Polysorbate identity and quantity dictate the extensional flow properties of protein-excipient solutions

While protein medications are promising for treatment of cancer and autoimmune diseases, challenges persist in terms of development and injection stability of high-concentration formulations. Here, the extensional flow properties of protein-excipient solutions are examined via dripping-onto-substrate extensional rheology, using a model ovalbumin (OVA) protein and biocompatible excipients polysorbate 20 (PS20) and 80 (PS80). Despite similar PS structures, differences in extensional flow are observed based on PS identity in two regimes: at moderate total concentrations where surface tension differences drive changes in extensional flow behavior, and at small PS:OVA ratios, which impact the onset of weakly elastic flow behavior. Undesirable elasticity is observed in ultra-concentrated formulations, independent of PS identity; higher PS contents are required to observe these effects than in analogous polymeric excipient solutions. These studies reveal novel extensional flow behaviors in protein-excipient solutions, and provide a straightforward methodology for assessing the extensional flow stability of new protein-excipient formulations.     

Human DDX17 Unwinds Rift Valley Fever Virus Non-Coding RNAs

Rift Valley fever virus (RVFV) is a mosquito-transmitted virus from the Bunyaviridae family that causes high rates of mortality and morbidity in humans and ruminant animals. Previous studies indicated that DEAD-box helicase 17 (DDX17) restricts RVFV replication by recognizing two primary non-coding RNAs in the S-segment of the genome: the intergenic region (IGR) and 5′ non-coding region (NCR). However, we lack molecular insights into the direct binding of DDX17 with RVFV non-coding RNAs and information on the unwinding of both non-coding RNAs by DDX17. Therefore, we performed an extensive biophysical analysis of the DDX17 helicase domain (DDX17_135–555) and RVFV non-coding RNAs, IGR and 5’ NCR. The homogeneity studies using analytical ultracentrifugation indicated that DDX17_135–555, IGR, and 5’ NCR are pure. Next, we performed small-angle X-ray scattering (SAXS) experiments, which suggested that DDX17 and both RNAs are homogenous as well. SAXS analysis also demonstrated that DDX17 is globular to an extent, whereas the RNAs adopt an extended conformation in solution. Subsequently, microscale thermophoresis (MST) experiments were performed to investigate the direct binding of DDX17 to the non-coding RNAs. The MST experiments demonstrated that DDX17 binds with the IGR and 5’ NCR with a dissociation constant of 5.77 ± 0.15 µM and 9.85 ± 0.11 µM, respectively. As DDX17_135–555 is an RNA helicase, we next determined if it could unwind IGR and NCR. We developed a helicase assay using MST and fluorescently-labeled oligos, which suggested DDX17_135–555 can unwind both RNAs. Overall, our study provides direct evidence of DDX17_135–555 interacting with and unwinding RVFV non-coding regions.     

α-Methylene-β-Lactone Scaffold for Developing Chemical Probes at the Two Ends of the Selectivity Spectrum

The utilities of an α-methylene-β-lactone (MeLac) moiety as a warhead composed of multiple electrophilic sites are reported. We demonstrate that a MeLac-alkyne not only reacts with diverse proteins as a broadly reactive measurement probe, but also recruits reduced endogenous glutathione (GSH) to assemble a selective chemical probe of GSH-β-lactone (GSH-Lac)-alkyne in live cells. Tandem mass spectrometry reveals that MeLac reacts with nucleophilic cysteine, serine, lysine, threonine, and tyrosine residues, through either Michael or acyl addition. A peptide-centric proteomics platform demonstrates that the proteomic selectivity profiles of orlistat and parthenolide, which have distinct reactivities, are measurable by MeLac-alkyne as a high-coverage probe. The GSH-Lac-alkyne selectively probes the glutathione S-transferase P responsible for multidrug resistance. The assembly of the GSH-Lac probe exemplifies a modular and scalable route to develop selective probes with different recognizing moieties.     

Bibliometric and text mining approaches to evaluate landfill design standards

Scientometrics - In 2014, Canadians generated 961 kg of waste per capita. Landfilling is a logical choice for many Canadian communities because of land availability. This paper examines...     

Finite element modeling of resistive surface layers by micro-contact impedance spectroscopy

Micro-contact impedance spectroscopy (MCIS) is potentially a powerful tool for the exploration of resistive surface layers on top of a conductive bulk or substrate material. MCIS employs micro-contacts in contrast to conventional IS where macroscopic electrodes are used. To extract the conductivity of each region accurately using MCIS requires the data to be corrected for geometry. Using finite element modeling on a system where the resistivity of the surface layer is at least a factor of ten greater than the bulk/substrate, we show how current flows through the two layers using two typical micro-contact configurations. This allows us to establish if and what is the most accurate and reliable method for extracting conductivity values for both regions. For a top circular micro-contact and a full bottom counter electrode, the surface layer conductivity (σ_s) can be accurately extracted using a spreading resistance equation if the thickness is ~10 times the micro-contact radius; however, bulk conductivity (σ_b) values can not be accurately determined. If the contact radius is 10 times the thickness of the resistive surface, a geometrical factor using the micro-contact area provides accurate σ_s values. In this case, a spreading resistance equation also provides a good approximation for σ_b. For two top circular micro-contacts on thin resistive surface layers, the MCIS response from the surface layer is independent of the contact separation; however, the bulk response is dependent on the contact separation and at small separations contact interference occurs. As a consequence, there is not a single ideal experimental setup that works; to obtain accurate σ_s and σ_b values the micro-contact radius, surface layer thickness and the contact separation must all be considered together. Here we provide scenarios where accurate σ_s and σ_b values can be obtained that highlight the importance of experimental design and where appropriate equations can be employed for thin and thick resistive surface layers.     

Deployment of a cloud pipeline for real-time visual inspection using fast streaming high-definition images

We investigate the challenges of building an end-to-end cloud pipeline for real-time intelligent visual inspection system for use in automotive manufacturing. Current methods of visual detection in automotive assembly are highly labor intensive, and thus prone to errors. An automated process is sought that can operate within the real-time constraints of the assembly line and can reduce errors. Components of the cloud pipeline include capture of a large set of high-definition images from a camera setup at the assembly location, transfer and storage of the images as needed, execution of object detection, and notification to a human operator when a fault is detected. The end-to-end execution must complete within a fixed time frame before the next car arrives in the assembly line. In this article, we report the design, development, and experimental evaluation of the tradeoffs of performance, accuracy, and scalability for a cloud system.