Matching Items (132)
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
Background
The reproductive ground plan hypothesis of social evolution suggests that reproductive controls of a solitary ancestor have been co-opted during social evolution, facilitating the division of labor among social insect workers. Despite substantial empirical support, the generality of this hypothesis is not universally accepted. Thus, we investigated the prediction of particular genes with pleiotropic effects on ovarian traits and social behavior in worker honey bees as a stringent test of the reproductive ground plan hypothesis. We complemented these tests with a comprehensive genome scan for additional quantitative trait loci (QTL) to gain a better understanding of the genetic architecture of the ovary size of honey bee workers, a morphological trait that is significant for understanding social insect caste evolution and general insect biology.
Results
Back-crossing hybrid European x Africanized honey bee queens to the Africanized parent colony generated two study populations with extraordinarily large worker ovaries. Despite the transgressive ovary phenotypes, several previously mapped QTL for social foraging behavior demonstrated ovary size effects, confirming the prediction of pleiotropic genetic effects on reproductive traits and social behavior. One major QTL for ovary size was detected in each backcross, along with several smaller effects and two QTL for ovary asymmetry. One of the main ovary size QTL coincided with a major QTL for ovary activation, explaining 3/4 of the phenotypic variance, although no simple positive correlation between ovary size and activation was observed.
Conclusions
Our results provide strong support for the reproductive ground plan hypothesis of evolution in study populations that are independent of the genetic stocks that originally led to the formulation of this hypothesis. As predicted, worker ovary size is genetically linked to multiple correlated traits of the complex division of labor in worker honey bees, known as the pollen hoarding syndrome. The genetic architecture of worker ovary size presumably consists of a combination of trait-specific loci and general regulators that affect the whole behavioral syndrome and may even play a role in caste determination. Several promising candidate genes in the QTL intervals await further study to clarify their potential role in social insect evolution and the regulation of insect fertility in general.
The reproductive ground plan hypothesis of social evolution suggests that reproductive controls of a solitary ancestor have been co-opted during social evolution, facilitating the division of labor among social insect workers. Despite substantial empirical support, the generality of this hypothesis is not universally accepted. Thus, we investigated the prediction of particular genes with pleiotropic effects on ovarian traits and social behavior in worker honey bees as a stringent test of the reproductive ground plan hypothesis. We complemented these tests with a comprehensive genome scan for additional quantitative trait loci (QTL) to gain a better understanding of the genetic architecture of the ovary size of honey bee workers, a morphological trait that is significant for understanding social insect caste evolution and general insect biology.
Results
Back-crossing hybrid European x Africanized honey bee queens to the Africanized parent colony generated two study populations with extraordinarily large worker ovaries. Despite the transgressive ovary phenotypes, several previously mapped QTL for social foraging behavior demonstrated ovary size effects, confirming the prediction of pleiotropic genetic effects on reproductive traits and social behavior. One major QTL for ovary size was detected in each backcross, along with several smaller effects and two QTL for ovary asymmetry. One of the main ovary size QTL coincided with a major QTL for ovary activation, explaining 3/4 of the phenotypic variance, although no simple positive correlation between ovary size and activation was observed.
Conclusions
Our results provide strong support for the reproductive ground plan hypothesis of evolution in study populations that are independent of the genetic stocks that originally led to the formulation of this hypothesis. As predicted, worker ovary size is genetically linked to multiple correlated traits of the complex division of labor in worker honey bees, known as the pollen hoarding syndrome. The genetic architecture of worker ovary size presumably consists of a combination of trait-specific loci and general regulators that affect the whole behavioral syndrome and may even play a role in caste determination. Several promising candidate genes in the QTL intervals await further study to clarify their potential role in social insect evolution and the regulation of insect fertility in general.
