A categorical data analysis approach to estimation of demographic characteristics for Texas county populations

The need for timely population data for health planning and Indicators of need has Increased the demand for population estimates. The data required to produce estimates is difficult to obtain and the process is time consuming. Estimation methods that require less effort and fewer data are needed. The structure preserving estimator (SPREE) is a promising technique not previously used to estimate county population characteristics. This study first uses traditional regression estimation techniques to produce estimates of county population totals. Then the structure preserving estimator, using the results produced in the first phase as constraints, is evaluated.^ Regression methods are among the most frequently used demographic methods for estimating populations. These methods use symptomatic indicators to predict population change. This research evaluates three regression methods to determine which will produce the best estimates based on the 1970 to 1980 indicators of population change. Strategies for stratifying data to improve the ability of the methods to predict change were tested. Difference-correlation using PMSA strata produced the equation which fit the data the best. Regression diagnostics were used to evaluate the residuals.^ The second phase of this study is to evaluate use of the structure preserving estimator in making estimates of population characteristics. The SPREE estimation approach uses existing data (the association structure) to establish the relationship between the variable of interest and the associated variable(s) at the county level. Marginals at the state level (the allocation structure) supply the current relationship between the variables. The full allocation structure model uses current estimates of county population totals to limit the magnitude of county estimates. The limited full allocation structure model has no constraints on county size. The 1970 county census age - gender population provides the association structure, the allocation structure is the 1980 state age - gender distribution.^ The full allocation model produces good estimates of the 1980 county age - gender populations. An unanticipated finding of this research is that the limited full allocation model produces estimates of county population totals that are superior to those produced by the regression methods. The full allocation model is used to produce estimates of 1986 county population characteristics. ^

DEVELOPMENT OF NOVEL METHODS TO MINIMIZE THE IMPACT OF SEQUENCING ERRORS IN THE NEXT-GENERATION SEQUENCING DATA ANALYSIS

Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

Bayesian inference and its application to meta-analysis of epidemiologic data

In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayesian method are illustrated. Part Two applies the Bayesian meta-analysis program, the Confidence Profile Method (CPM), to clinical trial data and evaluates the merits of using Bayesian meta-analysis for overviews of clinical trials.^ The Bayesian method of meta-analysis produced similar results to the classical results because of the large sample size, along with the input of a non-preferential prior probability distribution. These results were anticipated through explanations in Part One of the mechanics of the Bayesian approach. ^

The SanaViz: Human Centered Geovisualization to facilitate visual exploration of Public Health data

These three manuscripts are presented as a PhD dissertation for the study of using GeoVis application to evaluate telehealth programs. The primary reason of this research was to understand how the GeoVis applications can be designed and developed using combined approaches of HC approach and cognitive fit theory and in terms utilized to evaluate telehealth program in Brazil. First manuscript The first manuscript in this dissertation presented a background about the use of GeoVisualization to facilitate visual exploration of public health data. The manuscript covered the existing challenges that were associated with an adoption of existing GeoVis applications. The manuscript combines the principles of Human Centered approach and Cognitive Fit Theory and a framework using a combination of these approaches is developed that lays the foundation of this research. The framework is then utilized to propose the design, development and evaluation of “the SanaViz” to evaluate telehealth data in Brazil, as a proof of concept. Second manuscript The second manuscript is a methods paper that describes the approaches that can be employed to design and develop “the SanaViz” based on the proposed framework. By defining the various elements of the HC approach and CFT, a mixed methods approach is utilized for the card sorting and sketching techniques. A representative sample of 20 study participants currently involved in the telehealth program at the NUTES telehealth center at UFPE, Recife, Brazil was enrolled. The findings of this manuscript helped us understand the needs of the diverse group of telehealth users, the tasks that they perform and helped us determine the essential features that might be necessary to be included in the proposed GeoVis application “the SanaViz”. Third manuscript The third manuscript involved mix- methods approach to compare the effectiveness and usefulness of the HC GeoVis application “the SanaViz” against a conventional GeoVis application “Instant Atlas”. The same group of 20 study participants who had earlier participated during Aim 2 was enrolled and a combination of quantitative and qualitative assessments was done. Effectiveness was gauged by the time that the participants took to complete the tasks using both the GeoVis applications, the ease with which they completed the tasks and the number of attempts that were taken to complete each task. Usefulness was assessed by System Usability Scale (SUS), a validated questionnaire tested in prior studies. In-depth interviews were conducted to gather opinions about both the GeoVis applications. This manuscript helped us in the demonstration of the usefulness and effectiveness of HC GeoVis applications to facilitate visual exploration of telehealth data, as a proof of concept. Together, these three manuscripts represent challenges of combining principles of Human Centered approach, Cognitive Fit Theory to design and develop GeoVis applications as a method to evaluate Telehealth data. To our knowledge, this is the first study to explore the usefulness and effectiveness of GeoVis to facilitate visual exploration of telehealth data. The results of the research enabled us to develop a framework for the design and development of GeoVis applications related to the areas of public health and especially telehealth. The results of our study showed that the varied users were involved with the telehealth program and the tasks that they performed. Further it enabled us to identify the components that might be essential to be included in these GeoVis applications. The results of our research answered the following questions; (a) Telehealth users vary in their level of understanding about GeoVis (b) Interaction features such as zooming, sorting, and linking and multiple views and representation features such as bar chart and choropleth maps were considered the most essential features of the GeoVis applications. (c) Comparing and sorting were two important tasks that the telehealth users would perform for exploratory data analysis. (d) A HC GeoVis prototype application is more effective and useful for exploration of telehealth data than a conventional GeoVis application. Future studies should be done to incorporate the proposed HC GeoVis framework to enable comprehensive assessment of the users and the tasks they perform to identify the features that might be necessary to be a part of the GeoVis applications. The results of this study demonstrate a novel approach to comprehensively and systematically enhance the evaluation of telehealth programs using the proposed GeoVis Framework.

