Virus-Based Nanoreactors with GALT Activity for Classic Galactosemia Therapy

Enzymatic nanoreactors were obtained by galactose-1-phosphate uridylyl-transferase (GALT) encapsulation into plant virus capsids by a molecular self-assembly strategy. The aim of this work was to produce virus-like nanoparticles containing GALT for an enzyme-replacement therapy for classic galactosemia. The encapsulation efficiency and the catalytic constants of bio-nanoreactors were determined by using different GALT and virus coat protein ratios. The substrate affinity of nanoreactors was slightly lower than that of the free enzyme; the activity rate was 16 % of the GALT free enzyme. The enzymatic nanoreactors without functionalization were internalized into different cell lines including fibroblast and kidney cells, but especially into hepatocytes. The enzymatic nanoreactors are an innovative enzyme preparation with potential use for the treatment of classic galactosemia.     

Performance Evaluation of Two High‐Shear Impellers in an Unbaffled Stirred Tank

High‐shear impellers (HSIs) are mixers used in industrial stirred tanks to incorporate powders into liquids and break down particle agglomerates. A detailed numerical study of two commercial ring‐style HSIs of laboratory scale was carried out and their performance was compared with the Rushton turbine (RT). It was found that power and pumping numbers or their ratio cannot be simply connected for properly selecting an impeller in applications where highly localized viscous dissipation is desirable. The ratio of the average viscous dissipation in the impeller swept volume to the mean in the entire volume at two constant values of power input turned out to be lower for HSIs compared to that evaluated for RT. However, at higher power input, the dimensionless average viscous dissipation in the blade swept volume was found to be similar for the HSI of two rings and the RT, corroborating the high local viscous dissipation of this HSI when operated at higher speeds.     

Describing natural colors with Munsell and NCS color systems

The Munsell Color System and the Natural Color System are widely used but they have some limitations due to the manufacturing process and sampling choices. To estimate quantitatively these limitations we compared the colors of natural scenes with the colors represented by these systems under a wide range of illuminants. Spectral data from the two systems and from natural scenes were used in the analysis. It was found that a considerable portion of natural colors are not accounted by these systems, mainly colors with low lightness levels. Under D65 the Munsell Color System color volume corresponds to 72% of the Natural Color System color volume which in turn represents only 53% of the natural scenes color volume. If individual colors are considered, less than half are contained within these systems. To obtain a complete match to the natural colors contained by the color systems thresholds of 7 and 5 CIELAB units would be required for Munsell Color System and Natural Color System, respectively. Variations with the illuminant are generally modest showing that both system work similarly across different illuminations. Although these Color Systems have limitations in describing low lightness colors they perform quite well for medium to high levels of lightness.     

Implementation of periodic boundary conditions for loading of mechanical metamaterials and other complex geometric microstructures using finite element analysis

The implementation of periodic boundary conditions (PBCs) is one of the most important and difficult steps in the computational analysis of structures and materials. This is especially true in cases such as mechanical metamaterials which typically possess intricate geometries and designs which makes finding and implementing the correct PBCs a difficult challenge. In this work, we analyze one of the most common PBCs implementation technique, as well as implement and validate an alternative generic method which is suitable to simulate any possible 2D microstructural geometry with a quadrilateral unit cell regardless of symmetry and mode of deformation. A detailed schematic of how both these methods can be employed to study 3D systems is also presented.

     

Managing Water to Minimize Risk in Tailings Storage Facility Design,Construction, and Operation

Mine Water and the Environment - Reducing the amount of water in a milled tailings storage facility (TSF) is the primary way to reduce the risk of a catastrophic failure. In addition, a significant...     

Assembly and Characterization of Biocompatible Coenzyme Q10-Enriched Lipid Nanoparticles

Coenzyme Q₁₀ (CoQ₁₀) is a strongly hydrophobic lipid that functions in the electron transport chain and as an antioxidant. CoQ₁₀ was conferred with aqueous solubility by incorporation into nanoparticles containing phosphatidylcholine (PtdCho) and apolipoprotein (apo) A-I. These particles, termed CoQ₁₀ nanodisks (ND), contain 1.0 mg CoQ₁₀/5 mg PtdCho/2 mg apoA-I (97% CoQ₁₀ solubilization efficiency). UV/Vis absorbance spectroscopy of CoQ₁₀ ND revealed a characteristic absorbance peak centered at 275 nm. Incorporation of CoQ₁₀ into ND resulted in quenching of apoA-I tryptophan fluorescence emission. Gel filtration chromatography of CoQ₁₀ ND gave rise to a single major absorbance peak and HPLC of material extracted from this peak confirmed the presence of CoQ₁₀. Incubation of cultured cells with CoQ₁₀ ND, but not empty ND, resulted in a significant increase in the CoQ₁₀ content of mitochondria as well as enhanced oxidative phosphorylation, as observed by a ~24% increase in maximal oxygen consumption rate. Collectively, a facile method to solubilize significant quantities of CoQ₁₀ in lipid nanoparticles has been developed. The availability of CoQ₁₀ ND provides a novel means to investigate biochemical aspects of CoQ₁₀ uptake by cells and/or administer it to subjects deficient in this key lipid as a result of inborn errors of metabolism, statin therapy, or otherwise.     

DC servomechanism parameter identification: a Closed Loop Input Error approach

This paper presents a Closed Loop Input Error (CLIE) approach for on-line parametric estimation of a continuous-time model of a DC servomechanism functioning in closed loop. A standard Proportional Derivative (PD) position controller stabilizes the loop without requiring knowledge on the servomechanism parameters. The analysis of the identification algorithm takes into account the control law employed for closing the loop. The model contains four parameters that depend on the servo inertia, viscous, and Coulomb friction as well as on a constant disturbance. Lyapunov stability theory permits assessing boundedness of the signals associated to the identification algorithm. Experiments on a laboratory prototype allows evaluating the performance of the approach.     

Application and Sensitivity Analysis of Artificial Neural Network for Prediction of Chemical Oxygen Demand

Integrating water quality forecasting model with river restoration techniques makes river restoration more effective and efficient. This research investigates how to use the Artificial Neural Network (ANN) to predict the Chemical Oxygen Demand (COD) during river restoration in Wuxi city, China. Specifically, we applied a Multi-Layer Perceptron (MLP) using ten neurons in a single hidden layer and seven input variables (Temperature, Dissolved Oxygen, Total Nitrogen, Total Phosphorus, Suspended Sediment, Transparency, and NH₃-N) to simulate COD. The modeled results have a correlation coefficient of 0.966, 0.949, and 0.890 with the observations for the raining, validation, and testing phases, respectively. When presenting the trained network to an independent data set, the ANN model still shows a good predictive capability, indicating by a correlation coefficient of 0.978, a root mean square error (RMSE) of 0.628 mg/L, and a mean square error (MSE) of 0.394 mg²/L². A sensitivity analysis was further implemented to analyze the effect of each of the input variables on prediction of COD. DO, TO, and Transparency have relatively low influences on the estimate of COD, and can be removed from the input variables. The results from this study indicate that ANN models can provide satisfactory estimates of COD during the process of bacterial treatment and is a useful supportive tool for river restoration.