Matching Items (116)
Filtering by
Description
Colorimetric assays are an important tool in point-of-care testing that offers several advantages to traditional testing methods such as rapid response times and inexpensive costs. A factor that currently limits the portability and accessibility of these assays are methods that can objectively determine the results of these assays. Current solutions consist of creating a test reader that standardizes the conditions the strip is under before being measured in some way. However, this increases the cost and decreases the portability of these assays. The focus of this study is to create a machine learning algorithm that can objectively determine results of colorimetric assays under varying conditions. To ensure the flexibility of a model to several types of colorimetric assays, three models were trained on the same convolutional neural network with different datasets. The images these models are trained on consist of positive and negative images of ETG, fentanyl, and HPV Antibodies test strips taken under different lighting and background conditions. A fourth model is trained on an image set composed of all three strip types. The results from these models show it is able to predict positive and negative results to a high level of accuracy.
ContributorsFisher, Rachel (Author) / Blain Christen, Jennifer (Thesis director) / Anderson, Karen (Committee member) / School of Life Sciences (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
In this thesis I introduce a new direction to computing using nonlinear chaotic dynamics. The main idea is rich dynamics of a chaotic system enables us to (1) build better computers that have a flexible instruction set, and (2) carry out computation that conventional computers are not good at it. Here I start from the theory, explaining how one can build a computing logic block using a chaotic system, and then I introduce a new theoretical analysis for chaos computing. Specifically, I demonstrate how unstable periodic orbits and a model based on them explains and predicts how and how well a chaotic system can do computation. Furthermore, since unstable periodic orbits and their stability measures in terms of eigenvalues are extractable from experimental times series, I develop a time series technique for modeling and predicting chaos computing from a given time series of a chaotic system. After building a theoretical framework for chaos computing I proceed to architecture of these chaos-computing blocks to build a sophisticated computing system out of them. I describe how one can arrange and organize these chaos-based blocks to build a computer. I propose a brand new computer architecture using chaos computing, which shifts the limits of conventional computers by introducing flexible instruction set. Our new chaos based computer has a flexible instruction set, meaning that the user can load its desired instruction set to the computer to reconfigure the computer to be an implementation for the desired instruction set. Apart from direct application of chaos theory in generic computation, the application of chaos theory to speech processing is explained and a novel application for chaos theory in speech coding and synthesizing is introduced. More specifically it is demonstrated how a chaotic system can model the natural turbulent flow of the air in the human speech production system and how chaotic orbits can be used to excite a vocal tract model. Also as another approach to build computing system based on nonlinear system, the idea of Logical Stochastic Resonance is studied and adapted to an autoregulatory gene network in the bacteriophage λ.
ContributorsKia, Behnam (Author) / Ditto, William (Thesis advisor) / Huang, Liang (Committee member) / Lai, Ying-Cheng (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
Description
V(D)J recombination is responsible for generating an enormous repertoire of immunoglobulins and T cell receptors, therefore it is a centerpiece to the formation of the adaptive immune system. The V(D)J recombination process proceeds through two steps, site-specific cleavage at RSS (Recombination Signal Sequence) site mediated by the RAG recombinase (RAG1/2) and the subsequent imprecise resolution of the DNA ends, which is carried out by the ubiquitous non-homologous end joining pathway (NHEJ). The V(D)J recombination reaction is obliged to be tightly controlled under all circumstances, as it involves generations of DNA double strand breaks, which are considered the most dangerous lesion to a cell. Multifaceted regulatory mechanisms have been evolved to create great diversity of the antigen receptor repertoire while ensuring genome stability. The RAG-mediated cleavage reaction is stringently regulated at both the pre-cleavage stage and the post-cleavage stage. Specifically, RAG1/2 first forms a pre-cleavage complex assembled at the boarder of RSS and coding flank, which ensures the appropriate DNA targeting. Subsequently, this complex initiates site-specific cleavage, generating two types of double stranded DNA breaks, hairpin-ended coding ends (HP-CEs) and blunt signal ends (SEs). After the cleavage, RAG1/2 proteins bind and retain the recombination ends to form post-cleavage complexes (PCC), which collaborates with the NHEJ machinery for appropriate transfer of recombination ends to NHEJ for proper end resolution. However, little is known about the molecular basis of this collaboration, partly attributed to the lack of sensitive assays to reveal the interaction of PCC with HP-CEs. Here, for the first time, by using two complementary fluorescence-based techniques, fluorescence anisotropy and fluorescence resonance energy transfer (FRET), I managed to monitor the RAG1/2-catalyzed cleavage reaction in real time, from the pre-cleavage to the post-cleavage stages. By examining the dynamic fluorescence changes during the RAG-mediated cleavage reactions, and by manipulating the reaction conditions, I was able to characterize some fundamental properties of RAG-DNA interactions before and after cleavage. Firstly, Mg2+, known as a physiological cofactor at the excision step, also promotes the HP-CEs retention in the RAG complex after cleavage. Secondly, the structure of pre-cleavage complex may affect the subsequent collaborations with NHEJ for end resolution. Thirdly, the non-core region of RAG2 may have differential influences on the PCC retention of HP-CEs and SEs. Furthermore, I also provide the first evidence of RAG1-mediated regulation of RAG2. Our study provides important insights into the multilayered regulatory mechanisms, in modulating recombination events in developing lymphocytes and paves the way for possible development of detection and diagnotic markers for defective recombination events that are often associated immunodeficiency and/or lymphoid malignancy.
