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Cancer is the second leading cause of death in the United States and novel methods of treating advanced malignancies are of high importance. Of these deaths, prostate cancer and breast cancer are the second most fatal carcinomas in men and women respectively, while pancreatic cancer is the fourth most fatal

Cancer is the second leading cause of death in the United States and novel methods of treating advanced malignancies are of high importance. Of these deaths, prostate cancer and breast cancer are the second most fatal carcinomas in men and women respectively, while pancreatic cancer is the fourth most fatal in both men and women. Developing new drugs for the treatment of cancer is both a slow and expensive process. It is estimated that it takes an average of 15 years and an expense of $800 million to bring a single new drug to the market. However, it is also estimated that nearly 40% of that cost could be avoided by finding alternative uses for drugs that have already been approved by the Food and Drug Administration (FDA). The research presented in this document describes the testing, identification, and mechanistic evaluation of novel methods for treating many human carcinomas using drugs previously approved by the FDA. A tissue culture plate-based screening of FDA approved drugs will identify compounds that can be used in combination with the protein TRAIL to induce apoptosis selectively in cancer cells. Identified leads will next be optimized using high-throughput microfluidic devices to determine the most effective treatment conditions. Finally, a rigorous mechanistic analysis will be conducted to understand how the FDA-approved drug mitoxantrone, sensitizes cancer cells to TRAIL-mediated apoptosis.
ContributorsTaylor, David (Author) / Rege, Kaushal (Thesis advisor) / Jayaraman, Arul (Committee member) / Nielsen, David (Committee member) / Kodibagkar, Vikram (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Alzheimer's disease (AD) is the most common type of dementia, affecting one in nine people age 65 and older. One of the most important neuropathological characteristics of Alzheimer's disease is the aggregation and deposition of the protein beta-amyloid. Beta-amyloid is produced by proteolytic processing of the Amyloid Precursor Protein (APP).

Alzheimer's disease (AD) is the most common type of dementia, affecting one in nine people age 65 and older. One of the most important neuropathological characteristics of Alzheimer's disease is the aggregation and deposition of the protein beta-amyloid. Beta-amyloid is produced by proteolytic processing of the Amyloid Precursor Protein (APP). Production of beta-amyloid from APP is increased when cells are subject to stress since both APP and beta-secretase are upregulated by stress. An increased beta-amyloid level promotes aggregation of beta-amyloid into toxic species which cause an increase in reactive oxygen species (ROS) and a decrease in cell viability. Therefore reducing beta-amyloid generation is a promising method to control cell damage following stress. The goal of this thesis was to test the effect of inhibiting beta-amyloid production inside stressed AD cell model. Hydrogen peroxide was used as stressing agent. Two treatments were used to inhibit beta-amyloid production, including iBSec1, an scFv designed to block beta-secretase site of APP, and DIA10D, a bispecific tandem scFv engineered to cleave alpha-secretase site of APP and block beta-secretase site of APP. iBSec1 treatment was added extracellularly while DIA10D was stably expressed inside cell using PSECTAG vector. Increase in reactive oxygen species and decrease in cell viability were observed after addition of hydrogen peroxide to AD cell model. The increase in stress induced toxicity caused by addition of hydrogen peroxide was dramatically decreased by simultaneously treating the cells with iBSec1 or DIA10D to block the increase in beta-amyloid levels resulting from the upregulation of APP and beta-secretase.
ContributorsSuryadi, Vicky (Author) / Sierks, Michael (Thesis advisor) / Nielsen, David (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Life Cycle Assessment (LCA) is used in the chemical process sector to compare the environmental merits of different product or process alternatives. One of the tasks that involves much time and cost in LCA studies is the specification of the exact materials and processes modeled which has limited its widespread

