Mechanisms of Arsenic Detoxification and Resistance

Arsenic is a ubiquitous environmental toxic substance. As a consequence of continual exposure to arsenic, nearly every organism, from Escherichia coli to humans have evolved arsenic detoxification pathways. One of the pathways is extrusion of arsenic from inside the cells, thereby conferring resistance. The R773 arsRDABC operon in E. coli encodes an ArsAB efflux pump that confers resistance to arsenite. ArsA is the catalytic subunit of the pump, while ArsB forms the oxyanion conducting pathway. ArsD is an arsenite metallochaperone that binds arsenite and transfers it to ArsA. The interaction of ArsA and ArsD allows for resistance to As(III) at environmental concentrations. The interaction between ArsA ATPase and ArsD metallochaperone was examined. A quadruple mutant in the arsD gene encoding a K2A/K37A/K62A/K104A ArsD is unable to interact with ArsA. An error-prone mutagenesis approach was used to generate random mutations in the arsA gene that restored interaction with the quadruple arsD mutant in yeast two-hybrid assays. Three such mutants encoding Q56R, F120I and D137V ArsA were able to restore interaction with the quadruple ArsD mutant. Structural models generated by in silico docking suggest that an electrostatic interface favors reversible interaction between ArsA and ArsD. Mutations in ArsA that propagate changes in hydrogen bonding and salt bridges to the ArsA-ArsD interface also affect their interactions. The second objective was to examine the mechanism of arsenite resistance through methylation and subsequent volatilization. Microbial ArsM (As(III) S-adenosylmethyltransferase) catalyzes the formation of trimethylarsine as the volatile end product. The net result is loss of arsenic from cells. The gene for CrArsM from the eukaryotic green alga Chlamydomonas reinhardtii was chemically synthesized and expressed in E. coli. The purified protein catalyzed the methylation of arsenite into methyl-, dimethyl- and trimethyl products. Synthetic purified CrArsM was crystallized in an unliganded form. Biochemical and biophysical studies conducted on CrArsM sheds new light on the pathways of biomethylation. While in microbes ArsM detoxifies arsenic, the human homolog, hAS3MT, converts inorganic arsenic into more toxic and carcinogenic forms. An understanding of the enzymatic mechanism of ArsM will be critical in deciphering its parallel roles in arsenic detoxification and carcinogenesis.

Hybrid multi-objective optimization and hybridized self-organizing response surface method

Numerical optimization is a technique where a computer is used to explore design parameter combinations to find extremes in performance factors. In multi-objective optimization several performance factors can be optimized simultaneously. The solution to multi-objective optimization problems is not a single design, but a family of optimized designs referred to as the Pareto frontier. The Pareto frontier is a trade-off curve in the objective function space composed of solutions where performance in one objective function is traded for performance in others. A Multi-Objective Hybridized Optimizer (MOHO) was created for the purpose of solving multi-objective optimization problems by utilizing a set of constituent optimization algorithms. MOHO tracks the progress of the Pareto frontier approximation development and automatically switches amongst those constituent evolutionary optimization algorithms to speed the formation of an accurate Pareto frontier approximation. Aerodynamic shape optimization is one of the oldest applications of numerical optimization. MOHO was used to perform shape optimization on a 0.5-inch ballistic penetrator traveling at Mach number 2.5. Two objectives were simultaneously optimized: minimize aerodynamic drag and maximize penetrator volume. This problem was solved twice. The first time the problem was solved by using Modified Newton Impact Theory (MNIT) to determine the pressure drag on the penetrator. In the second solution, a Parabolized Navier-Stokes (PNS) solver that includes viscosity was used to evaluate the drag on the penetrator. The studies show the difference in the optimized penetrator shapes when viscosity is absent and present in the optimization. In modern optimization problems, objective function evaluations may require many hours on a computer cluster to perform these types of analysis. One solution is to create a response surface that models the behavior of the objective function. Once enough data about the behavior of the objective function has been collected, a response surface can be used to represent the actual objective function in the optimization process. The Hybrid Self-Organizing Response Surface Method (HYBSORSM) algorithm was developed and used to make response surfaces of objective functions. HYBSORSM was evaluated using a suite of 295 non-linear functions. These functions involve from 2 to 100 variables demonstrating robustness and accuracy of HYBSORSM.