ContributorsWang, Guannan (Author) / Chang, Yung (Thesis advisor) / Levitus, Marcia (Committee member) / Misra, Rajeev (Committee member) / Anderson, Karen (Committee member) / Arizona State University (Publisher)
Created2012
Description
Complex dynamical systems consisting interacting dynamical units are ubiquitous in nature and society. Predicting and reconstructing nonlinear dynamics of units and the complex interacting networks among them serves the base for the understanding of a variety of collective dynamical phenomena. I present a general method to address the two outstanding problems as a whole based solely on time-series measurements. The method is implemented by incorporating compressive sensing approach that enables an accurate reconstruction of complex dynamical systems in terms of both nodal equations that determines the self-dynamics of units and detailed coupling patterns among units. The representative advantages of the approach are (i) the sparse data requirement which allows for a successful reconstruction from limited measurements, and (ii) general applicability to identical and nonidentical nodal dynamics, and to networks with arbitrary interacting structure, strength and sizes. Another two challenging problem of significant interest in nonlinear dynamics: (i) predicting catastrophes in nonlinear dynamical systems in advance of their occurrences and (ii) predicting the future state for time-varying nonlinear dynamical systems, can be formulated and solved in the framework of compressive sensing using only limited measurements. Once the network structure can be inferred, the dynamics behavior on them can be investigated, for example optimize information spreading dynamics, suppress cascading dynamics and traffic congestion, enhance synchronization, game dynamics, etc. The results can yield insights to control strategies design in the real-world social and natural systems. Since 2004, there has been a tremendous amount of interest in graphene. The most amazing feature of graphene is that there exists linear energy-momentum relationship when energy is low. The quasi-particles inside the system can be treated as chiral, massless Dirac fermions obeying relativistic quantum mechanics. Therefore, the graphene provides one perfect test bed to investigate relativistic quantum phenomena, such as relativistic quantum chaotic scattering and abnormal electron paths induced by klein tunneling. This phenomenon has profound implications to the development of graphene based devices that require stable electronic properties.
ContributorsYang, Rui (Author) / Lai, Ying-Cheng (Thesis advisor) / Duman, Tolga M. (Committee member) / Akis, Richard (Committee member) / Huang, Liang (Committee member) / Arizona State University (Publisher)
Created2012
Description
What can classical chaos do to quantum systems is a fundamental issue highly relevant to a number of branches in physics. The field of quantum chaos has been active for three decades, where the focus was on non-relativistic quantumsystems described by the Schr¨odinger equation. By developing an efficient method to solve the Dirac equation in the setting where relativistic particles can tunnel between two symmetric cavities through a potential barrier, chaotic cavities are found to suppress the spread in the tunneling rate. Tunneling rate for any given energy assumes a wide range that increases with the energy for integrable classical dynamics. However, for chaotic underlying dynamics, the spread is greatly reduced. A remarkable feature, which is a consequence of Klein tunneling, arise only in relativistc quantum systems that substantial tunneling exists even for particle energy approaching zero. Similar results are found in graphene tunneling devices, implying high relevance of relativistic quantum chaos to the development of such devices. Wave propagation through random media occurs in many physical systems, where interesting phenomena such as branched, fracal-like wave patterns can arise. The generic origin of these wave structures is currently a matter of active debate. It is of fundamental interest to develop a minimal, paradigmaticmodel that can generate robust branched wave structures. In so doing, a general observation in all situations where branched structures emerge is non-Gaussian statistics of wave intensity with an algebraic tail in the probability density function. Thus, a universal algebraic wave-intensity distribution becomes the criterion for the validity of any minimal model of branched wave patterns. Coexistence of competing species in spatially extended ecosystems is key to biodiversity in nature. Understanding the dynamical mechanisms of coexistence is a fundamental problem of continuous interest not only in evolutionary biology but also in nonlinear science. A continuous model is proposed for cyclically competing species and the effect of the interplay between the interaction range and mobility on coexistence is investigated. A transition from coexistence to extinction is uncovered with a non-monotonic behavior in the coexistence probability and switches between spiral and plane-wave patterns arise. Strong mobility can either promote or hamper coexistence, while absent in lattice-based models, can be explained in terms of nonlinear partial differential equations.
