Excipient Effects on Humanized Monoclonal Antibody Interactions with Silicone Oil Emulsion

Silicone oil is a lubricant used for plunger depression in prefilled glass syringes. Many therapeutic protein products are stored in prefilled syringes and may be exposed to the silicone oil-water interface for up to 18-24 months. At the present, our understanding of how proteins interact with this interface remains poorly understood. In this work, the interaction of three humanized monoclonal antibodies (humAbs) with silicone oil emulsion was assessed in presence of sodium chloride, sucrose, Tween® 20, Tween® 80, and poloxamer 188. It was found that the amount of humAb adsorbed was antibody- and excipient-dependent. Once adsorbed, the tryptophan exposure to solvent resembled that of unfolded protein and was independent of the identity of different excipients present in the formulation buffer. Protein aggregation was not detected in solution. But, colloidal destabilization of silicone oil emulsion resulting from protein adsorption lowered the activation energy barrier to flocculation thereby enabling heterogeneous aggregates comprised of protein-coated silicone oil microdroplets to form. The size of these flocs was dependent on the solution ionic strength. Flocculation occurred in the presence of all excipients examined except in the presence of surfactant. In formulations containing surfactant, there was competition between humAb and surfactant molecules for adsorption sites at the silicone oil-water interface. The results suggest that the kinetics of humAb displacement from the silicone oil interface was surfactant-dependent. Whether the mechanism of this replacement involved the formation of protein-surfactant complex remains uncertain

Performance Models for Split-execution Computing Systems

Split-execution computing leverages the capabilities of multiple computational models to solve problems, but splitting program execution across different computational models incurs costs associated with the translation between domains. We analyze the performance of a split-execution computing system developed from conventional and quantum processing units (QPUs) by using behavioral models that track resource usage. We focus on asymmetric processing models built using conventional CPUs and a family of special-purpose QPUs that employ quantum computing principles. Our performance models account for the translation of a classical optimization problem into the physical representation required by the quantum processor while also accounting for hardware limitations and conventional processor speed and memory. We conclude that the bottleneck in this split-execution computing system lies at the quantum-classical interface and that the primary time cost is independent of quantum processor behavior.Comment: Presented at 18th Workshop on Advances in Parallel and Distributed Computational Models [APDCM2016] on 23 May 2016; 10 page

A link between evolution and society fostering the UN sustainable development goals

Given the multitude of challenges Earth is facing, sustainability science is of key importance to our continued existence. Evolution is the fundamental biological process underlying the origin of all biodiversity. This phylogenetic diversity fosters the resilience of ecosystems to environmental change, and provides numerous resources to society, and options for the future. Genetic diversity within species is also key to the ability of populations to evolve and adapt to environmental change. Yet, the value of evolutionary processes and the consequences of their impairment have not generally been considered in sustainability research. We argue that biological evolution is important for sustainability and that the concepts, theory, data, and methodological approaches used in evolutionary biology can, in crucial ways, contribute to achieving the UN Sustainable Development Goals (SDGs). We discuss how evolutionary principles are relevant to understanding, maintaining, and improving Nature Contributions to People (NCP) and how they contribute to the SDGs. We highlight specific applications of evolution, evolutionary theory, and evolutionary biology's diverse toolbox, grouped into four major routes through which evolution and evolutionary insights can impact sustainability. We argue that information on both within-species evolutionary potential and among-species phylogenetic diversity is necessary to predict population, community, and ecosystem responses to global change and to make informed decisions on sustainable production, health, and well-being. We provide examples of how evolutionary insights and the tools developed by evolutionary biology can not only inspire and enhance progress on the trajectory to sustainability, but also highlight some obstacles that hitherto seem to have impeded an efficient uptake of evolutionary insights in sustainability research and actions to sustain SDGs. We call for enhanced collaboration between sustainability science and evolutionary biology to understand how integrating these disciplines can help achieve the sustainable future envisioned by the UN SDGs

X-ray Spectroscopic Study of the Electronic Structure of a Trigonal High-Spin Fe(IV)═O Complex Modeling Non-Heme Enzyme Intermediates and Their Reactivity

