Matching Items (114)
Description
Yellow-bellied marmots (Marmota flavivent) are semi-fossorial ground-dwelling sciurid rodents native to the western United States. They are facultatively social and live in colonies that may contain over 50 individuals. Marmot populations are well studied in terms of their diet, life cycle, distribution, and behavior, however, knowledge about viruses associated with marmots is very limited. In this study we aim to identify DNA viruses by non-invasive sampling of their feces. Viral DNA was extracted from fecal material of 35 individual marmots collected in Colorado and subsequently submitted to rolling circle amplification for circular molecule enrichment. Using a viral metagenomics approach which included high-throughput sequencing and verification of viral genomes using PCR, cloning and sequencing, a diverse group of single-stranded (ss) DNA viruses were identified. Diverse ssDNA viruses were identified that belong to two established families, Genomoviridae (n=7) and Anelloviridae (n=1) and several others that belong to unclassified circular replication associated encoding single-stranded (CRESS) DNA virus groups (n=19). There were also circular DNA molecules extracted (n=4) that appear to encode one viral-like gene and are composed of <1545 nt. The viruses that belonged to the family Genomoviridae clustered with those in the Gemycircularvirus genus. The genomoviruses were extracted from 6 samples. These clustered with gemycircularvirus extracted from arachnids and feces. The anellovirus, extracted from one sample, identified here has a genome sequence that is most similar to those from other rodent species, lagomorphs, and mosquitos. The CRESS viruses identified here were extracted from 9 samples and are novel and cluster with others identified from avian species. This study gives a snapshot of viruses associated with marmots based on fecal sampling.
ContributorsKhalifeh, Anthony (Author) / Varsani, Arvind (Thesis director) / Kraberger, Simona (Committee member) / Dolby, Greer (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
To date, there have been few, if any, studies evaluating the venom toxin levels in dogs that have been naturally envenomated by pit vipers. Understanding venom toxin pharmacokinetics in a clinical setting is important for a variety of reasons, including the potential to better elucidate treatment options, prognosis, and other factors associated with pit viper envenomation. In addition, dogs serve as a comparative species to humans for evaluating pit viper envenomations. This pilot study’s primary objective was to address the question of “What do we see?” in dogs presenting for rattlesnake envenomation. To answer this question, we obtained serum from envenomated dogs presenting at three veterinary clinics, then used enzyme-linked immunosorbent assay (ELISA) and western blot analysis to measure total venom and key toxins in sera. Phospholipase A2, a primary venom toxin, was identified in a few samples by the western blot, and contributed to the positive correlation between percent echinocytes in the blood and venom concentration. Medical data records were compared to venom concentrations measured using ELISA to determine whether there were any significant correlations. First, the hematological results were compared. Clotting times showed a strong positive correlation, clotting times and platelets showed a negative correlation, while echinocytes and platelets showed no correlation. When compared to venom concentration, clotting times showed a negative correlation, while age showed a positive correlation. Weight and platelets were also compared to venom concentration, but no significant correlations were found. The logistics of this study provided a real-world model where time elapsed between envenomation and hospital admission, thus giving a realistic look at what occurs in both animal and human medicine.
ContributorsNelson, Alexis (Co-author, Co-author) / DeNardo, Dale (Thesis director) / Woods, Craig (Thesis director) / Varsani, Arvind (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Human papillomavirus (HPV) is the causative agent of cervical cancer. Persistent infection with high-risk HPV 16, 18 or 45 species is associated with the development and progression of cervical cancer. HPV genotyping and Pap smear tests are the regular methods used to detect pre-invasive cervical lesions, but there is a need for developing a rapid biomarker to profile immunity to these viruses. The viral E7 oncogene is expressed in most HPV-associated cancers and anti-E7 antibodies can be detected in the blood of patients with cervical cancer. This research was focused on viral E7 oncogene expression to be used in development of low-cost point of care tests, enabling patients from low resource settings to detect the asymptotic stage of cervical cancer and be able to seek treatment early. In order to produce the E7 protein in vitro to measure antibody levels, GST tagged E7 genes from HPV 16, 18 and 45 species were inserted into the pDEST15 vector and expressed in E. coli BL21DE3 cells that were induced with 1mM of IPTG. The E7-GST fused expressed protein was then purified using glutathione beads and resolved on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Protein expression was 5.8 \u03bcg/ml for HPV 16E7 in 500 ml culture and for the 500 ml culture of HPV 18 E7 and 45 E7 were 10.5 \u03bcg/ml and 10.5 \u03bcg/ml for HPV 18E7 and 45E7 respectively. High yield values are showing high expression levels of GST-tagged E7 recombinant protein which can be used for serotyping a number of individuals. This shows that HPV E7 can be produced in large quantities that can potentially be used in point of care tests that can help identify women at risk of cervical cancer. In conclusion, the E7 protein produced in this study can potentially be used to induce humoral responses in patients\u2019 sera for understanding the immune response of cervical cancer.
