Matching Items (157)
Description
Diabesity is a global epidemic affecting millions worldwide. Diabesity is the term given to the link between obesity and Type II diabetes. It is estimated that ~90% of patients diagnosed with Type II diabetes are overweight or have struggled with excess body fat in the past. Type II diabetes is characterized by insulin resistance which is an impaired response of the body to insulin that leads to high blood glucose levels. Adipose tissue, previously thought of as an inert tissue, is now recognized as a major endocrine organ with an important role in the body's immune response and the development of chronic inflammation. It is speculated that adipose tissue inflammation is a major contributor to insulin resistance particular to Type II diabetes. This literature review explores the popular therapeutic targets and marketed drugs for the treatment of Type II diabetes and their role in decreasing adipose tissue inflammation. rAGE is currently in pre-clinical studies as a possible target to combat adipose tissue inflammation due to its relation to insulin resistance. Metformin and Pioglitazone are two drugs already being marketed that use unique chemical pathways to increase the production of insulin and/or decrease blood glucose levels. Sulfonylureas is one of the first FDA approved drugs used in the treatment of Type II diabetes, however, it has been discredited due to its life-threatening side effects. Bariatric surgery is a form of invasive surgery to rid the body of excess fat and has shown to normalize blood glucose levels. These treatments are all secondary to lifestyle changes, such as diet and exercise which can help halt the progression of Type II diabetes patients.
ContributorsRobles, Alondra Maria (Author) / Woodbury, Neal (Thesis director) / Redding, Kevin (Committee member) / Allen, James (Committee member) / Hendrickson, Kirstin (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Recently, we have demonstrated that a novel RNA origami (RNA-OG) nanostructure functions as a TLR3 agonist both in vitro and in vivo. This RNA nanostructure could induce effective antitumor immunity in a CT26-OVA-iRFP tumor model that expresses both ovalbumin (OVA) and near infrared protein (iRFP), rendering a significant delay in tumor growth or complete tumor-regression. However, in a similar tumor line that expresses iRFP but not OVA, i.e. a CT26-Neo-iRFP model, RNA-OG induced responses that were consistently inferior to those observed in CT26-OVA-iRFP. Interestingly, the antitumor immunity initially generated against CT26-OVA-iRFP was found to render the mice immune to a challenge with the more malignant CT26-Neo-iRFP line. In addition to OVA expression, the two cell lines also showed different levels of MHC-I. Ongoing research has been focused on deciphering the molecular nature of the different responses. Then, we can search for strategies that increase the tumor immunogenicity, and therefore improve the therapeutic efficacy of RNA-OG for inducing long-term tumor-regression.
ContributorsMatiski, Lawrence Theodore Mazzei (Author) / Chang, Yung (Thesis director) / Yan, Hao (Committee member) / School of Molecular Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The Heliobacterial Reaction Center (HbRC) is the simplest Type I Reaction Center (RC) known today. However, upon illumination it has been found to produce menaquinol, and this has led to experiments investigating the function of this reduction scheme. The goal of the experiment was to investigate the mechanisms of menaquinol production through the use of Photosystem II (PSII) herbicides that are known to inhibit the QB quinone site in Type II RCs. Seven herbicides were chosen, and out of all of them terbuthylazine showed the greatest effect on the RC in isolated membranes when Transient Absorption Spectroscopy was used. In addition, terbuthylazine decreased menaquinone reduction to menaquinol by ~72%, slightly more than the reported effect of teburtryn (68%)1. In addition, terbuthylazine significantly impacted growth of whole cells under high light more than terbutryn.
ContributorsOdeh, Ahmad Osameh (Author) / Redding, Kevin (Thesis director) / Woodbury, Neal (Committee member) / Allen, James (Committee member) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Predicting the binding sites of proteins has historically relied on the determination of protein structural data. However, the ability to utilize binding data obtained from a simple assay and computationally make the same predictions using only sequence information would be more efficient, both in time and resources. The purpose of this study was to evaluate the effectiveness of an algorithm developed to predict regions of high-binding on proteins as it applies to determining the regions of interaction between binding partners. This approach was applied to tumor necrosis factor alpha (TNFα), its receptor TNFR2, programmed cell death protein-1 (PD-1), and one of its ligand PD-L1. The algorithms applied accurately predicted the binding region between TNFα and TNFR2 in which the interacting residues are sequential on TNFα, however failed to predict discontinuous regions of binding as accurately. The interface of PD-1 and PD-L1 contained continuous residues interacting with each other, however this region was predicted to bind weaker than the regions on the external portions of the molecules. Limitations of this approach include use of a linear search window (resulting in inability to predict discontinuous binding residues), and the use of proteins with unnaturally exposed regions, in the case of PD-1 and PD-L1 (resulting in observed interactions which would not occur normally). However, this method was overall very effective in utilizing the available information to make accurate predictions. The use of the microarray to obtain binding information and a computer algorithm to analyze is a versatile tool capable of being adapted to refine accuracy.
