Modulation of Pharmacologically Relevant Properties of Piperidine Derivatives by Functional Groups in an Equatorial or Axial β-Position to the Amino Group

Thirteen epimeric pairs of 5-substituted N-piperonyl-3-phenylpiperidine derivatives were synthesized in order to explore the stereospecific modulation of basicity, lipophilicity, aqueous solubility, and membrane permeation by functional groups in equatorial or axial positions beta to the amine unit. While this comprehensive data set provides enhanced insight into multiple factors that affect basicity and lipophilicity, it fills an important knowledge gap, providing a frame of reference for the property-based design of bioactive compounds. Impacts on amine basicity are very pronounced for the β-equatorial functional groups and parallel basicity-lowering effects known for acyclic amine derivatives. For β-axial functional groups, the basicity-lowering effects are generally decreased, with the nitrile group as the only exception. Basicity and lipophilicity modulations observed for β-axial functional groups are quite diverse and rationalized in terms of intramolecular hydrogen bonding, dipolar interactions, and special solvation effects. Aqueous solubility and (artificial) membrane permeability are discussed with reference to lipophilicity.     

Photoactivatable Mussel‐Based Underwater Adhesive Proteins by an Expanded Genetic Code

Marine mussels exhibit potent underwater adhesion abilities under hostile conditions by employing 3,4‐dihydroxyphenylalanine (DOPA)‐rich mussel adhesive proteins (MAPs). However, their recombinant production is a major biotechnological challenge. Herein, a novel strategy based on genetic code expansion has been developed by engineering efficient aminoacyl‐transfer RNA synthetases (aaRSs) for the photocaged noncanonical amino acid ortho‐nitrobenzyl DOPA (ONB‐DOPA). The engineered ONB‐DOPARS enables in vivo production of MAP type 5 site‐specifically equipped with multiple instances of ONB‐DOPA to yield photocaged, spatiotemporally controlled underwater adhesives. Upon exposure to UV light, these proteins feature elevated wet adhesion properties. This concept offers new perspectives for the production of recombinant bioadhesives.     

Opening of New Synthetic Routes Using Segmented Microflow in Multistep Syntheses

The application of microfluidics in organic chemistry is a valuable tool to access new synthesis pathways and to break limitations set by traditional batch chemistry. In the past, the majority of research focused on solving problems associated with individual reactions. It is necessary to advance the field by incorporating flow chemistry in longer multistep syntheses to open more direct paths towards complicated compounds. Several strategies were developed to meet the demands of a four‐step synthesis, which includes biphasic nitrations, gaseous substrates, and very fast reactions on multifunctional molecules. A unique micro flow setup was applied in each reaction to meet its specific requirements.     

The fatty acid composition of lipids from muscle and adipose tissues of pigs fed various oil mixtures differing in their ratio between oleic acid and linoleic acid

High concentrations of polyunsaturated fatty acids (PUFA) in meat have detrimental effects on its technical properties. The present study was carried out to investigate whether PUFA levels in pork can be reduced by increasing the concentrations of oleic acid in pig diets. To this end a bifactorial experiment was carried out with 48 female growing finishing pigs. Six different diets were used with two different concentrations of linoleic acid (12 vs. 24 g/kg) and three different concentrations of oleic acid (12 vs. 18 vs. 24 g/kg). The experiment started at a body weight (BW) of 58 kg and continued until 115 kg BW. The fatty acid composition of total lipids of backfat, perirenal fat and musculus (m.) longissimus dorsi was analysed. Concentrations of linoleic acid and total PUFA in backfat and perirenal fat were affected only by the dietary linoleic acid content but not at all by the dietary oleic acid content. Increasing the dietary concentration of oleic acid raised the level of oleic acid in those tissues at the expense of saturated fatty acids, suggesting competition between monounsaturated fatty acids and saturated fatty acids for incorporation into triglycerides. At the low dietary linoleic acid concentration, the percentages of linoleic acid and total PUFA in total lipids of m. longissimus dorsi were also unaffected by the dietary oleic acid content. In contrast, at the high dietary linoleic acid concentration, percentages of linoleic acid and total PUFA of the m. longissimus dorsi were reduced by increasing the dietary concentration of oleic acid, suggesting that oleic acid and linoleic acid compete for incorporation into muscle lipids. Thus, at high dietary linoleic acid levels the fatty acid composition of the m. longissimus dorsi was favourably affected by high dietary oleic acid concentrations; in backfat and perirenal fat, however, no beneficial effect of high dietary oleic acid levels was seen.     

