ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Displaying 1 - 10 of 108
Description
In the 1970s James Watson recognized the inability of conventional DNA replication machinery to replicate the extreme termini of chromosomes known as telomeres. This inability is due to the requirement of a building block primer and was termed the end replication problem. Telomerase is nature's answer to the end replication problem. Telomerase is a ribonucleoprotein which extends telomeres through reverse transcriptase activity by reiteratively copying a short intrinsic RNA sequence to generate 3' telomeric extensions. Telomeres protect chromosomes from erosion of coding genes during replication, as well as differentiate native chromosome ends from double stranded breaks. However, controlled erosion of telomeres functions as a naturally occurring molecular clock limiting the replicative capacity of cells. Telomerase is over activated in many cancers, while inactivation leads to multiple lifespan limiting human diseases. In order to further study the interaction between telomerase RNA (TR) and telomerase reverse transcriptase protein (TERT), vertebrate TERT fragments were screened for solubility and purity following bacterial expression. Soluble fragments of medaka TERT including the RNA binding domain (TRBD) were identified. Recombinant medaka TRBD binds specifically to telomerase RNA CR4/CR5 region. Ribonucleotide and amino acid pairs in close proximity within the medaka telomerase RNA-protein complex were identified using photo-activated cross-linking in conjunction with mass spectrometry. The identified cross-linking amino acids were mapped on known crystal structures of TERTs to reveal the RNA interaction interface of TRBD. The identification of this RNA TERT interaction interface furthers the understanding of the telomerase complex at a molecular level and could be used for the targeted interruption of the telomerase complex as a potential cancer treatment.
ContributorsBley, Christopher James (Author) / Chen, Julian (Thesis advisor) / Allen, James (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2011
Description
Telomerase ribonucleoprotein is a unique reverse transcriptase that adds telomeric DNA repeats to chromosome ends. Telomerase RNA (TER) is extremely divergent in size, sequence and has to date only been identified in vertebrate, yeast, ciliate and plant species. Herein, the identification and characterization of TERs from an evolutionarily distinct group, filamentous fungi, is presented. Based on phylogenetic analysis of 69 TER sequences and mutagenesis analysis of in vitro reconstituted Neurospora telomerase, we discovered a conserved functional core in filamentous fungal TERs sharing homologous structural features with vertebrate TERs. This core contains the template-pseudoknot and P6/P6.1 domains, essential for enzymatic activity, which retain function in trans. The in vitro reconstituted Neurospora telomerase is highly processive, synthesizing canonical TTAGGG repeats. Similar to Schizosaccharomycetes pombe, filamentous fungal TERs utilize the spliceosomal splicing machinery for 3' processing. Neurospora telomerase, while associating with the Est1 protein in vivo, does not bind homologous Ku or Sm proteins found in both budding and fission yeast telomerase holoenzyme, suggesting a unique biogenesis pathway. The development of Neurospora as a model organism to study telomeres and telomerase may shed light upon the evolution of the canonical TTAGGG telomeric repeat and telomerase processivity within fungal species.
ContributorsQi, Xiaodong (Author) / Chen, Julian (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Chaput, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
Telomerase is a specialized enzyme that adds telomeric DNA repeats to the chromosome ends to counterbalance the progressive telomere shortening over cell divisions. It has two essential core components, a catalytic telomerase reverse transcriptase protein (TERT), and a telomerase RNA (TR). TERT synthesizes telomeric DNA by reverse transcribing a short template sequence in TR. Unlike TERT, TR is extremely divergent in size, sequence and structure and has only been identified in three evolutionarily distant groups. The lack of knowledge on TR from important model organisms has been a roadblock for vigorous studies on telomerase regulation. To address this issue, a novel in vitro system combining deep-sequencing and bioinformatics search was developed to discover TR from new phylogenetic groups. The system has been validated by the successful identification of TR from echinoderm purple sea urchin Strongylocentrotus purpuratus. The sea urchin TR (spTR) is the first invertebrate TR that has been identified and can serve as a model for understanding how the vertebrate TR evolved with vertebrate-specific traits. By using phylogenetic comparative analysis, the secondary structure of spTR was determined. The spTR secondary structure reveals unique sea urchin specific structure elements as well as homologous structural features shared by TR from other organisms. This study enhanced the understanding of telomerase mechanism and the evolution of telomerase RNP. The system that was used to identity telomerase RNA can be employed for the discovery of other TR as well as the discovery of novel RNA from other RNP complex.
