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Description
Lipid microdomains play a vital role in a number of biological processes. They are often a target of diseases and viruses. Viruses in particular utilize lipid microdomains to gain entry and fuse with the host-cell membrane. Measles virus (MV) a human pathogen, spread from cell to cell by inducing fusion of cellular membranes. This causes the formation of large multinucleated cells, syncytia. It has been previously reported that lipid microdomains are essential for measles virus infection/replication. In this study we used methyl beta cyclodextrin (MBCD), a cholesterol-sequestering agent to disrupt lipid microdomains. Through transfection of Vero h/SLAM cells, we found that Measles virus fusion was dependent on lipid microdomains integrity. Indeed, a dose dependent fusion inhibition was documented with increasing concentrations of MBCD resulting in reduced formation of syncytia.
ContributorsKwan, Jason (Author) / Reyes del Valle, Jorge (Thesis director) / Chang, Yung (Committee member) / Mor, Tsafrir (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / School of Life Sciences (Contributor)
Created2013-05
Description
The Community Action Research Experiences (CARE) Program collaborated with the WellCare Foundation (WCF) to assess the referral sources of the clinic in order to more effectively reach additional potential patients. Archival data were analyzed from a 19-month period from the medical records of patients. Also, data were collected from interviews with the case manager of agencies that were a known referral source of WCF. These case manager interviews were completed over a one-month period. For the archival data part of the project, data were collected from 117 patients. Four representatives from community agencies participated in phone interviews. The results indicated that the most common referral sources were word of mouth, followed by community agency referrals. The results also indicated that WCF appears to have served a unique niche that is not served by other non-profit health clinics. These results led to implications for action and direction for future applied research.
ContributorsEbbing, Brittany Gabrielle (Author) / Spinrad, Tracy (Thesis director) / Dumka, Larry (Committee member) / Brougham, Jennifer (Committee member) / Barrett, The Honors College (Contributor) / T. Denny Sanford School of Social and Family Dynamics (Contributor) / School of Life Sciences (Contributor)
Created2013-05
Description
Abstract As we move forward in education reform in the globalized 21st century, the United States must visit new ways to teach science in high school classrooms. The goal of this investigation is to analyze the current research literature for the best and most promising teaching strategies and techniques in secondary education biology classrooms that promote academic excellence for all students. Looking at policy and school reform literature in science education to establish the context of the current system, the paper will not focus on the political as or systematic changes needed to ground an overall successful system. However, because of their inherent effect on the education system, the political aspects of education reform will be briefly addressed. The primary focus, by addressing the emphasis on standardization, inflexibility of instruction and lack of creativity specifically in high school biology classrooms, seeks to clarify small changes that can influence students' academic outcomes. The United States is performing on such a poor level in science and math proficiency that it cannot match students abroad and this is seen through test scores and the production of competent graduates. This investigation serves to organize literature from education researchers and showcase best and promising teaching and learning practices that catalyze academic excellence for all students in our pluralistic, democratic and complex schooling and societal contexts.
ContributorsHildebrandt, Kevin Andrew (Author) / Ovando, Carlos (Thesis director) / Schugurensky, Daniel, 1958- (Committee member) / Fischman, Gustavo (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of International Letters and Cultures (Contributor)
Created2013-05
Description
Previous findings from our lab have demonstrated that nicotine and social reward have synergistic effects when experienced together versus when experienced separately. The purpose of this experiment is to understand the neural mechanisms underlying this synergistic effect by quantifying Fos protein, a marker for neural activation, in various brain regions. We utilized the conditioning place preference (CPP) model to assess reward. Four groups of adolescent male rats (n=120) were given either nicotine (Nic) (0.1 mg/kg/mL) or saline (Sal) and were placed in the CPP apparatus either with a social partner (Soc) or alone (Iso). Thus, groups were: 1.)Sal+Iso, 2).Sal+Soc, 3).Nic+Iso, 4).Nic+Soc. Brains of some the rats (n=40) were collected for Fos staining 90 minutes after the last conditioning session to obtain Fos data in response to direct exposure to the stimuli. The following regions were analyzed for Fos expression: central amygdala (CeA), medial amygdala (MeA), basolateral amygdala (BLA), nucleus accumbens core (NAcCore), and nucleus accumbens shell (NAcShell). Place preference changes occurred in socially-conditioned groups reflecting social reward and in nicotine-conditioned groups reflecting nicotine reward. As expected, the Sal+Iso control group failed to display a preference change. Fos data revealed a significant increase in Fos expression in the CeA, MeA, NAcCore and NAcShell for socially-conditioned animals and a significant decrease in the NAcCore for nicotine-conditioned groups. Experiencing both social and nicotine rewards together appeared to produce greater activation in the BLA. However, there was an increase in Fos expression in the negative control group relative to Nic+Iso group. The results of CPP suggest that social, nicotine and their combination are rewarding. The combination of the nicotine and social reward could have been more rewarding than social and nicotine separately, but the test was not sensitive to reward magnitude. The increase in Fos expression in the negative control group in the BLA could be due to isolation stress. Overall, these results suggest that these brain regions had greater activation to social reward.