Fe K-edge X-ray absorption spectroscopy (XAS) has long been used for the study of high-valent iron intermediates in biological and artificial catalysts. 4p-mixing into the 3d orbitals complicates the pre-edge analysis but when correctly understood via 1s2p resonant inelastic X-ray scattering and Fe L-edge XAS, it enables deeper insight into the geometric structure and correlates with the electronic structure and reactivity. This study shows that in addition to the 4p-mixing into the 3dz2 orbital due to the short iron-oxo bond, the loss of inversion in the equatorial plane leads to 4p mixing into the 3dx2-y2,xy, providing structural insight and allowing the distinction of 6- vs 5-coordinate active sites as shown through application to the Fe(IV)═O intermediate of taurine dioxygenase. Combined with O K-edge XAS, this study gives an unprecedented experimental insight into the electronic structure of Fe(IV)═O active sites and their selectivity for reactivity enabled by the π-pathway involving the 3dxz/yz orbitals. Finally, the large effect of spin polarization is experimentally assigned in the pre-edge (i.e., the α/β splitting) and found to be better modeled by multiplet simulations rather than by commonly used time-dependent density functional theory

The Vehicle, Spring 1995

Table of Contents Poetry The SwimmersJennifer Moropage 2 Everlasting ArmsSue Songerpage 2 Talking to an AddictBridgett Jensenpage 3 SecretsTiffany Abbottpage 5 CryingMatthew Berrypage 6 winter fieldsKeith Spearpage 7 untitledKemp Nishan Munizpage 7 Rainy Night in ParisDiana Matijaspage 8 nap timeKelly A. Pricepage 10 Angel of the EarthHeather Anne Winterspage 10 Color DreamsMatthew J. Nelsonpage 12 Dandelion PaintSandy Beauchamppage 13 Merry Go Round MarathonElizabeth Bromleypage 14 The ArmadilloKeith Spearpage 15 The Shoe SagaJennifer Moropage 16 Coffee Cup Confessional BoothSue Songerpage 18 What Gravity, A Rock And A Rabbit Have To Do With My Love LifeMartin Paul Brittpage 19 Good Bye, Good KnightRich Birdpage 20 Photography Railroad Station IKelly A. Pricepage 22 1000 VinesKelly A. Pricepage 23 Self PortraitKelly A. Pricepage 24 Prose Queen of Dead AirBryan Levekpage 26 Closer to the noiseMichell Heidelpage 29 Somewhere in BetweenKimberly Hunterpage 32 Miss SteakBryan Levekpage 37 Chasing the ChasteTerry Bassettpage 43 Biographies Authors, editorspage 48https://thekeep.eiu.edu/vehicle/1065/thumbnail.jp

Mechanism of selective benzene hydroxylation catalyzed by iron-containing zeolites

A direct, catalytic conversion of benzene to phenol would have wide-reaching economic impacts. Fe zeolites exhibit a remarkable combination of high activity and selectivity in this conversion, leading to their past implementation at the pilot plant level. There were, however, issues related to catalyst deactivation for this process. Mechanistic insight could resolve these issues, and also provide a blueprint for achieving high performance in selective oxidation catalysis. Recently, we demonstrated that the active site of selective hydrocarbon oxidation in Fe zeolites, named α-O, is an unusually reactive Fe(IV)=O species. Here, we apply advanced spectroscopic techniques to determine that the reaction of this Fe(IV)=O intermediate with benzene in fact regenerates the reduced Fe(II) active site, enabling catalytic turnover. At the same time, a small fraction of Fe(III)-phenolate poisoned active sites form, defining a mechanism for catalyst deactivation. Density-functional theory calculations provide further insight into the experimentally defined mechanism. The extreme reactivity of α-O significantly tunes down (eliminates) the rate-limiting barrier for aromatic hydroxylation, leading to a diffusion-limited reaction coordinate. This favors hydroxylation of the rapidly diffusing benzene substrate over the slowly diffusing (but more reactive) oxygenated product, thereby enhancing selectivity. This defines a mechanism to simultaneously attain high activity (conversion) and selectivity, enabling the efficient oxidative upgrading of inert hydrocarbon substrates