ContributorsLi, Yang (Author) / Chen, Julian Jl (Thesis advisor) / Yan, Hao (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2011
Description
Mostly, manufacturing tolerance charts are used these days for manufacturing tolerance transfer but these have the limitation of being one dimensional only. Some research has been undertaken for the three dimensional geometric tolerances but it is too theoretical and yet to be ready for operator level usage. In this research, a new three dimensional model for tolerance transfer in manufacturing process planning is presented that is user friendly in the sense that it is built upon the Coordinate Measuring Machine (CMM) readings that are readily available in any decent manufacturing facility. This model can take care of datum reference change between non orthogonal datums (squeezed datums), non-linearly oriented datums (twisted datums) etc. Graph theoretic approach based upon ACIS, C++ and MFC is laid out to facilitate its implementation for automation of the model. A totally new approach to determining dimensions and tolerances for the manufacturing process plan is also presented. Secondly, a new statistical model for the statistical tolerance analysis based upon joint probability distribution of the trivariate normal distributed variables is presented. 4-D probability Maps have been developed in which the probability value of a point in space is represented by the size of the marker and the associated color. Points inside the part map represent the pass percentage for parts manufactured. The effect of refinement with form and orientation tolerance is highlighted by calculating the change in pass percentage with the pass percentage for size tolerance only. Delaunay triangulation and ray tracing algorithms have been used to automate the process of identifying the points inside and outside the part map. Proof of concept software has been implemented to demonstrate this model and to determine pass percentages for various cases. The model is further extended to assemblies by employing convolution algorithms on two trivariate statistical distributions to arrive at the statistical distribution of the assembly. Map generated by using Minkowski Sum techniques on the individual part maps is superimposed on the probability point cloud resulting from convolution. Delaunay triangulation and ray tracing algorithms are employed to determine the assembleability percentages for the assembly.
ContributorsKhan, M Nadeem Shafi (Author) / Phelan, Patrick E (Thesis advisor) / Montgomery, Douglas C. (Committee member) / Farin, Gerald (Committee member) / Roberts, Chell (Committee member) / Henderson, Mark (Committee member) / Arizona State University (Publisher)
Created2011
Description
There is increasing interest in the medical and behavioral health communities towards developing effective strategies for the treatment of chronic diseases. Among these lie adaptive interventions, which consider adjusting treatment dosages over time based on participant response. Control engineering offers a broad-based solution framework for optimizing the effectiveness of such interventions. In this thesis, an approach is proposed to develop dynamical models and subsequently, hybrid model predictive control schemes for assigning optimal dosages of naltrexone, an opioid antagonist, as treatment for a chronic pain condition known as fibromyalgia. System identification techniques are employed to model the dynamics from the daily diary reports completed by participants of a blind naltrexone intervention trial. These self-reports include assessments of outcomes of interest (e.g., general pain symptoms, sleep quality) and additional external variables (disturbances) that affect these outcomes (e.g., stress, anxiety, and mood). Using prediction-error methods, a multi-input model describing the effect of drug, placebo and other disturbances on outcomes of interest is developed. This discrete time model is approximated by a continuous second order model with zero, which was found to be adequate to capture the dynamics of this intervention. Data from 40 participants in two clinical trials were analyzed and participants were classified as responders and non-responders based on the models obtained from system identification. The dynamical models can be used by a model predictive controller for automated dosage selection of naltrexone using feedback/feedforward control actions in the presence of external disturbances. The clinical requirement for categorical (i.e., discrete-valued) drug dosage levels creates a need for hybrid model predictive control (HMPC). The controller features a multiple degree-of-freedom formulation that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed loop system. The nominal and robust performance of the proposed control scheme is examined via simulation using system identification models from a representative participant in the naltrexone intervention trial. The controller evaluation described in this thesis gives credibility to the promise and applicability of control engineering principles for optimizing adaptive interventions.
