of crop plants.
The synthesis of trehalose proceeds by a two-step pathway in which a trehalose-phosphate synthase (TPS) uses UDP-glucose and glucose-6-phosphate to produce trehalose-6 phosphate (T6P) that is subsequently dephosphorylated by trehalose-6 phosphate phosphatase (TPP).
While plants usually do not accumulate high amounts of trehalose, their genome encodes large families of putative trehalose biosynthesis genes, with many members lacking obvious enzymatic activity.
Thus, the function of putative trehalose biosynthetic proteins in plants is only vaguely understood. To gain a deeper insight into the role of trehalose biosynthetic proteins in crops, we assessed the enzymatic activity of the TPS/TPP family from tomato (Solanum lycopersicum L.) and investigated their expression pattern in different tissues as well as in response to temperature shifts. From the 10 TPS isoforms tested, only the 2 proteins belonging to class I showed enzymatic activity, while all 5 TPP isoforms investigated were catalytically active.
Most of the TPS/TPP family members showed the highest expression in mature leaves, and promoter-reporter gene studies suggest that the two class I TPS genes have largely overlapping expression patterns within the vasculature, with only subtle differences in expression in fruits and flowers.
The majority of tomato TPS/TPP genes were induced by heat stress, and individual family members also responded to cold.
This suggests that trehalose biosynthetic pathway genes could play an important role during temperature stress adaptation.
In summary, our study represents a further step toward the exploitation of the TPS and TPP gene families for the improvement of tomato stress resistance.
After a long history of floodplain degradation and substantial losses of inundation areas over the last decades, a rethinking of floodplain management has taken place in Germany.
Floodplains are now acknowledged as important areas for both biodiversity and society. This transformation has been significantly supported by nationwide research activities. A systematic assessment of the current floodplain management is still lacking.
We therefore developed a scheme to assess floodplain management through the steps of identification, analysis, implementation, and evaluation.
Reviewing the data and literature on nationwide floodplain-related research and activities, we defined key elements of floodplain management for Germany.
We concluded that research activities already follow a strategic nationwide approach of identifying and analyzing floodplains.
Progress in implementation is slow, however, and potentials are far from being reached.
Nevertheless, new and unique initiatives enable Germany to stay on the long-term path of giving rivers more space and improving floodplain conditions.
In this paper, we define a variant of Roe algebras for spaces with cylindrical ends and use this to study questions regarding existence and classification of metrics of positive scalar curvature on such manifolds which are collared on the cylindrical end.
We discuss how our constructions are related to relative higher index theory as developed by Chang, Weinberger, and Yu and use this relationship to define higher rho-invariants for positive scalar curvature metrics on manifolds with boundary.
This paves the way for the classification of these metrics.
Finally, we use the machinery developed here to give a concise proof of a result of Schick and the author, which relates the relative higher index with indices defined in the presence of positive scalar curvature on the boundary.
In the soil bacterium Pseudomonas putida, the motor torque for flagellar rotation is generated by the two stators MotAB and MotCD.
Here, we construct mutant strains in which one or both stators are knocked out and investigate their swimming motility in fluids of different viscosity and in heterogeneous structured environments (semisolid agar).
Besides phase-contrast imaging of single-cell trajectories and spreading cultures, dual-color fluorescence microscopy allows us to quantify the role of the stators in enabling P. putida's three different swimming modes, where the flagellar bundle pushes, pulls, or wraps around the cell body.
The MotAB stator is essential for swimming motility in liquids, while spreading in semisolid agar is not affected. Moreover, if the MotAB stator is knocked out, wrapped mode formation under low-viscosity conditions is strongly impaired and only partly restored for increased viscosity and in semisolid agar.
In contrast, when the MotCD stator is missing, cells are indistinguishable from the wild type in fluid experiments but spread much more slowly in semisolid agar.
Analysis of the microscopic trajectories reveals that the MotCD knockout strain forms sessile clusters, thereby reducing the number of motile cells, while the swimming speed is unaffected. Together, both stators ensure a robust wild type that swims efficiently under different environmental conditions.
IMPORTANCE
Because of its heterogeneous habitat, the soil bacterium Pseudomonas putida needs to swim efficiently under very different environmental conditions. In this paper, we knocked out the stators MotAB and MotCD to investigate their impact on the swimming motility of P. putida.
While the MotAB stator is crucial for swimming in fluids, in semisolid agar, both stators are sufficient to sustain a fast-swimming phenotype and increased frequencies of the wrapped mode, which is known to be beneficial for escaping mechanical traps. However, in contrast to the MotAB knockout, a culture of MotCD knockout cells spreads much more slowly in the agar, as it forms nonmotile clusters that reduce the number of motile cells.
Because of its heterogeneous habitat, the soil bacterium Pseudomonas putida needs to swim efficiently under very different environmental conditions. In this paper, we knocked out the stators MotAB and MotCD to investigate their impact on the swimming motility of P. putida.