Application of the general linear model to assess the effect of missing data on bone marrow mononuclear cell therapy with infusion timing and follow-up MRI

With most clinical trials, missing data presents a statistical problem in evaluating a treatment's efficacy. There are many methods commonly used to assess missing data; however, these methods leave room for bias to enter the study. This thesis was a secondary analysis on data taken from TIME, a phase 2 randomized clinical trial conducted to evaluate the safety and effect of the administration timing of bone marrow mononuclear cells (BMMNC) for subjects with acute myocardial infarction (AMI).^ We evaluated the effect of missing data by comparing the variance inflation factor (VIF) of the effect of therapy between all subjects and only subjects with complete data. Through the general linear model, an unbiased solution was made for the VIF of the treatment's efficacy using the weighted least squares method to incorporate missing data. Two groups were identified from the TIME data: 1) all subjects and 2) subjects with complete data (baseline and follow-up measurements). After the general solution was found for the VIF, it was migrated Excel 2010 to evaluate data from TIME. The resulting numerical value from the two groups was compared to assess the effect of missing data.^ The VIF values from the TIME study were considerably less in the group with missing data. By design, we varied the correlation factor in order to evaluate the VIFs of both groups. As the correlation factor increased, the VIF values increased at a faster rate in the group with only complete data. Furthermore, while varying the correlation factor, the number of subjects with missing data was also varied to see how missing data affects the VIF. When subjects with only baseline data was increased, we saw a significant rate increase in VIF values in the group with only complete data while the group with missing data saw a steady and consistent increase in the VIF. The same was seen when we varied the group with follow-up only data. This essentially showed that the VIFs steadily increased when missing data is not ignored. When missing data is ignored as with our comparison group, the VIF values sharply increase as correlation increases.^

Characterization of neurotransmitter inputs to cholinergic amacrine cells of the rabbit retina: Analysis of ACh release

The cholinergic amacrine cells of the rabbit retinal are the only neurons which accumulate choline and also synthesize acetylcholine (ACh). It is widely accepted that the physiologically evoked release of acetylcholine can be taken as a measure of the activity of the entire cholinergic population. Initially, we examined the possibility that these cells receive excitatory input via glutamate receptors from glutamatergic neurons. Glutamate analogs were found to cause massive ACh release from the rabbit retina. Glutamate was found to activate several different receptor subtypes. Selective glutamate antagonists were used to separate the responses evoked by the different glutamate receptor subtypes. The kainate receptor was determined pharmacologically to be the subtype activated physiologically. Since bipolar cells make direct contact with cholinergic amacrine cells, our results support the hypothesis the bipolar cell neurotransmitter is glutamate. Although NMDA receptors can be activated by NMDA analogs, they are not activated during the physiologically evoked release of ACh. A separate study examined the possibility that L-homocysteate could be the bipolar cell neurotransmitter and the results placed serious constraints on this possibility.^ GABA$\sb{\rm A}$ agonists and antagonists are known to have powerful effects on ACh release from the rabbit retina. By pharmacologically blocking the excitatory input from bipolar cells, we attempted to determine the site of GABA$\sb{\rm A}$ input. Our results suggest that the predominant site of GABA$\sb{\rm A}$ input is onto the bipolar cells presynaptic to cholinergic amacrine cells. In a separate study, we found SR-95531 to be a potent and selective GABA$\sb{\rm A}$ receptor antagonist. In addition, GABA$\sb{\rm B}$ agonists and antagonists were found to have minor or no effects on ACh release. Glycine was also examined, its inhibitory effects were found to be very similar to GABA$\sb{\rm A}$ agonists. In contrast, strychnine was found to increase basal but inhibit light evoked ACh release. Additional results indicated that the predominant site of glycinergic input is onto the presynaptic bipolar cells. Our results suggest a different role for glycine compared to GABA in shaping the light evoked release of ACh from the rabbit retina. ^

