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The use of monoclonal antibodies is ubiquitous in science and biomedicine but the generation and validation process of antibodies is nevertheless complicated and time-consuming. To address these issues we developed a novel selective technology based on an artificial cell surface construct by which secreted antibodies were connected to the corresponding hybridoma cell when they possess the desired antigen-specificity. Further the system enables the selection of desired isotypes and the screening for potential cross-reactivities in the same context. For the design of the construct we combined the transmembrane domain of the EGF-receptor with a hemagglutinin epitope and a biotin acceptor peptide and performed a transposon-mediated transfection of myeloma cell lines. The stably transfected myeloma cell line was used for the generation of hybridoma cells and an antigen- and isotype-specific screening method was established. The system has been validated for globular protein antigens as well as for haptens and enables a fast and early stage selection and validation of monoclonal antibodies in one step.
The prevalence of vitamin A deficiency in sub-Saharan Africa necessitates effective approaches to improve provitamin A content of major staple crops. Cassava holds much promise for food security in sub-Saharan Africa, but a negative correlation between beta-carotene, a provitamin A carotenoid, and dry matter content has been reported, which poses a challenge to cassava biofortification by conventional breeding. To identify suitable material for genetic transformation in tissue culture with the overall aim to increase beta-carotene and maintain starch content as well as better understand carotenoid composition, root and leaf tissues from thirteen field-grown cassava landraces were analyzed for agronomic traits, carotenoid, chlorophyll, and starch content. The expression of five genes related to carotenoid biosynthesis were determined in selected landraces. Analysis revealed a weak negative correlation between starch and beta-carotene content, whereas there was a strong positive correlation between root yield and many carotenoids including beta-carotene. Carotenoid synthesis genes were expressed in both white and yellow cassava roots, but phytoene synthase 2 (PSY2), lycopene-epsilon-cyclase (LCY epsilon), and beta-carotenoid hydroxylase (CHY beta) expression were generally higher in yellow roots. This study identified lines with reasonably high content of starch and beta-carotene that could be candidates for biofortification by further breeding or plant biotechnological means.
Abiotic stresses cause oxidative damage in plants. Here, we demonstrate that foliar application of an extract from the seaweed Ascophyllum nodosum, SuperFifty (SF), largely prevents paraquat (PQ)-induced oxidative stress in Arabidopsis thaliana. While PQ-stressed plants develop necrotic lesions, plants pre-treated with SF (i.e., primed plants) were unaffected by PQ. Transcriptome analysis revealed induction of reactive oxygen species (ROS) marker genes, genes involved in ROS-induced programmed cell death, and autophagy-related genes after PQ treatment. These changes did not occur in PQ-stressed plants primed with SF. In contrast, upregulation of several carbohydrate metabolism genes, growth, and hormone signaling as well as antioxidant-related genes were specific to SF-primed plants. Metabolomic analyses revealed accumulation of the stress-protective metabolite maltose and the tricarboxylic acid cycle intermediates fumarate and malate in SF-primed plants. Lipidome analysis indicated that those lipids associated with oxidative stress-induced cell death and chloroplast degradation, such as triacylglycerols (TAGs), declined upon SF priming. Our study demonstrated that SF confers tolerance to PQ-induced oxidative stress in A. thaliana, an effect achieved by modulating a range of processes at the transcriptomic, metabolic, and lipid levels.
Extreme weather resilience has been defined as being based on three pillars: resistance (the ability to lower impacts), recovery (the ability to bounce back), and adaptive capacity (the ability to learn and improve). These resilience pillars are important both before and after the occurrence of extreme weather events. Extreme weather insurance can influence these pillars of resilience depending on how particular insurance mechanisms are structured. We explore how the lessons learnt from the current best insurance practices can improve resilience to extreme weather events. We employ an extensive inventory of private property and agricultural crop insurance mechanisms to conduct a multi-criteria analysis of insurance market outcomes. We draw conclusions regarding the patterns in the best practice from six European countries to increase resilience. We suggest that requirements to buy a bundle extreme weather event insurance with general insurance packages are strengthened and supported with structures to financing losses through public-private partnerships. Moreover, support for low income households through income vouchers could be provided. Similarly, for the agricultural sector we propose moving towards comprehensive crop yield insurance linked to general agricultural subsidies. In both cases a nationally representative body can coordinate the various stakeholders into acting in concert.
