Simultaneous determination of 3-hydroxyanthranilic and cinnabarinic acid by high-performance liquid chromatography with photometric or electrochemical detection

A convenient and rapid method for the simultaneous determination by HPLC of 3-hydroxyanthranilic acid and the dimer derived by its oxidation, cinnabarinic acid, is described. Buffers or biological samples containing these two Trp metabolites were acidified to pH 2.0 and extracted with ethyl acetate with recoveries of 96.5 +/- 0.5 and 93.4 +/- 3.7% for 3-hydroxyanthranilic and cinnabarinic acid, respectively. The two compounds were separated on a reversed-phase (C18) column combined with ion-pair chromatography and detected photometrically or electrochemically. The method was applied successfully to biological systems in which formation of either 3-hydroxyanthranilic or cinnabarinic acid had been described previously. Thus, interferon-gamma-treated human peripheral blood mononuclear cells formed and released significant amounts of 3-hydroxyanthranilic acid into the culture medium and mouse liver nuclear fraction possessed high "cinnabarinic acid synthase" activity. In contrast, addition of 3-hydroxyanthranilic acid to human erythrocytes resulted in only marginal formation of cinnabarinic acid. We conclude that the method described is specific, sensitive, and suitable for the detection of the two Trp metabolites in biological systems.

Automatic extraction of femur contours from calibrated fluoroscopic images

Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity

Screening, optimization and extraction of polyhydroxyalkanoates and peptidoglycan from Bacillus megaterium

Bioplastics are polymers (such as polyesters) produced from bacterial fermentations that are biodegradable and nonhazardous. They are produced by a wide variety of bacteria and are made only when stress conditions allow, such as when nutrient levels are low, more specifically levels of nitrogen and oxygen. These stress conditions cause certain bacteria to build up excess carbon deposits as energy reserves in the form of polyhydroxyalkanoates (PHAs). PHAs can be extracted and formed into actual plastic with the same strength of conventional, synthetic-based plastics without the need to rely on foreign petroleum. The overall goal of this project was to select for a bacteria that could grow on sugars found in the lignocellulosic biomass, and get the bacteria to produce PHAs and peptidoglycan. Once this was accomplished the goal was to extract PHAs and peptidoglycan in order to make a stronger more rigid plastic, by combing them into a co-polymer. The individual goals of this project were to: (1) Select and screen bacteria that are capable of producing PHAs by utilizing the carbon/energy sources found in lignocellulosic biomass; (2) Maximize the utilization of those sugars present in woody biomass in order to produce optimal levels of PHAs. (3) Use room temperature ionic liquids (RTILs) in order to separate the cell membrane and peptidoglycan, allowing for better extraction of PHAs and more intact peptidoglycan. B. megaterium a Gram-positive PHA-producing bacterium was selected for study in this project. It was grown on a variety of different substrates in order to maximize both its growth and production of PHAs. The optimal conditions were found to be 30°C, pH 6.0 and sugar concentration of either 30g/L glucose or xylose. After optimal growth was obtained, both RTILs and enzymatic treatments were used to break the cell wall, in order to extract the PHAs, and peptidoglycan. PHAs and peptidoglycan were successfully extracted from the cell, and will be used in the future to create a new stronger co-polymer. Peptidoglycan recovery yield was 16% of the cells’ dry weight.

The Extraction of Manganese from Manganese Flue Dust.

It is estimated that 90 to 95% of the world’s consumption of manganese is used in the steel industry in the form of either ferromanganese or spiegeleisen. The remainder is used in the form of either salts or oxides, chloride, dioxide and monoxide.

Investigation of a Method for Extraction of Indium from Zinc Flue Dust.

In metallurgical practice today some of the relatively rare metal Indium is recovered as a by-product from the ores of other metals. Indium is a soft, silvery—white metal belonging to the third group of the periodic classification. It is situated just above tin in the electrochemical series.

The Extraction of Chromate Salts from Montana Chromite

In this thesis I have tried to determine the suit­able temperature, time and the amount of soda ash and lime needed for the calcining process. The leaching and purification tests were studied experimentally. The earlier process for making chromate from chromite was not the same as is used today. There­fore I have found it useful to put into this thesis the newest method for making chromate salts and their important uses.

EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.