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We present a feasibility study with several magnetic field configurations for creating spin-dependent forces that can split a low-energy ion beam by the Stern-Gerlach (SG) effect. To the best of our knowledge, coherent spin-splittings of charged particles have yet to be realised. Our proposal is based on ion source parameters taken from a recent experiment that demonstrated single-ion implantation from a high-brightness ion source combined with a radio-frequency Paul trap. The inhomogeneous magnetic fields can be created by permanently magnetised microstructures or from current-carrying wires with sizes in the micron range, such as those recently used in a successful implementation of the SG effect with neutral atoms. All relevant forces (Lorentz force and image charges) are taken into account, and measurable splittings are found by analytical and numerical calculations.
NK cells have emerged as promising candidates for cancer immunotherapy, especially due to their ability to fight circulating tumor cells thereby preventing metastases formation. Hence several studies have been performed to generate and expand highly cytotoxic NK cells ex vivo, e.g., by using specific cytokines to upregulate both their proliferation and surface expression of distinct activating receptors. Apart from an enhanced activity, application of NK cells as immunotherapeutic agent further requires sufficient cell numbers and a high purity. All these parameters depend on a variety of different factors including the starting material, additives like cytokines as well as the culture system. Here we analyzed PBMC-derived NK cells of five anonymized healthy donors expanded under specific conditions in an innovative perfusion bioreactor system with respect to their phenotype, IFN gamma production, and cytotoxicity in vitro. Important features of the meander type bioreactors used here are a directed laminar flow of medium and control of relevant process parameters. Cells are cultivated under "steady state" conditions in perfusion mode. Our data demonstrate that expansion of CD3(+) T cell depleted PBMCs in our standardized system generates massive amounts of highly pure (>85%) and potent anticancer active NK cells. These cells express a variety of important receptors driving NK cell recruitment, adhesion as well as activation. More specifically, they express the chemokine receptors CXCR3, CXCR4, and CCR7, the adhesion molecules L-selectin, LFA-1, and VLA-4, the activating receptors NKp30, NKp44, NKp46, NKG2D, DNAM1, and CD16 as well as the death ligands TRAIL and Fas-L. Moreover, the generated NK cells show a strong IFN gamma expression upon cultivation with K562 tumor cells and demonstrate a high cytotoxicity toward leukemic as well as solid tumor cell lines in vitro. Altogether, these characteristics promise a high clinical potency of thus produced NK cells awaiting further evaluation.
A better understanding of precipitation dynamics in the Indian subcontinent is required since India's society depends heavily on reliable monsoon forecasts. We introduce a non-linear, multiscale approach, based on wavelets and event synchronization, for unravelling teleconnection influences on precipitation. We consider those climate patterns with the highest relevance for Indian precipitation. Our results suggest significant influences which are not well captured by only the wavelet coherence analysis, the state-of-the-art method in understanding linkages at multiple timescales. We find substantial variation across India and across timescales. In particular, El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) mainly influence precipitation in the south-east at interannual and decadal scales, respectively, whereas the North Atlantic Oscillation (NAO) has a strong connection to precipitation, particularly in the northern regions. The effect of the Pacific Decadal Oscillation (PDO) stretches across the whole country, whereas the Atlantic Multidecadal Oscillation (AMO) influences precipitation particularly in the central arid and semi-arid regions. The proposed method provides a powerful approach for capturing the dynamics of precipitation and, hence, helps improve precipitation forecasting.
Strong light-matter coupling can re-arrange the exciton energies in organic semiconductors. Here, we exploit strong coupling by embedding a fullerene-free organic solar cell (OSC) photo-active layer into an optical microcavity, leading to the formation of polariton peaks and a red-shift of the optical gap. At the same time, the open-circuit voltage of the device remains unaffected. This leads to reduced photon energy losses for the low-energy polaritons and a steepening of the absorption edge. While strong coupling reduces the optical gap, the energy of the charge-transfer state is not affected for large driving force donor-acceptor systems. Interestingly, this implies that strong coupling can be exploited in OSCs to reduce the driving force for electron transfer, without chemical or microstructural modifications of the photoactive layer. Our work demonstrates that the processes determining voltage losses in OSCs can now be tuned, and reduced to unprecedented values, simply by manipulating the device architecture.