ContributorsGoenaga, Julianna Gloria (Author) / Neisewander, Janet (Thesis director) / Orchinik, Miles (Committee member) / Olive, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Historical, Philosophical and Religious Studies (Contributor) / School of Life Sciences (Contributor)
Created2013-05
Description
Many of the derived features of the human skeleton can be divided into two adaptive suites: traits related to bipedalism and traits related to encephalization. The cervical spine connects these adaptive suites and is itself unique in its marked lordosis. I approach human cervical evolution from three directions: the functional significance of cervical curvature, the identification of cervical lordosis in osteological material, and the representation of the cervical spine in the hominin fossil record.
ContributorsFatica, Lawrence Martin (Author) / Kimbel, William (Thesis director) / Reed, Kaye (Committee member) / Schwartz, Gary (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Life Sciences (Contributor)
Created2014-05
Description
It is well known that deficiencies in key chemical elements (such as phosphorus, P) can reduce animal growth; however, recent empirical data have shown that high levels of dietary nutrients can also reduce animal growth. In ecological stoichiometry, this phenomenon is known as the "stoichiometric knife edge," but its underlying mechanisms are not well-known. Previous work has suggested that the crustacean zooplankter Daphnia reduces its feeding rates on phosphorus-rich food, causing low growth due to insufficient C (energy) intake. To test for this mechanism, feeding rates of Daphnia magna on algae (Scenedesmus acutus) differing in C:P ratio (P content) were determined. Overall, there was a significant difference among all treatments for feeding rate (p < 0.05) with generally higher feeding rates on P-rich algae. These data indicate that both high and low food C:P ratio do affect Daphnia feeding rate but are in contradiction with previous work that showed that P-rich food led to strong reductions in feeding rate. Additional experiments are needed to gain further insights.
ContributorsSchimpp, Sarah Ann (Author) / Elser, James (Thesis director) / Neuer, Susanne (Committee member) / Peace, Angela (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Sustainability (Contributor)
Created2014-05
Description
Background
The maintenance of chromosomal integrity is an essential task of every living organism and cellular repair mechanisms exist to guard against insults to DNA. Given the importance of this process, it is expected that DNA repair proteins would be evolutionarily conserved, exhibiting very minimal sequence change over time. However, BRCA1, an essential gene involved in DNA repair, has been reported to be evolving rapidly despite the fact that many protein-altering mutations within this gene convey a significantly elevated risk for breast and ovarian cancers.
Results
To obtain a deeper understanding of the evolutionary trajectory of BRCA1, we analyzed complete BRCA1 gene sequences from 23 primate species. We show that specific amino acid sites have experienced repeated selection for amino acid replacement over primate evolution. This selection has been focused specifically on humans and our closest living relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus). After examining BRCA1 polymorphisms in 7 bonobo, 44 chimpanzee, and 44 rhesus macaque (Macaca mulatta) individuals, we find considerable variation within each of these species and evidence for recent selection in chimpanzee populations. Finally, we also sequenced and analyzed BRCA2 from 24 primate species and find that this gene has also evolved under positive selection.
Conclusions
While mutations leading to truncated forms of BRCA1 are clearly linked to cancer phenotypes in humans, there is also an underlying selective pressure in favor of amino acid-altering substitutions in this gene. A hypothesis where viruses are the drivers of this natural selection is discussed.
The maintenance of chromosomal integrity is an essential task of every living organism and cellular repair mechanisms exist to guard against insults to DNA. Given the importance of this process, it is expected that DNA repair proteins would be evolutionarily conserved, exhibiting very minimal sequence change over time. However, BRCA1, an essential gene involved in DNA repair, has been reported to be evolving rapidly despite the fact that many protein-altering mutations within this gene convey a significantly elevated risk for breast and ovarian cancers.
Results
To obtain a deeper understanding of the evolutionary trajectory of BRCA1, we analyzed complete BRCA1 gene sequences from 23 primate species. We show that specific amino acid sites have experienced repeated selection for amino acid replacement over primate evolution. This selection has been focused specifically on humans and our closest living relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus). After examining BRCA1 polymorphisms in 7 bonobo, 44 chimpanzee, and 44 rhesus macaque (Macaca mulatta) individuals, we find considerable variation within each of these species and evidence for recent selection in chimpanzee populations. Finally, we also sequenced and analyzed BRCA2 from 24 primate species and find that this gene has also evolved under positive selection.
Conclusions
While mutations leading to truncated forms of BRCA1 are clearly linked to cancer phenotypes in humans, there is also an underlying selective pressure in favor of amino acid-altering substitutions in this gene. A hypothesis where viruses are the drivers of this natural selection is discussed.
ContributorsLou, Dianne I. (Author) / McBee, Ross M. (Author) / Le, Uyen Q. (Author) / Stone, Anne (Author) / Wilkerson, Gregory K. (Author) / Demogines, Ann M. (Author) / Sawyer, Sara L. (Author) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Life Sciences (Contributor)
Created2014-07-11
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 School of Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2012-05-23
Description
Background
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
ContributorsSun, Qian (Author) / Muckatira, Sherin (Author) / Yuan, Lei (Author) / Ji, Shuiwang (Author) / Newfeld, Stuart (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2013-12-03