Exosomes and Microvesicles: Identification and Targeting By Particle Size and Lipid Chemical Probes

Exosomes and microvesicles are two classes of submicroscopic vesicle released by cells into the extracellular space. Collectively referred to as extracellular vesicles, these membrane containers facilitate important cell–cell communication by carrying a diverse array of signaling molecules, including nucleic acids, proteins, and lipids. Recently, the role of extracellular vesicle signaling in cancer progression has become a topic of significant interest. Methods to detect and target exosomes and microvesicles are needed to realize applications of extracellular vesicles as biomarkers and, perhaps, therapeutic targets. Detection of exosomes and microvesicles is a complex problem as they are both submicroscopic and of heterogeneous cellular origins. In this Minireview, we highlight the basic biology of extracellular vesicles, and address available biochemical and biophysical detection methods. Detectible characteristics described here include lipid and protein composition, and physical properties such as the vesicle membrane shape and diffusion coefficient. In particular, we propose that detection of exosome and microvesicle membrane curvature with lipid chemical probes that sense membrane shape is a distinctly promising method for identifying and targeting these vesicles.     

Comprehensive interpretation of gel electrophoresis data

From temperature analysis of polyacrylamide gel electrophoresis data for rigid-rod DNA analytes, it is proposed that an entropic force term is responsible for the discrepancy between Ogston-Morris-Rodbard-Chrambach model predictions and experimental results. This entropic force originates from reduction of the orientational freedom of anisotropic analytes in small pores of polyacrylamide gels. Time-dependent fluorescence anisotropy decay measurements confirm that, even in the absence of an external field, orientation of anisotropic analytes is restricted in polyacrylamide gels. A new comprehensive model is proposed that takes this effect into consideration. Predictions based on this model are found to compare favorably with experimental data for linear and three-arm asymmetrically branched rigid-rod DNA analytes covering a broad range of molecular aspect ratios and sizes. A new length scale is also proposed for describing the effect of analyte topology on electrophoretic mobility. This length scale reduces to the analyte radius of gyration in the limiting cases of spherically symmetric and linear rigid-rod species. Based on these results, a general approach is proposed for interpreting gel electrophoresis data of charged analytes possessing simple and complex topologies.     

Near and far field contamination modeling in a large scale enclosure: Fire Dynamics Simulator comparisons with measured observations

The occurrence of a fire, no matter how small, often exposes objects to significant levels of contamination from the products of combustion. The production and dispersal of these contaminants has been an issue of relevance in the field of fire science for many years, though little work has been done to examine the contamination levels accumulated within an enclosure some time after an incident. This phenomenon is of great importance when considering the consequences associated with even low level contamination of sensitive materials, such as food, pharmaceuticals, clothing, electrical equipment, etc. Not only does such exposure present a localized hazard, but also the shipment of contaminated goods places distant recipients at risk. It is the intent of this paper to use a well-founded computational fluid dynamic (CFD) program, the Fire Dynamics Simulator (FDS), a large eddy simulation (LES) code developed by National Institute of Standards and Technology (NIST), to model smoke dispersion in order to assess the subject of air contamination and post fire surface contamination in a warehouse facility. Measured results are then compared with the results from the FDS model. Two components are examined: the production rate of contaminates and the trajectory of contaminates caused by the forced ventilation conditions. Each plays an important role in determining the extent to which the products of combustion are dispersed and the levels to which products are exposed to the contaminants throughout the enclosure. The model results indicate a good first-order approximation to the measured surface contamination levels. The proper application of the FDS model can provide a cost and time efficient means of evaluating contamination levels within a defined volume.     

Automated formation of lipid-bilayer membranes in a microfluidic device

Although membrane channel proteins are important to drug discovery and hold great promise as engineered nanopore sensing elements, their widespread application to these areas has been limited by difficulties in fabricating planar lipid-bilayer membranes. We present a method for forming these sub-5-nm-thick free-standing structures based on a self-assembly process driven by solvent extraction in a microfluidic channel. This facile automatable process forms high-quality membranes able to host channel proteins measurable at single-molecule conductance resolution.     

Ceramic Laminates by Gelcasting

Laminated ceramic composites are appealing for many applications due to their unique and customizable thermal and mechanical properties. Gelcasting is a relatively new, yet commercially proven, near-net-shape processing technique suitable for laminate production. A review of gelcasting techniques and a discussion of their application to laminate processing are provided, along with an overview of laminate design and processing concerns. Specific examples of single-phase laminates produced via gelcasting are provided, including porous/dense alumina and magnetically aligned iron titanate and barium hexaferrite structures.     

