Characterization of Apo-Form Selective Inhibition of Indoleamine 2,3-Dioxygenase**

Indoleamine-2,3-dioxygenase 1 (IDO1) is a heme-containing enzyme that catalyzes the rate-limiting step in the kynurenine pathway of tryptophan (TRP) metabolism. As it is an inflammation-induced immunoregulatory enzyme, pharmacological inhibition of IDO1 activity is currently being pursued as a potential therapeutic tool for the treatment of cancer and other disease states. As such, a detailed understanding of the mechanism of action of IDO1 inhibitors with various mechanisms of inhibition is of great interest. Comparison of an apo-form-binding IDO1 inhibitor (GSK5628) to the heme-coordinating compound, epacadostat (Incyte), allows us to explore the details of the apo-binding inhibition of IDO1. Herein, we demonstrate that GSK5628 inhibits IDO1 by competing with heme for binding to a heme-free conformation of the enzyme (apo-IDO1), whereas epacadostat coordinates its binding with the iron atom of the IDO1 heme cofactor. Comparison of these two compounds in cellular systems reveals a long-lasting inhibitory effect of GSK5628, previously undescribed for other known IDO1 inhibitors. Detailed characterization of this apo-binding mechanism for IDO1 inhibition might help design superior inhibitors or could confer a unique competitive advantage over other IDO1 inhibitors vis-à-vis specificity and pharmacokinetic parameters.     

Managing nutrient losses from rural point sources and urban environments

Nutrient loss from rural point sources and urban environments need to be minimised as part of strategies to overcome declining water quality on the Swan Coastal Plain and in the Peel-Harvey estuary in Western Australia. This paper discusses the management of nutrient losses from domestic effluent, urban stormwater runoff, domestic gardens and public open space, intensive animal industries and intensive irrigated agriculture. Measures to minimise nutrient losses from these sources are outlined, using cooperative, technological and regulatory approaches.     

Computational auditory models in predicting noise reduction performance for wideband telephony applications

The performance of several noise reduction algorithms intended for wideband telephony was evaluated both subjectively and objectively. The chosen algorithms were based on statistical modeling, spectral subtraction, Wiener filtering, or subspace modelling principles. A customized wideband noise reduction database containing speech samples corrupted by three types of background noises at three SNR levels, along with their enhanced versions was created. The overall quality of the speech samples in the database was subsequently rated by a group of listeners with normal hearing capabilities. Comprehensive statistical analyses were performed to assess the reliability of the subjective data, and to assess the performance of noise reduction algorithms across varied noisy conditions. The subjective quality ratings were then used to investigate the performance of several auditory model-based objective quality metrics. Key results from these investigations include: (a) there was a high degree of inter- and intra-subject reliability in the subjective ratings, (b) noise reduction algorithms enhance speech quality for only a subset of the noise conditions, and (c) auditory model-based metrics perform similarly in predicting speech quality ratings, when speech quality scores pertaining to a particular noise condition were averaged.     

Temperature and wavelength dependent transmission of optically transparent glass fibre poly (methyl methacrylate) composites

The temperature and wavelength dependent transmission was measured for glass fibre reinforced transparent composites prepared by sheet lamination and pressure curing processes. A mathematical model using fibre volume content, glass fibre diameter, refractive index of the fibre and matrix, non-wet fibre content and thickness of the composites was used to predict the transmission of the composite as a function of temperature and wavelength. The transmission calculated from the model for 20–70 °C and between 500 to 800 nm agreed well with the measured optical transmission for a thin composite containing < 10 vol % of 17 m glass fibres. A small amount of non-wet fibre (e.g. 2.0% of total fibre) was predicted to reduce the maximum transmission by up to 17% for a composite containing 7.2 vol % fibres and a thickness of 0.5 mm.     

3D Knitting for Pneumatic Soft Robotics

Soft robots adapt passively to complex environments due to their inherent compliance, allowing them to interact safely with fragile or irregular objects and traverse uneven terrain. The vast tunability and ubiquity of textiles has enabled new soft robotic capabilities, especially in the field of wearable robots, but existing textile processing techniques (e.g., cut-and-sew, thermal bonding) are limited in terms of rapid, additive, accessible, and waste-free manufacturing. While 3D knitting has the potential to address these limitations, an incomplete understanding of the impact of structure and material on knit-scale mechanical properties and macro-scale device performance has precluded the widespread adoption of knitted robots. In this work, the roles of knit structure and yarn material properties on textile mechanics spanning three regimes–unfolding, geometric rearrangement, and yarn stretching–are elucidated and shown to be tailorable across unique knit architectures and yarn materials. Based on this understanding, 3D knit soft actuators for extension, contraction, and bending are constructed. Combining these actuation primitives enables the monolithic fabrication of entire soft grippers and robots in a single-step additive manufacturing procedure suitable for a variety of applications. This approach represents a first step in seamlessly “printing” conformal, low-cost, customizable textile-based soft robots on-demand.     

