Thesis (Ph. D.)--University of Missouri-Columbia, 2003. / Typescript. Vita. Includes bibliographical references (leaves 83-89). Also available on the Internet.

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 115-118).

Abstract Introduction: Breast cancer is the most common female cancer worldwide and it is also the principal cause of death from cancer among women globally. Breast cancer has the highest prevalence among Panamanian women and its incidence is also growing every year. Women living with and beyond breast cancer have special needs that have to be considered by society and the health care systems. After diagnosis, the quality of life (QOL) of women is highly affected, due to the emergence of physical, psychological and social effects which lead to changes in attitudes and expectations towards life. Purpose: To evaluate the QOL, among Panamanian women who suffer from breast cancer, factors that could influence QOL and the main life areas where these women are more affected when they receive this diagnosis. Methodology: A cross-sectional study was developed to measure the QOL of Panamanian breast cancer survivors in four domains (physical, social, psychological and environmental). A total of 240 survivor women completed 80% of the self-assessment QOL-BREF survey at the National Cancer Institute of Panama during March, 2013. Non-parametric statistical tests were used to define QOL based on the survey results, including sociodemographic and medical characteristics. A logistic regression model was performed to evaluate variables than can influence the quality of life among this population. Results: Higher socioeconomic indicators as well as having greater levels of spiritual belief, younger age and less than 5 years of cancer diagnosis appear to produce positive and statistically significant differences in QOL among breast cancer survivors. Conclusions: Breast cancer survivors in Panama have a good quality of life perception and are satisfied with their health. Support principally from family and friends plays a very important role in all aspects of QOL. Elderly women have different physical needs that could explain the lowest score reported in this study.

The proportion of authigenic to detrital clay minerals in terrestrial sediments is variable. It has previously been hypothesized that pure Mg-silicates in regions such as Amboseli Basin in Kenya occur due to the absence of Al-rich detritus. We tested this by replicating two Mg-silicate synthesis experiments while adding Al-rich smectite. The first study produced an X-ray amorphous Mg-silicate gel, with little response to addition of Al-rich smectite. The second experiment shifted the 060 peak associated with clay octahedral sheets, suggesting we synthesized trioctahedral domains in a smectite structure. Peak height increased linearly with more heating, indicating crystallinity changes. These results confirm that Al-rich detritus can influence the mineralogy of authigenic clays in saline, alkaline settings. By examining how clay neoformation is affected by silica saturation, we can better understand how the clays found in Neogene lacustrine environments are formed and the climate and of that time.

published_or_final_version / Mathematics / Master / Master of Philosophy

Many protein-protein interactions, especially those involved in eukaryotic signalling, are mediated by PDZ domains through the recognition of hydrophobic C-termini. The availability of experimental PDZ interaction data sets have led to the construction of computational methods to predict PDZ domain-peptide interactions. Such predictors are ideally suited to predict interactions in single organisms or for limited subsets of PDZ domains. As a result, the goal of my thesis has been to build general predictors that can be used to scan the proteomes of multiple organisms for ligands for almost all PDZ domains from select model organisms. A framework consisting of four steps: data collection, feature encoding, predictor training and evaluation was developed and applied for all predictors built in this thesis. The first predictor utilized PDZ domain-peptide sequence information from two interaction data sets obtained from high throughput protein microarray and phage display experiments in mouse and human, respectively. The second predictor used PDZ domain structure and peptide sequence information. I showed that these predictors are complementary to each other, are capable of predicting unseen interactions and can be used for the purposes of proteome scanning in human, worm and fly. As both positive and negative interactions are required for building a successful predictor, a major obstacle I addressed was the generation of artificial negative interactions for training. In particular, I used position weight matrices to generate such negatives for the positive only phage display data and used a semi-supervised learning approach to overcome the problem of over-prediction (i.e. prediction of too many positives). These predictors are available as a community web resource: http://webservice.baderlab.org/domains/POW. Finally, a Bayesian integration method combining information from different biological evidence sources was used to filter the human proteome scanning predictions from both predictors. This resulted in the construction of a comprehensive physiologically relevant high confidence PDZ mediated protein-protein interaction network in human.

