Phenoxybenzamine Is Neuroprotective in a Rat Model of Severe Traumatic Brain Injury

Phenoxybenzamine (PBZ) is an FDA approved α-1 adrenergic receptor antagonist that is currently used to treat symptoms of pheochromocytoma. However, it has not been studied as a neuroprotective agent for traumatic brain injury (TBI). While screening neuroprotective candidates, we found that phenoxybenzamine reduced neuronal death in rat hippocampal slice cultures following exposure to oxygen glucose deprivation (OGD). Using this system, we found that phenoxybenzamine reduced neuronal death over a broad dose range (0.1 μM–1 mM) and provided efficacy when delivered up to 16 h post-OGD. We further tested phenoxybenzamine in the rat lateral fluid percussion model of TBI. When administered 8 h after TBI, phenoxybenzamine improved neurological severity scoring and foot fault assessments. At 25 days post injury, phenoxybenzamine treated TBI animals also showed a significant improvement in both learning and memory compared to saline treated controls. We further examined gene expression changes within the cortex following TBI. At 32 h post-TBI phenoxybenzamine treated animals had significantly lower expression of pro-inflammatory signaling proteins CCL2, IL1β, and MyD88, suggesting that phenoxybenzamine may exert a neuroprotective effect by reducing neuroinflammation after TBI. These data suggest that phenonxybenzamine may have application in the treatment of TBI.     

Functional Chromatography Reveals Three Natural Products that Target the Same Protein with Distinct Mechanisms of Action

Access to lead compounds with defined molecular targets continues to be a barrier to the translation of natural product resources. As a solution, we developed a system that uses discrete, recombinant proteins as the vehicles for natural product isolation. Here, we describe the use of this functional chromatographic method to identify natural products that bind to the AAA+ chaperone, p97, a promising cancer target. Application of this method to a panel of fungal and plant extracts identified rheoemodin, 1‐hydroxydehydroherbarin, and phomapyrrolidone A as distinct p97 modulators. Excitingly, each of these molecules displayed a unique mechanism of p97 modulation. This discovery provides strong support for the application of functional chromatography to the discovery of protein modulators that would likely escape traditional high‐throughput or phenotypic screening platforms.     

Discovery of 5′′‐Chloro‐N‐[(5,6‐dimethoxypyridin‐2‐yl)methyl]‐2,2′:5′,3′′‐terpyridine‐3′‐carboxamide (MK‐1064): A Selective Orexin 2 Receptor Antagonist (2‐SORA) for the Treatment of Insomnia

The field of small‐molecule orexin antagonist research has evolved rapidly in the last 15 years from the discovery of the orexin peptides to clinical proof‐of‐concept for the treatment of insomnia. Clinical programs have focused on the development of antagonists that reversibly block the action of endogenous peptides at both the orexin 1 and orexin 2 receptors (OX₁R and OX₂R), termed dual orexin receptor antagonists (DORAs), affording late‐stage development candidates including Merck’s suvorexant (new drug application filed 2012). Full characterization of the pharmacology associated with antagonism of either OX₁R or OX₂R alone has been hampered by the dearth of suitable subtype‐selective, orally bioavailable ligands. Herein, we report the development of a selective orexin 2 antagonist (2‐SORA) series to afford a potent, orally bioavailable 2‐SORA ligand. Several challenging medicinal chemistry issues were identified and overcome during the development of these 2,5‐disubstituted nicotinamides, including reversible CYP inhibition, physiochemical properties, P‐glycoprotein efflux and bioactivation. This article highlights structural modifications the team utilized to drive compound design, as well as in vivo characterization of our 2‐SORA clinical candidate, 5′′‐chloro‐N‐[(5,6‐dimethoxypyridin‐2‐yl)methyl]‐2,2′:5′,3′′‐terpyridine‐3′‐carboxamide (MK‐1064), in mouse, rat, dog, and rhesus sleep models.     

Quantifying spectral changes experienced by plasmonic nanoparticles in a cellular environment to inform biomedical nanoparticle design

