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Description
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
High temperature CO2 perm-selective membranes offer potential for uses in various processes for CO2 separation. Recently, efforts are reported on fabrication of dense ceramic-carbonate dual-phase membranes. The membranes provide selective permeation to CO2 and exhibit high permeation flux at high temperature. Research on transport mechanism demonstrates that gas transport for

High temperature CO2 perm-selective membranes offer potential for uses in various processes for CO2 separation. Recently, efforts are reported on fabrication of dense ceramic-carbonate dual-phase membranes. The membranes provide selective permeation to CO2 and exhibit high permeation flux at high temperature. Research on transport mechanism demonstrates that gas transport for ceramic-carbonate dual-phase membrane is rate limited by ion transport in ceramic support. Reducing membrane thickness proves effective to improve permeation flux. This dissertation reports strategy to prepare thin ceramic-carbonate dual-phase membranes to increase CO2 permeance. The work also presents characteristics and gas permeation properties of the membranes. Thin ceramic-carbonate dual-phase membrane was constructed with an asymmetric porous support consisting of a thin small-pore ionic conducting ceramic top-layer and a large pore base support. The base support must be carbonate non-wettable to ensure formation of supported dense, thin membrane. Macroporous yttria-stabilized zirconia (YSZ) layer was prepared on large pore Bi1.5Y0.3Sm0.2O3-δ (BYS) base support using suspension coating method. Thin YSZ-carbonate dual-phase membrane (d-YSZ/BYS) was prepared via direct infiltrating Li/Na/K carbonate mixtures into top YSZ layers. The thin membrane of 10 μm thick offered a CO2 flux 5-10 times higher than the thick dual-phase membranes. Ce0.8Sm0.2O1.9 (SDC) exhibited highest CO2 flux and long-term stability and was chosen as ceramic support for membrane performance improvement. Porous SDC layers were co-pressed on base supports using SDC and BYS powder mixtures which provided better sintering comparability and carbonate non-wettability. Thin SDC-carbonate dual-phase membrane (d-SDC/SDC60BYS40) of 150 μm thick was synthesized on SDC60BYS40. CO2 permeation flux for d-SDC/SDC60BYS40 exhibited increasing dependence on temperature and partial pressure gradient. The flux was higher than other SDC-based dual-phase membranes. Reducing membrane thickness proves effective to increase CO2 permeation flux for the dual-phase membrane.
ContributorsLu, Bo (Author) / Lin, Yuesheng (Thesis advisor) / Crozier, Peter (Committee member) / Herrmann, Macus (Committee member) / Forzani, Erica (Committee member) / Lind, Mary Laura (Committee member) / Arizona State University (Publisher)
Created2014
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Description
A new photocatalytic material was synthesized to investigate its performance for the photoreduction of carbon dioxide (CO2) in the presence of water vapor (H2O) to valuable products such as carbon monoxide (CO) and methane (CH4). The performance was studied using a gas chromatograph (GC) with a flame ionization detector (FID)