Life Cycle Assessment (LCA) is used in the chemical process sector to compare the environmental merits of different product or process alternatives. One of the tasks that involves much time and cost in LCA studies is the specification of the exact materials and processes modeled which has limited its widespread application. To overcome this, researchers have recently created probabilistic underspecification as an LCA streamlining method, which uses a structured data classification system to enable an LCA modeler to specify materials and processes in a less precise manner. This study presents a statistical procedure to understand when streamlined LCA methods can be used, and what their impact on overall model uncertainty is. Petrochemicals and polymer product systems were chosen to examine the impacts of underspecification and mis-specification applied to LCA modeling. Ecoinvent database, extracted using GaBi software, was used for data pertaining to generic crude oil refining and polymer manufacturing modules. By assessing the variation in LCA results arising out of streamlined materials classification, the developed statistics estimate the amount of overall error incurred by underspecifying and mis-specifying material impact data in streamlined LCA. To test the impact of underspecification and mis-specification at the level of a product footprint, case studies of HDPE containers and aerosol air fresheners were conducted. Results indicate that the variation in LCA results decreases as the specificity of materials increases. For the product systems examined, results show that most of the variability in impact assessment is due to the differences in the regions from which the environmental impact datasets were collected; the lower levels of categorization of materials have relatively smaller influence on the variance. Analyses further signify that only certain environmental impact categories viz. global warming potential, freshwater eutrophication, freshwater ecotoxicity, human toxicity and terrestrial ecotoxicity are affected by geographic variations. Outcomes for the case studies point out that the error in the estimation of global warming potential increases as the specificity of a component of the product decreases. Fossil depletion impact estimates remain relatively robust to underspecification. Further, the results of LCA are much more sensitive to underspecification of materials and processes than mis-specification.
ContributorsMurali, Ashwin Krishna (Author) / Dooley, Kevin (Thesis advisor) / Dai, Lenore (Thesis advisor) / Nielsen, David (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Control engineering offers a systematic and efficient approach to optimizing the effectiveness of individually tailored treatment and prevention policies, also known as adaptive or ``just-in-time'' behavioral interventions. These types of interventions represent promising strategies for addressing many significant public health concerns. This dissertation explores the development of decision algorithms for

Control engineering offers a systematic and efficient approach to optimizing the effectiveness of individually tailored treatment and prevention policies, also known as adaptive or ``just-in-time'' behavioral interventions. These types of interventions represent promising strategies for addressing many significant public health concerns. This dissertation explores the development of decision algorithms for adaptive sequential behavioral interventions using dynamical systems modeling, control engineering principles and formal optimization methods. A novel gestational weight gain (GWG) intervention involving multiple intervention components and featuring a pre-defined, clinically relevant set of sequence rules serves as an excellent example of a sequential behavioral intervention; it is examined in detail in this research.

 

A comprehensive dynamical systems model for the GWG behavioral interventions is developed, which demonstrates how to integrate a mechanistic energy balance model with dynamical formulations of behavioral models, such as the Theory of Planned Behavior and self-regulation. Self-regulation is further improved with different advanced controller formulations. These model-based controller approaches enable the user to have significant flexibility in describing a participant's self-regulatory behavior through the tuning of controller adjustable parameters. The dynamic simulation model demonstrates proof of concept for how self-regulation and adaptive interventions influence GWG, how intra-individual and inter-individual variability play a critical role in determining intervention outcomes, and the evaluation of decision rules.

 

Furthermore, a novel intervention decision paradigm using Hybrid Model Predictive Control framework is developed to generate sequential decision policies in the closed-loop. Clinical considerations are systematically taken into account through a user-specified dosage sequence table corresponding to the sequence rules, constraints enforcing the adjustment of one input at a time, and a switching time strategy accounting for the difference in frequency between intervention decision points and sampling intervals. Simulation studies illustrate the potential usefulness of the intervention framework.

The final part of the dissertation presents a model scheduling strategy relying on gain-scheduling to address nonlinearities in the model, and a cascade filter design for dual-rate control system is introduced to address scenarios with variable sampling rates. These extensions are important for addressing real-life scenarios in the GWG intervention.
ContributorsDong, Yuwen (Author) / Rivera, Daniel E (Thesis advisor) / Dai, Lenore (Committee member) / Forzani, Erica (Committee member) / Rege, Kaushal (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2014
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Description
The production of nanomaterials has been increasing and so are their applications in various products, while the environmental impacts and human impacts of these nanomaterials are still in the process of being explored. In this thesis, a process for

producing nano-titanium dioxide (nano-TiO2) is studied and a case-study has been

The production of nanomaterials has been increasing and so are their applications in various products, while the environmental impacts and human impacts of these nanomaterials are still in the process of being explored. In this thesis, a process for

producing nano-titanium dioxide (nano-TiO2) is studied and a case-study has been conducted on comparative Life Cycle Assessment (LCA) of the application of these nano-TiO2 particles in the sunscreen lotion as a UV-blocker with the conventional organic chemical sunscreen lotion using GaBi software. Nano-TiO2 particles were identified in the sunscreen lotion using Transmission Electron Microscope suggesting the use of these particles in the lotion.

