Synthesis and evaluation of an intercalator-polyamide hairpin designed to target the inverted CCAAT box 2 in the topoisomerase IIalpha promoter

The synthesis and DNA-binding properties of a novel naphthalimide-polyamide hairpin (3) designed to target the inverted CCAAT box 2 (ICB2) site on the topoisomerase IIalpha (topoIIalpha) promoter are described. The polyamide component of 3 was derived from the minor-groove binder, 2, and tailored to bind to the 5'-TTGGT sequence found in and flanking ICB2. The propensity of mitonafide 4 to intercalate between G-C base pairs was exploited by the incorporation of a naphthalimide moiety at the N terminus of 2. Hybrid 3 targeted 5'-CGATTGGT and covered eight contiguous base pairs, which included the underlined ICB2 site. DNase I footprinting analysis with the topoIIalpha promoter sequence demonstrated that 3 bound selectively to the ICB2 and ICB3 sites. Thermal-denaturation studies confirmed these results, and the highest degree of stabilization was found for ICB2 and -3 in preference to ICB1 (4.1, 4.6, and 0.6 degrees C, respectively). CD studies confirmed minor-groove binding and suggested a 1:1 binding stoichiometry. Emission-titration experiments established intercalative binding. Surface plasmon resonance results showed strong binding to ICB2 (2.5x10(7) M(-1)) with no observable binding to ICB1. Furthermore, the binding constant of 3 to ICB2 was larger than that of the parent polyamide 2. The increased binding affinity was primarily due to a reduction in the dissociation-rate constant of the polyamide-DNA complex, which can be attributed to the N-terminal naphthalimide moiety. In addition, the binding site of 3 was larger than that of 2, which innately improved sequence selectivity. We conclude that the polyamide-naphthalimide 3 selectively binds to the ICB2 site by simultaneous intercalation and minor-groove binding, and warrants further investigation as a model compound for the regulation of topoIIalpha gene expression.     

Exploring the influence of granular iron additives on 1,1,1-trichloroethane reduction

Bimetallic reductants are frequently more reactive toward organohalides than unamended iron and can also alter product distributions, yet a molecular-level explanation for these phenomena remains elusive. In this study, surface characterization of six iron-based bimetallic reductants (Au/Fe, Co/Fe, Cu/Fe, Ni/Fe, Pd/Fe, and Pt/Fe) revealed that displacement plating produced a non-uniform overlayer of metallic additive on iron. Batch studies demonstrated that not all additives enhanced rates of 1,1,1-trichloroethane (1,1,1-TCA) reduction nor was there any clear periodic trend in the observed reactivity (Ni/Fe approximately Pd/Fe > Cu/Fe > Co/ Fe > Au/Fe approximately Fe > Pt/Fe). Pseudo-first-order rate constants for 1,1,1-TCA reduction (kobs values) did, however, correlate closely with the solubility of atomic hydrogen within each additive. This suggests absorbed atomic hydrogen, rather than galvanic corrosion, is responsible for the enhanced reactivity of bimetallic reductants. In addition, all additives shifted product distributions to favor the combined yield of ethylene plus ethane over 1,1-dichloroethane. In rate-enhancing bimetallic systems, branching ratios between 1,1-dichloroethane and the combination of ethylene and ethane were uniquely dependent on kobs values, indicating an intimate link between rate-determining and product-determining steps. We propose that our results are best explained by an X-philic pathway involving atomic hydrogen with a hydride-like character.     

Low temperature uniform plastic deformation of metallic glasses during elastic iteration

Molecular dynamics simulations and dynamic mechanical analysis experiments were employed to investigate the mechanical behavior of metallic glasses subjected to iteration deformation in a nominally elastic region. It was found that cyclic deformation leads to the formation of irreversible shear transformation zones (STZs) and a permanent uniform strain. The initiation of STZs is directly correlated with the atomic heterogeneity of the metallic glass and the accumulated permanent strain has a linear relation with the number of STZs. This study reveals a new deformation mode and offers insights into the atomic mechanisms of STZ formation and low temperature uniform plastic deformation of metallic glasses.     

