Distinct Pharmacological Properties of Gaseous CO and CO-Releasing Molecule in Human Platelets

Carbon monoxide (CO)—gaseous or released by CO-RMs—both possess antiplatelet properties; however, it remains uncertain whether the mechanisms involved are the same. Here, we characterise the involvement of soluble guanylate cyclase (sGC) in the effects of CO—delivered by gaseous CO–saturated buffer (CO_G) and generated by CORM-A1—on platelet aggregation and energy metabolism, as well as on vasodilatation in aorta, using light transmission aggregometry, Seahorse XFe technique, and wire myography, respectively. ODQ completely prevented the inhibitory effect of CO_G on platelet aggregation, but did not modify antiplatelet effect of CORM-A1. In turn, CO_G did not affect, whereas CORM-A1 substantially inhibited energy metabolism in platelets. Even though activation of sGC by BAY 41-2272 or BAY 58-2667 inhibited significantly platelet aggregation, their effects on energy metabolism in platelets were absent or weak and could not contribute to antiplatelet effects of sGC activation. In contrast, vasodilatation of murine aortic rings, induced either by CO_G or CORM-A1, was dependent on sGC. We conclude that the source (CO_G vs. CORM-A1) and kinetics (rapid vs. slow) of CO delivery represent key determinants of the mechanism of antiplatelet action of CO, involving either impairment of energy metabolism or activation of sGG.     

Methanol Synthesis with Steel Mill Gases: Performance Investigations in an On-Site Technical Center

An on-site laboratory with direct access to cleaned and conditioned steel mill gases was recently put into operation. The long-term performance and stability of Clariant's MegaMax®800 methanol synthesis catalyst utilizing steel mill gases is currently being investigated. First test results revealed that in order to investigate deactivation mechanisms arising from particular properties of the cleaned steel mill gases, the overlaying effect of thermal deactivation of the catalyst has to be minimized.     

Biocomposites of Epoxidized Natural Rubber/Poly(lactic acid) Modified with Natural Fillers (Part I)

The study aimed to prepare sustainable and degradable elastic blends of epoxidized natural rubber (ENR) with poly(lactic acid) (PLA) that were reinforced with flax fiber (FF) and montmorillonite (MMT), simultaneously filling the gap in the literature regarding the PLA-containing polymer blends filled with natural additives. The performed study reveals that FF incorporation into ENR/PLA blend may cause a significant improvement in tensile strength from (10 ± 1) MPa for the reference material to (19 ± 2) MPa for the fibers-filled blend. Additionally, it was found that MMT employment in the role of the filler might contribute to ENR/PLA plasticization and considerably promote the blend elongation up to 600%. This proves the successful creation of the unique and eco-friendly PLA-containing polymer blend exhibiting high elasticity. Moreover, thanks to the performed accelerated thermo-oxidative and ultraviolet (UV) aging, it was established that MMT incorporation may delay the degradation of ENR/PLA blends under the abovementioned conditions. Additionally, mold tests revealed that plant-derived fiber addition might highly enhance the ENR/PLA blend’s biodeterioration potential enabling faster and more efficient growth of microorganisms. Therefore, materials presented in this research may become competitive and eco-friendly alternatives to commonly utilized petro-based polymeric products.     

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.

     

Metabolic Glycoengineering in hMSC-TERT as a Model for Skeletal Precursors by Using Modified Azide/Alkyne Monosaccharides

Metabolic glycoengineering enables a directed modification of cell surfaces by introducing target molecules to surface proteins displaying new features. Biochemical pathways involving glycans differ in dependence on the cell type; therefore, this technique should be tailored for the best results. We characterized metabolic glycoengineering in telomerase-immortalized human mesenchymal stromal cells (hMSC-TERT) as a model for primary hMSC, to investigate its applicability in TERT-modified cell lines. The metabolic incorporation of N-azidoacetylmannosamine (Ac₄ManNAz) and N-alkyneacetylmannosamine (Ac₄ManNAl) into the glycocalyx as a first step in the glycoengineering process revealed no adverse effects on cell viability or gene expression, and the in vitro multipotency (osteogenic and adipogenic differentiation potential) was maintained under these adapted culture conditions. In the second step, glycoengineered cells were modified with fluorescent dyes using Cu-mediated click chemistry. In these analyses, the two mannose derivatives showed superior incorporation efficiencies compared to glucose and galactose isomers. In time-dependent experiments, the incorporation of Ac₄ManNAz was detectable for up to six days while Ac₄ManNAl-derived metabolites were absent after two days. Taken together, these findings demonstrate the successful metabolic glycoengineering of immortalized hMSC resulting in transient cell surface modifications, and thus present a useful model to address different scientific questions regarding glycosylation processes in skeletal precursors.     

Depassivation and repassivation of stainless steels by stepwise pH change

Immersion tests with different stainless steels have been performed, while the pH was stepwise decreased and then increased again. During 8.5-day exposure, the depassivation and repassivation pH values as a function of pitting resistance equivalent number were determined. There is always a gap between both pH values (depassivation and repassivation), indicating that for every steel, there are conditions where an existing passive layer can be maintained but cannot be rebuilt after depassivation. In such environments, the passive layer is thicker, consisting mainly of molybdenum and iron rich oxides, while chromium is dissolved. Usually, depending on conditions, the passive layer is more chromium-rich, especially the inner layer. This is relevant, for example, for acidizing jobs in oil and gas industry, proving that repassivation after acidizing will happen promptly, when the pH is increased again.     

A Distinct Cytokine Profile and Stromal Vascular Fraction Metabolic Status without Significant Changes in the Lipid Composition Characterizes Lipedema

Lipedema is an adipose tissue disorder characterized by the disproportionate increase of subcutaneous fat tissue in the lower and/or upper extremities. The underlying pathomechanism remains unclear and no molecular biomarkers to distinguish the disease exist, leading to a large number of undiagnosed and misdiagnosed patients. To unravel the distinct molecular characteristic of lipedema we performed lipidomic analysis of the adipose tissue and serum of lipedema versus anatomically- and body mass index (BMI)-matched control patients. Both tissue groups showed no significant changes regarding lipid composition. As hyperplastic adipose tissue represents low-grade inflammation, the potential systemic effects on circulating cytokines were evaluated in lipedema and control patients using the Multiplex immunoassay system. Interestingly, increased systemic levels of interleukin 11 (p = 0.03), interleukin 28A (p = 0.04) and interleukin 29 (p = 0.04) were observed. As cytokines can influence metabolic activity, the metabolic phenotype of the stromal vascular fraction was examined, revealing significantly increased mitochondrial respiration in lipedema. In conclusion, despite sharing a comparable lipid profile with healthy adipose tissue, lipedema is characterized by a distinct systemic cytokine profile and metabolic activity of the stromal vascular fraction.     

Courses Based on iGEM/BIOMOD Competitions Are the Ideal Format for Research-Based Learning of Xenobiology

Synthetic biology and especially xenobiology, as emerging new fields of science, have reached an intellectual and experimental maturity that makes them suitable for integration into the university curricula of chemical and biological disciplines. Novel scientific fields that include laboratory work are perfect playgrounds for developing highly motivating research-based teaching modules. We believe that research-based learning enriched by digital tools is the best approach for teaching new emerging essentials of academic education. This is especially true when the scientific field as such is still not canonized with text books and best-practice examples. Our experience shows that iGEM/BIOMOD competitions represent an excellent basis for designing research-based courses in xenobiology. Therefore, we present a report on “iGEM–Synthetic Biology” offered at the Technische Universität Berlin as an example.