The composition of edible oils modifies β-sitosterol/γ-oryzanol oleogels. Part I: Stripped triglyceride oils

The role of the fatty acid (FA) composition of triglycerides (TAGs) on sterol/sterol ester oleogels has been studied. Minor oil components of three vegetable oils with varying degrees of unsaturation (iodine values, IV) were removed. Typical oil quality parameters were determined before and after the treatment, and oleogels were produced using all six oils. Characteristic gel properties such as transition temperatures, mechanical properties and microstructure were tested. The results were compared regarding the impact of IV and the stripping procedure. Minor components were essentially removed during stripping, resulting in significantly different oil properties such as peroxide value, free FA and viscosity. However, peroxides formed rapidly in stripped flaxseed oil. Gel–sol transition temperatures and enthalpies were higher in gels from untreated oils and decreased with IV in samples with stripped oils. In contrast, the sol–gel transition was suppressed due to minor oil components in untreated oils. The effect of IV on gel formation was much less and linked to a lower solvent viscosity in more unsaturated oils. Nevertheless, gel firmness was significantly higher in oleogels from untreated oils and decreased slightly with IV in stripped oils. That was associated with differences in the arrangement of network building blocks, which was confirmed using atomic force microscopy. This study showed that the FA composition of TAGs has a limited effect on oleogel properties compared to those of minor oil components. The next part of this study focuses on modifying oleogel properties by adding selected minor components to stripped oils at varying concentrations.     

Process Design in World 3.0 – Challenges and Strategies to Master the Raw Material Change

The evolution of global energy supply chains leads to a raw material change in the chemical industry. Despite this change, the value‐added chains of the chemical industry have to keep up their output of diverse high‐quality products desired by the customers. C1 chemistry in combination with suitable conversion technologies yielding olefins and aromatics will play a key role in mastering this challenge. New chemical value‐added chains have to be developed and assessed, resulting in an increasing importance of conceptual process design. All this will take place in what Ghemawat has called the World 3.0, a globally linked but regionally diverse world. This diversity creates further challenges for process design in the chemical industries. A systematic concept to address these challenges is given here, including strategies for optimization and decision support.     

Silica nanoparticles as a tool for fluorescence collection efficiency enhancement

In this work we demonstrate enhancement of the fluorescence collection efficiency for chlorophyll-containing photosynthetic complexes deposited on SiO₂ spherical nanoparticles. Microscopic images of fluorescence emission reveal ring-like emission patterns associated with chlorophyll-containing complexes coupled to electromagnetic modes within the silica nanoparticles. The interaction leaves no effect upon the emission spectra of the complexes, and the transient behavior of the fluorescence also remains unchanged, which indicates no influence of the silica nanoparticles on the radiative properties of the fluorophores. We interpret this enhancement as a result of efficient scattering of electromagnetic field by the dielectric nanoparticles that increases collection efficiency of fluorescence emission.     

The influence of the type of oil phase on the self‐assembly process of γ‐oryzanol + β‐sitosterol tubules in organogel systems

Mixtures of γ‐oryzanol and β‐sitosterol were used to structure different oils (decane, limonene, sunflower oil, castor oil, and eugenol). The γ‐oryzanol and β‐sitosterol mixtures self‐assemble into double‐walled hollow tubules (～10 nm in diameter) in the oil phase, which aggregate to form a network resulting in firm organogels. The self‐assembly of the sterol molecules into tubules was studied using light scattering and rheology. By using different oils, the influence of the polarity of the oil on the self‐assembly was studied. The effects of temperature and structurant concentration on the tubuler formation process were determined and the thermodynamic theory of self‐assembly was applied to calculate the change in Gibbs free energy (ΔG⁰), enthalpy (ΔH⁰), and entropy (ΔS⁰) resulting from the aggregation of the structurants was determined. The self‐assembly was found to be enthalpy‐driven as characterized by a negative ΔH⁰ and ΔS⁰. A decreasing polarity of the oil promotes the self‐assembly leading to formation of tubules at higher temperatures and lower structurant concentrations.     

Production process for diesel fuel components poly(oxymethylene) dimethyl ethers from methane-based products by hierarchical optimization with varying model depth

Poly(oxymethylene) dimethyl ethers (OMEs) are attractive components for tailoring diesel fuels. They belong to the group of oxygenates that reduce soot formation in the combustion when added to diesel fuels and can be produced on a large scale from methane-based products. This opens a new route for gas-to-liquid technology. The present work deals with a particularly favorable route for the large scale production in which OMEs are formed from methylal and trioxane. An OME process based on these educts is designed using two process models of varying depth. In a hierarchical optimization, in which the optimum obtained with a reduced model is used as a starting point for the optimization with the detailed model, an optimal design is found. The resulting design is further adopted to practical needs including a possibility of side-product purge. This work shows that OME production from methylal and trioxane is feasible with technology that could be used in very large scales. The physical property model that is required for the design of the OME process is described in the present work. It is based on literature data on thermo-physical properties and reaction data from previous work of our group. That database is complemented in the present work by measurements of the density of pure OMEs and the vapor–liquid equilibrium in the system (dioxymethylene dimethyl ether + trioxane).     