Fundamentals towards a Modular Microstructured Production Plant

For years, microtechnology is being considered as an emerging technique for chemical engineering tasks to overcome safety issues corresponding to high volumes and gaining higher selectivities and yields in reaction technology. Whereas in reaction technology a broad variety of microstructured equipment is available, in product purification/separation adequate equipment is missing. Research is focused on modular fast and flexible smaller production plants being operated continuously instead of batchwise in order to reduce engineering efforts and time‐to‐process. To cope with these demands, an appropriate definition of modules, which could be easily chosen and combined, is inevitable. In addition, these modules have to be well characterized concerning fluid dynamics and separation performance. This paper focuses on the characterization of available modules/devices. A standard method and analysis of the results concerning manufacturing accuracy and operation range is proposed. Miniplant technology is described as an efficient tool to validate process concepts proposed by process simulation studies. Necessary model parameters are determined for industrial complex mixtures in miniaturized laboratory equipment. Parameters are calculated model based to gain maximal accuracy. State of the art of miniplant technology is described and basic characteristic data are presented.     

MontiCore: a framework for compositional development of domain specific languages

Domain specific languages (DSLs) are increasingly used today. Coping with complex language definitions, evolving them in a structured way, and ensuring their error freeness are the main challenges of DSL design and implementation. The use of modular language definitions and composition operators are therefore inevitable in the independent development of language components. In this article, we discuss these arising issues by describing a framework for the compositional development of textual DSLs and their supporting tools. We use a redundance-free definition of a readable concrete syntax and a comprehensible abstract syntax as both representations significantly overlap in their structure. For enhancing the usability of the abstract syntax, we added concepts like associations and inheritance to a grammar-based definition in order to build up arbitrary graphs (as known from metamodeling). Two modularity concepts, grammar inheritance and embedding, are discussed. They permit compositional language definition and thus simplify the extension of languages based on already existing ones. We demonstrate that compositional engineering of new languages is a useful concept when project-individual DSLs with appropriate tool support are defined.     

MultiETSC: automated machine learning for early time series classification

Early time series classification (EarlyTSC) involves the prediction of a class label based on partial observation of a given time series. Most EarlyTSC algorithms consider the trade-off between accuracy and earliness as two competing objectives, using a single dedicated hyperparameter. To obtain insights into this trade-off requires finding a set of non-dominated (Pareto efficient) classifiers. So far, this has been approached through manual hyperparameter tuning. Since the trade-off hyperparameters only provide indirect control over the earliness-accuracy trade-off, manual tuning is tedious and tends to result in many sub-optimal hyperparameter settings. This complicates the search for optimal hyperparameter settings and forms a hurdle for the application of EarlyTSC to real-world problems. To address these issues, we propose an automated approach to hyperparameter tuning and algorithm selection for EarlyTSC, building on developments in the fast-moving research area known as automated machine learning (AutoML). To deal with the challenging task of optimising two conflicting objectives in early time series classification, we propose MultiETSC, a system for multi-objective algorithm selection and hyperparameter optimisation (MO-CASH) for EarlyTSC. MultiETSC can potentially leverage any existing or future EarlyTSC algorithm and produces a set of Pareto optimal algorithm configurations from which a user can choose a posteriori. As an additional benefit, our proposed framework can incorporate and leverage time-series classification algorithms not originally designed for EarlyTSC for improving performance on EarlyTSC; we demonstrate this property using a newly defined, “naïve” fixed-time algorithm. In an extensive empirical evaluation of our new approach on a benchmark of 115 data sets, we show that MultiETSC performs substantially better than baseline methods, ranking highest (avg. rank 1.98) compared to conceptually simpler single-algorithm (2.98) and single-objective alternatives (4.36).