Synthesis,Characterization and Application of New Rhodium Complexes for Indirect Electrochemical Cofactor Regeneration

Electroenzymatic synthesis often suffers from electrochemical reaction steps which proceed slower than the coupled enzyme reaction. For indirect electrochemical cofactor regeneration, we here report two new mediators with superior properties compared to the established rhodium complex (2,2′‐bipyridyl)(pentamethylcyclopentadienyl)rhodium [Cp*Rh(2,2′‐bipyridine)]. After constructing a robotic system for fast and reliable cyclic voltammetry measurements, we screened twelve rhodium complexes with substituted 2,2′‐bipyridine ligands for their reduction potentials and catalytic activity towards the reduction of NADP. Promising complexes were investigated in more detail by cyclic voltammetry and under batch electrolysis conditions. The new complexes Cp*Rh(5,5′‐methyl‐2,2′‐bipyridine) and Cp*Rh(4,4′‐methoxy‐2,2′‐bipyridine) reduced NADP to NADPH three times faster than the established mediator, resulting in volumetric productivities of up to 136 mmol L⁻¹ d⁻¹ and turnover frequencies of up to 113 h⁻¹. This increased reaction rate of these new mediators makes indirect electrochemical approach significantly more competitive to other methods of cofactor regeneration. Abbreviations: ADH=alcohol dehydrogenase; Ag|AgCl=silver|silver chloride reference electrode; bpy=2,2′‐bipyridine; ci=current increase; Cp*=pentamethylcyclopentadienyl; CV=cyclic voltammetry; Ep=peak potential; equiv=equivalent; NADP/NADPH=nicotinamide adenine dinucleotide phosphate oxidised/reduced form.     

Electrodeposition of palladium-dotted nickel nanowire networks as a robust self-supported methanol electrooxidation catalyst

Journal of Materials Science - Mass activity and long-term stability are two major issues in current fuel cell catalyst designs. While supported catalysts normally suffer from poor long-term...     

Toxizitätsreduktion durch (Grundwasser-) Sanierung?

The usage of an automatized and continuously (on-line) working biomonitor for the surveillance of groundwater remediation is presented and the data are compared to different discontinuous acute biotests. The use of an on-line biomonitor at the SAFIRA groundwater remediation testsite showed to be superior to the discontinuous tests. The long-time surveillance of two different remediation techniques revealed a decrease in remediation efficiency of one technique while the other technique -using activated carbon- did not show any reduction in efficiency. The validation of these results with other acute biotests (algae, fishembryo, daphnia and genotoxicity) indicated a complex groundwater contamination which can not be explained by the quantitatively main contaminant monochlorobenzene. It is suggested to use ecotoxicological biotests and knowledge in parallel to the conventional chemical analysis before a remediation strategy is designed. All anthropogenic contaminations (toxic or unwanted) should be identified beforehand such that the developed remediation techniques would be more target-oriented.     

Determination of CFTR densities in erythrocyte plasma membranes using recognition imaging

CFTR (cystic fibrosis transmembrane conductance regulator) is a cAMP-regulated chloride (Cl(-)) channel that plays an important role in salt and fluid movement across epithelia. Cystic fibrosis (CF), the most common genetic disease among Caucasians, is caused by mutations in the gene encoding CFTR. The most predominant mutation, F508del, disturbs CFTR protein trafficking, resulting in a reduced number of CFTR in the plasma membrane. Recent studies indicate that CFTR is not only found in epithelia but also in human erythrocytes. Although considerable attempts have been made to quantify CFTR in cells, conclusions on numbers of CFTR molecules localized in the plasma membrane have been drawn indirectly. AFM has the power to provide the needed information, since both sub-molecular spatial resolution and direct protein recognition via antibody-antigen interaction can be observed. We performed a quantification study of the CFTR copies in erythrocyte membranes at the single molecule level, and compared the difference between healthy donors and CF patients. We detected that the number of CFTR molecules is reduced by 70% in erythrocytes of cystic fibrosis patients.     