Metal nanoparticles (NPs) scatter and absorb light in precise, designable ways, making them agile candidates for a variety of biomedical applications. When NPs are introduced to a physiological environment and interact with cells, their physicochemical properties can change as proteins adsorb on their surface and they agglomerate within intracellular endosomal vesicles. Since the plasmonic properties of metal NPs are dependent on their geometry and local environment, these physicochemical changes may alter the NPs'' plasmonic properties, on which applications such as plasmonic photothermal therapy and photonic gene circuits are based. Here we systematically study and quantify how metal NPs'' optical spectra change upon introduction to a cellular environment in which NPs agglomerate within endosomal vesicles. Using darkfield hyperspectral imaging, we measure changes in the peak wavelength, broadening, and distribution of 100-nm spherical gold NPs'' optical spectra following introduction to human breast adenocarcinoma Sk-Br-3 cells as a function of NP exposure dose and time. On a cellular level, spectra shift up to 78.6 ± 23.5 nm after 24 h of NP exposure. Importantly, spectra broaden with time, achieving a spectral width of 105.9 ± 11.7 nm at 95% of the spectrum''s maximum intensity after 24 h. On an individual intracellular NP cluster (NPC) level, spectra also show significant shifting, broadening, and heterogeneity after 24 h. Cellular transmission electron microscopy (TEM) and electromagnetic simulations of NPCs support the trends in spectral changes we measured. These quantitative data can help guide the design of metal NPs introduced to cellular environments in plasmonic NP-mediated biomedical technologies.     

Delays to Large Construction Projects in Ghana： A Risk Overview

Delay to large scale projects, which is as a result of actions or inactions of some project stakeholders, is becoming a global phenomena and Ghana is no exception. The objective of the research is to identify, rate and rank the most significant risk factors that causes delay on projects and examine the social impact of these delays to recommend modalities to help mitigate these risk factors. The study adopted quantitative methods with the distribution of 144 questionnaires to built environment professionals receiving a response rate of 75.7%. The instrument listed 58 common factors under eight categories that contribute to the causes of delay for respondents to rate. Analysis of data non-parametric test revealed that client, contractor, material and finance category factors significantly resulted in the schedule delay of large infrastructural projects. The survey analysis revealed that micro-factors that result in delays to large construction projects are time constraint, cost overrun, payment problems, dispute and litigation. The research recommended the following modalities to minimize such delays： availability of resources, improved communication and coordination, proper scope definition and feasibilities, utilization of modern technology, appropriate application of technologically based systems and competent project management＇s structures.     

High Speed Imaging of Generation and Collapse of Multielectron Bubbles in Liquid Helium

We present experimental results on the generation and collapse of multielectron bubbles in liquid helium. By applying voltage pulses to a tungsten tip above the surface of the liquid, millimetre sized deformations were formed. Using high speed photography, we have imaged the disintegration of these deformations into bubbles of sizes ranging from ten to few hundred microns. At temperatures less than 2 K, the bubbles split into smaller bubbles and then disappeared in a time scale of few milliseconds. Smaller bubbles were formed at temperatures around 3 K, but were visible for more than hundreds of milliseconds. Although we have not been able to measure their charge directly, some of these bubbles responded to electric fields, implying these were indeed multielectron bubbles. With the existing theoretical picture, it is not possible to understand the strong dependence of the lifetime of multielectron bubbles on temperature.     

Effect of hollow sphere size and size distribution on the quasi-static and high strain rate compressive properties of Al-A380–Al2O3 syntactic foams

Metal matrix syntactic foams are promising materials for energy absorption; however, few studies have examined the effects of hollow sphere dimensions and foam microstructure on the quasi-static and high strain rate properties of the resulting foam. Aluminum alloy A380 syntactic foams containing Al₂O₃ hollow spheres sorted by size and size range were synthesized by a sub-atmospheric pressure infiltration technique. The resulting samples were tested in compression at strain rates ranging from 10^?3 s^?1 using a conventional load frame to 1720 s^?1 using a Split Hopkinson Pressure-bar test apparatus. It is shown that the quasi-static compressive stress–strain curves exhibit distinct deformation events corresponding to initial failure of the foam at the critical resolved shear stress and subsequent failures and densification events until the foam is deformed to full density. The peak strength, plateau strength, and toughness of the foam increases with increasing hollow sphere wall thickness to diameter (t/D) ratio. Since t/D was found to increase with decreasing hollow sphere diameter, the foams produced with smaller spheres showed improved performance. The compressive properties did not show measurable strain rate dependence.     

Creating targeted initial populations for genetic product searches in heterogeneous markets

Genetic searches often use randomly generated initial populations to maximize diversity and enable a thorough sampling of the design space. While many of these initial configurations perform poorly, the trade-off between population diversity and solution quality is typically acceptable for small-scale problems. Navigating complex design spaces, however, often requires computationally intelligent approaches that improve solution quality. This article draws on research advances in market-based product design and heuristic optimization to strategically construct ‘targeted’ initial populations. Targeted initial designs are created using respondent-level part-worths estimated from discrete choice models. These designs are then integrated into a traditional genetic search. Two case study problems of differing complexity are presented to illustrate the benefits of this approach. In both problems, targeted populations lead to computational savings and product configurations with improved market share of preferences. Future research efforts to tailor this approach and extend it towards multiple objectives are also discussed.