Matching Items (287)
Description
The first numerical predictions of the dynamical diquark model of multiquark exotic hadrons are presented. Using Born-Oppenheimer potentials calculated from lattice QCD and phenomenological diquark(triquark) masses, mass eigenvalues that are degenerate in spin and isospin are computed from numerical solutions to both coupled and uncoupled Schroedinger equations. Assuming reasonable estimates of the fine-structure splittings, we find that the band structure of our mass spectra agrees well with the experimentally observed spectrum of charmonium-like states. Using our best fits, we predict a number of unobserved states, such as pentaquark states that lie below the charmonium-plus-nucleon threshold.
ContributorsPeterson, Curtis Taylor Taylor (Author) / Lebed, Richard (Thesis director) / Belitsky, Andrei (Committee member) / Department of Physics (Contributor, Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
In this study, we demonstrate the effectiveness of a cancer type specific FrAmeShifT (FAST) vaccine. A murine breast cancer (mBC) FAST vaccine and a murine pancreatic cancer (mPC) FAST vaccine were tested in the 4T1 breast cancer syngeneic mouse model. The mBC FAST vaccine, both with and without check point inhibitors (CPI), significantly slowed tumor growth, reduced pulmonary metastasis and increased the cell-mediated immune response. In terms of tumor volumes, the mPC FAST vaccine was comparable to the untreated controls. However, a significant difference in tumor volume did emerge when the mPC vaccine was used with CPI. The collective data indicated that the immune checkpoint blockade therapy was only beneficial with suboptimal neoantigens. More importantly, the FAST vaccine, though requiring notably less resources, performed similarly to the personalized version of the frameshift breast cancer vaccine in the same mouse model. Furthermore, because the frameshift peptide (FSP) array provided a strong rationale for a focused vaccine, the FAST vaccine can theoretically be expanded and translated to any human cancer type. Overall, the FAST vaccine is a promising treatment that would provide the most benefit to patients while eliminating most of the challenges associated with current personal cancer vaccines.
ContributorsMurphy, Sierra Nicole (Author) / Johnston, Stephen (Thesis director) / Peterson, Milene (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The goal of this paper is to discuss the most efficient method to achieve early detection in lung cancers by reducing the occurrences of false-positive readings. Imaging techniques (computed tomography screenings) have greater impact than non-imaging techniques in early detection for lung cancer. On the other hand, positron emission tomography and non-imaging techniques, such as liquid biopsy, are better at distinguishing cancer stages. Therefore, these techniques are not suitable early detection methods for lung cancer. Based on literature reviews, the combination that is most capable of early lung cancer detection incorporate low-dose computed tomography screenings, thin-section computed tomography screenings, and computer-aided diagnosis. Low-dose computed tomography screenings has lower radiation-associated risks compared to the standard-dose computed tomography. This technique can be used as both at the first examination and the follow-up examinations. Thin-section computed tomography screenings can be used as a supplement to check if there is any nodules that have not yet been discovered. Computer-aided diagnosis is an add-on method to make sure the computed tomography screenings images are being correctly labeled. Identifying other contributing factors to the effectiveness of the early lung cancer detection, such as the amount of forced expiratory volume, forced vital capacity, and the presence of emphysema, could also decrease the percentage of false positive outcomes.
ContributorsChuang, Hao-Yun (Author) / Johnston, Stephen (Thesis director) / Peterson, Milene (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Background
Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions.
Results
We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/.
Conclusions
Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods.
Multicellular organisms consist of cells of many different types that are established during development. Each type of cell is characterized by the unique combination of expressed gene products as a result of spatiotemporal gene regulation. Currently, a fundamental challenge in regulatory biology is to elucidate the gene expression controls that generate the complex body plans during development. Recent advances in high-throughput biotechnologies have generated spatiotemporal expression patterns for thousands of genes in the model organism fruit fly Drosophila melanogaster. Existing qualitative methods enhanced by a quantitative analysis based on computational tools we present in this paper would provide promising ways for addressing key scientific questions.
