Matching Items (151)
Description
Immunosignaturing is a technology that allows the humoral immune response to be observed through the binding of antibodies to random sequence peptides. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides in a multiplexed fashion. There are computational and statistical challenges to the analysis of immunosignaturing data. The overall aim of my dissertation is to develop novel computational and statistical methods for immunosignaturing data to access its potential for diagnostics and drug discovery. Firstly, I discovered that a classification algorithm Naive Bayes which leverages the biological independence of the probes on our array in such a way as to gather more information outperforms other classification algorithms due to speed and accuracy. Secondly, using this classifier, I then tested the specificity and sensitivity of immunosignaturing platform for its ability to resolve four different diseases (pancreatic cancer, pancreatitis, type 2 diabetes and panIN) that target the same organ (pancreas). These diseases were separated with >90% specificity from controls and from each other. Thirdly, I observed that the immunosignature of type 2 diabetes and cardiovascular complications are unique, consistent, and reproducible and can be separated by 100% accuracy from controls. But when these two complications arise in the same person, the resultant immunosignature is quite different in that of individuals with only one disease. I developed a method to trace back from informative random peptides in disease signatures to the potential antigen(s). Hence, I built a decipher system to trace random peptides in type 1 diabetes immunosignature to known antigens. Immunosignaturing, unlike the ELISA, has the ability to not only detect the presence of response but also absence of response during a disease. I observed, not only higher but also lower peptides intensities can be mapped to antigens in type 1 diabetes. To study immunosignaturing potential for population diagnostics, I studied effect of age, gender and geographical location on immunosignaturing data. For its potential to be a health monitoring technology, I proposed a single metric Coefficient of Variation that has shown potential to change significantly when a person enters a disease state.
ContributorsKukreja, Muskan (Author) / Johnston, Stephen Albert (Thesis advisor) / Stafford, Phillip (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2012
Description
Alzheimer's Disease (AD) is the most common form of dementia observed in elderly patients and has significant social-economic impact. There are many initiatives which aim to capture leading causes of AD. Several genetic, imaging, and biochemical markers are being explored to monitor progression of AD and explore treatment and detection options. The primary focus of this thesis is to identify key biomarkers to understand the pathogenesis and prognosis of Alzheimer's Disease. Feature selection is the process of finding a subset of relevant features to develop efficient and robust learning models. It is an active research topic in diverse areas such as computer vision, bioinformatics, information retrieval, chemical informatics, and computational finance. In this work, state of the art feature selection algorithms, such as Student's t-test, Relief-F, Information Gain, Gini Index, Chi-Square, Fisher Kernel Score, Kruskal-Wallis, Minimum Redundancy Maximum Relevance, and Sparse Logistic regression with Stability Selection have been extensively exploited to identify informative features for AD using data from Alzheimer's Disease Neuroimaging Initiative (ADNI). An integrative approach which uses blood plasma protein, Magnetic Resonance Imaging, and psychometric assessment scores biomarkers has been explored. This work also analyzes the techniques to handle unbalanced data and evaluate the efficacy of sampling techniques. Performance of feature selection algorithm is evaluated using the relevance of derived features and the predictive power of the algorithm using Random Forest and Support Vector Machine classifiers. Performance metrics such as Accuracy, Sensitivity and Specificity, and area under the Receiver Operating Characteristic curve (AUC) have been used for evaluation. The feature selection algorithms best suited to analyze AD proteomics data have been proposed. The key biomarkers distinguishing healthy and AD patients, Mild Cognitive Impairment (MCI) converters and non-converters, and healthy and MCI patients have been identified.