ContributorsMakuyana, Ntombizodwa (Author) / Anderson, Karen (Thesis director) / Ewaisha, Radwa (Committee member) / Varsani, Arvind (Committee member) / Hou, Ching-Wen (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
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
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
Description
Learning from high dimensional biomedical data attracts lots of attention recently. High dimensional biomedical data often suffer from the curse of dimensionality and have imbalanced class distributions. Both of these features of biomedical data, high dimensionality and imbalanced class distributions, are challenging for traditional machine learning methods and may affect the model performance. In this thesis, I focus on developing learning methods for the high-dimensional imbalanced biomedical data. In the first part, a sparse canonical correlation analysis (CCA) method is presented. The penalty terms is used to control the sparsity of the projection matrices of CCA. The sparse CCA method is then applied to find patterns among biomedical data sets and labels, or to find patterns among different data sources. In the second part, I discuss several learning problems for imbalanced biomedical data. Note that traditional learning systems are often biased when the biomedical data are imbalanced. Therefore, traditional evaluations such as accuracy may be inappropriate for such cases. I then discuss several alternative evaluation criteria to evaluate the learning performance. For imbalanced binary classification problems, I use the undersampling based classifiers ensemble (UEM) strategy to obtain accurate models for both classes of samples. A small sphere and large margin (SSLM) approach is also presented to detect rare abnormal samples from a large number of subjects. In addition, I apply multiple feature selection and clustering methods to deal with high-dimensional data and data with highly correlated features. Experiments on high-dimensional imbalanced biomedical data are presented which illustrate the effectiveness and efficiency of my methods.
ContributorsYang, Tao (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013
Description
Globally, about two-thirds of the population is latently infected with herpes simplex virus type 1 (HSV-1). HSV-1 is a large double stranded DNA virus with a genome size of ~150kbp. Small defective genomes, which minimally contain an HSV-1 origin of replication and packaging signal, arise naturally via recombination during viral DNA replication. These small defective genomes can be mimicked by constructing a bacterial plasmid containing the HSV-1 origin of replication and packaging signal, transfecting these recombinant plasmids into mammalian cells, and infecting with a replicating helper virus. The absence of most viral genes in the amplicon vector allows large pieces of foreign DNA (up to 150kbp) to be incorporated. The HSV-1 amplicon is replicated and packaged by the helper virus to form HSV-1 particles containing the amplicon DNA. We constructed a novel HSV-1 amplicon vector system containing lambda phage-derived attR sites to facilitate insertion of transgenes by Invitrogen Gateway recombination. To demonstrate that the amplicon vectors work as expected, we packaged the vector constructs expressing Emerald GFP using the replication-competent helper viruses OK-14 or HSV-mScartlet-I-UL25 in Vero cells and demonstrate that the vector stock can subsequently transduce and express Emerald GFP. In further work, we will insert transgenes into the amplicon vector using Invitrogen Gateway recombination to study their functionality.