Optimization of anisotropic composite panels with T-shaped stiffeners including transverse shear effects and out-of-plane loading

A two-step method to optimize anisotropic composite panels with T-shaped stiffeners, including a new formulation of the transverse shear properties and an approximation of the ply contiguity (blocking) constraints as functions of the lamination parameters is provided. At the first step, a representative element of the stiffened panel (superstiffener) is optimized using mathematical programming and lamination parameters subjected to combined loading (in-plane and out-of-plane) under strength (laminate or ply failure), buckling and practical design constraints. Ply blocking constraints are imposed at this step to improve convergence towards practical laminates. At the second step, the actual superstiffener’s laminates are obtained by using a genetic algorithm. Results, for the case considered, show that the inclusion of transverse shear effects has an associated 2.5% mass penalty and that neglecting its effects might invoke earlier buckling failure. In addition, the influence of designing for failure strength at laminate or ply level is assessed.     

LINKING RIVER MANAGEMENT TO SPECIES CONSERVATION USING DYNAMIC LANDSCAPE‐SCALE MODELS

Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape‐scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km² catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub‐basins composing the catchment. We use geographic data to characterize stream segments with respect to channel size, confinement, position and connectedness within the stream network. Simulated streamflow dynamics are then applied to model fish metapopulation dynamics in stream segments, using hypothesized effects of streamflow magnitude and variability on population processes, conditioned by channel characteristics. The resulting time series simulate spatially explicit, annual changes in species occurrences or assemblage metrics (e.g. species richness) across the catchment as outcomes of management scenarios. Sensitivity analyses using alternative, plausible links between streamflow components and metapopulation processes, or allowing for alternative modes of fish dispersal, demonstrate large effects of ecological uncertainty on model outcomes and highlight needed research and monitoring. Nonetheless, with uncertainties explicitly acknowledged, dynamic, landscape‐scale simulations may prove useful for quantitatively comparing river management alternatives with respect to species conservation. Published 2012. This article is a U.S. Government work and is in the public domain in the USA.     

A Stress and Coping Model of Medication Adherence and Viral Load in HIV-Positive Men and Women on Highly Active Antiretroviral Therapy (HAART).

The authors tested a structural model that incorporated age, time since diagnosis, social support, coping, and negative mood as predictors of medication adherence and HIV viral load on 188 men and 134 women on highly active antiretroviral therapy (HAART). The authors used psychosocial latent factors formed from baseline measures to predict latent factors of adherence, as assessed by electronic monitoring and self-report, and viral load defined by indicators assessed over a 15-month period. Results from the model indicate that greater negative mood and lower social support are related to greater use of avoidance-oriented coping strategies. Use of these coping strategies by patients on HAART is related to poorer medication adherence and, subsequently, higher viral load. This model advances researchers' understanding of the contribution of psychosocial variables in predicting treatment adherence and disease progression in HIV-positive men and women. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Cover Picture: Functionalized Gold Nanoparticles Mimic Catalytic Activity of a Polysiloxane‐Synthesizing Enzyme (Adv. Mater. 10/2005)

A system that acts as a biomimetic of the silica‐synthesizing enzyme found in a marine sponge is reported by Morse and co‐workers on p. 1234. Gold nanoparticles (GNPs) are functionalized with the same organic moieties that are found in the enzyme's catalytic site. Interaction between the nucleophilic (OH‐terminated) and hydrogen‐bonding (imidazole‐terminated) GNPs, as shown on the cover, is required for the hydrolysis of a silicon alkoxide precursor and subsequent polycondensation to form silica at a low temperature and near‐neutral pH. Replacement of either of the required functional groups by a non‐reactive methyl group abolishes catalysis in this synthetic system, as it does in the biological enzyme. Cover art provided by Peter Allen.     

An analytical framework for local feedforward networks

Interference in neural networks occurs when learning in one area of the input space causes unlearning in another area. Networks that are less susceptible to interference are referred to as spatially local networks. To obtain a better understanding of these properties, a theoretical framework, consisting of a measure of interference and a measure of network localization, is developed. These measures incorporate not only the network weights and architecture but also the learning algorithm. Using this framework to analyze sigmoidal, multilayer perceptron (MLP) networks that employ the backpropagation learning algorithm on the quadratic cost function, we address a familiar misconception that single-hidden-layer sigmoidal networks are inherently nonlocal by demonstrating that given a sufficiently large number of adjustable weights, single-hidden-layer sigmoidal MLPs exist that are arbitrarily local and retain the ability to approximate any continuous function on a compact domain.