Matching Items (200)
Description
Blood donations today undergo extensive screening for transfusion transmitted infections (TTI) since the discovery of the first infectious agent in the early 1900s. Nucleic Acid Testing (NAT) is a serological test used widely in disease detection. NAT is known to rapidly and effectively detect pathogenic genomic material in blood by reducing the "window period" of infection. However, NAT produces false negative results for disease positive samples posing a risk of disease transmission. Therefore, NAT is used in conjunction with the Enzyme-Linked Immunosorbent Assay (ELISA) to mitigate these risks. However, the ELISA assay also poses the same risk as NAT. This study proposes immunosignaturing as an alternative serological test that may combat this risk and investigates whether it would be more effective than other standardized serological tests in disease detection. Immunosignaturing detects antibodies by utilizing a microarray of randomized peptide sequences. Immunosignaturing provides information about an individual's immune health from the pattern of reactivity of antibody-peptide binding. Unlike ELISA and NAT, immunosignaturing can be programmed to detect any disease and detect multiple diseases simultaneously. Using ELISA, NAT, and immunosignaturing, immune profiles of asymptomatic patients were constructed for 10 different classes of blood borne diseases. A pattern of infection was identified for each disease and the sensitivity and specificity of these assays were assessed relative to each other. Results indicate that immunosignaturing can be a viable diagnostic tool in blood testing. Immunosignatures demonstrated increased sensitivity and specificity compared to ELISA and NAT in discerning disease positive and negative samples within and across different classes of disease.
ContributorsSharma, Megumi (Author) / McFadden, Grant (Thesis director) / Nickerson, Cheryl (Committee member) / Green, Alex (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Cancer is one of the leading causes of death globally according to the World Health Organization. Although improved treatments and early diagnoses have reduced cancer related mortalities, metastatic disease remains a major clinical challenge. The local tumor microenvironment plays a significant role in cancer metastasis, where tumor cells respond and adapt to a plethora of biochemical and biophysical signals from stromal cells and extracellular matrix (ECM) proteins. Due to these complexities, there is a critical need to understand molecular mechanisms underlying cancer metastasis to facilitate the discovery of more effective therapies. In the past few years, the integration of advanced biomaterials and microengineering approaches has initiated the development of innovative platform technologies for cancer research. These technologies enable the creation of biomimetic in vitro models with physiologically relevant (i.e. in vivo-like) characteristics to conduct studies ranging from fundamental cancer biology to high-throughput drug screening. In this review article, we discuss the biological significance of each step of the metastatic cascade and provide a broad overview on recent progress to recapitulate these stages using advanced biomaterials and microengineered technologies. In each section, we will highlight the advantages and shortcomings of each approach and provide our perspectives on future directions.
ContributorsPeela, Nitish (Author) / Nikkhah, Mehdi (Thesis director) / LaBaer, Joshua (Committee member) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Glioblastoma is the most aggressive and lethal brain tumor, due to its resistance to current conventional therapy. The resistance to chemo- and radiotherapy has been attributed to a special population of cells known as glioma stem cells. Previous literature has shown the importance of a Central Nervous System-restricted transcription factor OLIG2 in maintaining the tumor-propagating potential of these glioma stem cells. OLIG2's function was further elucidated, with its pro-mitogenic function due to its ability to negatively regulate the p53 pathway by suppressing the acetylation of the p53 protein's C terminal domain. Past work in our lab has confirmed that one of OLIG2's partner proteins is Histone Deacetylase 1 (HDAC1). In vitro experiments have also shown that targeting HDAC1 using hairpin RNA in glioma stem cells negatively impacts proliferation. In a survival study using a murine glioma model, targeting Hdac1 using hairpin RNA is shown to reduce tumor burden and increase survival. In this paper, we demonstrate that silencing Hdac1 expression reduces proliferation, increases cell death, likely a result of increased acetylation of p53. Olig2 expression levels seem to be unaffected in GSCs, demonstrating that the Hdac1 protein ablation is indeed lethal to GSCs. This work builds upon previously collected results, confirming that Hdac1 is a potential surrogate target for Olig2's pro-mitotic function in regulating the p53 pathway.
ContributorsLoo, Vincent You Wei (Author) / LaBaer, Joshua (Thesis director) / Mehta, Shwetal (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
CREB3L1 has been previously shown to auto-acetylate itself when prepared from HeLa cell based in vitro protein expression lysates. To circumvent the concerns of the contamination of co-purified human proteins from HeLa lysates, the protein was purified through insect cell transfection in vitro. The objective of this study was to assay the auto-acetylation activity of CREB3L1 prepared from insect cells using the baculovirus expression vector system (BEVS). To this end, His-tagged CREB3L1 was affinity purified from Hi5 cells using an IMAC column and used for acetylation assay. Samples were taken different time points and auto-acetylation was by western using antibodies specific to acetylated lysines. Auto-acetylation activity was observed after overnight incubation. Future experiments will focus on the improvement of purification yield and the identification of the substrates and interacting proteins of CREB3L1 to better understand the biological functions of this novel acetyltransferase.