Results
We develop a set of computational methods and open source tools for identifying co-expressed embryonic domains and the associated genes simultaneously. To map the expression patterns of many genes into the same coordinate space and account for the embryonic shape variations, we develop a mesh generation method to deform a meshed generic ellipse to each individual embryo. We then develop a co-clustering formulation to cluster the genes and the mesh elements, thereby identifying co-expressed embryonic domains and the associated genes simultaneously. Experimental results indicate that the gene and mesh co-clusters can be correlated to key developmental events during the stages of embryogenesis we study. The open source software tool has been made available at http://compbio.cs.odu.edu/fly/.
Conclusions
Our mesh generation and machine learning methods and tools improve upon the flexibility, ease-of-use and accuracy of existing methods.
ContributorsZhang, Wenlu (Author) / Feng, Daming (Author) / Li, Rongjian (Author) / Chernikov, Andrey (Author) / Chrisochoides, Nikos (Author) / Osgood, Christopher (Author) / Konikoff, Charlotte (Author) / Newfeld, Stuart (Author) / Kumar, Sudhir (Author) / Ji, Shuiwang (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2013-12-28
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
Description
Background
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
ContributorsYuan, Lei (Author) / Woodard, Alexander (Author) / Ji, Shuiwang (Author) / Jiang, Yuan (Author) / Zhou, Zhi-Hua (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / Ira A. Fulton Schools of Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2012-05-23
Description
The objective of this thesis was to determine whether Zika Virus (ZIKV) can be effectively inactivated by Selective Photonic Disinfection (SEPHODIS) and determine whether key proteins involved in the infection process are preserved, making SEPHODIS a possible source for vaccine development. As of January 2018, there have been 3,720 confirmed cases of Congenital Zika Syndrome in infants, making a Zika Vaccine a high priority (Mitchell, 2018). SEPHODIS is a process that involves prolonged exposure of an object to a pulsing laser which can render it ineffective. Initially, ZIKV was subjected to laser inactivation for 6 hours, then a plaque assay was performed on both laser-treated and control samples. ZIKV was inactivated two-fold? after laser treatment, when compared with control, as indicated by the plaque assay results. Additionally, both samples were submitted to ELISA to evaluate antigenicity with a panel of monoclonal and human sera. As a second control, virus inactivated by formaldehyde (2%) was used. ELISA results showed that antigenicity of some proteins were preserved while others were probably disturbed. However, ELISA results show that ZIKV envelope protein (E-protein), the protein responsible for viral entry into cells, was effectively preserved after laser-treatment, implying that if laser parameters were tweaked to obtain more complete inactivation, then SEPHODIS may be an appropriate source for the development of a vaccine.
ContributorsViafora, Ataiyo Blue (Author) / Johnston, Stephen (Thesis director) / Tsen, Kong-Thon (Committee member) / School of Life Sciences (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Coronaviruses are a significant group of viruses that cause enteric and respiratory infections in a variety of animals, including humans. Outbreaks of Severe Acute Respiratory Syndrome (SARS) and Middle Eastern Respiratory Syndrome (MERS) in the past 15 years has increased research into coronaviruses to gain an understanding of their structure and function so one day therapies and vaccines may be produced. These viruses have four main structural proteins: the spike, nucleocapsid, envelope, and membrane proteins. The envelope (E) protein is an integral membrane protein in the viral envelope that acts as a viroporin for transport of cations and plays an important role in pathogenesis and viral assembly. E contains a hydrophobic transmembrane domain with polar residues that is conserved across coronavirus species and may be significant to its function. This experiment looks at the possible role of one polar residue in assembly, the 15th residue glutamine, in the Mouse Hepatitis Virus (MHV) E protein. The glutamine 15 residue was mutated into positively charged residues lysine or arginine. Plasmids with these mutations were co-expressed with the membrane protein (M) gene to produce virus-like particles (VLPs). VLPs are produced when E and M are co-expressed together and model assembly of the coronavirus envelope, but they are not infectious as they do not contain the viral genome. Observing their production with the mutated E protein gives insight into the role the glutamine residue plays in assembly. The experiment showed that a changing glutamine 15 to positive charges does not appear to significantly affect the assembly of the VLPs, indicating that this specific residue may not have a large impact on viral assembly.