Many protein-protein interactions, especially those involved in eukaryotic signalling, are mediated by PDZ domains through the recognition of hydrophobic C-termini. The availability of experimental PDZ interaction data sets have led to the construction of computational methods to predict PDZ domain-peptide interactions. Such predictors are ideally suited to predict interactions in single organisms or for limited subsets of PDZ domains. As a result, the goal of my thesis has been to build general predictors that can be used to scan the proteomes of multiple organisms for ligands for almost all PDZ domains from select model organisms. A framework consisting of four steps: data collection, feature encoding, predictor training and evaluation was developed and applied for all predictors built in this thesis. The first predictor utilized PDZ domain-peptide sequence information from two interaction data sets obtained from high throughput protein microarray and phage display experiments in mouse and human, respectively. The second predictor used PDZ domain structure and peptide sequence information. I showed that these predictors are complementary to each other, are capable of predicting unseen interactions and can be used for the purposes of proteome scanning in human, worm and fly. As both positive and negative interactions are required for building a successful predictor, a major obstacle I addressed was the generation of artificial negative interactions for training. In particular, I used position weight matrices to generate such negatives for the positive only phage display data and used a semi-supervised learning approach to overcome the problem of over-prediction (i.e. prediction of too many positives). These predictors are available as a community web resource: http://webservice.baderlab.org/domains/POW. Finally, a Bayesian integration method combining information from different biological evidence sources was used to filter the human proteome scanning predictions from both predictors. This resulted in the construction of a comprehensive physiologically relevant high confidence PDZ mediated protein-protein interaction network in human.

Late expression factor 3 is one of the six AcMNPV genes essential for DNA replication identified through transient replication assays. LEF-3 is a single stranded DNA binding protein responsible for the transportation of the viral helicase (P143) into the nucleus of the infected cell. In this study, a protein complementation-based assay was adapted to identify the region(s) of LEF-3 that is (are) involved in LEF-3-LEF-3 protein interactions. The full-length LEF-3, or various truncated LEF-3 regions were fused with Venus1 (N- terminus portions of full length Venus, a modified yellow fluorescence protein) or Venus2 (C- terminus). Venus1 and Venus2 fragments generated a functional fluorescent Venus protein when the two fragments were brought together by protein-protein interaction of the fused LEF-3 constructs. Fluorescence generated by coexpression of full-length LEF-3 fusion proteins confirmed that LEF-3 exists as homo-oligomer. Interaction between the full-length and the N- terminal (aa 1-189) or C- terminal regions (aa 190-385), and between the various truncated LEF-3 regions suggested the complexity of LEF-3 oligomeric structure. LEF-3 constructs deleted for NLS function revealed cytoplasmic fluorescence, suggesting that LEF-3-LEF-3 interactions occur in the absence of DNA or nuclear proteins. Because LEF-3 is essential for nuclear transporting the viral helicase (P143), the ability of LEF-3 to interact with another viral protein was investigated. P47, a sub-unit of the viral RNA polymerase was chosen because it is cytoplasmic when expressed on its own. The interaction between LEF-3 and P47 produced complete nuclear localized fluorescent signals. Overall, the results suggest that there are multiple regions of LEF-3 that are capable of closely interacting, and that multiple domains are likely involved in the oligomerization of full-length LEF-3. The interaction of LEF-3 with P47 suggests that P47 may be another LEF-3 cargo protein. / Thesis (Master, Microbiology & Immunology) -- Queen's University, 2011-05-27 15:02:53.983

In this thesis, we give a new definition of Hardy Spaces on hyperconvex domains in terms of Monge-Amp`ere measures which unifies the Hardy spaces on polydiscs and balls. Also we survey Monge-Amp`ere operators and Monge- Amp`ere measures.

Author's `Characterization of subgradients: 1` (31 leaves) in pocket / Bibliography: leaves 229-231 / 231 leaves : 1 port ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, 1986