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    Biomaterial based strategies to reconstruct the nigrostriatal pathway in organotypic slice co-cultures
    (Amsterdam [u.a.] : Elsevier, 2021) Ucar, Buket; Kajtez, Janko; Foidl, Bettina M.; Eigel, Dimitri; Werner, Carsten; Long, Katherine R.; Emnéus, Jenny; Bizeau, Joëlle; Lomora, Mihai; Pandit, Abhay; Newland, Ben; Humpel, Christian
    Protection or repair of the nigrostriatal pathway represents a principal disease-modifying therapeutic strategy for Parkinson's disease (PD). Glial cell line-derived neurotrophic factor (GDNF) holds great therapeutic potential for PD, but its efficacious delivery remains difficult. The aim of this study was to evaluate the potential of different biomaterials (hydrogels, microspheres, cryogels and microcontact printed surfaces) for reconstructing the nigrostriatal pathway in organotypic co-culture of ventral mesencephalon and dorsal striatum. The biomaterials (either alone or loaded with GDNF) were locally applied onto the brain co-slices and fiber growth between the co-slices was evaluated after three weeks in culture based on staining for tyrosine hydroxylase (TH). Collagen hydrogels loaded with GDNF slightly promoted the TH+ nerve fiber growth towards the dorsal striatum, while GDNF loaded microspheres embedded within the hydrogels did not provide an improvement. Cryogels alone or loaded with GDNF also enhanced TH+ fiber growth. Lines of GDNF immobilized onto the membrane inserts via microcontact printing also significantly improved TH+ fiber growth. In conclusion, this study shows that various biomaterials and tissue engineering techniques can be employed to regenerate the nigrostriatal pathway in organotypic brain slices. This comparison of techniques highlights the relative merits of different technologies that researchers can use/develop for neuronal regeneration strategies. © 2020
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    Nitrous oxide emissions from winter oilseed rape cultivation
    (Amsterdam [u.a.] : Elsevier, 2017) Ruser, Reiner; Fuß, Roland; Andres, Monique; Hegewald, Hannes; Kesenheimer, Katharina; Köbke, Sarah; Räbiger, Thomas; Quinones, Teresa Suarez; Augustin, Jürgen; Christen, Olaf; Dittert, Klaus; Kage, Henning; Lewandowski, Iris; Prochnow, Annette; Stichnothe, Heinz; Flessa, Heinz
    Winter oilseed rape (Brassica napus L., WOSR) is the major oil crop cultivated in Europe. Rapeseed oil is predominantly used for production of biodiesel. The framework of the European Renewable Energy Directive requires that use of biofuels achieves GHG savings of at least 50% compared to use of fossil fuel starting in 2018. However, N2O field emissions are estimated using emission factors that are not specific for the crop and associated with strong uncertainty. N2O field emissions are controlled by N fertilization and dominate the GHG balance of WOSR cropping due to the high global warming potential of N2O. Thus, field experiments were conducted to increase the data basis and subsequently derive a new WOSR-specific emission factor. N2O emissions and crop yields were monitored for three years over a range of N fertilization intensities at five study sites representative of German WOSR production. N2O fluxes exhibited the typical high spatial and temporal variability in dependence on soil texture, weather and nitrogen availability. The annual N2O emissions ranged between 0.24 kg and 5.48 kg N2O-N ha−1 a−1. N fertilization increased N2O emissions, particularly with the highest N treatment (240 kg N ha−1). Oil yield increased up to a fertilizer amount of 120 kg N ha−1, higher N-doses increased grain yield but decreased oil concentrations in the seeds. Consequently oil yield remained constant at higher N fertilization. Since, yield-related emission also increased exponentially with N surpluses, there is potential for reduction of the N fertilizer rate, which offers perspectives for the mitigation of GHG emissions. Our measurements double the published data basis of annual N2O flux measurements in WOSR. Based on this extended dataset we modeled the relationship between N2O emissions and fertilizer N input using an exponential model. The corresponding new N2O emission factor was 0.6% of applied fertilizer N for a common N fertilizer amount under best management practice in WOSR production (200 kg N ha−1 a−1). This factor is substantially lower than the linear IPCC Tier 1 factor (EF1) of 1.0% and other models that have been proposed. © 2017
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    Ammonia and greenhouse gas emissions from slurry storage : A review
    (Amsterdam [u.a.] : Elsevier, 2020) Kupper, Thomas; Häni, Christoph; Neftel, Albrecht; Kincaid, Chris; Bühler, Marcel; Amon, Barbara; VanderZaag, Andrew
