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End date: 2019 Ă— Start date: 2019 Ă— Type: Article Ă— Publisher: Basel : MDPI Ă— WGL Institute: PIK Ă—

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Now showing 1 - 6 of 6
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    Photodynamic opening of the blood-brain barrier using different photosensitizers in mice
    (Basel : MDPI, 2019) Semyachkina-Glushkovskaya, Oxana; Borisova, Ekaterina; Mantareva, Vanya; Angelov, Ivan; Eneva, Ivelina; Terskov, Andrey; Mamedova, Aysel; Shirokov, Alexander; Khorovodov, Alexander; Klimova, Maria; Agranovich, Ilana; Blokhina, Inna; Lezhnev, Nikita; Kurths, Jurgen
    In a series of previous studies, we demonstrated that the photodynamic therapy (PDT), as a widely used tool for treatment of glioblastoma multiforme (GBM), also site-specifically opens the blood-brain barrier (BBB) in PDT-dose and age-related manner via reversible disorganization of the tight junction machinery. To develop the effective protocol of PDT-opening of the BBB, here we answer the question of what kind of photosensitizer (PS) is the most effective for the BBB opening. We studied the PDT-opening of the BBB in healthy mice using commercial photosensitizers (PSs) such as 5-aminolevulenic acid (5-ALA), aluminum phthalocyanine disulfonate (AlPcS), zinc phthalocyanine (ZnPc) and new synthetized PSs such as galactose functionalized ZnPc (GalZnPc). The spectrofluorimetric assay of Evans Blue albumin complex (EBAC) leakage and 3-D confocal imaging of FITC-dextran 70 kDa (FITCD) extravasation clearly shows a revisable and dose depended PDT-opening of the BBB toEBACand FITCD associated with a decrease in presence of tight junction (TJ) in the vascular endothelium. The PDT effects on the BBB permeability, TJ expression and the fluorescent signal from the brain tissues are more pronounced in PDT-GalZnPc vs. PDT-5-ALA/AlPcS/ZnPc. These pre-clinical data are the first important informative platform for an optimization of the PDT protocol in the light of new knowledge about PDT-opening of the BBB for drug brain delivery and for the therapy of brain diseases. © 2019 by the authors.
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    Implications of Winter NAO Flavors on Present and Future European Climate
    (Basel : MDPI, 2019) Rousi, Efi; Rust, Henning W.; Ulbrich, Uwe; Anagnostopoulou, Christina
    The North Atlantic Oscillation (NAO), a basic variability mode in the Northern Hemisphere, undergoes changes in its temporal and spatial characteristics, with significant implications on European climate. In this paper, different NAO flavors are distinguished for winter in simulations of a Coupled Atmosphere-Ocean GCM, using Self-Organizing Maps, a topology preserving clustering algorithm. These flavors refer to various sub-forms of the NAO pattern, reflecting the range of positions occupied by its action centers, the Icelandic Low and the Azores High. After having defined the NAO flavors, composites of winter temperature and precipitation over Europe are created for each one of them. The results reveal significant differences between NAO flavors in terms of their effects on the European climate. Generally, the eastwardly shifted NAO patterns induce a stronger than average influence on European temperatures. In contrast, the effects of NAO flavors on European precipitation anomalies are less coherent, with various areas responding differently. These results confirm that not only the temporal, but also the spatial variability of NAO is important in regulating European climate. © 2020 by the authors.
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    Modelling Climate Change’s Impact on the Hydrology of Natura 2000 Wetland Habitats in the Vistula and Odra River Basins in Poland
    (Basel : MDPI, 2019) O’Keeffe, Joanna; Marcinkowski, Paweł; Utratna, Marta; Piniewski, Mikołaj; Kardel, Ignacy; Kundzewicz, Zbigniew; Okruszko, Tomasz
    Climate change is expected to affect the water cycle through changes in precipitation, river streamflow, and soil moisture dynamics, and therefore, present a threat to groundwater and surface water-fed wetland habitats and their biodiversity. This article examines the past trends and future impacts of climate change on riparian, water-dependent habitats within the special areas of conservation (SAC) of the Natura 2000 network located within Odra and Vistula River basins in Poland. Hydrological modelling using the Soil and Water Assessment Tool (SWAT) was driven by a set of nine EURO-CORDEX regional climate models under two greenhouse gas concentration trajectories. Changes in the duration of flooding and inundation events were used to assess climate change’s impact on surface water-fed wetland habitats. The groundwater-fed wetlands were evaluated on the basis of changes in soil water content. Information about the current conservation status, threats, and pressures that affect the habitats suggest that the wetlands might dry out. Increased precipitation projected for the future causing increased water supply to both surface water and groundwater-fed wetlands would lead to beneficial outcomes for habitats with good, average, or reduced conservation status. However, habitats with an excellent conservation status that are already in optimum condition could be negatively affected by climate change as increased soil water or duration of overbank flow would exceed their tolerance.