Environmental factors shape the spatial distribution and dynamics of populations. Understanding how these factors interact with movement behavior is critical for efficient conservation, in particular for migratory species. Adult female green sea turtles, Chelonia mydas, migrate between foraging and nesting sites that are generally separated by thousands of kilometers. As an emblematic endangered species, green turtles have been intensively studied, with a focus on nesting, migration, and foraging. Nevertheless, few attempts integrated these behaviors and their trade‐offs by considering the spatial configurations of foraging and nesting grounds as well as environmental heterogeneity like oceanic currents and food distribution. We developed an individual‐based model to investigate the impact of local environmental conditions on emerging migratory corridors and reproductive output and to thereby identify conservation priority sites. The model integrates movement, nesting, and foraging behavior. Despite being largely conceptual, the model captured realistic movement patterns which confirm field studies. The spatial distribution of migratory corridors and foraging hot spots was mostly constrained by features of the regional landscape, such as nesting site locations, distribution of feeding patches, and oceanic currents. These constraints also explained the mixing patterns in regional forager communities. By implementing alternative decision strategies of the turtles, we found that foraging site fidelity and nesting investment, two characteristics of green turtles' biology, are favorable strategies under unpredictable environmental conditions affecting their habitats. Based on our results, we propose specific guidelines for the regional conservation of green turtles as well as future research suggestions advancing spatial ecology of sea turtles. Being implemented in an easy to learn open‐source software, our model can coevolve with the collection and analysis of new data on energy budget and movement into a generic tool for sea turtle research and conservation. Our modeling approach could also be useful for supporting the conservation of other migratory marine animals.
Locally delivered anti-inflammatory compounds can restore the homeostasis of the degenerated intervertebral disc (IVD). With beneficial effects on IVD cells, epigallocatechin 3-gallate (EGCG) is a promising therapeutic candidate. However, EGCG is prone to rapid degradation and/or depletion. Therefore, the purpose of this study was to develop a method for controlled EGCG delivery in the degenerated IVD. Primary IVD cells were isolated from human donors undergoing IVD surgeries. EGCG was encapsulated into microparticles by electrospraying of glutaraldehyde-crosslinked gelatin. The resulting particles were characterized in terms of cytocompatibility and anti-inflammatory activity, and combined with a thermoresponsive carrier to produce an injectable EGCG delivery system. Subsequently, electrospraying was scaled up using the industrial NANOSPIDER (TM) technology. The produced EGCG microparticles reduced the expression of inflammatory (IL-6, IL-8, COX-2) and catabolic (MMP1, MMP3, MMP13) mediators in pro-inflammatory 3D cell cultures. Combining the EGCG microparticles with the carrier showed a trend towards modulating EGCG activity/release. Electrospray upscaling was achieved, leading to particles with homogenous spherical morphologies. In conclusion, electrospray-based encapsulation of EGCG resulted in cytocompatible microparticles that preserved the activity of EGCG and showed the potential to control EGCG release, thus favoring IVD health by downregulating local inflammation. Future studies will focus on further exploring the biological activity of the developed delivery system for potential clinical use.
Intra-organ communication guides morphogenetic processes that are essential for an organ to carry out complex physiological functions. In the heart, the growth of the myocardium is tightly coupled to that of the endocardium, a specialized endothelial tissue that lines its interior. Several molecular pathways have been implicated in the communication between these tissues including secreted factors, components of the extracellular matrix, or proteins involved in cell-cell communication. Yet, it is unknown how the growth of the endocardium is coordinated with that of the myocardium. Here, we show that an increased expansion of the myocardial atrial chamber volume generates higher junctional forces within endocardial cells. This leads to biomechanical signaling involving VE-cadherin, triggering nuclear localization of the Hippo pathway transcriptional regulator Yap1 and endocardial proliferation. Our work suggests that the growth of the endocardium results from myocardial chamber volume expansion and ends when the tension on the tissue is relaxed.
The Argentine-German Geodetic Observatory (AGGO) is one of the very few sites in the Southern Hemisphere equipped with comprehensive cutting-edge geodetic instrumentation. The employed observation techniques are used for a wide range of geophysical applications. The data set provides gravity time series and selected gravity models together with the hydrometeorological monitoring data of the observatory. These parameters are of great interest to the scientific community, e.g. for achieving accurate realization of terrestrial and celestial reference frames. Moreover, the availability of the hydrometeorological products is beneficial to inhabitants of the region as they allow for monitoring of environmental changes and natural hazards including extreme events. The hydrological data set is composed of time series of groundwater level, modelled and observed soil moisture content, soil temperature, and physical soil properties and aquifer properties. The meteorological time series include air temperature, humidity, pressure, wind speed, solar radiation, precipitation, and derived reference evapotranspiration. These data products are extended by gravity models of hydrological, oceanic, La Plata estuary, and atmospheric effects. The quality of the provided meteorological time series is tested via comparison to the two closest WMO (World Meteorological Organization) sites where data are available only in an inferior temporal resolution. The hydrological series are validated by comparing the respective forward-modelled gravity effects to independent gravity observations reduced up to a signal corresponding to local water storage variation. Most of the time series cover the time span between April 2016 and November 2018 with either no or only few missing data points. The data set is available at https://doi.org/10.588/GFZ.5.4.2018.001 (Mikolaj et al., 2018).