ContributorsDubey, Rashmi (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Wu, Tong (Committee member) / Arizona State University (Publisher)
Created2012
Description
Early spacecraft missions to Mars, including the Marnier and Viking orbiters and landers revealed a morphologically and compositionally diverse landscape that reshaped widely held views of Mars. More recent spacecraft including Mars Global Surveyor, Mars Odyssey, Mars Express, Mars Reconnaissance Orbiter, and the Mars Exploration Rovers have further refined, enhanced, and diversified our understanding of Mars. In this dissertation, I take a multiple-path approach to planetary and Mars science including data analysis and instrument development. First, I present several tools necessary to effectively use new, complex datasets by highlighting unique and innovative data processing techniques that allow for the regional to global scale comparison of multiple datasets. Second, I present three studies that characterize several processes on early Mars, where I identify a regional, compositionally distinct, in situ, stratigraphically significant layer in Ganges and Eos Chasmata that formed early in martian history. This layer represents a unique period in martian history where primitive mantle materials were emplaced over large sections of the martian surface. While I originally characterized this layer as an effusive lava flow, based on the newly identified regional or global extent of this layer, I find the only likely scenario for its emplacement is the ejecta deposit of the Borealis Basin forming impact event. I also re-examine high thermal inertia, flat-floored craters identified in Viking data and conclude they are typically more mafic than the surrounding plains and were likely infilled by primitive volcanic materials during, or shortly after the Late Heavy Bombardment. Furthermore, the only plausible source for these magmas is directly related to the impact process, where mantle decompression melting occurs as result of the removal of overlying material by the impactor. Finally, I developed a new laboratory microscopic emission and reflectance spectrometer designed to help improve the interpretation of current remote sensing or in situ data from planetary bodies. I present the design, implementation, calibration, system performance, and preliminary results of this instrument. This instrument is a strong candidate for the next generation in situ rover instruments designed to definitively assess sample mineralogy and petrology while preserving geologic context.
ContributorsEdwards, Christopher (Author) / Christensen, Philip R. (Thesis advisor) / Bell, James (Committee member) / Sharp, Thomas (Committee member) / Clarke, Amanda B (Committee member) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2012
Description
Single cell analysis has become increasingly important in understanding disease onset, progression, treatment and prognosis, especially when applied to cancer where cellular responses are highly heterogeneous. Through the advent of single cell computerized tomography (Cell-CT), researchers and clinicians now have the ability to obtain high resolution three-dimensional (3D) reconstructions of single cells. Yet to date, no live-cell compatible version of the technology exists. In this thesis, a microfluidic chip with the ability to rotate live single cells in hydrodynamic microvortices about an axis parallel to the optical focal plane has been demonstrated. The chip utilizes a novel 3D microchamber design arranged beneath a main channel creating flow detachment into the chamber, producing recirculating flow conditions. Single cells are flowed through the main channel, held in the center of the microvortex by an optical trap, and rotated by the forces induced by the recirculating fluid flow. Computational fluid dynamics (CFD) was employed to optimize the geometry of the microchamber. Two methods for the fabrication of the 3D microchamber were devised: anisotropic etching of silicon and backside diffuser photolithography (BDPL). First, the optimization of the silicon etching conditions was demonstrated through design of experiment (DOE). In addition, a non-conventional method of soft-lithography was demonstrated which incorporates the use of two positive molds, one of the main channel and the other of the microchambers, compressed together during replication to produce a single ultra-thin (<200 µm) negative used for device assembly. Second, methods for using thick negative photoresists such as SU-8 with BDPL have been developed which include a new simple and effective method for promoting the adhesion of SU-8 to glass. An assembly method that bonds two individual ultra-thin (<100 µm) replications of the channel and the microfeatures has also been demonstrated. Finally, a pressure driven pumping system with nanoliter per minute flow rate regulation, sub-second response times, and < 3% flow variability has been designed and characterized. The fabrication and assembly of this device is inexpensive and utilizes simple variants of conventional microfluidic fabrication techniques, making it easily accessible to the single cell analysis community.