ContributorsNi, Xuan (Author) / Lai, Ying-Cheng (Thesis advisor) / Huang, Liang (Committee member) / Yu, Hongbin (Committee member) / Akis, Richard (Committee member) / Arizona State University (Publisher)
Created2012
Description
Introduction: Human papillomavirus (HPV) infection is seen in up to 90% of cases of cervical cancer, the third leading cancer cause of death in women. Current HPV screening focuses on only two HPV types and covers roughly 75% of HPV-associated cervical cancers. A protein based assay to test for antibody biomarkers against 98 HPV antigens from both high and low risk types could provide an inexpensive and reliable method to screen for patients at risk of developing invasive cervical cancer. Methods: 98 codon optimized, commercially produced HPV genes were cloned into the pANT7_cGST vector, amplified in a bacterial host, and purified for mammalian expression using in vitro transcription/translation (IVTT) in a luminescence-based RAPID ELISA (RELISA) assay. Monoclonal antibodies were used to determine immune cross-reactivity between phylogenetically similar antigens. Lastly, several protein characteristics were examined to determine if they correlated with protein expression. Results: All genes were successfully moved into the destination vector and 86 of the 98 genes (88%) expressed protein at an adequate level. A difference was noted in expression by gene across HPV types but no correlation was found between protein size, pI, or aliphatic index and expression. Discussion: Further testing is needed to express the remaining 12 HPV genes. Once all genes have been successfully expressed and purified at high concentrations, DNA will be printed on microscope slides to create a protein microarray. This microarray will be used to screen HPV-positive patient sera for antibody biomarkers that may be indicative of cervical cancer and precancerous cervical neoplasias.
ContributorsMeshay, Ian Matthew (Author) / Anderson, Karen (Thesis director) / Magee, Mitch (Committee member) / Katchman, Benjamin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Background: Measles virus (MV) infections are the main cause of vaccine-preventable death in children younger than 5 years. The World Health Organization (WHO) has estimated there are over 20 million cases of measles every year. Currently, diagnostic methods rely on enzyme immunoassays (EIA) to detect IgM or IgG Abs in serum. These commercial assays measure reactivity against the immunodominant N antigen and can have a false negative rates of 20-30%. Centralized testing by clinical labs can delay rapid screening in an outbreak setting. This study aims to develop a rapid molecular diagnostic assay to detect IgG reactive to five individual MV proteins representing 85% of the measles proteome. Methods: MV genes were subcloned into pANT_cGST vector to generate C-terminal GST fusion proteins. Single MV cistrons were expressed using in vitro transcription/translation (IVTT) with human cell lysate. Expression of GST-tagged proteins was measured using a sandwich ELISA for GST expression using relative light units (RLUs) as readouts. Single MV antigens were used as bait to determine the IgG-dependent reactivity in 12 serum samples obtained from immunized animals with previously determined neutralization titer (NT) and the correlation between NT and ELISA reactivity was determined. Results: Protein expression of five measles genes of interest, M, N, F, H, and L, was measured. L exhibited the strongest protein expression with an average RLU value of 4.34 x 10^9. All proteins were expressed at least 50% greater than control (2.33 x 10^7 RLU). As expected, reactivity against the N was the highest, followed by reactivity against M, F, H and L. The best correlation with NT titer was reactivity against F (R^2 = 0.62). Conclusion: These data indicate that the expression of single MV genes M, N, F, H, and L are suitable antigens for serologic capture analysis of measles immunity.