Polymer sequestrants for biological and environmental applications

Toxic contaminates have profound consequences on both health and the environment. Consequently, effective approaches for addressing the effects of these toxicants are paramount. Here, we review recent progress in developing polymeric sequestrants for biological toxins, heavy metals and organic micropollutants. Polymers have several advantages as sequestration materials, including relatively low cost and high affinity for target compounds. As a result a number of polymer‐based toxin‐mitigation applications have been investigated. Naturally occurring toxins may be neutralized with polymers capable of binding and eliminating them from the body. Heavy metal contamination from mining operations, energy and industrial sources may also be mitigated with appropriate chelating polymers, both for environmental remediation and in chelation therapy for metal poisoning. Micropollutants such as pesticides from agriculture and polycyclic aromatic hydrocarbons from combustion processes may also be isolated using polymeric materials. Each of these applications illustrates the capabilities of polymers for eliminating toxic contaminants, thereby facilitating greater health and sustainability. © 2019 Society of Chemical Industry     

High-throughput DNA methylation datasets for evaluating false discovery rate methodologies

When analyzing high-throughput genomic data, the multiple comparison problem is most often addressed through estimation of the false discovery rate (FDR), using methods such as the Benjamini & Hochberg, Benjamini & Yekutieli, the q-value method, or in controlling the family-wise error rate (FWER) using Holm's step down method. To date, research studies that have compared various FDR/FWER methodologies have made use of limited simulation studies and/or have applied the methods to one or more microarray gene expression dataset(s). However, for microarray datasets the veracity of each null hypothesis tested is unknown so that an objective evaluation of performance cannot be rendered for application data. Due to the role of methylation in X-chromosome inactivation, we postulate that high-throughput methylation datasets may provide an appropriate forum for assessing the performance of commonly used FDR methodologies. These datasets preserve the complex correlation structure between probes, offering an advantage over simulated datasets. Using several methylation datasets, commonly used FDR methods including the q-value, Benjamini & Hochberg, and Benjamini & Yekutieli procedures as well as Holm's step down method were applied to identify CpG sites that are differentially methylated when comparing healthy males to healthy females. The methods were compared with respect to their ability to identify CpG sites located on sex chromosomes as significant, by reporting the sensitivity, specificity, and observed FDR. These datasets are useful for characterizing the performance of multiple comparison procedures, and may find further utility in other tasks such as comparing variable selection capabilities of classification methods and evaluating the performance of meta-analytic methods for microarray data.     

Improving nitrogen reduction in waste stabilisation ponds.

This paper reviews the performance of two waste stablisation ponds (WSP) systems in the South Island of New Zealand that have been upgraded to multiple ponds-in-series to improve effluent quality. Results of monitoring are provided which show that it is possible to achieve relatively low ammonia (approximately 1 g/m3) and total nitrogen (approximately 10 g/m3) effluent concentrations through the use of nitrification filter beds (rock trickling filters) and sand filters. Evidence suggests that the nitrification and denitrification processes in the extra biofilm surface area provided by the rock filters or rock bank protection is primarily responsible for the improved effluent quality. The paper also compares the WSP results with effluent quality predicted by published formulae. It is concluded that these formulae do not reliably predict the performance of WSP systems and the development of universally applicable design guidelines would be useful.     

Behaviour of oil droplets during spray drying of milk-protein-stabilised oil-in-water emulsions

The effects of spray drying on the behaviour of oil droplets in oil-in-water emulsions (12.0%, w/w, maltodextrin; 20.0%, w/w, soya oil) stabilised with either sodium caseinate or whey protein isolate (WPI) were examined as a function of protein concentration (0.5–5.0%, w/w). Spray drying and redispersion caused a shift in the droplet size distribution to larger values for all emulsions made using low protein concentrations (0.5–2.0%, w/w), in comparison with their respective parent emulsions. However, the droplet size distribution was affected only very slightly by spray drying when the protein concentration was above 2.0% (w/w). The effects of maltodextrin concentration (1.0–25.0%, w/w) on the behaviour of WPI-stabilised emulsions (0.5–10.0%, w/w, WPI, 20.0%, w/w, soya oil) were also examined. Emulsions containing low levels of maltodextrin showed marked re-coalescence during spray drying and redispersion even at a WPI concentration of 10.0% (w/w).