ContributorsGraham, Allie M. (Author) / Munday, Michael D. (Author) / Kaftanoglu, Osman (Author) / Page, Robert (Author) / Amdam, Gro (Author) / Rueppell, Olav (Author) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2011-04-13
Description
Magnetic resonance imaging (MRI) data of metastatic brain cancer patients at the Barrow Neurological Institute sparked interest in the radiology department due to the possibility that tumor size distributions might mimic a power law or an exponential distribution. In order to consider the question regarding the growth trends of metastatic brain tumors, this thesis analyzes the volume measurements of the tumor sizes from the BNI data and attempts to explain such size distributions through mathematical models. More specifically, a basic stochastic cellular automaton model is used and has three-dimensional results that show similar size distributions of those of the BNI data. Results of the models are investigated using the likelihood ratio test suggesting that, when the tumor volumes are measured based on assuming tumor sphericity, the tumor size distributions significantly mimic the power law over an exponential distribution.
ContributorsFreed, Rebecca (Co-author) / Snopko, Morgan (Co-author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
As a biology major, many of my classes have included studying the fundamentals of genetics or investigating the way genetics influence heritability of certain diseases. When I began taking upper-division psychology courses, the genetic factors of psychological disorders became an important part of the material. I was exposed to a new idea: that genes were equally important in studying somatic diseases as they were to psychological disorders. As important as genetics are to psychology, they are not part of the required courses for the major; I found many of my peers in psychology courses did not have a grasp on genetic fundamentals in the same way biology majors did. This was a disconnect that I also found in my own life outside the classroom. Growing up, my mother consistently reminded me to limit my carbs and watch my sugars. Diabetes was very prevalent in my family and I was also at risk. I was repeatedly reminded of my own genes and the risk I faced in having this biological disorder. However, my friend whose father was an alcoholic did not warn her in the same way. While she did know of her father's history, she was not warned of the potential for her to become an alcoholic. While my behavior was altered due to my mother's warning and my own knowledge of the genetic risk of diabetes, I wondered if other people at genetic risk of psychological disorders also altered their behavior. Through my thesis, I hope to answer if students have the same perceived genetic knowledge of psychological diseases as they do for biological ones. In my experience, it is not as well known that psychological disorders have genetic factors. For example, alcohol is commonly used by college students. Alcohol use disorder is present in 16.2% of college aged students and "40-60% of the variance of risk explained by genetic influences." (DSM V, 2013) Compare this to diabetes that has "several common genetic variants that account for about 10% of the total genetic effects," but is much more openly discussed even though it is less genetically linked. (McVay, 2015)This stems from the stigma/taboo surrounding many psychological disorders. If students do know that psychological disorder are genetically influenced, I expect their knowledge to be skewed or inaccurate. As part of a survey, I hope to see how strong they believe the genetic risk of certain diseases are as well as where they gained this knowledge. I hypothesize that only students with a background in psychology will be able to correctly assign the genetic risk of the four presented diseases. Completing this thesis will require in-depth study of the genetic factors, an understanding of the way each disease is perceived and understood by the general population, and a statistical analysis of the survey responses. If the survey data turns out as I expect where students do not have a strong grasp of diseases that could potentially influence their own health, I hope to find a way to educate students on biological and psychological diseases, their genetic risk, and how to speak openly about them.