Simulation of induced current densities in the human body atindustrial induction heating frequencies

At industrial workplaces in the vicinity of induction heating and melting devices, workers are exposed to strong magnetic fields. Up until now, little knowledge about the coupling of external fields into the human body at low frequencies existed. This paper provides numerical investigations to clarify the ratio between external homogeneous magnetic fields and induced current densities inside the human body in the frequency range from 250 Hz up to 10 kHz. The finite-difference time-domain (FDTD) method is used to calculate the induced current density in a realistic inhomogeneous 1 cm resolution human body model with appropriate tissue parameters. The magnitude of the external magnetic field equals the reference value for occupational exposure in the current guideline of the International Commission on Nonionizing Radiation Protection (ICNIRP). It was found that the calculated maximum current densities inside the body may exceed the basic restrictions of the ICNIRP guideline at least up to a factor of two. Finally, the suitability of the human body model for dosimetric investigations is discussed in view of fine-resolution models presented in the literature     

Controlling signaling with a specifically designed Gi-coupled receptor

We are developing a system to control G protein signaling in vivo to regulate a broad range of physiologic responses. Our system utilizes G protein-coupled peptide receptors engineered to respond exclusively to synthetic small molecule ligands and not to their natural ligand(s). These engineered receptors are designated RASSLs (receptor activated solely by a synthetic ligand). We have made two prototype RASSLs that are based on the human kappa opioid receptor. Small molecule drugs that activate the kappa receptor are nonaddictive and safe to administer in vivo. Binding and signaling assays reveal 200-2000-fold reductions in the ability of our RASSLs to bind or be activated by dynorphin, an endogenous peptide ligand of the kappa opioid receptor. In a high-throughput signaling assay, these prototype RASSLs expressed in Chinese hamster ovary K1 cells showed little or no response to a panel of 21 opioid peptides but still signaled normally in response to small molecule drugs such as spiradoline. Activation of a RASSL by spiradoline also caused proliferation of rat-1a tissue culture cells. These data provide evidence that G protein-coupled receptors can be made into RASSLs. The potential in vivo applications for RASSLs include the positive enrichment of transfected cells and the development of new animal models of disease.     

Active learning for extended finite state machines

We present a black-box active learning algorithm for inferring extended finite state machines (EFSM)s by dynamic black-box analysis. EFSMs can be used to model both data flow and control behavior of software and hardware components. Different dialects of EFSMs are widely used in tools for model-based software development, verification, and testing. Our algorithm infers a class of EFSMs called register automata. Register automata have a finite control structure, extended with variables (registers), assignments, and guards. Our algorithm is parameterized on a particular theory, i.e., a set of operations and tests on the data domain that can be used in guards.Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We also show that, under these conditions, our framework induces a generalization of the classical Nerode equivalence and canonical automata construction to the symbolic setting. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.     

Fixed-Parameter Algorithms for Cluster Vertex Deletion

We initiate the first systematic study of the NP-hard Cluster Vertex Deletion (CVD) problem (unweighted and weighted) in terms of fixed-parameter algorithmics. In the unweighted case, one searches for a minimum number of vertex deletions to transform a graph into a collection of disjoint cliques. The parameter is the number of vertex deletions. We present efficient fixed-parameter algorithms for CVD applying the fairly new iterative compression technique. Moreover, we study the variant of CVD where the maximum number of cliques to be generated is prespecified. Here, we exploit connections to fixed-parameter algorithms for (weighted) Vertex Cover.     

Particle–Fluid–Structure Interaction for Debris Flow Impact on Flexible Barriers

Flexible barriers are increasingly used for the protection from debris flow in mountainous terrain due to their low cost and environmental impact. However, the development of a numerical tool for the rational design of such structures is still a challenge. In this work, a hybrid computational framework is presented, using a total Lagrangian formulation of the finite element method to represent a flexible barrier. The actions exerted on the structure by a debris flow are obtained from simultaneous simulations of the flow of a fluid‐grain mixture, using two conveniently coupled solvers: the discrete element method governs the motion of the grains, while the free‐surface non‐Newtonian fluid phase is solved using the lattice Boltzmann method. Simulations on realistic geometries show the dependence of the momentum transfer on the barrier on the composition of the debris flow, challenging typical assumptions made during the design process today. In particular, we demonstrate that both grains and fluid contribute in a nonnegligible way to the momentum transfer. Moreover, we show how the flexibility of the barrier reduces its vulnerability to structural collapse, and how the stress is distributed on its fabric, highlighting potential weak points.