Feature-based Groundwater Hydrograph Clustering Using Unsupervised Self-Organizing Map-Ensembles

Hydrograph clustering helps to identify dynamic patterns within aquifers systems, an important foundation of characterizing groundwater systems and their influences, which is necessary to effectively manage groundwater resources. We develope an unsupervised modeling approach to characterize and cluster hydrographs on regional scale according to their dynamics. We apply feature-based clustering to improve the exploitation of heterogeneous datasets, explore the usefulness of existing features and propose new features specifically useful to describe groundwater hydrographs. The clustering itself is based on a powerful combination of Self-Organizing Maps with a modified DS2L-Algorithm, which automatically derives the cluster number but also allows to influence the level of detail of the clustering. We further develop a framework that combines these methods with ensemble modeling, internal cluster validation indices, resampling and consensus voting to finally obtain a robust clustering result and remove arbitrariness from the feature selection process. Further we propose a measure to sort hydrographs within clusters, useful for both interpretability and visualization. We test the framework with weekly data from the Upper Rhine Graben System, using more than 1800 hydrographs from a period of 30 years (1986-2016). The results show that our approach is adaptively capable of identifying homogeneous groups of hydrograph dynamics. The resulting clusters show both spatially known and unknown patterns, some of which correspond clearly to external controlling factors, such as intensive groundwater management in the northern part of the test area. This framework is easily transferable to other regions and, by adapting the describing features, also to other time series-clustering applications.

     

Effects of the Anti-Tumorigenic Agent AT101 on Human Glioblastoma Cells in the Microenvironmental Glioma Stem Cell Niche

Glioblastoma (GBM) is a barely treatable disease due to its profound chemoresistance. A distinct inter- and intratumoral heterogeneity reflected by specialized microenvironmental niches and different tumor cell subpopulations allows GBMs to evade therapy regimens. Thus, there is an urgent need to develop alternative treatment strategies. A promising candidate for the treatment of GBMs is AT101, the R(-) enantiomer of gossypol. The present study evaluates the effects of AT101, alone or in combination with temozolomide (TMZ), in a microenvironmental glioma stem cell niche model of two GBM cell lines (U251MG and U87MG). AT101 was found to induce strong cytotoxic effects on U251MG and U87MG stem-like cells in comparison to the respective native cells. Moreover, a higher sensitivity against treatment with AT101 was observed upon incubation of native cells with a stem-like cell-conditioned medium. This higher sensitivity was reflected by a specific inhibitory influence on the p-p42/44 signaling pathway. Further, the expression of CXCR7 and the interleukin-6 receptor was significantly regulated upon these stimulatory conditions. Since tumor stem-like cells are known to mediate the development of tumor recurrences and were observed to strongly respond to the AT101 treatment, this might represent a promising approach to prevent the development of GBM recurrences.     

Surface Reconstruction Engineering with Synergistic Effect of Mixed-Salt Passivation Treatment toward Efficient and Stable Perovskite Solar Cells

Surface passivation treatment is a widely used strategy to resolve trap-mediated nonradiative recombination toward high-efficiency metal-halide perovskite photovoltaics. However, a lack of passivation with mixture treatment has been investigated, as well as an in-depth understanding of its passivation mechanism. Here, a systematic study on a mixed-salt passivation strategy of formamidinium bromide (FABr) coupled with different F-substituted alkyl lengths of ammonium iodide is demonstrated. It is obtained better device performance with decreasing chain length of the F-substituted alkyl ammonium iodide in the presence of FABr. Moreover, they unraveled a synergistic passivation mechanism of the mixed-salt treatment through surface reconstruction engineering, where FABr dominates the reformation of the perovskite surface via reacting with the excess PbI₂. Meanwhile, ammonium iodide passivates the perovskite grain boundaries both on the surface and top perovskite bulk through penetration. This synergistic passivation engineer results in a high-quality perovskite surface with fewer defects and suppressed ion migration, leading to a champion efficiency of 23.5% with mixed-salt treatment. In addition, the introduction of the moisture resisted F-substituted groups presents a more hydrophobic perovskite surface, thus enabling the decorated devices with excellent long-term stability under a high humid atmosphere as well as operational conditions.     