ContributorsSchwab, Anna (Author) / LaBaer, Joshua (Thesis director) / Qiu, Ji (Committee member) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Finding life beyond Earth could change our understanding of life and habitability. The best place to look for life beyond Earth is Jupiter's moon, Europa. It has been estimated Europa may have a liquid, salt-water subsurface with 2 to 3 times the volume of all Earth's oceans. Knowing that all life requires water, it is in our best interest to explore Europa. This thesis explored the plausibility of life on Europa in four of its environments: on the surface, under the ice shell, in the liquid subsurface, and at the bottom of the liquid subsurface. Each of these environments were defined from science literature and compared to known Earth analogs. Europa's surface is not likely to support life, as there is not liquid water present. There is also extremely high radiation bombardment and extremely low surface temperatures that are estimated to be well out of the range for supporting life. It is more plausible that life could be under Europa's ice shell than on the surface. Under the surface, radiation exposure dramatically reduces. Researchers have found organisms on Earth that can live in similar environments as Europa's ice as well. These organisms require some interaction with liquid water though. Uncertainties about Europa's ice shell thickness and radiation load per depth it experiences, as well as there being limited research on organisms in ice environments, hinder us from definitively assessing the plausibility of life under the surface. The best environment on Europa to look for life on Europa is the subsurface. There remain a lot of uncertainties about the subsurface, however, that make it difficult to assess the plausibility of finding life. These uncertainties include its depth, water activity, salinity, temperature, pressure, and structure. This subsurface may be suitable for life, but until we can further understand the environment of the subsurface, we cannot make definite conclusions. As for assessing the plausibility of life at the bottom of Europa's subsurface, there is not much we know about this environment either. It has been suggested there may be hydrothermal vents, but no evidence has either supported or rejected this idea. Without a clear understanding of the environment at the bottom of the subsurface, the plausibility of life here cannot be definitively answered. It is apparent we need to further study Europa. In particular, we need to focus on understanding the subsurface. When the subsurface is better defined, we can better assess the plausibility of life being present. Fortunately, both NASA and the ESA are currently planning missions to Europa that are scheduled to launch in the 2020s.
ContributorsHoward, Cheyenne Whiffen (Author) / Farmer, Jack (Thesis director) / Shock, Everett (Committee member) / School of Earth and Space Exploration (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Open source image analytics and data mining software are widely available but can be overly-complicated and non-intuitive for medical physicians and researchers to use. The ASU-Mayo Clinic Imaging Informatics Lab has developed an in-house pipeline to process medical images, extract imaging features, and develop multi-parametric models to assist disease staging and diagnosis. The tools have been extensively used in a number of medical studies including brain tumor, breast cancer, liver cancer, Alzheimer's disease, and migraine. Recognizing the need from users in the medical field for a simplified interface and streamlined functionalities, this project aims to democratize this pipeline so that it is more readily available to health practitioners and third party developers.
ContributorsBaer, Lisa Zhou (Author) / Wu, Teresa (Thesis director) / Wang, Yalin (Committee member) / Computer Science and Engineering Program (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Almost every form of cancer deregulates the expression and activity of anabolic glycosyltransferase (GT) enzymes, which incorporate particular monosaccharides in a donor acceptor as well as linkage- and anomer-specific manner to assemble complex and diverse glycans that significantly affect numerous cellular events, including tumorigenesis and metastasis. Because glycosylation is not template-driven, GT deregulation yields heterogeneous arrays of aberrant intact glycan products, some in undetectable quantities in clinical bio-fluids (e.g., blood plasma). Numerous glycan features (e.g., 6 sialylation, β-1,6-branching, and core fucosylation) stem from approximately 25 glycan “nodes:” unique linkage specific monosaccharides at particular glycan branch points that collectively confer distinguishing features upon glycan products. For each node, changes in normalized abundance (Figure 1) may serve as nearly 1:1 surrogate measure of activity for culpable GTs and may correlate with particular stages of carcinogenesis. Complementary to traditional top down glycomics, the novel bottom-up technique applied herein condenses each glycan node and feature into a single analytical signal, quantified by two GC-MS instruments: GCT (time-of-flight analyzer) and GCMSD (transmission quadrupole analyzers). Bottom-up analysis of stage 3 and 4 breast cancer cases revealed better overall precision for GCMSD yet comparable clinical performance of both GC MS instruments and identified two downregulated glycan nodes as excellent breast cancer biomarker candidates: t-Gal and 4,6-GlcNAc (ROC AUC ≈ 0.80, p < 0.05). Resulting from the activity of multiple GTs, t-Gal had the highest ROC AUC (0.88) and lowest ROC p‑value (0.001) among all analyzed nodes. Representing core-fucosylation, glycan node 4,6-GlcNAc is a nearly 1:1 molecular surrogate for the activity of α-(1,6)-fucosyltransferase—a potential target for cancer therapy. To validate these results, future projects can analyze larger sample sets, find correlations between breast cancer stage and changes in t-Gal and 4,6-GlcNAc levels, gauge the specificity of these nodes for breast cancer and their potential role in other cancer types, and develop clinical tests for reliable breast cancer diagnosis and treatment monitoring based on t-Gal and 4,6-GlcNAc.
