Molecular Recognition of Two 2,4‐syn‐Functionalized (S)‐Glutamate Analogues by the Kainate Receptor GluK3 Ligand Binding Domain

The kainate receptors are the least studied subfamily of ionotropic glutamate receptors. These receptors are thought to have a neuromodulatory role and have been associated with a variety of disorders in the central nervous system. This makes kainate receptors interesting potential drug targets. Today, structures of the ligand binding domain (LBD) of the kainate receptor GluK3 are only known in complex with the endogenous agonist glutamate, the natural product kainate, and two synthetic agonists. Herein we report structures of GluK3 LBD in complex with two 2,4‐syn‐functionalized (S)‐glutamate analogues to investigate their structural potential as chemical scaffolds. Similar binding affinities at GluK3 were determined for the 2‐(methylcarbamoyl)ethyl analogue (K_i=4.0 μM ) and the 2‐(methoxycarbonyl)ethyl analogue (K_i=1.7 μM ), in agreement with the similar positioning of the compounds within the binding pocket. As the binding affinity is similar to that of glutamate, this type of Cγ substituent could be used as a scaffold for introduction of even larger substituents reaching into unexplored binding site regions to achieve subtype selectivity.     

Modeling analyte transport and capture in porous bead sensors

Porous agarose microbeads, with high surface to volume ratios and high binding densities, are attracting attention as highly sensitive, affordable sensor elements for a variety of high performance bioassays. While such polymer microspheres have been extensively studied and reported on previously and are now moving into real-world clinical practice, very little work has been completed to date to model the convection, diffusion, and binding kinetics of soluble reagents captured within such fibrous networks. Here, we report the development of a three-dimensional computational model and provide the initial evidence for its agreement with experimental outcomes derived from the capture and detection of representative protein and genetic biomolecules in 290 μm porous beads. We compare this model to antibody-mediated capture of C-reactive protein and bovine serum albumin, along with hybridization of oligonucleotide sequences to DNA probes. These results suggest that, due to the porous interior of the agarose bead, internal analyte transport is both diffusion and convection based, and regardless of the nature of analyte, the bead interiors reveal an interesting trickle of convection-driven internal flow. On the basis of this model, the internal to external flow rate ratio is found to be in the range of 1:170 to 1:3100 for beads with agarose concentration ranging from 0.5% to 8% for the sensor ensembles here studied. Further, both model and experimental evidence suggest that binding kinetics strongly affect analyte distribution of captured reagents within the beads. These findings reveal that high association constants create a steep moving boundary in which unbound analytes are held back at the periphery of the bead sensor. Low association constants create a more shallow moving boundary in which unbound analytes diffuse further into the bead before binding. These models agree with experimental evidence and thus serve as a new tool set for the study of bioagent transport processes within a new class of medical microdevices.     

Stereocontrolled Synthesis and Pharmacological Evaluation of Azetidine‐2,3‐Dicarboxylic Acids at NMDA Receptors

The four stereoisomers of azetidine‐2,3‐dicaroxylic acid (L ‐trans‐ADC, L ‐cis‐ADC, D ‐trans‐ADC, and D ‐cis‐ADC) were synthesized in a stereocontrolled fashion following two distinct strategies: one providing the two cis‐ADC enantiomers and one giving access to the two trans‐ADC enantiomers. The four azetidinic amino acids were characterized in a radioligand binding assay ([³H]CGP39653) at native NMDA receptors: L ‐trans‐ADC showed the highest affinity (K_i=10 μM ) followed by the D ‐cis‐ADC stereoisomer (21 μM ). In contrast, the two analogues L ‐cis‐ADC and D ‐trans‐ADC were low‐affinity ligands (>100 and 90 μM , respectively). Electrophysiological characterization of the ADC compounds at the four NMDA receptor subtypes NR1/NR2A, NR1/NR2B, NR1/NR2C, and NR1/NR2D expressed in Xenopus oocytes showed that L ‐trans‐ADC displayed the highest agonist potency at NR1/NR2D (EC₅₀=50 μM ), which was 9.4‐, 3.4‐, and 1.9‐fold higher than the respective potencies at NR1/NR2A–C. D ‐cis‐ADC was shown to be a partial agonist at NR1/NR2C and NR1/NR2D with medium‐range micromolar potencies (EC₅₀=720 and 230 μM , respectively). A subsequent in silico ligand–protein docking study suggested an unusual binding mode for these amino acids in the agonist binding site.     

Content of antioxidant hydroquinones substituted by β-1,6-linked oligosaccharides in wheat milled fractions,flours and breads

The objective of this study was to quantify seven antioxidant hydroquinones, substituted by β-1,6-linked oligosaccharides, in wheat-based food products by HPLC. These novel compounds were discovered and characterised in our previous study. All seven compounds were quantified in wheat germ and bran. The most abundant compound, 4-hydroxy-3-methoxyphenyl β-d-glucopyranosyl-(1 → 6)-β-d-glucopyranosyl-(1 → 6)-β-d-glucopyranoside, was present at 6.3 g/kg in germ and 0.7 g/kg in bran. In whole-wheat grains, as well as in several kinds of wheat flour and wheat bread, these antioxidants were present at much lower concentrations; only two of them could be quantified. None of these compounds were detected in low-protein flour mixture. Their total content in analysed wheat products decreased in the following order: germ > bran > whole grains ∼ whole grain flours > refined flours > refined bread ? low-protein flour mixture. It correlated well with the antioxidant capacity of water–ethanol extracts of these products determined by Trolox equivalent antioxidant capacity (TEAC) assay (r² = 0.984). The contribution of the analysed compounds to the total antioxidant capacity of wheat germ extract was 52%, whereas the contribution of the most abundant compound was 38%.     