ContributorsDeśapāṇḍe, Sunīla (Author) / Rivera, Daniel E. (Thesis advisor) / Si, Jennie (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2011
Description
Natural products that target the DNA of cancer cells have been an important source of knowledge and understanding in the development of anticancer chemotherapeutic agents. Bleomycin (BLM) exemplifies this class of DNA damaging agent. The ability of BLM to chelate metal ions and effect oxidative damage of the deoxyribose sugar moiety of DNA has been studied extensively for four decades. Here, the study of BLM A5 was conducted using a previously isolated library of hairpin DNAs found to bind strongly to metal free BLM. The ability of BLM to effect single-stranded was then extensively characterized on both the 3′ and 5′-arms of the hairpin DNAs. The strongly bound DNAs were found to be efficient substrates for Fe·BLM A5-mediated cleavage. Surprisingly, the most prevalent site of damage by BLM was found to be a 5′-AT-3′ dinucleotide sequence. This dinucleotide sequence and others generally not cleaved by BLM when examined using arbitrarily chosen DNA substrate were found in examining the library of ten hairpin DNAs. In total, 111 sites of DNA damage were found to be produced by exposure of the hairpin DNA library to Fe·BLM A5. Also, an assay was developed with which to test the propensity of the hairpin DNAs to undergo double stranded DNA damage. Adapting methods previously described by the Povirk laboratory, one hairpin was characterized using this method. The results were in accordance with those previously reported.
ContributorsSegerman, Zachary (Author) / Hecht, Sidney M. (Thesis advisor) / Levitus, Marcia (Committee member) / Ghirlanda, Giovanna (Committee member) / Arizona State University (Publisher)
Created2011
Description
The properties of materials depend heavily on the spatial distribution and connectivity of their constituent parts. This applies equally to materials such as diamond and glasses as it does to biomolecules that are the product of billions of years of evolution. In science, insight is often gained through simple models with characteristics that are the result of the few features that have purposely been retained. Common to all research within in this thesis is the use of network-based models to describe the properties of materials. This work begins with the description of a technique for decoupling boundary effects from intrinsic properties of nanomaterials that maps the atomic distribution of nanomaterials of diverse shape and size but common atomic geometry onto a universal curve. This is followed by an investigation of correlated density fluctuations in the large length scale limit in amorphous materials through the analysis of large continuous random network models. The difficulty of estimating this limit from finite models is overcome by the development of a technique that uses the variance in the number of atoms in finite subregions to perform the extrapolation to large length scales. The technique is applied to models of amorphous silicon and vitreous silica and compared with results from recent experiments. The latter part this work applies network-based models to biological systems. The first application models force-induced protein unfolding as crack propagation on a constraint network consisting of interactions such as hydrogen bonds that cross-link and stabilize a folded polypeptide chain. Unfolding pathways generated by the model are compared with molecular dynamics simulation and experiment for a diverse set of proteins, demonstrating that the model is able to capture not only native state behavior but also partially unfolded intermediates far from the native state. This study concludes with the extension of the latter model in the development of an efficient algorithm for predicting protein structure through the flexible fitting of atomic models to low-resolution cryo-electron microscopy data. By optimizing the fit to synthetic data through directed sampling and context-dependent constraint removal, predictions are made with accuracies within the expected variability of the native state.
ContributorsDe Graff, Adam (Author) / Thorpe, Michael F. (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Matyushov, Dmitry (Committee member) / Ozkan, Sefika B. (Committee member) / Treacy, Michael M. J. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Due to restructuring and open access to the transmission system, modern electric power systems are being operated closer to their operational limits. Additionally, the secure operational limits of modern power systems have become increasingly difficult to evaluate as the scale of the network and the number of transactions between utilities increase. To account for these challenges associated with the rapid expansion of electric power systems, dynamic equivalents have been widely applied for the purpose of reducing the computational effort of simulation-based transient security assessment. Dynamic equivalents are commonly developed using a coherency-based approach in which a retained area and an external area are first demarcated. Then the coherent generators in the external area are aggregated and replaced by equivalenced models, followed by network reduction and load aggregation. In this process, an improperly defined retained area can result in detrimental impacts on the effectiveness of the equivalents in preserving the dynamic characteristics of the original unreduced system. In this dissertation, a comprehensive approach has been proposed to determine an appropriate retained area boundary by including the critical generators in the external area that are tightly coupled with the initial retained area. Further-more, a systematic approach has also been investigated to efficiently predict the variation in generator slow coherency behavior when the system operating condition is subject to change. Based on this determination, the critical generators in the external area that are tightly coherent with the generators in the initial retained area are retained, resulting in a new retained area boundary. Finally, a novel hybrid dynamic equivalent, consisting of both a coherency-based equivalent and an artificial neural network (ANN)-based equivalent, has been proposed and analyzed. The ANN-based equivalent complements the coherency-based equivalent at all the retained area boundary buses, and it is designed to compensate for the discrepancy between the full system and the conventional coherency-based equivalent. The approaches developed have been validated on a large portion of the Western Electricity Coordinating Council (WECC) system and on a test case including a significant portion of the eastern interconnection.