ContributorsMyers, Jakrey R (Author) / Meldrum, Deirdre (Thesis advisor) / Johnson, Roger (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Molybdenum and uranium isotope variations are potentially powerful tools for reconstructing the paleoredox history of seawater. Reliable application and interpretation of these proxies requires not only detailed knowledge about the fractionation factors that control the distribution of molybdenum and uranium isotopes in the marine system, but also a thorough understanding of the diagenetic processes that may affect molybdenum and uranium isotopes entering the rock record. Using samples from the Black Sea water column, the first water column profile of 238U/235U variations from a modern euxinic basin has been measured. This profile allows the direct determination of the 238U/235U fractionation factor in a euxinic marine setting. More importantly however, these data demonstrate the extent of Rayleigh fractionation of U isotopes that can occur in euxinic restricted basins. Because of this effect, the offset of 238U/235U between global average seawater and coeval black shales deposited in restricted basins is expected to depend on the degree of local uranium drawdown from the water column, potentially complicating the interpretation 238U/235U paleorecords. As an alternative to the black shales typically used for paleoredox reconstructions, molybdenum and uranium isotope variations in bulk carbonate sediments from the Bahamas are examined. The focus of this work was to determine what processes, if any, fractionate molybdenum and uranium isotopes during incorporation into bulk carbonate sediments and their subsequent diagenesis. The results demonstrate that authigenic accumulation of molybdenum and uranium from anoxic and sulfidic pore waters is a dominant process controlling the concentration and isotopic composition of these sediments during early diagenesis. Examination of ODP drill core samples from the Bahamas reveals similar behavior for sediments during the first ~780ka of burial, but provides important examples where isolated cores and samples occasionally demonstrate additional fractionation, the cause of which remains poorly understood.
ContributorsRomaniello, Stephen J. (Author) / Anbar, Ariel (Thesis advisor) / Hartnett, Hilairy (Committee member) / Herrmann, Achim (Committee member) / Shock, Everett (Committee member) / Wadhwa, Meenakshi (Committee member) / Arizona State University (Publisher)
Created2012
Description
DNA methylation, a subset of epigenetics, has been found to be a significant marker associated with variations in gene expression and activity across the entire human genome. As of now, however, there is little to no information about how DNA methylation varies between different tissues inside a singular person's body. By using research data from a preliminary study of lean and obese clinical subjects, this study attempts to put together a profile of the differences in DNA methylation that can be observed between two particular body tissues from this subject group: blood and skeletal muscle. This study allows us to start describing the changes that occur at the epigenetic level that influence how differently these two tissues operate, along with seeing how these tissues change between individuals of different weight classes, especially in the context of the development of symptoms of Type 2 Diabetes.
ContributorsRappazzo, Micah Gabriel (Author) / Coletta, Dawn (Thesis director) / Katsanos, Christos (Committee member) / Dinu, Valentin (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / Department of Psychology (Contributor)
Created2013-12
Description
In oxygenic photosynthesis, Photosystem I (PSI) and Photosystem II (PSII) are two transmembrane protein complexes that catalyze the main step of energy conversion; the light induced charge separation that drives an electron transfer reaction across the thylakoid membrane. Current knowledge of the structure of PSI and PSII is based on three structures: PSI and PSII from the thermophilic cyanobacterium Thermosynechococcus elonagatus and the PSI/light harvesting complex I (PSI-LHCI) of the plant, Pisum sativum. To improve the knowledge of these important membrane protein complexes from a wider spectrum of photosynthetic organisms, photosynthetic apparatus of the thermo-acidophilic red alga, Galdieria sulphuraria and the green alga, Chlamydomonas reinhardtii were studied. Galdieria sulphuraria grows in extreme habitats such as hot sulfur springs with pH values from 0 to 4 and temperatures up to 56°C. In this study, both membrane protein complexes, PSI and PSII were isolated from this organism and characterized. Ultra-fast fluorescence spectroscopy and electron microscopy studies of PSI-LHCI supercomplexes illustrate how this organism has adapted to low light environmental conditions by tightly coupling PSI and LHC, which have not been observed in any organism so far. This result highlights the importance of structure-function relationships in different ecosystems. Galdieria sulphuraria PSII was used as a model protein to show the amenability of integral membrane proteins to top-down mass spectrometry. G.sulphuraria PSII has been characterized with unprecedented detail with identification of post translational modification of all the PSII subunits. This study is a technology advancement paving the way for the usage of top-down mass spectrometry for characterization of other large integral membrane proteins. The green alga, Chlamydomonas reinhardtii is widely used as a model for eukaryotic photosynthesis and results from this organism can be extrapolated to other eukaryotes, especially agricultural crops. Structural and functional studies on the PSI-LHCI complex of C.reinhardtii grown under high salt conditions were studied using ultra-fast fluorescence spectroscopy, circular dichroism and MALDI-TOF. Results revealed that pigment-pigment interactions in light harvesting complexes are disrupted and the acceptor side (ferredoxin docking side) is damaged under high salt conditions.