The LCA modeling includes the comparison of the environmental impacts of producing nano-TiO2 particles with that of conventional organic chemical UV-blockers (octocrylene and avobenzone). It also compares the environmental life cycle impacts of the two sunscreen lotions studied. TRACI 2.1 was used for the assessment of the impacts which were then normalized and weighted for the ranking of the impact categories.

Results indicate that nano-TiO2 had higher impacts on the environment than the conventional organic chemical UV-blockers (octocrylene and avobenzone). For the two sunscreen lotions studied, nano-TiO2 sunscreen variant had lower environmental life cycle impacts than its counterpart because of the other chemicals used in the formulation. In the organic chemical sunscreen variant the major impacts came from production of glycerine, ethanol, and avobenzone but in the nano-TiO2 sunscreen variant the major impacts came from the production of nano-TiO2 particles.

Analysis further signifies the trade-offs between few environmental impact categories, for example, the human toxicity impacts were more in the nano-TiO2 sunscreen variant, but the other environmental impact categories viz. fossil fuel depletion, global warming potential, eutrophication were less compared to the organic chemical sunscreen variant.
ContributorsThakur, Ankita (Author) / Dooley, Kevin (Thesis advisor) / Dai, Lenore (Committee member) / Lind, Mary Laura (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Alzheimer's disease (AD) is the most common form of dementia leading to cognitive dysfunction and memory loss as well as emotional and behavioral disorders. It is the 6th leading cause of death in United States, and the only one among top 10 death causes that cannot be prevented, cured or

Alzheimer's disease (AD) is the most common form of dementia leading to cognitive dysfunction and memory loss as well as emotional and behavioral disorders. It is the 6th leading cause of death in United States, and the only one among top 10 death causes that cannot be prevented, cured or slowed. An estimated 5.4 million Americans live with AD, and this number is expected to triple by year 2050 as the baby boomers age. The cost of care for AD in the US is about $200 billion each year. Unfortunately, in addition to the lack of an effective treatment or AD, there is also a lack of an effective diagnosis, particularly an early diagnosis which would enable treatment to begin before significant neuronal damage has occurred.

Increasing evidence implicates soluble oligomeric forms of beta-amyloid and tau in the onset and progression of AD. While many studies have focused on beta-amyloid, soluble oligomeric tau species may also play an important role in AD pathogenesis. Antibodies that selectively identify and target specific oligomeric tau variants would be valuable tools for both diagnostic and therapeutic applications and also to study the etiology of AD and other neurodegenerative diseases.

Recombinant human tau (rhTau) in monomeric, dimeric, trimeric and fibrillar forms were synthesized and purified to perform LDH assay on human neuroblastoma cells, so that trimeric but not monomeric or dimeric rhTau was identified as extracellularly neurotoxic to neuronal cells. A novel biopanning protocol was designed based on phage display technique and atomic force microscopy (AFM), and used to isolate single chain antibody variable domain fragments (scFvs) that selectively recognize the toxic tau oligomers. These scFvs selectively bind tau variants in brain tissue of human AD patients and AD-related tau transgenic rodent models and have potential value as early diagnostic biomarkers for AD and as potential therapeutics to selectively target toxic tau aggregates.
ContributorsTian, Huilai (Author) / Sierks, Michael R (Thesis advisor) / Dai, Lenore (Committee member) / Tillery, Stephen H (Committee member) / Nielsen, David R (Committee member) / Stabenfeldt, Sarah (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Gene therapy is a promising technology for the treatment of various nonheritable and genetically acquired diseases. It involves delivery of a therapeutic gene into target cells to induce cellular responses against diseases. Successful gene therapy requires an efficient gene delivery vector to deliver genetic materials into target cells. There are