ContributorsVelarde, Kimberly (Author) / Hogue, Ian B (Thesis advisor) / Manfredsson, Fredric (Committee member) / Sandoval, Ivette (Committee member) / Varsani, Arvind (Committee member) / Arizona State University (Publisher)
Created2021
Description
This dissertation constructs a new computational processing framework to robustly and precisely quantify retinotopic maps based on their angle distortion properties. More generally, this framework solves the problem of how to robustly and precisely quantify (angle) distortions of noisy or incomplete (boundary enclosed) 2-dimensional surface to surface mappings. This framework builds upon the Beltrami Coefficient (BC) description of quasiconformal mappings that directly quantifies local mapping (circles to ellipses) distortions between diffeomorphisms of boundary enclosed plane domains homeomorphic to the unit disk. A new map called the Beltrami Coefficient Map (BCM) was constructed to describe distortions in retinotopic maps. The BCM can be used to fully reconstruct the original target surface (retinal visual field) of retinotopic maps. This dissertation also compared retinotopic maps in the visual processing cascade, which is a series of connected retinotopic maps responsible for visual data processing of physical images captured by the eyes. By comparing the BCM results from a large Human Connectome project (HCP) retinotopic dataset (N=181), a new computational quasiconformal mapping description of the transformed retinal image as it passes through the cascade is proposed, which is not present in any current literature. The description applied on HCP data provided direct visible and quantifiable geometric properties of the cascade in a way that has not been observed before. Because retinotopic maps are generated from in vivo noisy functional magnetic resonance imaging (fMRI), quantifying them comes with a certain degree of uncertainty. To quantify the uncertainties in the quantification results, it is necessary to generate statistical models of retinotopic maps from their BCMs and raw fMRI signals. Considering that estimating retinotopic maps from real noisy fMRI time series data using the population receptive field (pRF) model is a time consuming process, a convolutional neural network (CNN) was constructed and trained to predict pRF model parameters from real noisy fMRI data
ContributorsTa, Duyan Nguyen (Author) / Wang, Yalin (Thesis advisor) / Lu, Zhong-Lin (Committee member) / Hansford, Dianne (Committee member) / Liu, Huan (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2022
Description
Caracals (Caracal caracal) are a felid species native to regions of southern Africa and western and central Asia. Despite their relatively high prevalence, the majority of research conducted on caracals has been undertaken on captive individuals, which encounter significantly different environments and exhibit different behaviors in comparison to caracals in the wild. Thereby, they likely have a vastly different virome. The goal of this study was to identify known and unknown DNA viruses associated with free-ranging caracals. Caracal fecal and organ samples were obtained from a caracal surveillance study undertaken in the Western Cape region of South Africa. Parasitic ticks found feeding on caracals were also obtained. Using a viral metagenomic informed approach, a novel circovirus (family Circoviridae) was detected and characterized in caracal fecal, kidney, spleen, and liver samples, as well as in ticks feeding on the caracals. To our knowledge, this is the first circovirus identified in caracals. The novel circovirus was determined to be closely related to a canine circovirus. These findings expand the knowledge of viral diversity and caracals and are greatly important to caracal conservation efforts as well as conservation efforts of other animals within their ecosystem.
ContributorsCollins, Courtney (Author) / Varsani, Arvind (Thesis director) / Dolby, Greer (Committee member) / Kraberger, Simona (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor)
Created2022-05
Description
Retinotopic map, the map between visual inputs on the retina and neuronal activation in brain visual areas, is one of the central topics in visual neuroscience. For human observers, the map is typically obtained by analyzing functional magnetic resonance imaging (fMRI) signals of cortical responses to slowly moving visual stimuli on the retina. Biological evidences show the retinotopic mapping is topology-preserving/topological (i.e. keep the neighboring relationship after human brain process) within each visual region.
Unfortunately, due to limited spatial resolution and the signal-noise ratio of fMRI, state of art retinotopic map is not topological.
The topic was to model the topology-preserving condition mathematically, fix non-topological retinotopic map with numerical methods, and improve the quality of retinotopic maps.
The impose of topological condition, benefits several applications.
With the topological retinotopic maps, one may have a better insight on human retinotopic maps, including better cortical magnification factor quantification, more precise description of retinotopic maps, and potentially better exam ways of in Ophthalmology clinic.
ContributorsTu, Yanshuai (Author) / Wang, Yalin (Thesis advisor) / Lu, Zhong-Lin (Committee member) / Crook, Sharon (Committee member) / Yang, Yezhou (Committee member) / Zhang, Yu (Committee member) / Arizona State University (Publisher)
Created2022