ContributorsHaller, Sarah S. (Author) / Hogue, Brenda (Thesis director) / Liu, Wei (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor) / Biodesign Institute (Contributor)
Created2017-05
Description
PD-L1 blockade has shown recent success in cancer therapy and cancer vaccine regimens. One approach for anti-PD-L1 antibodies has been their application as adjuvants for cancer vaccines. Given the disadvantages of such antibodies, including long half-life and adverse events related to their use, a novel strategy using synbodies in place of antibodies can be tested. Synbodies offer a variety of advantages, including shorter half-life, smaller size, and cheaper cost. Peptides that could bind PD-L1 were identified via peptide arrays and used to construct synbodies. These synbodies were tested with inhibition ELISA assays, SPR, and pull down assays. Additional flow cytometry analysis was done to determine the binding specificity of the synbodies to PD-L1 and the ability of those synbodies to inhibit the PD-L1/PD-1 interaction. Although analysis of permeabilized cells expressing PD-L1 indicated that the synbodies could successfully bind PD-L1, those results were not replicated in non-permeabilized cells. Further assays suggested that the binding of the synbodies was non-specific. Other tests were done to see if the synbodies could inhibit the PD-1/PD-L1 interaction. This assay did not yield any conclusive results and further experimentation is needed to determine the efficacy of the synbodies in inhibiting this interaction.
ContributorsMujahed, Tala (Author) / Johnston, Stephen (Thesis director) / Blattman, Joseph (Committee member) / Diehnelt, Chris (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The devastating 2014 Ebola virus outbreak in Western Africa demonstrated the lack of therapeutic approaches available for the virus. Although monoclonal antibodies (mAb) and other molecules have been developed that bind the virus, no therapeutic has shown the efficacy needed for FDA approval. Here, a library of 50 peptide based ligands that bind the glycoprotein of the Zaire Ebola virus (GP) were developed. Using whole virus screening of vesicular stomatitis virus pseudotyped with GP, low affinity peptides were identified for ligand construction. In depth analysis showed that two of the peptide based molecules bound the Zaire GP with <100 nM KD. One of these two ligands was blocked by a known neutralizing mAb, 2G4, and showed cross-reactivity to the Sudan GP. This work presents ligands with promise for therapeutic applications across multiple variants of the Ebola virus.
ContributorsRabinowitz, Joshua Avraam (Author) / Diehnelt, Chris (Thesis director) / Johnston, Stephen (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Both technological and scientific fields continue to revolutionize in a similar fashion; however, a major difference is that high-tech corporations have found models to continue progressions while still keeping product costs low. The main objective was to identify which, if any, components of certain technological models could be used with the vaccine and pharmaceutical markets to significantly lower their costs. Smartphones and computers were the two main items investigated while the two main items from the scientific standpoint were vaccines and pharmaceuticals. One concept had the ability to conceivably decrease the costs of vaccines and drugs and that was "market competition". If the United States were able to allow competition within the vaccine and drug companies, it would allow for the product prices to be best affected. It would only take a few small companies to generate generic versions of the drugs and decrease the prices. It would force the larger competition to most likely decrease their prices. Furthermore, the PC companies use a cumulative density function (CDF) to effectively divide their price setting in each product cycle. It was predicted that if this CDF model were applied to the vaccine and drug markets, the prices would no longer have to be extreme. The corporations would be able to set the highest price for the wealthiest consumers and then slowly begin to decrease the costs for the middle and lower class. Unfortunately, the problem within the vaccine and pharmaceutical markets was not the lack of innovation or business models. The problem lied with their liberty to choose product costs due to poor U.S. government regulations.
ContributorsCalderon, Gerardo (Author) / Johnston, Stephen (Thesis director) / Diehnelt, Chris (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12