Gene therapy is a promising technology for the treatment of various nonheritable and genetically acquired diseases. It involves delivery of a therapeutic gene into target cells to induce cellular responses against diseases. Successful gene therapy requires an efficient gene delivery vector to deliver genetic materials into target cells. There are two major classes of gene delivery vectors: viral and non-viral vectors. Recently, non-viral vectors such as cationic polymers have attracted more attention than viral vectors because they are versatile and non-immunogenic. However, cationic polymers suffer from poor gene delivery efficiency due to biological barriers. The objective of this research is to develop strategies to overcome the barriers and enhance polymer-mediated transgene expression. This study aimed to (i) develop new polymer vectors for gene delivery, (ii) investigate the intracellular barriers in polymer-mediated gene delivery, and (iii) explore new approaches to overcome the barriers. A cationic polymer library was developed by employing a parallel synthesis and high-throughput screening method. Lead polymers from the library were identified from the library based on relative levels of transgene expression and toxicity in PC3-PSMA prostate cancer cells. However, transgene expression levels were found to depend on intracellular localization of polymer-gene complexes (polyplexes). Transgene expression was higher when polyplexes were dispersed rather than localized in the cytoplasm. Combination treatments using small molecule chemotherapeutic drugs, e.g. histone deacetylase inhibitors (HDACi) or Aurora kinase inhibitor (AKI) increased dispersion of polyplexes in the cytoplasm and significantly enhanced transgene expression. The combination treatment using polymer-mediated delivery of p53 tumor-suppressor gene and AKI increased p53 expression in PC3-PSMA cells, inhibited the cell proliferation by ~80% and induced apoptosis. Polymer-mediated p53 gene delivery in combination with AKI offers a promising treatment strategy for in vivo and clinical studies of cancer gene therapy.
ContributorsBarua, Sutapa (Author) / Rege, Kaushal (Thesis advisor) / Dai, Lenore (Committee member) / Meldrum, Deirdre R. (Committee member) / Sierks, Michael (Committee member) / Voelkel-Johnson, Christina (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Temporary bonding-debonding of flexible plastic substrates to rigid carriers may facilitate effective substrate handling by automated tools for manufacture of flexible microelectronics. The primary challenges in implementing practical temporary bond-debond technology originate from the stress that is developed during high temperature processing predominately through thermal-mechanical property mismatches between carrier, adhesive

Temporary bonding-debonding of flexible plastic substrates to rigid carriers may facilitate effective substrate handling by automated tools for manufacture of flexible microelectronics. The primary challenges in implementing practical temporary bond-debond technology originate from the stress that is developed during high temperature processing predominately through thermal-mechanical property mismatches between carrier, adhesive and substrate. These stresses are relaxed through bowing of the bonded system (substrate-adhesive-carrier), which causes wafer handling problems, or through delamination of substrate from rigid carrier. Another challenge inherent to flexible plastic substrates and linked to stress is their dimensional instability, which may manifest itself in irreversible deformation upon heating and cooling cycles. Dimensional stability is critical to ensure precise registration of different layers during photolithography. The global objective of this work is to determine comprehensive experimental characterization and develop underlying fundamental engineering concept that could enable widespread adoption and scale-up of temporary bonding processing protocols for flexible microelectronics manufacturing. A series of carriers with different coefficient of thermal expansion (CTE), modulus and thickness were investigated to correlate the thermo-mechanical properties of carrier with deformation behavior of bonded systems. The observed magnitude of system bow scaled with properties of carriers according to well-established Stoney's equation. In addition, rheology of adhesive impacted the deformation of bonded system. In particular, distortion-bowing behavior correlated directly with the relative loss factor of adhesive and flexible plastic substrate. Higher loss factor of adhesive compared to that of substrate allowed the stress to be relaxed with less bow, but led to significantly greater dimensional distortion. Conversely, lower loss factor of adhesive allowed less distortion but led to larger wafer bow. A finite element model using ANSYS was developed to predict the trend in bow-distortion of bonded systems as a function of the viscoelastic properties of adhesive. Inclusion of the viscoelasticity of flexible plastic substrate itself was critical to achieving good agreement between simulation and experiment. Simulation results showed that there is a limited range within which tuning the rheology of adhesive can control the stress-distortion. Therefore, this model can aid in design of new adhesive formulations compatible with different processing requirements of various flexible microelectronics applications.
ContributorsHaq, Jesmin (Author) / Raupp, Gregory B (Thesis advisor) / Vogt, Bryan D (Thesis advisor) / Dai, Lenore (Committee member) / Loy, Douglas (Committee member) / Li, Jian (Committee member) / Arizona State University (Publisher)
Created2011
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Description
Over the past years, an interest has arisen in resolving two major issues: increased carbon dioxide (CO2) emissions and depleting energy resources. A convenient solution would be a process that could simultaneously use CO2 while producing energy. The photocatalytic reduction of CO2 to fuels over the photocatalyst titanium dioxide (TiO2)