Minimizing makespan for hybrid flowshops with batch, discrete processing machines and arbitrary job sizes

This research aims at a study of the hybrid flow shop problem which has parallel batch-processing machines in one stage and discrete-processing machines in other stages to process jobs of arbitrary sizes. The objective is to minimize the makespan for a set of jobs. The problem is denoted as: FF: batch1,sj:Cmax. The problem is formulated as a mixed-integer linear program. The commercial solver, AMPL/CPLEX, is used to solve problem instances to their optimality. Experimental results show that AMPL/CPLEX requires considerable time to find the optimal solution for even a small size problem, i.e., a 6-job instance requires 2 hours in average. A bottleneck-first-decomposition heuristic (BFD) is proposed in this study to overcome the computational (time) problem encountered while using the commercial solver. The proposed BFD heuristic is inspired by the shifting bottleneck heuristic. It decomposes the entire problem into three sub-problems, and schedules the sub-problems one by one. The proposed BFD heuristic consists of four major steps: formulating sub-problems, prioritizing sub-problems, solving sub-problems and re-scheduling. For solving the sub-problems, two heuristic algorithms are proposed; one for scheduling a hybrid flow shop with discrete processing machines, and the other for scheduling parallel batching machines (single stage). Both consider job arrival and delivery times. An experiment design is conducted to evaluate the effectiveness of the proposed BFD, which is further evaluated against a set of common heuristics including a randomized greedy heuristic and five dispatching rules. The results show that the proposed BFD heuristic outperforms all these algorithms. To evaluate the quality of the heuristic solution, a procedure is developed to calculate a lower bound of makespan for the problem under study. The lower bound obtained is tighter than other bounds developed for related problems in literature. A meta-search approach based on the Genetic Algorithm concept is developed to evaluate the significance of further improving the solution obtained from the proposed BFD heuristic. The experiment indicates that it reduces the makespan by 1.93 % in average within a negligible time when problem size is less than 50 jobs.

Novel hybrid columns made of ultra-high performance concrete and fiber reinforced polymers

The application of advanced materials in infrastructure has grown rapidly in recent years mainly because of their potential to ease the construction, extend the service life, and improve the performance of structures. Ultra-high performance concrete (UHPC) is one such material considered as a novel alternative to conventional concrete. The material microstructure in UHPC is optimized to significantly improve its material properties including compressive and tensile strength, modulus of elasticity, durability, and damage tolerance. Fiber-reinforced polymer (FRP) composite is another novel construction material with excellent properties such as high strength-to-weight and stiffness-to-weight ratios and good corrosion resistance. Considering the exceptional properties of UHPC and FRP, many advantages can result from the combined application of these two advanced materials, which is the subject of this research. The confinement behavior of UHPC was studied for the first time in this research. The stress-strain behavior of a series of UHPC-filled fiber-reinforced polymer (FRP) tubes with different fiber types and thicknesses were tested under uniaxial compression. The FRP confinement was shown to significantly enhance both the ultimate strength and strain of UHPC. It was also shown that existing confinement models are incapable of predicting the behavior of FRP-confined UHPC. Therefore, new stress-strain models for FRP-confined UHPC were developed through an analytical study. In the other part of this research, a novel steel-free UHPC-filled FRP tube (UHPCFFT) column system was developed and its cyclic behavior was studied. The proposed steel-free UHPCFFT column showed much higher strength and stiffness, with a reasonable ductility, as compared to its conventional reinforced concrete (RC) counterpart. Using the results of the first phase of column tests, a second series of UHPCFFT columns were made and studied under pseudo-static loading to study the effect of column parameters on the cyclic behavior of UHPCFFT columns. Strong correlations were noted between the initial stiffness and the stiffness index, and between the moment capacity and the reinforcement index. Finally, a thorough analytical study was carried out to investigate the seismic response of the proposed steel-free UHPCFFT columns, which showed their superior earthquake resistance, as compared to their RC counterparts.

Nano-grids of Yeast Cytochrome C

One innovative thought in biomolecular electronics is the exploitation of electron transfer proteins. Using nature's self assembly techniques, proteins can build highly organized edifices with retained functional activity, and they can serve as platforms for biosensors. In this research work, Yeast Cytochrome C (YCC) is immobilized with a help of a linker molecule, 3-Mercaptopropyltrimethoxysilane (3-MPTS) on a hydroxylated surface of a silicon substrate. Atomic Force Microscopy (AFM) is used for characterization. AFM data shows immobilization of one YCC molecule in between eight grids that are formed by the linker molecules. 3-MPTS monolayers are organized in grids that are 1.2 nm apart. Immobilization of 3-MPTS was optimized using a concentration of 5 mM in a completely dehydrated state for 30 minutes. The functionally active grids of YCC can now be incorporated with Cytochrome C oxidase on a Platinum electrode surface for transfer of electrons in development of biosensors, such as nitrate sensor, that are small in size, cheaper, and easier to manufacture than the top-down approach of fabrication of molecular biodevices