ContributorsMushtaq, Zuena (Author) / Anderson, Karen (Thesis director) / Reyes del Valle, Jorge (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
F2-isoprostanes are a series of prostaglandin-like compounds derived from the free radical-mediated lipid peroxidation of arachidonic acid, a polyunsaturated fatty acid that is ubiquitously expressed in cell membranes. F2-isoprostanes are biomarkers of oxidative stress, an imbalance between oxidants and antioxidants that can cause damage to DNA, proteins, lipids, and carbohydrates. Increased production of lipid peroxidation products have been implicated in the pathology of a number of conditions and diseases in humans. The objective of this thesis was to (1) optimize the LC/MS/MS F2-isoprostane method currently used in human samples for use in research animals and veterinary medicine, including the use of solid phase extraction, and (2) validate the optimized method in rodent and canine experimental studies. Our optimized method showed that Lyprinol treatment in dogs with osteoarthritis decreases F2-isoprostane levels nearly 2-fold. In addition, adjuvant alpha-tocopherol prevented tumor-induced increased F2-isoprostane levels. Finally, contrary to earlier studies using less specific ELISA F2-isoprostane methods, we demonstrate that unconditioned dogs benefit from low intensity exercise. Our data demonstrate successful optimization of the human LC/MS/MS F2-isoprostane method in rats and canines. Importantly, our results emphasize the need to use the more sensitive and specific LC/MS/MS method as compared to ELISA-based assays in order to distinguish the 15- and 5-series F2-isoprostanes, evidenced in particular by the two canine studies.
ContributorsCorrigan, Devin Connell (Author) / Redding, Kevin (Thesis director) / Anderson, Karen (Committee member) / Mustacich, Debbie (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
Background: Human papillomavirus (HPV) is the cause of 99.7% of cervical cancers. Research of cervical cancer has made this disease mostly curable in the developing world. Head and neck cancer, which is increasingly caused by HPV, still is associated with a mortality rate of 50,000 in the US annually. This study proposed to evaluate the biology of HPV-16 in head and neck tumors by using RT-qPCR to measure the RNA expression and its relation to physical status of the virus. Methods: This study was to develop an assay that uses RT-qPCR to determine the quantitative expression of HPV-16 RNA coding for proteins E1, E2, E4, E5, E6, and E7 in tumor samples. The assay development started with creation of primers. It went on to test the primers on template DNA through traditional PCR and then on DNA from HPV-16 positive cell lines, SiHa and CaSki, using RT-qPCR. This paper also describes the troubleshooting methods taken for the PCR reaction. Once the primers are verified, the RT-qPCR process can be carried out on RNA purified from tumor samples. Results: No primer sets have been confirmed to produce a product through PCR or RT-qPCR. The primer sequences match up correctly with known sequences for HPV-16 E1, E2, E4, E5, E6, and E7. RT-qPCR showed results consistent with the hypothesis. Conclusion: The RT-qPCR protocol must be optimized to confirm the primer sequences work as desired. Then primers will be used to study physical status and RNA expression in HPV-positive and HPV-negative head and neck tumor samples. This assay can help shed light on which proteins are expressed most in tumors of the head and neck and will aid in the development of future screening and treatment options.
ContributorsKhazanovich, Jakob (Author) / Anderson, Karen (Thesis director) / Mangone, Marco (Committee member) / Sundaresan, Sri Krishna (Committee member) / Barrett, The Honors College (Contributor)
Created2015-05
Description
Background: High risk types of human papillomavirus (HPV) are known to cause cancer, including cervical (99%) and oropharyngeal cancer (70%). HPV type 16 is the most common subtype. Three antigens that are critical for integration or tumor progression are E2, E6 and E7. In this study, we developed a systematic approach to identify naturally-processed HPV16-derived HLA class I epitopes for immunotherapy development. Methods: K562 cells, which lack HLA expression, were transduced with each HPV16 antigen using lentivirus and supertransfected with HLA-A2 by nucleofection. Stable cell lines expressing each antigen were selected for and maintained throughout the investigation. In order to establish a Gateway-compatible vector for robust transient gene expression, a Gateway recombination expression cloning cassette was inserted into the commercial Lonza pMAX GFP backbone, which has been experimentally shown to display high transfection expression efficiency. GFP was cloned into the vector and plain K562 cells were transfected with the plasmid by nucleofection. Results: Expression of K562-A2 was tested at various time points by flow cytometry and A2 expression was confirmed. Protein expression was shown for the transduced K562 E7 by Western blot analysis. High transfection efficiency of the pMAX_GFP_Dest vector (up to 97% GFP+ cells) was obtained 48 hours post transfection, comparable to the commercial GFP-plasmid. Conclusion: We have established a rapid system for target viral antigen co-expression with single HLA molecules for analysis of antigen presentation. Using HPV as a model system, our goal is to identify specific antigenic peptide sequences to develop immunotherapeutic treatments for HPV-associated cancers.
ContributorsVarda, Bianca Marie (Author) / Anderson, Karen (Thesis director) / Borges, Chad (Committee member) / Krishna, Sri (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05