Addressing data center efficiency: lessons learned from process evaluations of utility energy efficiency programs

This paper summarizes the unique challenges related to addressing energy efficiency in the data center industry and lessons learned from original research and two process evaluations of energy efficiency programs with components that specifically target data centers. The lessons learned include: creating program opportunities specifically focused on data centers; clearly identifying target data centers able to implement energy efficiency programs; understanding decision making in these facilities; and effectively communicating the program opportunities to the target market. The growing energy use of data centers has drawn international attention from policy makers, regulators, industry consortiums, and electric utilities. Any program effective at improving the energy performance of data centers must include specific strategies and processes aimed at confronting a number of challenges specific to this industry, including: the concentrated and rapidly growing energy use of these facilities; the rapid pace of innovation; the extremely high reliability requirements; and the significant split incentives due to the typical data center management structure. The process evaluations covered in this paper are the Pacific Gas and Electric (PG&E) High-Tech program and the Silicon Valley Power (SVP) Public Benefits Program. While the PG&E evaluation was a more complete process evaluation, the SVP evaluation focused specifically on participation from co-location facilities. These process evaluations together included interviews with program participants, nonparticipants and utility staff and also included outreach to a large variety of industry stakeholders. In addition, the PG&E evaluation included detailed process-mapping used to identify the necessity and importance of all program processes. The insights gathered from these evaluations are not only applicable to US electrical utilities but can also be applied to any international organization looking to create incentives for energy efficiency or demand reduction in this industry.     

The beginnings of Applied Optics

A commemorative editorial for the 50th anniversary of Applied Optics describes how OSA's second journal was born.     

Application of neural networks to predict the steady state performance of a Run-Around Membrane Energy Exchanger

Modeling the performance characteristics of thermal systems has been a research interest for many decades with moisture transfer systems experiencing a resurgence over the last decade, especially in heating, ventilating, and air conditioning (HVAC) applications. In this study, a neural network (NN) model is developed to predict the heat and moisture transfer performances (i.e., the sensible and latent effectivenesses) of a novel HVAC energy exchanger called the Run-Around Membrane Energy Exchanger (RAMEE) which is able to transfer both heat and moisture between exhaust and supply air streams. The training data set for the NN model covers a wide range of design and operating parameters and is produced using an experimentally validated finite difference (FD) model. Two separate NNs (one for sensible and one for latent energy transfer) each with five inputs and one output, are selected to represent the RAMEE. The results from NN models are numerically and experimentally validated. The root mean squared error (RMSE) between the FD and NN models are 0.05 °C and 2 × 10^?5 kg_v/kg_a, indicating satisfactory agreement for energy exchange calculations. The paper reports the weights and biases to make the results of this study reproducible. These NN models are very fast and easy to use therefore, they might be used for design and for estimating the annual energy savings in different buildings which use the RAMEE in their HVAC system. Additionally, the NN models can be used with optimization algorithms to maximize energy savings and minimize life-cycle costs for a given system.     

Optimization of the lyophilization process for long-term stability of solid-lipid nanoparticles