A yeast expression plasmid was constructed containing a cardenolide biosynthetic module, referred to as CARD II, using the AssemblX toolkit, which enables the assembly of large DNA constructs. The genes cloned into the vector were (a) a Δ5‐3β‐hydroxysteroid dehydrogenase gene from Digitalis lanata, (b) a steroid Δ5‐isomerase gene from Comamonas testosteronii, (c) a mutated steroid‐5β‐reductase gene from Arabidopsis thaliana, and (d) a steroid 21‐hydroxylase gene from Mus musculus. A second plasmid bearing an ADR/ADX fusion gene from Bos taurus was also constructed. A Saccharomyces cerevisiae strain bearing these two plasmids was generated. This strain, termed “CARD II yeast”, was capable of producing 5β‐pregnane‐3β,21‐diol‐20‐one, a central intermediate in 5β‐cardenolide biosynthesis, starting from pregnenolone which was added to the culture medium. Using this approach, five consecutive steps in cardenolide biosynthesis were realized in baker's yeast.
The computation of such synthetic GFs is computationally and operationally demanding. As a consequence, the onthe-fly recalculation of synthetic GFs in each iteration of an optimisation is time-consuming and impractical. Therefore, the pre-calculation and efficient storage of synthetic GFs on a dense grid of source to receiver combinations enables the efficient lookup and utilisation of GFs in time-critical scenarios. We present a Python-based framework and toolkit - Pyrocko-GF - that enables the pre-calculation of synthetic GF stores, which are independent of their numerical calculation method and GF transfer function. The framework aids in the creation of such GF stores by interfacing a suite of established numerical forward modelling codes in seismology (computational back ends). So far, interfaces to back ends for layered Earth model cases have been provided; however, the architecture of Pyrocko-GF is designed to cover back ends for other geometries (e.g. full 3-D heterogeneous media) and other physical quantities (e.g. gravity, pressure, tilt). Therefore, Pyrocko-GF defines an extensible GF storage format suitable for a wide range of GF types, especially handling elasticity and wave propagation problems. The framework assists with visualisations, quality control, and the exchange of GF stores, which is supported through an online platform that provides many pre-calculated GF stores for local, regional, and global studies. The Pyrocko-GF toolkit comes with a well-documented application programming interface (API) for the Python programming language to efficiently facilitate forward modelling of geophysical processes, e.g. synthetic waveforms or static displacements for a wide range of source models.
Cell-free protein synthesis (CFPS) based on eukaryotic Sf21 lysate is gaining interest among researchers due to its ability to handle the synthesis of complex human membrane proteins (MPs). Additionally Sf21 cell-free systems contain endogenous microsomal vesicles originally derived from the endoplasmic reticulum (ER). After CFPS, MPs will be translocated into the microsomal vesicles membranes present in the lysates. Thus microsomal membranes offer a natural environment for de novo synthesized MPs. Despite the advantage of synthesizing complex MPs with post translational modifications directly into the microsomal membranes without any additional solubilization supplements, batch based Sf21 cell-free synthesis suffers from low yields. The bottleneck for MPs in particular after the synthesis and incorporation into the microsomal membranes is to analyze their functionality. Apart from low yields of the synthesized MPs with batch based cell-free synthesis, the challenges arise in the form of cytoskeleton elements and peripheral endogenous proteins surrounding the microsomes which may impede the functional analysis of the synthesized proteins. So careful sample processing after the synthesis is particularly important for developing the appropriate functional assays. Here we demonstrate how MPs (native and batch synthesized) from ER derived microsomes can be processed for functional analysis by electrophysiology and radioactive uptake assay methods. Treatment of the microsomal membranes either with a sucrose washing step in the case of human serotonin transporter (hSERT) and sarco/endoplasmic reticulum Ca2+/ATPase (SERCA) pump or with mild detergents followed by the preparation of proteoliposomes in the case of the human voltage dependent anionic channel (hVDAC1) helps to analyze the functional properties of MPs.