    Storage of slurry is an important emission source for ammonia (NH3), nitrous oxide (N2O), methane (CH4), carbon dioxide (CO2) and hydrogen sulfide (H2S) from livestock production. Therefore, this study collected published emission data from stored cattle and pig slurry to determine baseline emission values and emission changes due to slurry treatment and coverage of stores. Emission data were collected from 120 papers yielding 711 records of measurements conducted at farm-, pilot- and laboratory-scale. The emission data reported in a multitude of units were standardized and compiled in a database. Descriptive statistics of the data from untreated slurry stored uncovered revealed a large variability in emissions for all gases. To determine baseline emissions, average values based on a weighting of the emission data according to the season and the duration of the emission measurements were constructed using the data from farm-scale and pilot-scale studies. Baseline emissions for cattle and pig slurry stored uncovered were calculated. When possible, it was further distinguished between storage in tanks without slurry treatment and storage in lagoons which implies solid-liquid separation and biological treatment. The baseline emissions on an area or volume basis are: for NH3: 0.12 g m−2 h-1 and 0.15 g m−2 h-1 for cattle and pig slurry stored in lagoons, and 0.08 g m−2 h-1 and 0.24 g m−2 h-1 for cattle and pig slurry stored in tanks; for N2O: 0.0003 g m−2 h-1 for cattle slurry stored in lagoons, and 0.002 g m−2 h-1 for both slurry types stored in tanks; for CH4: 0.95 g m-3 h-1 and 3.5 g m-3 h-1 for cattle and pig slurry stored in lagoons, and 0.58 g m-3 h-1 and 0.68 g m-3 h-1 for cattle and pig slurry stored in tanks; for CO2: 6.6 g m−2 h-1 and 0.3 g m−2 h-1 for cattle and pig slurry stored in lagoons, and 8.0 g m−2 h-1 for both slurry types stored in tanks; for H2S: 0.04 g m−2 h-1 and 0.01 g m−2 h-1 for cattle and pig slurry stored in lagoons. Related to total ammoniacal nitrogen (TAN), baseline emissions for tanks are 16% and 15% of TAN for cattle and pig slurry, respectively. Emissions of N2O and CH4 relative to nitrogen (N) and volatile solids (VS) are 0.13% of N and 0.10% of N and 2.9% of VS and 4.7% of VS for cattle and pig slurry, respectively. Total greenhouse gas emissions from slurry stores are dominated by CH4. The records on slurry treatment using acidification show a reduction of NH3 and CH4 emissions during storage while an increase occurs for N2O and a minor change for CO2 as compared to untreated slurry. Solid-liquid separation causes higher losses for NH3 and a reduction in CH4, N2O and CO2 emissions. Anaerobically digested slurry shows higher emissions during storage for NH3 while losses tend to be lower for CH4 and little changes occur for N2O and CO2 compared to untreated slurry. All cover types are found to be efficient for emission mitigation of NH3 from stores. The N2O emissions increase in many cases due to coverage. Lower CH4 emissions occur for impermeable covers as compared to uncovered slurry storage while for permeable covers the effect is unclear or emissions tend to increase. Limited and inconsistent data regarding emission changes with covering stores are available for CO2 and H2S. The compiled data provide a basis for improving emission inventories and highlight the need for further research to reduce uncertainty and fill data gaps regarding emissions from slurry storage.
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    Towards hybrid one-pot/one-electrode Pd-NPs-based nanoreactors for modular biocatalysis
    (Amsterdam [u.a.] : Elsevier, 2021) Koch, M.; Apushkinskaya, N.; Zolotukhina, E.V.; Silina, Y.E.
    Here, fundamental aspects affecting template-assisted engineering of oxidase-associated peroxide oxidation co-catalysis of the modeled microanalytical system based on the hybrid palladium nanoparticles (Pd-NPs) with tailored functional properties were studied. By an accurate tuning and validation of the experimental setup, a modular Pd-NPs-doped one-pot/one-electrode amperometric nanobiosensor for advanced multiplex analyte detection was constructed. The specific operational conditions (electrochemical read-out mode, pH, regeneration procedure) of the modular one-pot/one-electrode nanobiosensor allowed a reliable sensing of L-lactate (with linear dynamic range, LDR = 500 µM – 2 mM, R2 = 0.977), D-glucose (with LDR = 200 µM – 50 mM, R2 = 0.987), hydrogen peroxide (with LDR = 20 µM – 100 mM, R2 = 0.998) and glutaraldehyde (with LDR = 1 – 100 mM, R2 = 0.971). In addition, mechanistic aspects influencing the performance of Pd-NPs-doped one-pot/one-electrode for multiplex analyte sensing were studied in detail. The designed one-pot/one-electrode amperometric nanobiosensor showed a thin layer electrochemical behavior that greatly enhanced electron transfer between the functional hybrid layer and the electrode. Finally, a specific regeneration procedure of the hybrid one-pot/one-electrode and algorithm towards its usage for modular biocatalysis were developed. The reported strategy can readily be considered as a guideline towards the fabrication of commercialized nanobiosensors with tailored properties for advanced modular biocatalysis.