ContributorsParasher, Nisha (Author) / Amdam, Gro (Thesis director) / Toft, Carolyn Cavaugh (Committee member) / Ostwald, Madeleine (Committee member) / Department of Psychology (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Honeybees (Apis mellifera) are pollinators that face multiple challenges during foraging such as fungicides applied to floral sources. Fungicides are chemicals used to inhibit key fungal mechanisms like metabolism, but their effects remain relatively unknown in bees. In addition, studying the maturing bee can help us identify demographics that are more vulnerable to toxic materials like fungicides. The purpose of this study is test whether maturation and the fungicide Pristine influence the permeability of the blood-brain barrier. Specifically, we use a transportable dye to test how blood brain barrier transporter function responds to toxic insult and how it changes with age. Oral ingestion of Pristine by female workers did not have an effect on blood brain barrier permeability which suggests Pristine may have no or longer term consequences in the bee. However, blood brain barrier permeability changed with the bee's age which could be explained by the regulation of blood brain barrier transporters during natural transitions in hive task or the presence of hemolymph protein filtration
ContributorsPatel, Aamir S. (Author) / Amdam, Gro (Thesis director) / Harrison, Jon (Committee member) / Ozturk, Cahit (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Dire wolves have recently risen to fame as a result of the popular television program Game of Thrones, and thus many viewers know dire wolves as the sigil and loyal companions of the Stark house. Far fewer recognize dire wolves by their scientific name, Canis dirus, or understand the population history of this ‘fearsome wolf’ species that roamed the Americas until the megafaunal mass extinction event of the Late Pleistocene. Although numerous studies have examined the species using morphological and geographical methods, thus far their results have been either inconclusive or contradictory. Remaining questions include the relationships dire wolves share with other members of the Canis genus and the internal structure of their populations. Advancements in ancient DNA recovery methods may make it possible to study dire wolf specimens at the molecular level for the first time and may therefore prove useful in clarifying the answers to these questions. Eighteen dire wolf specimens were collected from across the United States and subjected to ancient DNA extraction, library preparation, amplification and purification, bait preparation and capture, and next-generation sequencing. There was an average of 76.9 unique reads and 5.73% coverage when mapped to the Canis familiaris reference genome in ultraconserved regions of the mitochondrial genome. The results indicate that endogenous ancient DNA was not successfully recovered and perhaps ancient DNA recovery methods have not advanced to the point of retrieving informative amounts of DNA from particularly old, thermally degraded specimens. Nevertheless, the ever-changing nature of ancient DNA research makes it vital to continually test the limitations of the field and suggests that ancient DNA recovery methods will prove useful in illuminating dire wolf population history at some point in the future.
ContributorsSkerry, Katherine Marie (Author) / Stone, Anne (Thesis director) / Amdam, Gro (Committee member) / Larson, Greger (Committee member) / School of Human Evolution and Social Change (Contributor) / School of Nutrition and Health Promotion (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Prostate cancer is the second most common kind of cancer in men. Fortunately, it has a 99% survival rate. To achieve such a survival rate, a variety of aggressive therapies are used to treat prostate cancers that are caught early. Androgen deprivation therapy (ADT) is a therapy that is given in cycles to patients. This study attempted to analyze what factors in a group of 79 patients caused them to stick with or discontinue the treatment. This was done using naïve Bayes classification, a machine-learning algorithm. The usage of this algorithm identified high testosterone as an indicator of a patient persevering with the treatment, but failed to produce statistically significant high rates of prediction.
ContributorsMillea, Timothy Michael (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Vitellogenin (vg) is a precursor protein of egg yolk in honeybees, but it is also known to have immunological functions. The purpose of this experiment was to determine the effect of vg on the viral load of deformed wing virus (DWV) in worker honey bees (Apis mellifera). I hypothesized that a reduction in vg expression would lead to an increase in the viral load. I collected 180 worker bees and split them into four groups: half the bees were subjected to a vg gene knockdown by injections of double stranded vg RNA, and the rest were injected with green fluorescent protein (gfp) double stranded RNA. Half of each group was thereafter injected with DWV, and half given a sham injection. The rate of mortality in all four groups was higher than expected, leaving only 17 bees total. I dissected these bees' fat bodies and extracted their RNA to test for vg and DWV. PCR results showed that, out of the small group of remaining bees, the levels of vg were not statistically different. Furthermore, both groups of virus-injected bees showed similar viral loads. Because of the high mortality rate bees and the lack of differing levels of vg transcript between experimental and control groups, I could not draw conclusions from these results. The high mortality could be caused by several factors: temperature-induced stress, repeated stress from the two injections, and stress from viral infection. In addition, it is possible that the vg dsRNA batch I used was faulty. This thesis exemplifies that information cannot safely be extracted when loss of sampling units result in a small datasets that do not represent the original sampling population.
ContributorsCrable, Emma Lewis (Author) / Amdam, Gro (Thesis director) / Wang, Ying (Committee member) / Dahan, Romain (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05