The novel space-borne Global Navigation Satellite System Reflectometry (GNSS-R) technique has recently shown promise in monitoring the ocean state and surface wind speed with high spatial coverage and unprecedented sampling rate. The L-band signals of GNSS are structurally able to provide a higher quality of observations from areas covered by dense clouds and under intense precipitation, compared to those signals at higher frequencies from conventional ocean scatterometers. As a result, studying the inner core of cyclones and improvement of severe weather forecasting and cyclone tracking have turned into the main objectives of GNSS-R satellite missions such as Cyclone Global Navigation Satellite System (CYGNSS). Nevertheless, the rain attenuation impact on GNSS-R wind speed products is not yet well documented. Evaluating the rain attenuation effects on this technique is significant since a small change in the GNSS-R can potentially cause a considerable bias in the resultant wind products at intense wind speeds. Based on both empirical evidence and theory, wind speed is inversely proportional to derived bistatic radar cross section with a natural logarithmic relation, which introduces high condition numbers (similar to ill-posed conditions) at the inversions to high wind speeds. This paper presents an evaluation of the rain signal attenuation impact on the bistatic radar cross section and the derived wind speed. This study is conducted simulating GNSS-R delay-Doppler maps at different rain rates and reflection geometries, considering that an empirical data analysis at extreme wind intensities and rain rates is impossible due to the insufficient number of observations from these severe conditions. Finally, the study demonstrates that at a wind speed of 30 m/s and incidence angle of 30 degrees, rain at rates of 10, 15, and 20 mm/h might cause overestimation as large as approximate to 0.65 m/s (2%), 1.00 m/s (3%), and 1.3 m/s (4%), respectively, which are still smaller than the CYGNSS required uncertainty threshold. The simulations are conducted in a pessimistic condition (severe continuous rainfall below the freezing height and over the entire glistening zone) and the bias is expected to be smaller in size in real environments.
Fractures serve as highly conductive preferential flow paths for fluids in rocks, which are difficult to exactly reconstruct in numerical models. Especially, in low-conductive rocks, fractures are often the only pathways for advection of solutes and heat. The presented study compares the results from hydraulic and tracer tomography applied to invert a theoretical discrete fracture network (DFN) that is based on data from synthetic cross-well testing. For hydraulic tomography, pressure pulses in various injection intervals are induced and the pressure responses in the monitoring intervals of a nearby observation well are recorded. For tracer tomography, a conservative tracer is injected in different well levels and the depth-dependent breakthrough of the tracer is monitored. A recently introduced transdimensional Bayesian inversion procedure is applied for both tomographical methods, which adjusts the fracture positions, orientations, and numbers based on given geometrical fracture statistics. The used Metropolis-Hastings-Green algorithm is refined by the simultaneous estimation of the measurement error’s variance, that is, the measurement noise. Based on the presented application to invert the two-dimensional cross-section between source and the receiver well, the hydraulic tomography reveals itself to be more suitable for reconstructing the original DFN. This is based on a probabilistic representation of the inverted results by means of fracture probabilities.
The success of the ensemble Kalman filter has triggered a strong interest in expanding its scope beyond classical state estimation problems. In this paper, we focus on continuous-time data assimilation where the model and measurement errors are correlated and both states and parameters need to be identified. Such scenarios arise from noisy and partial observations of Lagrangian particles which move under a stochastic velocity field involving unknown parameters. We take an appropriate class of McKean–Vlasov equations as the starting point to derive ensemble Kalman–Bucy filter algorithms for combined state and parameter estimation. We demonstrate their performance through a series of increasingly complex multi-scale model systems.
Nuclear lamins are nucleus-specific intermediate filaments (IF) found at the inner nuclear membrane (INM) of the nuclear envelope (NE). Together with nuclear envelope transmembrane proteins, they form the nuclear lamina and are crucial for gene regulation and mechanical robustness of the nucleus and the whole cell. Recently, we characterized Dictyostelium NE81 as an evolutionarily conserved lamin-like protein, both on the sequence and functional level. Here, we show on the structural level that the Dictyostelium NE81 is also capable of assembling into filaments, just as metazoan lamin filament assemblies. Using field-emission scanning electron microscopy, we show that NE81 expressed in Xenopous oocytes forms filamentous structures with an overall appearance highly reminiscent of Xenopus lamin B2. The in vitro assembly properties of recombinant His-tagged NE81 purified from Dictyostelium extracts are very similar to those of metazoan lamins.
Super-resolution stimulated emission depletion (STED) and expansion microscopy (ExM), as well as transmission electron microscopy of negatively stained purified NE81, demonstrated its capability of forming filamentous structures under low-ionic-strength conditions. These results recommend Dictyostelium as a non-mammalian model organism with a well-characterized nuclear envelope involving all relevant protein components known in animal cells.
Peroxisome biogenesis disorders (PBDs) are nontreatable hereditary diseases with a broad range of severity. Approximately 65% of patients are affected by mutations in the peroxins Pex1 and Pex6. The proteins form the heteromeric Pex1/Pex6 complex, which is important for protein import into peroxisomes. To date, no structural data are available for this AAA+ ATPase complex. However, a wealth of information can be transferred from low-resolution structures of the yeast scPex1/scPex6 complex and homologous, well-characterized AAA+ ATPases. We review the abundant records of missense mutations described in PBD patients with the aim to classify and rationalize them by mapping them onto a homology model of the human Pex1/Pex6 complex. Several mutations concern functionally conserved residues that are implied in ATP hydrolysis and substrate processing. Contrary to fold destabilizing mutations, patients suffering from function-impairing mutations may not benefit from stabilizing agents, which have been reported as potential therapeutics for PBD patients.
During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007–2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash–Sutcliffe efficiency of 0.72 and a Kling–Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.