ContributorsZaare, Sahba (Author) / Borges, Chad (Thesis director) / LaBaer, Joshua (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Yellowstone National Park has a vibrant variety of flora, fauna, and hydrothermal systems all collected together in one large and complex system. Studies have been conducted for at least several decades in order to make sense of this system in ways that may be relevant to other similar geologies around the world. The latest update in this ever-ongoing study involves the collection and analysis of water samples from 2016. These samples have been analyzed for conductivity, pH, temperature, dissolved organic carbon, dissolved inorganic carbon, carbon isotopes, dissolved oxygen, ferrous iron, sulfide, silica, and more. While not many trends were found in this data in regards to dissolved organic carbon values, this is a substantial addition to a growing body of information that could yield more impressive information in times to come. In addition, factors that have yet to analyzed for this 2016 data, such as concentrations of metals and metalloids, may provide some insights when put through a chloride vs sulfate framework to separate out different reaction regions.
ContributorsDoan, Cuong Le (Author) / Shock, Everett (Thesis director) / Gould, Ian (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Disturbances in the protein interactome often play a large role in cancer progression. Investigation of protein-protein interactions (PPI) can increase our understanding of cancer pathways and will disclose unknown targets involved in cancer disease biology. Although numerous methods are available to study protein interactions, most platforms suffer from drawbacks including high false positive rates, low throughput, and lack of quantification. Moreover, most methods are not compatible for use in a clinical setting. To address these limitations, we have developed a multiplexed, in-solution protein microarray (MISPA) platform with broad applications in proteomics. MISPA can be used to quantitatively profile PPIs and as a robust technology for early detection of cancers. This method utilizes unique DNA barcoding of individual proteins coupled with next generation sequencing to quantitatively assess interactions via barcode enrichment. We have tested the feasibility of this technology in the detection of patient immune responses to oropharyngeal carcinomas and in the discovery of novel PPIs in the B-cell receptor (BCR) pathway. To achieve this goal, 96 human papillomavirus (HPV) antigen genes were cloned into pJFT7-cHalo (99% success) and pJFT7-n3xFlag-Halo (100% success) expression vectors. These libraries were expressed via a cell-free in vitro transcription-translation system with 93% and 96% success, respectively. A small-scale study of patient serum interactions with barcoded HPV16 antigens was performed and a HPV proteome-wide study will follow using additional patient samples. In addition, 15 query proteins were cloned into pJFT7_nGST expression vectors, expressed, and purified with 93% success to probe a library of 100 BCR pathway proteins and detect novel PPIs.
ContributorsRinaldi, Capria Lakshmi (Author) / LaBaer, Joshua (Thesis director) / Mangone, Marco (Committee member) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Video object segmentation (VOS) is an important task in computer vision with a lot of applications, e.g., video editing, object tracking, and object based encoding. Different from image object segmentation, video object segmentation must consider both spatial and temporal coherence for the object. Despite extensive previous work, the problem is still challenging. Usually, foreground object in the video draws more attention from humans, i.e. it is salient. In this thesis we tackle the problem from the aspect of saliency, where saliency means a certain subset of visual information selected by a visual system (human or machine). We present a novel unsupervised method for video object segmentation that considers both low level vision cues and high level motion cues. In our model, video object segmentation can be formulated as a unified energy minimization problem and solved in polynomial time by employing the min-cut algorithm. Specifically, our energy function comprises the unary term and pair-wise interaction energy term respectively, where unary term measures region saliency and interaction term smooths the mutual effects between object saliency and motion saliency. Object saliency is computed in spatial domain from each discrete frame using multi-scale context features, e.g., color histogram, gradient, and graph based manifold ranking. Meanwhile, motion saliency is calculated in temporal domain by extracting phase information of the video. In the experimental section of this thesis, our proposed method has been evaluated on several benchmark datasets. In MSRA 1000 dataset the result demonstrates that our spatial object saliency detection is superior to the state-of-art methods. Moreover, our temporal motion saliency detector can achieve better performance than existing motion detection approaches in UCF sports action analysis dataset and Weizmann dataset respectively. Finally, we show the attractive empirical result and quantitative evaluation of our approach on two benchmark video object segmentation datasets.
ContributorsWang, Yilin (Author) / Li, Baoxin (Thesis advisor) / Wang, Yalin (Committee member) / Cleveau, David (Committee member) / Arizona State University (Publisher)
Created2013