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    Deep Geothermal Energy for Lower Saxony (North Germany) – Combined Investigations of Geothermal Reservoir Characteristics
    (Amsterdam [u.a.] : Elsevier, 2014) Hahne, Barbara; Thomas, Rüdiger; Bruckman, Viktor J.; Hangx, Suzanne; Ask, Maria
    For the economic success of a geothermal project the hydraulic properties and temperature of the geothermal reservoir are crucial. New methodologies in seismics, geoelectrics and reservoir geology are tested within the frame of the collaborative research programme “Geothermal Energy and High-Performance Drilling” (gebo). Within nine geoscientific projects, tools were developed that help in the evaluation and interpretation of acquired data. Special emphasis is placed on the investigation of rock properties, on the development of early reservoir assessment even during drilling, and on the interaction between the drilling devices and the reservoir formation. The propagation of fractures and the transport of fluid and heat within the regional stress field are investigated using different approaches (field studies, seismic monitoring, multi-parameter modelling). Geologic structural models have been created for simulation of the local stress field and hydromechanical processes. Furthermore, a comprehensive dataset of hydrogeochemical environments was collected allowing characterisation and hydrogeochemical modelling of the reservoir.
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    Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change
    (Amsterdam [u.a.] : Elsevier, 2017) Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco; Asseng, Senthold; Baranowski, Piotr; Basso, Bruno; Bodin, Per; Buis, Samuel; Cammarano, Davide; Deligios, Paola; Destain, Marie-France; Dumont, Benjamin; Ewert, Frank; Ferrise, Roberto; François, Louis; Gaiser, Thomas; Hlavinka, Petr; Jacquemin, Ingrid; Kersebaum, Kurt Christian; Kollas, Chris; Krzyszczak, Jaromir; Lorite, Ignacio J.; Minet, Julien; Minguez, M. Ines; Montesino, Manuel; Moriondo, Marco; Müller, Christoph; Nendel, Claas; Öztürk, Isik; Perego, Alessia; Rodríguez, Alfredo; Ruane, Alex C.; Ruget, Françoise; Sanna, Mattia; Semenov, Mikhail A.; Slawinski, Cezary; Stratonovitch, Pierre; Supit, Iwan; Waha, Katharina; Wang, Enli; Wu, Lianhai; Zhao, Zhigan; Rötter, Reimund P.
    Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (−2 to +9°C) and precipitation (−50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.
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    Livelihood and climate trade-offs in Kenyan peri-urban vegetable production
    (Amsterdam [u.a.] : Elsevier, 2017) Kurgat, Barnabas K.; Stöber, Silke; Mwonga, Samuel; Lotze-Campen, Hermann; Rosenstock, Todd S.
    Trade-offs between livelihood and environmental outcomes due to agricultural intensification in sub-Saharan Africa are uncertain. The present study measured yield, economic performance and nitrous oxide (N2O) emissions in African indigenous vegetable (AIV) production to investigate the optimal nutrient management strategies. In order to achieve this, an on-farm experiment with four treatments – (1) 40 kg N/ha diammonium phosphate (DAP), (2) 10 t/ha cattle manure, (3) 20 kg N/ha DAP and 5 t/ha cattle manure and (4) a no-N input control – was performed for two seasons. Yields and N2O emissions were directly measured with subsampling and static chambers/gas chromatography, respectively. Economic outcomes were estimated from semi-structured interviews (N = 12). Trade-offs were quantified by calculating N2O emissions intensity (N2OI) and N2O emissions economic intensity (N2OEI). The results indicate that, DAP alone resulted at least 14% greater yields, gross margin and returns to labour in absolute terms but had the highest emissions (p = 0.003). Productivity-climate trade-offs, expressed as N2OI, were statistically similar for DAP and mixed treatments. However, N2OEI was minimized under mixed management (p = 0.0004) while maintaining productivity and gross margins. We therefore conclude that soil fertility management strategies that mix inorganic and organic source present a pathway to sustainable intensification in AIV production. Future studies of GHG emissions in crop production need to consider not only productivity but economic performance when considering trade-offs.
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    Performance of seasonal forecasts for the flowering and veraison of two major Portuguese grapevine varieties
    (Amsterdam [u.a.] : Elsevier, 2023) Yang, Chenyao; Ceglar, Andrej; Menz, Christoph; Martins, Joana; Fraga, Helder; Santos, João A.