Plants are in permanent contact with various microorganisms and are always impacted by them. To better understand the first steps of a plant’s recognition of soil-borne microorganisms, the early release of volatile organic compounds (VOCs) emitted from roots of Medicago truncatula in response to the symbiont Rhizophagus irregularis or the pathogenic oomycete Aphanomyces euteiches was analysed. More than 90 compounds were released from roots as detected by an untargeted gas chromatography-mass spectrometry approach. Principal component analyses clearly distinguished untreated roots from roots treated with either R. irregularis or A. euteiches. Several VOCs were found to be emitted specifically in response to each of the microorganisms. Limonene was specifically emitted from wild-type roots after contact with R. irregularis spores but not from roots of the mycorrhiza-deficient mutant does not make infections3. The application of limonene to mycorrhizal roots, however, did not affect the mycorrhization rate. Inoculation of roots with A. euteiches zoospores resulted in the specific emission of several sesquiterpenes, such as nerolidol, viridiflorol and nerolidol-epoxyacetate but application of nerolidol to zoospores of A. euteiches did not affect their vitality. Therefore, plants discriminate between different microorganisms at early stages of their interaction and respond differently to the level of root-emitted volatiles.
Hungry cities: how local food self-sufficiency relates to climate change, diets, and urbanisation
(2019)
Using a newly developed model approach and combining it with remote sensing, population, and climate data, first insights are provided into how local diets, urbanisation, and climate change relates to local urban food self-sufficiency. In plain terms, by utilizing the global peri-urban (PU) food production potential approximately lbn urban residents (30% of global urban population) can be locally nourished, whereby further urbanisation is by far the largest pressure factor on PU agriculture, followed by a change of diets, and climate change. A simple global food transport model which optimizes transport and neglects differences in local emission intensities indicates that CO2 emissions related to food transport can be reduced by a factor of 10.
Terrestrial reptiles are particularly vulnerable to climate change. Their highest density and diversity can be found in hot drylands, ecosystems which demonstrate extreme climatic conditions. However, reptiles are not isolated systems but part of a large species assemblage with many trophic dependencies. While direct relations among climatic conditions, invertebrates, vegetation, or reptiles have already been explored, to our knowledge, species’ responses to direct and indirect pathways of multiple climatic and biotic factors and their interactions have rarely been examined comprehensively. We investigated direct and indirect effects of climatic and biotic parameters on the individual (body condition) and population level (occupancy) of eight abundant lizard species with different functional traits in an arid Australian lizard community using a 30‐yr multi‐trophic monitoring study. We used structural equation modeling to disentangle single and interactive effects. We then assessed whether species could be grouped into functional groups according to their functional traits and their responses to different parameters. We found that lizard species differed strongly in how they responded to climatic and biotic factors. However, the factors to which they responded seemed to be determined by their functional traits. While responses on body condition were determined by habitat, activity time, and prey, responses on occupancy were determined by habitat specialization, body size, and longevity. Our findings highlight the importance of indirect pathways through climatic and biotic interactions, which should be included into predictive models to increase accuracy when predicting species’ responses to climate change. Since one might never obtain all mechanistic pathways at the species level, we propose an approach of identifying relevant species traits that help grouping species into functional groups at different ecological levels, which could then be used for predictive modeling.
Underground coal gasification (UCG) enables utilization of coal reserves, currently not economically exploitable due to complex geological boundary conditions. Hereby, UCG produces a high-calorific synthesis gas that can be used for generation of electricity, fuels, and chemical feedstock. The present study aims to identify economically-competitive, site-specific end-use options for onshore- and offshore-produced UCG synthesis gas, taking into account the capture and storage (CCS) and/or utilization (CCU) of produced CO2. Modeling results show that boundary conditions favoring electricity, methanol, and ammonia production expose low costs for air separation, low compression power requirements, and appropriate shares of H-2/N-2. Hereby, a gasification agent ratio of more than 30% oxygen by volume is not favorable from the economic and CO2 mitigation viewpoints. Compared to the costs of an offshore platform with its technical equipment, offshore drilling costs are marginal. Thus, uncertainties related to parameters influenced by drilling costs are negligible. In summary, techno-economic process modeling results reveal that air-blown gasification scenarios are the most cost-effective ones, while offshore UCG-CCS/CCU scenarios are up to 1.7 times more expensive than the related onshore processes. Hereby, all investigated onshore scenarios except from ammonia production under the assumed worst-case conditions are competitive on the European market.