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    Integrated Solutions for the Water-Energy-Land Nexus: Are Global Models Rising to the Challenge?
    (Basel : MDPI, 2019) Johnson, Nils; Burek, Peter; Byers, Edward; Falchetta, Giacomo; Flörke, Martina; Fujimori, Shinichiro; Havlik, Petr; Hejazi, Mohamad; Hunt, Julian; Krey, Volker; Langan, Simon; Nakicenovic, Nebojsa; Palazzo, Amanda; Popp, Alexander; Riahi, Keywan; van Dijk, Michiel; van Vliet, Michelle; van Vuuren, Detlef; Wada, Yoshihide; Wiberg, David; Willaarts, Barbara; Zimm, Caroline; Parkinson, Simon
    Increasing human demands for water, energy, food and materials, are expected to accentuate resource supply challenges over the coming decades. Experience suggests that long-term strategies for a single sector could yield both trade-offs and synergies for other sectors. Thus, long-term transition pathways for linked resource systems should be informed using nexus approaches. Global integrated assessment models can represent the synergies and trade-offs inherent in the exploitation of water, energy and land (WEL) resources, including the impacts of international trade and climate policies. In this study, we review the current state-of-the-science in global integrated assessment modeling with an emphasis on how models have incorporated integrated WEL solutions. A large-scale assessment of the relevant literature was performed using online databases and structured keyword search queries. The results point to the following main opportunities for future research and model development: (1) improving the temporal and spatial resolution of economic models for the energy and water sectors; (2) balancing energy and land requirements across sectors; (3) integrated representation of the role of distribution infrastructure in alleviating resource challenges; (4) modeling of solution impacts on downstream environmental quality; (5) improved representation of the implementation challenges stemming from regional financial and institutional capacity; (6) enabling dynamic multi-sectoral vulnerability and adaptation needs assessment; and (7) the development of fully-coupled assessment frameworks based on consistent, scalable, and regionally-transferable platforms. Improved database management and computational power are needed to address many of these modeling challenges at a global-scale.
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    Improving the Accuracy of Hydrodynamic Simulations in Data Scarce Environments Using Bayesian Model Averaging: A Case Study of the Inner Niger Delta, Mali, West Africa
    (Basel : MDPI, 2019) Haque, Md Mominul; Seidou, Ousmane; Mohammadian, Abdolmajid; Djibo, Abdouramane Gado; Liersch, Stefan; Fournet, Samuel; Karam, Sara; Perera, Edangodage Duminda Pradeep; Kleynhans, Martin
    In this paper, the study area was the Inner Niger Delta (IND) in Mali, West Africa. The IND is threatened by climate change, increasing irrigation, and dam operations. 2D hydrodynamic modelling was used to simulate water levels, discharge, and inundation extent in the IND. Three different digital elevation models (DEM) (SRTM, MERIT, and a DEM derived from satellite images were used as a source of elevation data. Six different models were created, with different sources of elevation data and different downstream boundary conditions. Given that the performance of the models varies according to the location in the IND, the variable under consideration and the performance criteria, Bayesian Model Averaging (BMA) was used to assess the relative performance of each of the six models. The BMA weights, along with deterministic performance measures, such as the Nash Sutcliffe coefficient (NS) and the Pearson’s correlation coefficient (r), provide quantitative evidence as to which model is the best when simulating a particular hydraulic variable at a particular location. After the models were combined with BMA, both discharge and water levels could be simulated with reasonable precision (NS > 0.8). The results of this work can contribute to the more efficient management of water resources in the IND.
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    Multi-temporal analysis of forest fire probability using socio-economic and environmental variables
    (Basel : MDPI, 2019) Kim, Sea Jin; Lim, Chul-Hee; Kim, Gang Sun; Lee, Jongyeol; Geiger, Tobias; Rahmati, Omid; Son, Yowhan; Lee, Woo-Kyun
    As most of the forest fires in South Korea are related to human activity, socio-economic factors are critical in estimating their probability. To estimate and analyze how human activity is influencing forest fire probability, this study considered not only environmental factors such as precipitation, elevation, topographic wetness index, and forest type, but also socio-economic factors such as population density and distance from urban area. The machine learning Maximum Entropy (Maxent) and Random Forest models were used to predict and analyze the spatial distribution of forest fire probability in South Korea. The model performance was evaluated using the receiver operating characteristic (ROC) curve method, and models’ outputs were compared based on the area under the ROC curve (AUC). In addition, a multi-temporal analysis was conducted to determine the relationships between forest fire probability and socio-economic or environmental changes from the 1980s to the 2000s. The analysis revealed that the spatial distribution was concentrated in or around cities, and the probability had a strong correlation with variables related to human activity and accessibility over the decades. The AUC values for validation were higher in the Random Forest result compared to the Maxent result throughout the decades. Our findings can be useful for developing preventive measures for forest fire risk reduction considering socio-economic development and environmental conditions.