ContributorsBrooks, Meilia Catherine (Author) / Woodbury, Neal (Thesis director) / Diehnelt, Chris (Committee member) / Ghirlanda, Giovanna (Committee member) / Department of Psychology (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The free-base tetra-tolyl-porphyrin and the corresponding cobalt and iron porphyrin complexes were synthesized and characterized to show that this class of compound can be promising, tunable catalysts for carbon dioxide reduction. During cyclic voltammetry experiments, the iron porphyrin showed an on-set of ‘catalytic current’ at an earlier potential than the cobalt porphyrin’s in organic solutions gassed with carbon dioxide. The cobalt porphyrin yielded larger catalytic currents, but at the same potential as the electrode. This difference, along with the significant changes in the porphyrin’s electronic, optical and redox properties, showed that its capabilities for carbon dioxide reduction can be controlled by metal ions, allotting it unique opportunities for applications in solar fuels catalysis and photochemical reactions.
ContributorsSkibo, Edward Kim (Author) / Moore, Gary (Thesis director) / Woodbury, Neal (Committee member) / School of Molecular Sciences (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
ABSTRACT Peptide microarrays may prove to be a powerful tool for proteomics research and clinical diagnosis applications. Fodor et al. and Maurer et al. have shown proof-of-concept methods of light- and electrochemically-directed peptide microarray fabrication on glass and semiconductor microchips respectively. In this work, peptide microarray fabrication based on the abovementioned techniques were optimized. In addition, MALDI mass spectrometry based peptide synthesis characterization on semiconductor microchips was developed and novel applications of a CombiMatrix (CBMX) platform for electrochemically controlled synthesis were explored. We have investigated performance of 2-(2-nitrophenyl)propoxycarbonyl (NPPOC) derivatives as photo-labile protecting group. Specifically, influence of substituents on 4 and 5 positions of phenyl ring of NPPOC group on the rate of photolysis and the yield of the amine was investigated. The results indicated that substituents capable of forming a π-network with the nitro group enhanced the rate of photolysis and yield. Once such properly substituted NPPOC groups were used, the rate of photolysis/yield depended on the nature of protected amino group indicating that a different chemical step during the photo-cleavage process became the rate limiting step. We also focused on electrochemically-directed parallel synthesis of high-density peptide microarrays using the CBMX technology referred to above which uses electrochemically generated acids to perform patterned chemistry. Several issues related to peptide synthesis on the CBMX platform were studied and optimized, with emphasis placed on the reactions of electro-generated acids during the deprotection step of peptide synthesis. We have developed a MALDI mass spectrometry based method to determine the chemical composition of microarray synthesis, directly on the feature. This method utilizes non-diffusional chemical cleavage from the surface, thereby making the chemical characterization of high-density microarray features simple, accurate, and amenable to high-throughput. CBMX Corp. has developed a microarray reader which is based on electro-chemical detection of redox chemical species. Several parameters of the instrument were studied and optimized and novel redox applications of peptide microarrays on CBMX platform were also investigated using the instrument. These include (i) a search of metal binding catalytic peptides to reduce overpotential associated with water oxidation reaction and (ii) an immobilization of peptide microarrays using electro-polymerized polypyrrole.