A new photocatalytic material was synthesized to investigate its performance for the photoreduction of carbon dioxide (CO2) in the presence of water vapor (H2O) to valuable products such as carbon monoxide (CO) and methane (CH4). The performance was studied using a gas chromatograph (GC) with a flame ionization detector (FID) and a thermal conductivity detector (TCD). The new photocatalytic material was an ionic liquid functionalized reduced graphite oxide (IL-RGO (high conductive surface))-TiO2 (photocatalyst) nanocomposite. Brunauer-Emmett-Teller (BET), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, and UV-vis absorption spectroscopy techniques were employed to characterize the new catalyst. In the series of experiments performed, the nanocomposite material was confined in a UV-quartz batch reactor, exposed to CO2 and H2O and illuminated by UV light. The primary product formed was CO with a maximum production ranging from 0.18-1.02 µmol(gcatalyst-hour)-1 for TiO2 and 0.41-1.41 µmol(gcatalyst-hour)-1 for IL-RGO-TiO2. A trace amount of CH4 was also formed with its maximum ranging from 0.009-0.01 µmol(gcatalyst-hour)-1 for TiO2 and 0.01-0.04 µmol(gcatalyst-hour)-1 for IL-RGO-TiO2. A series of background experiments were conducted and results showed that; (a) the use of a ionic liquid functionalized reduced graphite oxide -TiO2 produced more products as compared to commercial TiO2, (b) the addition of methanol as a hole scavenger boosted the production of CO but not CH4, (c) a higher and lower reduction time of IL-RGO as compared to the usual 24 hours of reduction presented basically the same production of CO and CH4, (d) the positive effect of having an ionic liquid was demonstrated by the double production of CO obtained for IL-RGO-TiO2 as compared to RGO-TiO2 and (e) a change in the amount of IL-RGO in the IL-RGO-TiO2 represented a small difference in the CO production but not in the CH4 production. This work ultimately demonstrated the huge potential of the utility of a UV-responsive ionic liquid functionalized reduced graphite oxide-TiO2 nano-composite for the reduction of CO2 in the presence of H2O for the production of fuels.
ContributorsCastañeda Flores, Alejandro (Author) / Andino, Jean M (Thesis advisor) / Forzani, Erica (Committee member) / Torres, Cesar (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
Identification of early damage in polymer composite materials is of significant importance so that preventative measures can be taken before the materials reach catastrophic failure. Scientists have been developing damage detection technologies over many years and recently, mechanophore-based polymers, in which mechanical energy is translated to activate a chemical transformation,

Identification of early damage in polymer composite materials is of significant importance so that preventative measures can be taken before the materials reach catastrophic failure. Scientists have been developing damage detection technologies over many years and recently, mechanophore-based polymers, in which mechanical energy is translated to activate a chemical transformation, have received increasing attention. More specifically, the damage can be made detectable by mechanochromic polymers, which provide a visible color change upon the scission of covalent bonds under stress. This dissertation focuses on the study of a novel self-sensing framework for identifying early and in-situ damage by employing unique stress-sensing mechanophores. Two types of mechanophores, cyclobutane and cyclooctane, were utilized, and the former formed from cinnamoyl moeities and the latter formed from anthracene upon photodimerization. The effects on the thermal and mechanical properties with the addition of the cyclobutane-based polymers into epoxy matrices were investigated. The emergence of cracks was detected by fluorescent signals at a strain level right after the yield point of the polymer blends, and the fluorescence intensified with the accumulation of strain. Similar to the mechanism of fluorescence emission from the cleavage of cyclobutane, the cyclooctane moiety generated fluorescent emission with a higher quantum yield upon cleavage. The experimental results also demonstrated the success of employing the cyclooctane type mechanophore as a potential force sensor, as the fluorescence intensification was correlated with the strain increase.
ContributorsZou, Jin (Author) / Dai, Lenore L (Thesis advisor) / Chattopadhyay, Aditi (Thesis advisor) / Lind, Mary L (Committee member) / Mu, Bin (Committee member) / Yu, Hongyu (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
We report the synthesis of novel boronic acid-containing metal-organic frameworks (MOFs), which was synthesized via solvothermal synthesis of cobalt nitride with 3,5-Dicarboxyphenylboronic acid (3,5-DCPBC). Powder X-ray diffraction and BET surface area analysis have been used to verify the successful synthesis of this microporous material.

We have also made the attempts

We report the synthesis of novel boronic acid-containing metal-organic frameworks (MOFs), which was synthesized via solvothermal synthesis of cobalt nitride with 3,5-Dicarboxyphenylboronic acid (3,5-DCPBC). Powder X-ray diffraction and BET surface area analysis have been used to verify the successful synthesis of this microporous material.

We have also made the attempts of using zinc nitride and copper nitride as metal sources to synthesize the boronic acid-containing MOFs. However, the attempts were not successful. The possible reason is the existence of copper and zinc ions catalyzed the decomposition of 3,5-Dicarboxyphenylboronic acid, forming isophthalic acid. The ended product has been proved to be isophthalic acid crystals by the single crystal X-ray diffraction. The effects of solvents, reaction temperature, and added bases were investigated. The addition of triethylamine has been shown to tremendously improve the sample crystallinity by facilitating ligand deprotonation
ContributorsYu, Jiuhao (Author) / Mu, Bin (Thesis advisor) / Forzani, Erica (Committee member) / Nielsen, David (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