The large, shallow earthquakes at Northridge, California (1994), Chi-Chi, Taiwan (1999), and Wenchuan, China (2008), each triggered thousands of landslides. We have determined the position of these landslides along hillslopes, normalizing for statistical bias. The landslide patterns have a co-seismic signature, with clustering at ridge crests and slope toes. A cross-check against rainfall-induced landslide inventories seems to confirm that crest clustering is specific to seismic triggering as observed in previous studies. In our three study areas, the seismic ground motion parameters and lithologic and topographic features used do not seem to exert a primary control on the observed patterns of landslide clustering. However, we show that at the scale of the epicentral area, crest and toe clustering occur in areas with specific geological features. Toe clustering of seismically induced landslides tends to occur along regional major faults. Crest clustering is concentrated at sites where the lithology along hillslopes is approximately uniform, or made of alternating soft and hard strata, and without strong overprint of geological structures. Although earthquake-induced landslides locate higher on hillslopes in a statistically significant way, geological features strongly modulate the landslide position along the hillslopes. As a result the observation of landslide clustering on topographic ridges cannot be used as a definite indicator of the topographic amplification of ground shaking.
Sensors composed of a porous silicon monolayer covered with a film of nanostructured gold layer, which provide two optical signal transduction methods, are fabricated and thoroughly characterized concerning their sensing performance. For this purpose, silicon substrates were electrochemically etched in order to obtain porous silicon monolayers, which were subsequently immersed in gold salt solution facilitating the formation of a porous gold nanoparticle layer on top of the porous silicon. The deposition process was monitored by reflectance spectroscopy, and the appearance of a dip in the interference pattern of the porous silicon layer was observed. This dip can be assigned to the absorption of light by the deposited gold nanostructures leading to localized surface plasmon resonance. The bulk sensitivity of these sensors was determined by recording reflectance spectra in media having different refractive indices and compared to sensors exclusively based on porous silicon or gold nanostructures. A thorough analysis of resulting shifts of the different optical signals in the reflectance spectra on the wavelength scale indicated that the optical response of the porous silicon sensor is not influenced by the presence of a gold nanostructure on top. Moreover, the adsorption of thiol-terminated polystyrene to the sensor surface was solely detected by changes in the position of the dip in the reflectance spectrum, which is assigned to localized surface plasmon resonance in the gold nanostructures. The interference pattern resulting from the porous silicon layer is not shifted to longer wavelengths by the adsorption indicating the independence of the optical response of the two nanostructures, namely porous silicon and nanostructured gold layer, to refractive index changes and pointing to the successful realization of two sensors in one spot.
The majority of earthquakes occur unexpectedly and can trigger subsequent sequences of events that can culminate in more powerful earthquakes. This self-exciting nature of seismicity generates complex clustering of earthquakes in space and time. Therefore, the problem of constraining the magnitude of the largest expected earthquake during a future time interval is of critical importance in mitigating earthquake hazard. We address this problem by developing a methodology to compute the probabilities for such extreme earthquakes to be above certain magnitudes. We combine the Bayesian methods with the extreme value theory and assume that the occurrence of earthquakes can be described by the Epidemic Type Aftershock Sequence process. We analyze in detail the application of this methodology to the 2016 Kumamoto, Japan, earthquake sequence. We are able to estimate retrospectively the probabilities of having large subsequent earthquakes during several stages of the evolution of this sequence.
A Metabarcoding Analysis of the Mycobiome of Wheat Ears Across a Topographically Heterogeneous Field
(2019)
Compound flooding, such as the co-occurrence of fluvial floods and extreme coastal water levels (CWL), may lead to significant impacts in densely-populated Low Elevation Coastal Zones. They may overstrain disaster management owing to the co-occurrence of inundation from rivers and the sea. Recent studies are limited by analyzing joint dependence between river discharge and either CWL or storm surges, and little is known about return levels of compound flooding, accounting for the covariance between drivers. Here, we assess the compound flood severity and identify hotspots for northwestern Europe during 1970–2014, using a newly developed Compound Hazard Ratio (CHR) that compares the severity of compound flooding associated with extreme CWL with the unconditional T-year fluvial peak discharge. We show that extreme CWL and stronger storms greatly amplify fluvial flood hazards. Our results, based on frequency analyses of observational records during 2013/2014’s winter storm Xaver, reveal that the river discharge of the 50-year compound flood is up to 70% larger, conditioned on the occurrence of extreme CWL, than that of the at-site peak discharge. For this event, nearly half of the stream gauges show increased flood hazards, demonstrating the importance of including the compounding effect of extreme CWL in river flood risk management.