Macrophage-targeting oligopeptides from Mortierella alpina

The realm of natural products of early diverging fungi such as Mortierella species is largely unexplored. Herein, the nonribosomal peptide synthetase (NRPS) MalA catalysing the biosynthesis of the surface-active biosurfactants, malpinins, has been identified and biochemically characterised. The investigation of the substrate specificity of respective adenylation (A) domains indicated a substrate-tolerant enzyme with an unusual, inactive C-terminal NRPS module. Specificity-based precursor-directed biosynthesis yielded 20 new congeners produced by a single enzyme. Moreover, MalA incorporates artificial, click-functionalised amino acids which allowed postbiosynthetic coupling to a fluorophore. The fluorescent malpinin conjugate penetrates mammalian cell membranes via an phagocytosis-mediated mechanism, suggesting Mortierella oligopeptides as carrier peptides for directed cell targeting. The current study demonstrates substrate-specificity testing as a powerful tool to identify flexible NRPS modules and highlights basal fungi as reservoir for chemically tractable compounds in pharmaceutical applications.

Specificity profiling of a nonribosomal peptide synthetase of an early diverging fungus revealed high substrate flexibility. Feeding studies with click-functionalised amino acids enabled the production of fluorescent peptides targeting macrophages.     

Sampling and Analysis of Odorous Compounds in Water Treatment Plants

Abstract

The following analytical method has been used to identify some odorous compounds in the air of the water treatment plant Werdholzli, Zurich: sampling of contaminated air with the help of activated carbon, desorption by the solvents carbon disulphide and methylene chloride, separation of the carbon disulfide extract into a polar and a nonpolar fraction by adsorption column chromatography on silica. Hereafter gaschromatographic analysis of the polar fraction on glass capillary column (Ucon HB 5100); detection and identification were achieved by flame ionisation, thermoionic nitrogen selective detector and computerized mass spectrometry (Finnigan 3200 F, data system 6110).

The results show the presence of sulfur compounds: thiophenes, thiazoles; nitrogen compounds: pyrazines; oxygen compounds: phenols, alcohols and some unsatured hydrocarbons. The malodorous compounds were sulfur and nitrogen compounds in the range of 0.01-0.1 ppm.     

Coordination Chemistry of Gold Catalysts in Solution: A Detailed NMR Study

Coordination chemistry of gold catalysts bearing eight different ligands [L=PPh₃, JohnPhos (L2), Xphos (L3), DTBP, IMes, IPr, dppf, S‐tolBINAP (L8)] has been studied by NMR spectroscopy in solution at room temperature. Cationic or neutral mononuclear complexes LAuX (L=L2, L3, IMes, IPr; X=charged or neutral ligand) underwent simple ligand exchange without giving any higher coordinate complexes. For L2AuX the following ligand strength series was determined: MeOH?hex‐3‐yne <MeCN≈OTf^??Me₂S<2,6‐lutidine<4‐picoline<CF₃CO₂^?≈DMAP<TMTU<PPh₃<OH^?≈Cl^?. Some heteroligand complexes DTBPAuX exist in solution in equilibrium with the corresponding symmetrical species. Binuclear complexes dppf(AuOTf)₂ and S‐tolBINAP(AuOTf)₂ showed different behavior in exchange reactions with ligands depending on the ligand strength. Thus, PPh₃ causes abstraction of one gold atom to give mononuclear complexes LLAuPPh₃⁺ and (Ph₃P)_nAu⁺, but other N and S ligands give ordinary dicationic species LL(AuNu)₂²⁺. In reactions with different bases, LAu⁺ provided new oxonium ions whose chemistry was also studied: (DTBPAu)₃O⁺, (L2Au)₂OH⁺, (L2Au)₃O⁺, (L3Au)₂OH⁺, and (IMesAu)₂OH⁺. Ultimately, formation of gold hydroxide LAuOH (L=L2, L3, IMes) was studied. Ligand‐ or base‐assisted interconversions between (L2Au)₂OH⁺, (L2Au)₃O⁺, and L2AuOH are described. Reactions of dppf(AuOTf)₂ and S‐tolBINAP(AuOTf)₂ with bases provided more interesting oxonium ions, whose molecular composition was found to be [dppf(Au)₂]₃O₂²⁺, L8(Au)₂OH⁺, and [L8(Au)₂]₃O₂²⁺, but their exact structure was not established. Several reactions between different oxonium species were conducted to observe mixed heteroligand oxonium species. Reaction of L2AuNCMe⁺ with S^2? was studied; several new complexes with sulfide are described. For many reversible reactions the corresponding equilibrium constants were determined.     

Kazhdan constants for conjugacy classes of compact groups

Kazhdan constants relative to conjugacy classes of compact groups are computed. They depend on the nontrivial irreducible characters of the respective group. The result is applied, in particular, to finite groups of Lie type, symmetric groups, and the group SU(n).     

Blocked-micropores,surface functionalized,bio-compatible and silica-coated iron oxide nanocomposites as advanced MRI contrast agent

Quasi-critical fluctuations occur close to critical points or close to continuous phase transitions. In three-dimensional systems, precision tuning is required to access the fluctuation regime. Lowering the dimensionality enhances the parameter space for quasi-critical fluctuations considerably. This enables one to make use of novel properties emerging in fluctuating systems, such as giant susceptibilities, Casimir forces or novel quasi-particle interactions. Examples are discussed ranging from simple metal–adsorbate systems to unconventional superconductivity in iron-based superconductors.     

From a Point Cloud to a Simulation Model—Bayesian Segmentation and Entropy Based Uncertainty Estimation for 3D Modelling

The 3D modelling of indoor environments and the generation of process simulations play an important role in factory and assembly planning. In brownfield planning cases, existing data are often outdated and incomplete especially for older plants, which were mostly planned in 2D. Thus, current environment models cannot be generated directly on the basis of existing data and a holistic approach on how to build such a factory model in a highly automated fashion is mostly non-existent. Major steps in generating an environment model of a production plant include data collection, data pre-processing and object identification as well as pose estimation. In this work, we elaborate on a methodical modelling approach, which starts with the digitalization of large-scale indoor environments and ends with the generation of a static environment or simulation model. The object identification step is realized using a Bayesian neural network capable of point cloud segmentation. We elaborate on the impact of the uncertainty information estimated by a Bayesian segmentation framework on the accuracy of the generated environment model. The steps of data collection and point cloud segmentation as well as the resulting model accuracy are evaluated on a real-world data set collected at the assembly line of a large-scale automotive production plant. The Bayesian segmentation network clearly surpasses the performance of the frequentist baseline and allows us to considerably increase the accuracy of the model placement in a simulation scene.