Novel measurement system for respiratory aerosols and droplets in indoor environments

The SARS-CoV-2 pandemic has created a great demand for a better understanding of the spread of viruses in indoor environments. A novel measurement system consisting of one portable aerosol-emitting mannequin (emitter) and a number of portable aerosol-absorbing mannequins (recipients) was developed that can measure the spread of aerosols and droplets that potentially contain infectious viruses. The emission of the virus from a human is simulated by using tracer particles solved in water. The recipients inhale the aerosols and droplets and quantify the level of solved tracer particles in their artificial lungs simultaneously over time. The mobile system can be arranged in a large variety of spreading scenarios in indoor environments and allows for quantification of the infection probability due to airborne virus spreading. This study shows the accuracy of the new measurement system and its ability to compare aerosol reduction measures such as regular ventilation or the use of a room air purifier.     

Discovery of GPR183 Agonists Based on an Antagonist Scaffold

The G protein-coupled receptor GPR183/EBI2, which is activated by oxysterols, is a therapeutic target for inflammatory and metabolic diseases where both antagonists and agonists are of potential interest. Using the piperazine diamide core of the known GPR183 antagonist (E)-3-(4-bromophenyl)-1-(4-(4-methoxybenzoyl)piperazin-1-yl)prop-2-en-1-one (NIBR189) as starting point, we identified and sourced 79 structurally related compounds that were commercially available. In vitro screening of this compound collection using a Ca²⁺ mobilization assay resulted in the identification of 10 compounds with agonist properties. To enable establishment of initial structure-activity relationship trends, these were supplemented with five in-house compounds, two of which were also shown to be GPR183 agonists. Taken together, our findings suggest that the agonist activity of this compound series is dictated by the substitution pattern of one of the two distal phenyl rings, which functions as a molecular efficacy-switch.     

Structural Aspects and Prediction of Calmodulin-Binding Proteins

Calmodulin (CaM) is an important intracellular protein that binds Ca²⁺ and functions as a critical second messenger involved in numerous biological activities through extensive interactions with proteins and peptides. CaM’s ability to adapt to binding targets with different structures is related to the flexible central helix separating the N- and C-terminal lobes, which allows for conformational changes between extended and collapsed forms of the protein. CaM-binding targets are most often identified using prediction algorithms that utilize sequence and structural data to predict regions of peptides and proteins that can interact with CaM. In this review, we provide an overview of different CaM-binding proteins, the motifs through which they interact with CaM, and shared properties that make them good binding partners for CaM. Additionally, we discuss the historical and current methods for predicting CaM binding, and the similarities and differences between these methods and their relative success at prediction. As new CaM-binding proteins are identified and classified, we will gain a broader understanding of the biological processes regulated through changes in Ca²⁺ concentration through interactions with CaM.     

The influence of iodide on glass transition temperature of high-pressure nuclear waste glasses

The glass transition temperature (T_g) is a key parameter to investigate for application in nuclear waste immobilization in borosilicate glasses. T_g for several glasses containing iodine (I) has been measured in order to determine the I effect on T_g. Two series of glass composition (ISG and NH) containing up to 2.5 mol% I and synthesized under high pressure (0.5 to 1.5 GPa) have been investigated using differential scanning calorimetry (DSC). The I local environment in glasses has been determined using X-ray photoelectron spectroscopy and revealed that I is dissolved under its iodide form (I⁻). Results show that T_g is decreased with the I addition in the glass in agreement with previous results. We also observed that this T_g decrease is a strong function of glass composition. For NH, 2.5 mol% I induces a decrease of 24°C in T_g, whereas for ISG, 1.2 mol% decreases the T_g by 64°C. We interpret this difference as the result of the I dissolution mechanism and its effect on the polymerization of the boron network. The I dissolution in ISG is accompanied by a depolymerization of the boron network, whereas it is the opposite in NH. Although ISG corresponds to a standardized glass, for the particular case of I immobilization it appears less adequate than NH considering that the decrease in T_g for NH is small in comparison to ISG.     

Synthesis of Light Hydrocarbons from Biogas and Hydrogen: Investigation of a Fe-Mn-K/MgO Catalyst

Fischer-Tropsch synthesis of the CO₂ in biogas aims at producing light hydrocarbons and increasing its calorific value for feeding into the grid. Fe catalysts with Mn and K as promoters are supposed to yield high amounts of light hydrocarbons. Using a Fe-Mn-K/MgO catalyst, a parameter screening and long-term experiments were carried out. The catalyst shows, within the examined range, the highest selectivity to C₂–C₄ hydrocarbons at 450 °C, 8 bar(a), and a gas hourly space velocity of 350 h⁻¹. Calcination of the catalyst resulted in a significant drop of activity and an almost complete loss of selectivity to hydrocarbons. Admixture of steam to the reactant gas lowers the tendency to carbon deposition but also promotes the water-gas shift reaction and results in lower yields of hydrocarbons.