ContributorsKumar, Pallav (Author) / Woodbury, Neal (Thesis advisor) / Allen, James (Committee member) / Johnston, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
Membrane proteins act as sensors, gatekeepers and information carriers in the cell membranes. Functional engineering of these proteins is important for the development of molecular tools for biosensing, therapeutics and as components of artificial cells. However, using protein engineering to modify existing protein structures is challenging due to the limitations of structural changes and difficulty in folding polypeptides into defined protein structures. Recent studies have shown that nanoscale architectures created by DNA nanotechnology can be used to mimic various protein functions, including some membrane proteins. However, mimicking the highly sophisticated structural dynamics of membrane proteins by DNA nanostructures is still in its infancy, mainly due to lack of transmembrane DNA nanostructures that can mimic the dynamic behavior, ubiquitous to membrane proteins. Here, I demonstrate design of dynamic DNA nanostructures to mimic two important class of membrane proteins. First, I describe a DNA nanostructure that inserts through lipid membrane and dynamically reconfigures upon sensing a membrane-enclosed DNA or RNA target, thereby transducing biomolecular information across the lipid membrane similar to G-protein coupled receptors (GPCR’s). I use the non-destructive sensing property of our GPCR-mimetic nanodevice to sense cancer associated micro-RNA biomarkers inside exosomes without the need of RNA extraction and amplification. Second, I demonstrate a fully reversibly gated DNA nanopore that mimics the ligand mediated gating of ion channel proteins. The 20.4 X 20.4 nm-wide channel of the DNA nanopore allows timed delivery of folded proteins across synthetic and biological membranes. These studies represent early examples of dynamic DNA nanostructures in mimicking membrane protein functions. I envision that they will be used in synthetic biology to create artificial cells containing GPCR-like and ion channel-like receptors, in site-specific drug or vaccine delivery and highly sensitive biosensing applications.
ContributorsDey, Swarup (Author) / Yan, Hao (Thesis advisor) / Hariadi, Rizal F (Thesis advisor) / Liu, Yan (Committee member) / Stephanopoulos, Nicholas (Committee member) / Arizona State University (Publisher)
Created2021
Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
Description
Interdigitated back contact (IBC) solar cells have achieved the highest single junction silicon wafer-based solar cell power conversion efficiencies reported to date. This thesis is about the fabrication of a high-efficiency silicon heterojunction IBC solar cell for potential use as the bottom cell for a 3-terminal lattice-matched dilute-nitride Ga (In)NP(As)/Si monolithic tandem solar cell. An effective fabrication process has been developed and the process challenges related to open circuit voltage (Voc), series resistance (Rs), and fill factor (FF) are experimentally analyzed. While wet etching, the sample lost the initial passivation, and by changing the etchant solution and passivation process, the voltage at maximum power recovered to an initial value of over 710 mV before metallization. The factors reducing the series resistance loss in IBC cells were also studied. One of these factors was the Indium Tin Oxide (ITO) sputtering parameters, which impact the conductivity of the ITO layer and transport across the a-Si:H/ITO interface. For the standard recipe, the chamber pressure was 3.5 mTorr with no oxygen partial pressure, and the thickness of the ITO layer in contact with the a-Si:H layers, was optimized to 150 nm. The patterning method for the metal contacts and final annealing also change the contact resistance of the base and emitter stack layers. The final annealing step is necessary to recover the sputtering damage; however, the higher the annealing time the higher the final IBC series resistance. The best efficiency achieved was 19.3% (Jsc = 37 mA/cm2, Voc = 691 mV, FF = 71.7%) on 200 µm thick 1-15 Ω-cm n-type CZ C-Si with a designated area of 4 cm2.
ContributorsMoeini Rizi, Mansoure (Author) / Goodnick, Stephen (Thesis advisor) / Honsberg, Christina (Committee member) / Goryll, Michael (Committee member) / Smith, David (Committee member) / Bowden, Stuart (Committee member) / Arizona State University (Publisher)
Created2022
Description
The future will be replete with Artificial Intelligence (AI) based agents closely collaborating with humans. Although it is challenging to construct such systems for real-world conditions, the Intelligent Tutoring System (ITS) community has proposed several techniques to work closely with students. However, there is a need to extend these systems outside the controlled environment of the classroom. More recently, Human-Aware Planning (HAP) community has developed generalized AI techniques for collaborating with humans and providing personalized support or guidance to the collaborators. In this thesis, the take learning from the ITS community is extend to construct such human-aware systems for real-world domains and evaluate them with real stakeholders. First, the applicability of HAP to ITS is demonstrated, by modeling the behavior in a classroom and a state-of-the-art tutoring system called Dragoon. Then these techniques are extended to provide decision support to a human teammate and evaluate the effectiveness of the framework through ablation studies to support students in constructing their plan of study (\ipos). The results show that these techniques are helpful and can support users in their tasks. In the third section of the thesis, an ITS scenario of asking questions (or problems) in active environments is modeled by constructing questions to elicit a human teammate's model of understanding. The framework is evaluated through a user study, where the results show that the queries can be used for eliciting the human teammate's mental model.
ContributorsGrover, Sachin (Author) / Kambhampati, Subbarao (Thesis advisor) / Smith, David (Committee member) / Srivastava, Sidhharth (Committee member) / VanLehn, Kurt (Committee member) / Arizona State University (Publisher)
Created2022