OpenCell Technologies (United States)

Conventional flotation circuits struggle to recover valuable ultra-fine coal particles (less than 45μm), leading to significant losses. Conventional technologies typically discard these ultra-fines, sacrificing valuable resources to tailings. Eriez's StackCell® and Flotation Column technologies have demonstrated superior efficiency in the area of ultra-fine coal recovery compared to conventional methods, thanks to their application of wash water over deep froths. When deployed as part of Somerset International's patented Sub325® Fine Coal Recovery System, which captures a very high proportion of ultra-fines to product, total recovery and yield is maximised, thereby also reducing tailings waste. The fine coal recovery system flowsheet offers significant advantages by creating revenue from a waste stream and reducing tailings volumes reporting to tailings storage facilities.

Abstract Whilst the use of single-cell RNA sequencing (scRNA-seq) to understand target biology is well established, its predictive role in increasing the clinical success of therapeutic targets remains underexplored. Inspired by previous work on an association between genetic evidence and clinical success, we used retrospective analysis of known drug target genes to identify potential predictors of target clinical success from scRNA-seq data. We investigated whether successful drug targets are associated with cell type specific expression in a disease-relevant tissue (cell type specificity), and with cell type specific over-expression in disease patients compared to healthy controls (disease cell specificity). Analysing scRNA-seq data across diseases and tissues, we found that both cell type and disease cell specificity are features enriched in targets entering clinical development, and that cell type specificity in the disease-relevant tissue is robustly predictive of target progression from Phase I to II. While scRNA-seq analysis identifies a larger and complementary target space to that of direct genetic evidence, its association with specificity and drug approval appears less clear. We discuss how further expansion and harmonization of single-cell datasets, more sophisticated integration of this data in target discovery, and improved methods for tracking clinical trial outcomes could enhance our ability to leverage scRNA-seq insights in drug development in future.

Extracellular vesicles (EVs) released by a variety of cell types have been shown to act as a natural delivery system for bioactive molecules such as RNAs and proteins. EV therapy holds great promise as a safe and cell‐free therapy for many immunological and degenerative diseases. However, translation to clinical application is limited by several factors, including insufficient large‐scale manufacturing technologies and low yield. We have developed a novel drug delivery platform technology, BioDrone™, based on cell‐derived vesicles (CDVs) produced from diverse cell sources by using a proprietary extrusion process. This extrusion technology generates nanosized vesicles in far greater numbers than naturally obtained EVs. We demonstrate that the CDVs are surrounded by a lipid bilayer membrane with a correct membrane topology. Physical, biochemical and functional characterisation results demonstrate the potential of CDVs to act as effective therapeutics. Umbilical cord mesenchymal stem cell (UCMSC)‐derived CDVs exhibit a biological activity that is similar to UCMSCs or UCMSC‐derived EVs. Lastly, we present the establishment of a GMP‐compliant process to allow the production of a large number of UCMSC‐CDVs in a reproducible manner. GMP‐compliant manufacturing of CDVs will facilitate the preclinical and clinical evaluation of these emerging therapeutics in anti‐inflammatory or regenerative medicine. This study also represents a crucial step in the development of this novel drug delivery platform based on CDVs.

Delivery of large and structurally complex target molecules into cells is vital to the emerging areas of cellular modification and molecular therapy. Inadequacy of prevailing in vivo (viral) and in vitro (liposomal) gene transfer methods for delivery of proteins and a growing diversity of synthetic nanomaterials has encouraged development of alternative physical approaches. Efficacy of injury/diffusion-based delivery via shear mechanoporation is largely insensitive to cell type and target molecule; however, enhanced flexibility is typically accompanied by reduced gene transfer effectiveness. We detail a method to improve transfection efficiency through coordinated mechanical disruption of the cell membrane and electrophoretic insertion of DNA to the cell interior. An array of micromachined nozzles focuses ultrasonic pressure waves, creating a high-shear environment that promotes transient pore formation in membranes of transmitted cells. Acoustic Shear Poration (ASP) allows passive cytoplasmic delivery of small to large nongene macromolecules into established and primary cells at greater than 75% efficiency. Addition of an electrophoretic action enables active transport of target DNA molecules to substantially augment transfection efficiency of passive mechanoporation/diffusive delivery without affecting viability. This two-stage poration/insertion method preserves the compelling flexibility of shear-based delivery, yet substantially enhances capabilities for active transport and transfection of plasmid DNA.

Energy storage is a critical component of any initiative to make electric power and mobility more sustainable. As more solar and wind power generation are added to the electric grid, a mismatch between the periods of peak generation and peak demand necessitate some way to store energy and buffer transient fluctuations in the grid. Similarly, to transition from petroleum-based energy for transportation requires renewable technologies for storing energy with high energy density. This chapter addresses energy storage for smart grid systems, with a particular focus on the design aspects of electrical energy storage in lithium ion batteries.

Polyurethane (PU) closed cell foam samples with different densities were tested under loading and unloading compression tests at different temperatures and strain rates. Quasi-static compression tests were performed using the Lloyd LR5K Plus instrument at strain rates ranges from 0.033–0.267 s−1. Tests were conducted in a pre´cised enclosure to control the dependency of PU foam cells on temperature and humidity. In order to have an accurate comparison in compression and hysteresis curves for all tests; all PU foam samples were selected intentionally from the same foam block but with different location densities. Furthermore, all foam samples were tested in the direction of foam rise (thickness). First, PU foam samples were compressed with a circular platen up to 70% strain at different strain rates and different temperatures. Then, the platen was raised completely from the foam samples. During the experiment; stress-strain responses were measured and plotted for loading and unloading curves to determine stored energy, dissipation energy and peak stresses were calculated at 70% strain. Results have shown that PU foam sample responses under compression testing gets softer at higher temperatures when conducted at a constant strain rates. At constant temperatures, PU foam samples get harder at higher slip rates. Finally, both stored and dissipation energies were found to be dependent heavily on foam density, ambient temperature and strain rate.

The use of phase change materials (PCMs) in thermal storage is not a new concept, but engineers are continually finding new ways to utilize them in a wide range of applications. A PCM takes advantage of high latent heat in the phase change process to store large amounts of heat while undergoing only a small change in temperature. This property makes PCMs suitable for thermal storage purposes in a wide range of engineering applications. Due to the nature of these applications, it is vital to have a precise knowledge of the thermal characteristics of any PCM. Unfortunately, due to the low thermal conductivities and high latent heats found in PCMs, current measuring tools such as differential scanning calorimetry, provide inconsistent results. This paper conjectures that these errors come from the effects of low thermal diffusivity samples as well as improper data analysis methods.

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