Over the past years, an interest has arisen in resolving two major issues: increased carbon dioxide (CO2) emissions and depleting energy resources. A convenient solution would be a process that could simultaneously use CO2 while producing energy. The photocatalytic reduction of CO2 to fuels over the photocatalyst titanium dioxide (TiO2) is such a process. However, this process is presently inefficient and unsuitable for industrial applications. A step toward making this process more effective is to alter TiO2 based photocatalysts to improve their activity. The interactions of CO2 with oxygen-deficient and unmodified (210) surfaces of brookite TiO2 were studied using first-principle calculations on cluster systems. Charge and spin density analyses were implemented to determine if charge transfer to the CO2 molecule occurred and whether this charge transfer was comparable to that seen with the oxygen-deficient and unmodified anatase TiO2 (101) surfaces. Although the unmodified brookite (210) surface provided energetically similar CO2 interactions as compared to the unmodified anatase (101) surface, the unmodified brookite surface had negligible charge transfer to the CO2 molecule. This result suggests that unmodified brookite is not a suitable catalyst for the reduction of CO2. However, the results also suggest that modification of the brookite surface through the creation of oxygen vacancies may lead to enhancements in CO2 reduction. The computational results were supported with laboratory data for CO2 interaction with perfect brookite and oxygen-deficient brookite. The laboratory data, generated using diffuse reflectance Fourier transform infrared spectroscopy, confirms the presence of CO2- on only the oxygen-deficient brookite. Additional computational work was performed on I-doped anatase (101) and I-doped brookite (210) surface clusters. Adsorption energies and charge and spin density analyses were performed and the results compared. While charge and spin density analyses showed minute charge transfer to CO2, the calculated adsorption energies demonstrated an increased affinity for CO2adsorption onto the I-doped brookite surface. Gathering the results from all calculations, the computational work on oxygen-deficient, I-doped, and unmodified anatase and brookite surface structures suggest that brookite TiO2 is a potential photocatalysts for CO2 photoreduction.
ContributorsRodriguez, Monique M (Author) / Andino, Jean M (Thesis advisor) / Nielsen, David R (Committee member) / Dai, Lenore (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Electronic devices based on various stimuli responsive polymers are anticipated to have great potential for applications in innovative electronics due to their inherent intelligence and flexibility. However, the electronic properties of these soft materials are poor and the applications have been limited due to their weak compatibility with functional materials.

Electronic devices based on various stimuli responsive polymers are anticipated to have great potential for applications in innovative electronics due to their inherent intelligence and flexibility. However, the electronic properties of these soft materials are poor and the applications have been limited due to their weak compatibility with functional materials. Therefore, the integration of stimuli responsive polymers with other functional materials like Silicon is strongly demanded. Here, we present successful strategies to integrate environmentally sensitive hydrogels with Silicon, a typical high-performance electronic material, and demonstrate the intelligent and stretchable capability of this system. The goal of this project is to develop integrated smart devices comprising of soft stimuli responsive polymeric-substrates with conventional semiconductor materials such as Silicon, which can respond to various external stimuli like pH, temperature, light etc. Specifically, these devices combine the merits of high quality crystalline semiconductor materials and the mechanical flexibility/stretchability of polymers. Our innovative system consists of ultra-thin Silicon ribbons bonded to an intelligently stretchable substrate which is intended to interpret and exert environmental signals and provide the desired stress relief. As one of the specific examples, we chose as a substrate the standard thermo-sensitive poly(N-isopropylacrylamide) (PNIPAAm) hydrogel with fast response and large deformation. In order to make the surface of the hydrogel waterproof and smooth for high-quality Silicon transfer, we introduced an intermediate layer of poly(dimethylsiloxane) (PDMS) between the substrate and the Silicon ribbons. The optical microscope results have shown that the system enables stiff Silicon ribbons to become adaptive and drivable by the soft environmentally sensitive substrate. Furthermore, we pioneered the development of complex geometries with two different methods: one is using stereolithography to electronically control the patterns and build up their profiles layer by layer; the other is integrating different multifunctional polymers. In this report, we have designed a bilayer structure comprising of a PNIPAAm hydrogel and a hybrid hydrogel of N-isopropylacrylamide (NIPAAm) and acrylic acid (AA). Typical variable curvatures can be obtained by the hydrogels with different dimensional expansion. These structures hold interesting possibilities in the design of electronic devices with tunable curvature.
ContributorsPan, Yuping (Author) / Dai, Lenore (Thesis advisor) / Jiang, Hanqing (Thesis advisor) / Lind, Mary Laura (Committee member) / Arizona State University (Publisher)
Created2012