    Seasonal phenology forecasts are becoming increasingly demanded by winegrowers and viticulturists. Forecast performance needs to be investigated over space and time before practical applications. We assess seasonal forecast performance (skill, probability and accuracy) in predicting flowering and veraison stages of two representative varieties in Portugal over 1993–2017. The state-of-the-art forecast system ECMWF-SEAS5 provides 7-month seasonal forecasts and is coupled with a locally adapted phenology model. Overall, findings illustrate the dependence of forecast performance on initialization timings, regions and predicting subjects (stages and varieties). Forecast performance improves by delaying the initialization timing and only forecasts initialized on April 1st show better skills than climatology on predicting phenology terciles (early/normal/late). The considerable bias of daily values of seasonal climate predictions can represent the main barrier to accurate forecasts. Better prediction performance is consistently found in Central-Southern regions compared to Northern regions, attributing to an earlier phenology occurrence with a shorter forecast length. Comparable predictive skills between flowering and veraison for both varieties imply better predictability in summer. Consequently, promising seasonal phenology predictions are foreseen in Central-Southern wine regions using forecasts initialized on April 1st with approximately 1–2/3–4 months lead time for flowering/veraison: potential prediction errors are ∼2 weeks, along with an overall moderate forecast skill on categorical events. However, considerable inter-annual variability of forecast performance over the same classified phenology years reflects the substantial influence of climate variability. This may represent the main challenge for reliable forecasts in Mediterranean regions. Recommendations are suggested for methodological innovations and practical applications towards reliable regional phenology forecasts.
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    A review of coarse mineral dust in the Earth system
    (Amsterdam [u.a.] : Elsevier, 2022) Adebiyi, Adeyemi; Kok, Jasper F.; Murray, Benjamin J.; Ryder, Claire L.; Stuut, Jan-Berend W.; Kahn, Ralph A.; Knippertz, Peter; Formenti, Paola; Mahowald, Natalie M.; Pérez García-Pando, Carlos; Klose, Martina; Ansmann, Albert; Samset, Bjørn H.; Ito, Akinori; Balkanski, Yves; Di Biagio, Claudia; Romanias, Manolis N.; Huang, Yue; Meng, Jun
    Mineral dust particles suspended in the atmosphere span more than three orders of magnitude in diameter, from <0.1 µm to more than 100 µm. This wide size range makes dust a unique aerosol species with the ability to interact with many aspects of the Earth system, including radiation, clouds, hydrology, atmospheric chemistry, and biogeochemistry. This review focuses on coarse and super-coarse dust aerosols, which we respectively define as dust particles with a diameter of 2.5–10 µm and 10–62.5 µm. We review several lines of observational evidence indicating that coarse and super-coarse dust particles are transported farther than previously expected and that the abundance of these particles is substantially underestimated in current global models. We synthesize previous studies that used observations, theories, and model simulations to highlight the impacts of coarse and super-coarse dust aerosols on the Earth system, including their effects on dust-radiation interactions, dust-cloud interactions, atmospheric chemistry, and biogeochemistry. Specifically, coarse and super-coarse dust aerosols produce a net positive direct radiative effect (warming) at the top of the atmosphere and can modify temperature and water vapor profiles, influencing the distribution of clouds and precipitation. In addition, coarse and super-coarse dust aerosols contribute a substantial fraction of ice-nucleating particles, especially at temperatures above –23 °C. They also contribute a substantial fraction to the available reactive surfaces for atmospheric processing and the dust deposition flux that impacts land and ocean biogeochemistry by supplying important nutrients such as iron and phosphorus. Furthermore, we examine several limitations in the representation of coarse and super-coarse dust aerosols in current model simulations and remote-sensing retrievals. Because these limitations substantially contribute to the uncertainties in simulating the abundance and impacts of coarse and super-coarse dust aerosols, we offer some recommendations to facilitate future studies. Overall, we conclude that an accurate representation of coarse and super-coarse properties is critical in understanding the impacts of dust aerosols on the Earth system.
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    Rhodium-catalyzed borylative carbon monoxide reduction to gem-diborylmethane
    (Amsterdam [u.a.] : Elsevier, 2021) Xua, Jian-Xing; Wu, Fu-Peng; Wu, Xiao-Feng
    Herein, we developed a rhodium-catalyzed reduction of CO with bis(pinacolato)diboron (B2pin2) under atmospheric pressure of CO with silane as the hydride source, gem-diborylmethane [H2C(Bpin)2] as a versatile and fundamental C1 compound can be formed. Notably, this is the first example on transition metal-catalyzed borylation of CO. © 2020 The Author(s)