Short‐term hydropower planning coordinated with wind power in areas with congestion problems

In this paper, a day‐ahead planning algorithm for a multi‐reservoir hydropower system coordinated with wind power is developed. Coordination applies to real situations, where wind power and hydropower are owned by different utilities, sharing the same transmission lines, although hydropower has priority for transmission capacity. Coordination is thus necessary to minimize wind energy curtailments during congestion situations. The planning algorithm accounts for the uncertainty of wind power forecast. Only planning for the spot market is considered. Once the production bid is placed on the market, it cannot be changed. The solution of the stochastic optimization problem should, therefore, fulfill the transmission constraints for all wind power production scenarios. An evaluation algorithm is also developed to quantify the impact from the coordinated planning in the long run. The developed planning algorithm and the evaluation algorithm are applied in a case study. The results are compared with uncoordinated operation. The results of the case study show that coordination with wind power brings additional income to the hydropower utility and leads to significant reduction of wind energy curtailments. Copyright © 2007 John Wiley & Sons, Ltd.     

A pure embedding of attribute grammars

Attribute grammars are a powerful specification paradigm for many language processing tasks, particularly semantic analysis of programming languages. Recent attribute grammar systems use dynamic scheduling algorithms to evaluate attributes on demand. In this paper, we show how to remove the need for a generator, by embedding a dynamic approach in a modern, object-oriented and functional programming language. The result is a small, lightweight attribute grammar library that is part of our larger Kiama language processing library. Kiama’s attribute grammar library supports a range of advanced features including cached, uncached, higher order, parameterised and circular attributes. Forwarding is available to modularise higher order attributes and decorators abstract away from the details of attribute value propagation. Kiama also implements new techniques for dynamic extension and variation of attribute equations. We use the Scala programming language because of its support for domain-specific notations and emphasis on scalability. Unlike generators with specialised notation, Kiama attribute grammars use standard Scala notations such as pattern-matching functions for equations, traits and mixins for composition and implicit parameters for forwarding. A benchmarking exercise shows that our approach is practical for realistic language processing.     

Regressor and structure selection in NARX models using a structured ANOVA approach

Regressor selection can be viewed as the first step in the system identification process. The benefits of finding good regressors before estimating complex models are especially clear for nonlinear systems, where the class of possible models is huge. In this article, a structured way of using the tool analysis of variance (ANOVA) is presented and used for NARX model (nonlinear autoregressive model with exogenous input) identification with many candidate regressors.     

Spatial conditioning of transfer functions using local material distributions

In many applications of Direct Volume Rendering (DVR) the importance of a certain material or feature is highly dependent on its relative spatial location. For instance, in the medical diagnostic procedure, the patient's symptoms often lead to specification of features, tissues and organs of particular interest. One such example is pockets of gas which, if found inside the body at abnormal locations, are a crucial part of a diagnostic visualization. This paper presents an approach that enhances DVR transfer function design with spatial localization based on user specified material dependencies. Semantic expressions are used to define conditions based on relations between different materials, such as only render iodine uptake when close to liver. The underlying methods rely on estimations of material distributions which are acquired by weighing local neighborhoods of the data against approximations of material likelihood functions. This information is encoded and used to influence rendering according to the user's specifications. The result is improved focus on important features by allowing the user to suppress spatially less-important data. In line with requirements from actual clinical DVR practice, the methods do not require explicit material segmentation that would be impossible or prohibitively time-consuming to achieve in most real cases. The scheme scales well to higher dimensions which accounts for multi-dimensional transfer functions and multivariate data. Dual-Energy Computed Tomography, an important new modality in radiology, is used to demonstrate this scalability. In several examples we show significantly improved focus on clinically important aspects in the rendered images.     

Efficient visibility encoding for dynamic illumination in direct volume rendering

We present an algorithm that enables real-time dynamic shading in direct volume rendering using general lighting, including directional lights, point lights, and environment maps. Real-time performance is achieved by encoding local and global volumetric visibility using spherical harmonic (SH) basis functions stored in an efficient multiresolution grid over the extent of the volume. Our method enables high-frequency shadows in the spatial domain, but is limited to a low-frequency approximation of visibility and illumination in the angular domain. In a first pass, level of detail (LOD) selection in the grid is based on the current transfer function setting. This enables rapid online computation and SH projection of the local spherical distribution of visibility information. Using a piecewise integration of the SH coefficients over the local regions, the global visibility within the volume is then computed. By representing the light sources using their SH projections, the integral over lighting, visibility, and isotropic phase functions can be efficiently computed during rendering. The utility of our method is demonstrated in several examples showing the generality and interactive performance of the approach.