Publications

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Bacteria, algae and plants produce metal-specific chelators to capture required nutrient or toxic trace metals. Biological systems are thought to be very efficient, honed by evolutionary forces over time. Understanding the approaches used by living organisms to select for specific metals in the environment may lead to design of cheaper and more effective approaches for metal recovery and contaminant-metal remediation. In this study, the binding of a common siderophore, desferrioxamine B (DFO-B), to three aqueous metal cations, Fe(II), Fe(III), and UO{sub 2}(VI) was investigated using classical molecular dynamics. DFO-B has three acetohydroxamate groups and a terminal amine group that all deprotonate with increasing pH. For all three metals, complexes with DFO-B (-2) are the most stable and favored under alkaline conditions. Under more acidic conditions, the metal-DFO complexes involve chelation with both acetohydroxamate and acetylamine groups. The approach taken here allows for detailed investigation of metal binding to biologically-designed organic ligands.

The overarching goal is to develop novel technologies to elucidate molecular mechanisms of the innate immune response in host cells to pathogens such as bacteria and viruses including the mechanisms used by pathogens to subvert/suppress/obfuscate the immune response to cause their harmful effects. Innate immunity is our first line of defense against a pathogenic bacteria or virus. A comprehensive 'system-level' understanding of innate immunity pathways such as toll-like receptor (TLR) pathways is the key to deciphering mechanisms of pathogenesis and can lead to improvements in early diagnosis or developing improved therapeutics. Current methods for studying signaling focus on measurements of a limited number of components in a pathway and hence, fail to provide a systems-level understanding. We have developed a systems biology approach to decipher TLR4 pathways in macrophage cell lines in response to exposure to pathogenic bacteria and their lipopolysaccharide (LPS). Our approach integrates biological reagents, a microfluidic cell handling and analysis platform, high-resolution imaging and computational modeling to provide spatially- and temporally-resolved measurement of TLR-network components. The Integrated microfluidic platform is capable of imaging single cells to obtain dynamic translocation data as well as high-throughput acquisition of quantitative protein expression and phosphorylation information of selected cell populations. The platform consists of multiple modules such as single-cell array, cell sorter, and phosphoflow chip to provide confocal imaging, cell sorting, flow cytomtery and phosphorylation assays. The single-cell array module contains fluidic constrictions designed to trap and hold single host cells. Up to 100 single cells can be trapped and monitored for hours, enabling detailed statistically-significant measurements. The module was used to analyze translocation behavior of transcription factor NF-kB in macrophages upon activation by E. coli and Y. pestis LPS. The chip revealed an oscillation pattern in translocation of NF-kB indicating the presence of a negative feedback loop involving IKK. Activation of NF-kB is preceded by phosphorylation of many kinases and to correlate the kinase activity with translocation, we performed flow cytometric assays in the PhosphoChip module. Phopshorylated forms of p38. ERK and RelA were measured in macrophage cells challenged with LPS and showed a dynamic response where phosphorylation increases with time reaching a maximum at {approx}30-60min. To allow further downstream analysis on selected cells, we also implemented an optical-trapping based sorting of cells. This has allowed us to sort macrophages infected with bacteria from uninfected cells with the goal of obtaining data only on the infected (the desired) population. The various microfluidic chip modules and the accessories required to operate them such as pumps, heaters, electronic control and optical detectors are being assembled in a bench-top, semi-automated device. The data generated is being utilized to refine existing TLR pathway model by adding kinetic rate constants and concentration information. The microfluidic platform allows high-resolution imaging as well as quantitative proteomic measurements with high sensitivity (<pM) and time-resolution ({approx}15 s) in the same population of cells, a feat not achievable by current techniques. Furthermore, our systems approach combining the microfluidic platform and high-resolution imaging with the associated computational models and biological reagents will significantly improve our ability to study cell-signaling involved in host-pathogen interactions and other diseases such as cancer. The advances made in this project have been presented at numerous national and international conferences and are documented in many peer-reviewed publications as listed. Finer details of many of the component technologies are described in these publications. The chapters to follow in this report are also adapted from other manuscripts that are accepted for publication, submitted or in preparation to be submitted to peer-reviewed journals.

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This report documents work performed in the second phase of the Diagnostics While-Drilling (DWD) project in which a high-temperature (HT) version of the phase 1 low-temperature (LT) proof-of-concept (POC) DWD tool was built and tested. Descriptions of the design, fabrication and field testing of the HT tool are provided.

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Both conventional and combinatorial approaches were used to study the pore formation process in epoxy based polymer systems. Sandia National Laboratories conducted the initial work and collaborated with North Dakota State University (NDSU) using a combinatorial research approach to produce a library of novel monomers and crosslinkers capable of forming porous polymers. The library was screened to determine the physical factors that control porosity, such as porogen loading, polymer-porogen interactions, and polymer crosslink density. We have identified the physical and chemical factors that control the average porosity, pore size, and pore size distribution within epoxy based systems.

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This report summarizes the experimental and modeling effort undertaken to understand solute mixing in a water distribution network conducted during the last year of a 3-year project. The experimental effort involves measurement of extent of mixing within different configurations of pipe networks, measurement of dynamic mixing in a single mixing tank, and measurement of dynamic solute mixing in a combined network-tank configuration. High resolution analysis of turbulence mixing is carried out via high speed photography as well as 3D finite-volume based Large Eddy Simulation turbulence models. Macroscopic mixing rules based on flow momentum balance are also explored, and in some cases, implemented in EPANET. A new version EPANET code was developed to yield better mixing predictions. The impact of a storage tank on pipe mixing in a combined pipe-tank network during diurnal fill-and-drain cycles is assessed. Preliminary comparison between dynamic pilot data and EPANET-BAM is also reported.

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This report investigates the validity of several key assumptions in classical plasticity theory regarding material response to changes in the loading direction. Three metals, two rock types, and one ceramic were subjected to non-standard loading directions, and the resulting strain response increments were displayed in Gudehus diagrams to illustrate the approximation error of classical plasticity theories. A rigorous mathematical framework for fitting classical theories to the data, thus quantifying the error, is provided. Further data analysis techniques are presented that allow testing for the effect of changes in loading direction without having to use a new sample and for inferring the yield normal and flow directions without having to measure the yield surface. Though the data are inconclusive, there is indication that classical, incrementally linear, plasticity theory may be inadequate over a certain range of loading directions. This range of loading directions also coincides with loading directions that are known to produce a physically inadmissible instability for any nonassociative plasticity model.

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