Objectives: To optimize a lyophilization protocol for solid-lipid nanoparticles (SLNs) loaded with dexamethasone palmitate (Dex-P) and to compare the long-term stability of lyophilized SLNs and aqueous SLN suspensions at two storage conditions. Materials and Methods: The effect of various parameters of the lyophilization process on SLN redispersibility was evaluated. A three month stability study was conducted to compare changes in the particle size and drug loading of lyophilized SLNs with SLNs stored as aqueous suspensions at either 4°C or 25°C/60% relative humidity (RH). Results and Discussion: Of nine possible lyoprotectants tested, sucrose was shown to be the most efficient at achieving SLN redispersibility. Higher freezing temperatures, slower freezing rates, and longer secondary drying times were also shown to be beneficial. Loading of the SLNs with Dex-P led to slightly larger particle size and polydispersity index increases, but both parameters remained within an acceptable range. Drug loading and particle shape were maintained following lyophilization, and no large aggregates were detected. During the stability study, significant growth and drug loss were observed for aqueous SLN suspensions stored at 25°C/60% RH. In comparison, lyophilized SLNs stored at 4°C exhibited a consistent particle size and showed <20% drug loss. Other storage conditions led to intermediate results. Conclusions: A lyophilization protocol was developed that allowed SLNs to be reconstituted with minimal changes in their physicochemical properties. During a three month period, lyophilized SLNs stored at 4°C exhibited the greatest stability, showing no change in the particle size and a minimal reduction in drug retention.     

Vibration-Induced Attraction of a Particle Towards a Wall in Microgravity—The Mechanism of Attraction Force

The effects of small vibrations on a particle oscillating near a solid wall in a fluid cell, relevant to material processing such as crystal growth in space, have been investigated by three dimensional direct numerical simulations. Simulations have been conducted for a solid spherical particle suspended in a fluid cell filled with a fluid of 1 cSt viscosity, vibrating sinusoidally in a horizontal direction. The simulations revealed the existence of a vibration-induced force attracting the particle towards the nearest cell wall which varied with the cell vibration frequency. The mechanism for this attraction force as well as an example showing the effects of this force on the particle are presented in this paper. The predicted flow patterns around the particle unveiled an accelerated flow in the gap between the particle and the nearest wall as well as a pressure decrease in accordance with Bernoulli’s principle, which would result in the attraction force.     

Nearby boundaries create eddies near microscopic filter feeders

We show through calculations, simulations and experiments that the eddies often observed near sessile filter feeders are frequently due to the presence of nearby boundaries. We model the common filter feeder Vorticella, which is approximately 50 µm across and which feeds by removing bacteria from ocean or pond water that it draws towards itself. We use both an analytical stokeslet model and a Brinkman flow approximation that exploits the narrow-gap geometry to predict the size of the eddy caused by two parallel no-slip boundaries that represent the slides between which experimental observations are often made. We also use three-dimensional finite-element simulations to fully solve for the flow around a model Vorticella and analyse the influence of multiple nearby boundaries. Additionally, we track particles around live feeding Vorticella in order to determine the experimental flow field. Our models are in good agreement both with each other and with experiments. We also provide approximate equations to predict the experimental eddy sizes owing to boundaries both for the case of a filter feeder between two slides and for the case of a filter feeder attached to a perpendicular surface between two slides.     

Art students who cannot draw: Exploring the relations between drawing ability, visual memory, accuracy of copying, and dyslexia.

Some art students, despite being at art school, cannot draw very well, and would like to be able to draw well. It has been suggested that poor drawing may be a particular problem for students with dyslexia (and a high proportion of art school students is dyslexic). In Study 1 we studied 277 art students, using a questionnaire to assess self-perceived drawing ability and a range of background measures, including demography, education, a history of dyslexia, a self-administered spelling test, and personality and educational variables. In Study 2 we gave detailed drawing tests to a sample of 38 of the art students, stratified by self-rated drawing ability and spelling ability, and to 30 control participants. Students perceiving themselves as good at drawing did indeed draw better than self-perceived poor drawers, although the latter were still better than non-art student controls. In neither Study 1 nor Study 2 did skill at drawing relate to dyslexia or spelling ability, and neither did drawing ability relate to any of our wide range of background measures. However Study 2 did show that drawing ability was related both to ability at copying simple angles and proportions (using the “house” task of Cain, 1943), and also to visual memory (as suggested by Jones, 1922), poor drawers being less good at both immediate and delayed recall of the Rey-Osterrieth complex figure. (PsycINFO Database Record (c) 2010 APA, all rights reserved)