ContributorsMa, Feng (Author) / Vittal, Vijay (Thesis advisor) / Tylavsky, Daniel (Committee member) / Heydt, Gerald (Committee member) / Si, Jennie (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2011
Description
Proportional-Integral-Derivative (PID) controllers are a versatile category of controllers that are commonly used in the industry as control systems due to the ease of their implementation and low cost. One problem that continues to intrigue control designers is the matter of finding a good combination of the three parameters - P, I and D of these controllers so that system stability and optimum performance is achieved. Also, a certain amount of robustness to the process is expected from the PID controllers. In the past, many different methods for tuning PID parameters have been developed. Some notable techniques are the Ziegler-Nichols, Cohen-Coon, Astrom methods etc. For all these techniques, a simple limitation remained with the fact that for a particular system, there can be only one set of tuned parameters; i.e. there are no degrees of freedom involved to readjust the parameters for a given system to achieve, for instance, higher bandwidth. Another limitation in most cases is where a controller is designed in continuous time then converted into discrete-time for computer implementation. The drawback of this method is that some robustness due to phase and gain margin is lost in the process. In this work a method of tuning PID controllers using a loop-shaping approach has been developed where the bandwidth of the system can be chosen within an acceptable range. The loop-shaping is done against a Glover-McFarlane type ℋ∞ controller which is widely accepted as a robust control design method. The numerical computations are carried out entirely in discrete-time so there is no loss of robustness due to conversion and approximations near Nyquist frequencies. Some extra degrees of freedom owing to choice of bandwidth and capability of choosing loop-shapes are also involved and are discussed in detail. Finally, comparisons of this method against existing techniques for tuning PID controllers both in continuous and in discrete-time are shown. The results tell us that our design performs well for loop-shapes that are achievable through a PID controller.
ContributorsShafique, Md. Ashfaque Bin (Author) / Tsakalis, Konstantinos S. (Thesis advisor) / Rodriguez, Armando A. (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2011
Description
A major goal of synthetic biology is to recapitulate emergent properties of life. Despite a significant body of work, a longstanding question that remains to be answered is how such a complex system arose? In this dissertation, synthetic nucleic acid molecules with alternative sugar-phosphate backbones were investigated as potential ancestors of DNA and RNA. Threose nucleic acid (TNA) is capable of forming stable helical structures with complementary strands of itself and RNA. This provides a plausible mechanism for genetic information transfer between TNA and RNA. Therefore TNA has been proposed as a potential RNA progenitor. Using molecular evolution, functional sequences were isolated from a pool of random TNA molecules. This implicates a possible chemical framework capable of crosstalk between TNA and RNA. Further, this shows that heredity and evolution are not limited to the natural genetic system based on ribofuranosyl nucleic acids. Another alternative genetic system, glycerol nucleic acid (GNA) undergoes intrasystem pairing with superior thermalstability compared to that of DNA. Inspired by this property, I demonstrated a minimal nanostructure composed of both left- and right-handed mirro image GNA. This work suggested that GNA could be useful as promising orthogonal material in structural DNA nanotechnology.
ContributorsZhang, Su (Author) / Chaut, John C (Thesis advisor) / Ghirlanda, Giovanna (Committee member) / Yan, Hao (Committee member) / Arizona State University (Publisher)
Created2011