Modeling In Vitro Osteoarthritis Phenotypes in a Vascularized Bone Model Based on a Bone-Marrow Derived Mesenchymal Cell Line and Endothelial Cells

The subchondral bone and its associated vasculature play an important role in the onset of osteoarthritis (OA). Integration of different aspects of the OA environment into multi-cellular and complex human, in vitro models is therefore needed to properly represent the pathology. In this study, we exploited a mesenchymal stromal cell line/endothelial cell co-culture to produce an in vitro human model of vascularized osteogenic tissue. A cocktail of inflammatory cytokines, or conditioned medium from mechanically-induced OA engineered microcartilage, was administered to this vascularized bone model to mimic the inflamed OA environment, hypothesizing that these treatments could induce the onset of specific pathological traits. Exposure to the inflammatory factors led to increased network formation by endothelial cells, reminiscent of the abnormal angiogenesis found in OA subchondral bone, demineralization of the constructs, and increased collagen production, signs of OA related bone sclerosis. Furthermore, inflammation led to augmented expression of osteogenic (alkaline phosphatase (ALP) and osteocalcin (OCN)) and angiogenic (vascular endothelial growth factor (VEGF)) genes. The treatment, with a conditioned medium from the mechanically-induced OA engineered microcartilage, also caused increased demineralization and expression of ALP, OCN, ADAMTS5, and VEGF; however, changes in network formation by endothelial cells were not observed in this second case, suggesting a possible different mechanism of action in inducing OA-like phenotypes. We propose that this vascularized bone model could represent a first step for the in vitro study of bone changes under OA mimicking conditions and possibly serve as a tool in testing anti-OA drugs.     

Manipulating the Epigenome in Nuclear Transfer Cloning: Where,When and How

The nucleus of a differentiated cell can be reprogrammed to a totipotent state by exposure to the cytoplasm of an enucleated oocyte, and the reconstructed nuclear transfer embryo can give rise to an entire organism. Somatic cell nuclear transfer (SCNT) has important implications in animal biotechnology and provides a unique model for studying epigenetic barriers to successful nuclear reprogramming and for testing novel concepts to overcome them. While initial strategies aimed at modulating the global DNA methylation level and states of various histone protein modifications, recent studies use evidence-based approaches to influence specific epigenetic mechanisms in a targeted manner. In this review, we describe—based on the growing number of reports published during recent decades—in detail where, when, and how manipulations of the epigenome of donor cells and reconstructed SCNT embryos can be performed to optimize the process of molecular reprogramming and the outcome of nuclear transfer cloning.     

Determination of optimum imaging conditions in AC-SECM using the mathematical distance between approach curves displayed in the impedance domain

Scanning electrochemical microscopy (SECM) in its alternating current mode (AC-SECM) has been of growing importance to detect and interpret local variations of electrochemical surface properties with high spatial resolution. The sensitivity of AC-SECM and hence the quality of imaging was found to be highly dependent on the experimental conditions. It was commonly judged using approach curves in the distance domain. As an alternative to current-distance approach curves, the coordinate system based on real and imaginary part of impedance is suggested for their display. In this framework, the difference between the impedance vector magnitude, real or imaginary part of impedance over neighboring surfaces is considered as a measure of imaging contrast. The variable which grants maximum difference is selected for imaging while measurement conditions associated with this maximum indicate optimum scanning conditions. The methodology of determining these optimized parameters is laid out in this contribution and examples are given. Since the optimum parameters are identified before the actual lateral imaging, this time-saving method facilitates the visualization of local electrochemical properties at the highest possible quality.     

Adaptive Embedded/Immersed Unstructured Grid Techniques

Embedded mesh, immersed body or ficticious domain techniques have been used for many years as a way to discretize geometrically complex domains with structured grids. The use of such techniques within adaptive, unstructured grid solvers is relatively recent. The combination of body-fitted functionality for some portion of the domain, together with embedded mesh or immersed body functionality for another portion of the domain offers great advantages, which are increasingly being exploited. The present paper reviews the methodology from an implementational perspective.     

Evaluation of Orbital Lymphoproliferative and Inflammatory Disorders by Gene Expression Analysis

Non-specific orbital inflammation (NSOI) and IgG4-related orbital disease (IgG4-ROD) are often challenging to differentiate. Furthermore, it is still uncertain how chronic inflammation, such as IgG4-ROD, can lead to mucosa-associated lymphoid tissue (MALT) lymphoma. Therefore, we aimed to evaluate the diagnostic value of gene expression analysis to differentiate orbital autoimmune diseases and elucidate genetic overlaps. First, we established a database of NSOI, relapsing NSOI, IgG4-ROD and MALT lymphoma patients of our orbital center (2000–2019). In a consensus process, three typical patients of the above mentioned three groups (mean age 56.4 ± 17 years) at similar locations were selected. Afterwards, RNA was isolated using the RNeasy FFPE kit (Qiagen) from archived paraffin-embedded tissues. The RNA of these 12 patients were then subjected to gene expression analysis (NanoString nCounter^®), including a total of 1364 target genes. The most significantly upregulated and downregulated genes were used for a machine learning algorithm to distinguish entities. This was possible with a high probability (p < 0.0001). Interestingly, gene expression patterns showed a characteristic overlap of lymphoma with IgG4-ROD and NSOI. In contrast, IgG4-ROD shared only altered expression of one gene regarding NSOI. To validate our potential biomarker genes, we isolated the RNA of a further 48 patients (24 NSOI, 11 IgG4-ROD, 13 lymphoma patients). Then, gene expression pattern analysis of the 35 identified target genes was performed using a custom-designed CodeSet to assess the prediction accuracy of the multi-parameter scoring algorithms. They showed high accuracy and good performance (AUC ROC: IgG4-ROD 0.81, MALT 0.82, NSOI 0.67). To conclude, genetic expression analysis has the potential for faster and more secure differentiation between NSOI and IgG4-ROD. MALT-lymphoma and IgG4-ROD showed more genetic similarities, which points towards progression to lymphoma.