ContributorsThangaraj, Balakumar (Author) / Fromme, Petra (Thesis advisor) / Shock, Everett (Committee member) / Chen, Julian (Committee member) / Arizona State University (Publisher)
Created2010
Description
Continuous advancements in biomedical research have resulted in the production of vast amounts of scientific data and literature discussing them. The ultimate goal of computational biology is to translate these large amounts of data into actual knowledge of the complex biological processes and accurate life science models. The ability to rapidly and effectively survey the literature is necessary for the creation of large scale models of the relationships among biomedical entities as well as hypothesis generation to guide biomedical research. To reduce the effort and time spent in performing these activities, an intelligent search system is required. Even though many systems aid in navigating through this wide collection of documents, the vastness and depth of this information overload can be overwhelming. An automated extraction system coupled with a cognitive search and navigation service over these document collections would not only save time and effort, but also facilitate discovery of the unknown information implicitly conveyed in the texts. This thesis presents the different approaches used for large scale biomedical named entity recognition, and the challenges faced in each. It also proposes BioEve: an integrative framework to fuse a faceted search with information extraction to provide a search service that addresses the user's desire for "completeness" of the query results, not just the top-ranked ones. This information extraction system enables discovery of important semantic relationships between entities such as genes, diseases, drugs, and cell lines and events from biomedical text on MEDLINE, which is the largest publicly available database of the world's biomedical journal literature. It is an innovative search and discovery service that makes it easier to search
avigate and discover knowledge hidden in life sciences literature. To demonstrate the utility of this system, this thesis also details a prototype enterprise quality search and discovery service that helps researchers with a guided step-by-step query refinement, by suggesting concepts enriched in intermediate results, and thereby facilitating the "discover more as you search" paradigm.
avigate and discover knowledge hidden in life sciences literature. To demonstrate the utility of this system, this thesis also details a prototype enterprise quality search and discovery service that helps researchers with a guided step-by-step query refinement, by suggesting concepts enriched in intermediate results, and thereby facilitating the "discover more as you search" paradigm.
ContributorsKanwar, Pradeep (Author) / Davulcu, Hasan (Thesis advisor) / Dinu, Valentin (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2010
Description
Tempe Town Lake is the site of fifteen years’ worth of chemical data collection by ASU researchers. In 2018 the dataSONDE, an instrument capable of measuring different water quality parameters every thirty minutes for a month at a time was installed in the lake. The SONDE has the potential to completely reduce the need for sampling by hand. Before the SONDE becomes the sole means of gathering data, it is important to verify its accuracy. In this study, the measurements gathered by the SONDE (pH, dissolved oxygen, temperature, conductivity and colored dissolved organic matter) were compared to measurements gathered using the verified methods from the past fifteen years.
ContributorsSauer, Elinor Rayne (Author) / Hartnett, Hilairy (Thesis director) / Glaser, Donald (Committee member) / Shock, Everett (Committee member) / Historical, Philosophical & Religious Studies (Contributor) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
Background
Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria.
Methodology
We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure.
Principal Findings
We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations.
Conclusions
Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.
Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria.
Methodology
We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure.
Principal Findings
We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations.
Conclusions
Our results provide a new perspective on nuclear structure variations associated with malignancy and point to the value of automated quantitative 3D nuclear morphometry as an objective tool to enable development of sensitive and specific nuclear grade classification in breast cancer diagnosis.
ContributorsNandakumar, Vivek (Author) / Kelbauskas, Laimonas (Author) / Hernandez, Kathryn (Author) / Lintecum, Kelly (Author) / Senechal, Patti (Author) / Bussey, Kimberly (Author) / Davies, Paul (Author) / Johnson, Roger (Author) / Meldrum, Deirdre (Author) / Ira A. Fulton Schools of Engineering (Contributor) / School of Electrical, Computer and Energy Engineering (Contributor) / Biodesign Institute (Contributor) / Center for Biosignatures Discovery Automation (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Department of Physics (Contributor)
Created2012-01-05