AN ELECTROPHYSIOLOGICAL ANALYSIS OF THE AMYGDALOID AND SUBICULAR PROJECTIONS TO THE VENTROMEDIAL NUCLEUS OF THE HYPOTHALAMUS IN THE RABBIT

Electrophysiological experiments were performed on 96 male New Zealand white rabbits, anesthetized with urethane. Glass electrodes, filled with 2M NaCl, were used for microstimulation of three fiber pathways projecting from "limbic" centers to the ventromedial nucleus of the hypothalamus (VMH). Unitary and field potential recordings were made in the VMH after stimulation.^ Stimulation of the lateral portion of the fimbria, which carries fibers from the ventral subiculum of the hippocampal formation, evokes predominantly an inhibition of neurons medially in the VMH, and excitation of neurons located laterally.^ Stimulation of the dorsal portion of the stria terminalis, which carries fibers from the cortical nucleus of the amygdala, also produces predominantly an inhibition of cells medially and excitation laterally.^ Stimulation of the ventral component of the stria terminalis, which carries fibers from the medial nucleus of the amygdala, evokes excitation of cell medially, with little or no response seen laterally.^ Cells recorded medially in the VMH received convergent inputs from each of the three fiber systems: inhibition from fimbria and dorsal stria stimulation, excitation from ventral stria stimulation.^ The excitatory unitary responses recorded medially to ventral stria stimulation and laterally to fimbria and dorsal stria stimulation were subjected to a series of threshold stimulus intensities. From these tests it was determined that each of these three projections terminates monosynaptically on VMH neurons.^ The evidence for convergence upon single VMH neurons of projections from the amygdala and the hippocampal formation suggests this area of the brain to be important for integration of information from these two limbic centers. The VMH has been implied in a number of behavioral states: eating, reproduction, defense and aggression; it has further been linked to control of the anterior pituitary. These data provide a functional circuit through which the amygdaloid complex and the hippocampal formation can channel information from higher cortical centers into a hypothalamic area capable of coordinating behavioral and hormonal responses. ^

Application of stellar photometry to the analysis of microarray images

Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

Using GIS methods to assess the occurrence of neural tube defect births by residential proximity at conception to hazardous waste sites

In the United States, approximately 4,000 pregnancies each year are affected by the two most common birth defects, spina bifida and anencephaly. Studies have shown that exposure to environmental chemicals before and after conception may adversely affect reproduction by inducing cell death or dysfunction, which leads to infertility, fetal loss, lowered weight at birth, or birth anomalies in the offspring. The objective of the study was to evaluate the relationship between Neural Tube Defect births and residence at conception in proximity to hazardous waste sites in the Texas-Mexico border region between 1993 and 2000. ^ The study design was a nested matched case-control and utilized secondary data from a project, “The role of chemical and biological factors in the etiology of neural tube birth defects births along the Texas-Mexico Border” (Irina Cech, Principal Investigator). Geographic Information Systems (GIS) database methods were used to compare Neural Tube Defects cases to controls on status of conception residence occurring within a one-mile radius from hazardous waste sites, as compared to conception residence further away. Information on the exposures was obtained from the OnTarget Database and Environment Protection Agency website. Conditional logistic regression was used for the matched case-control study to investigate the relationship between an outcome of being a case or a control and proximity to hazardous waste sites. ^ The result of the study showed a 36 percent non-significant increased risk of having an NTD birth associated with maternal proximity to abandoned hazardous waste sites (95% CI = 0.62–3.02). In addition, there was a 24% non-significant elevated risk of having an NTD birth when living in proximity to air pollutant sites than when living further away (95% CI = 0.67–2.32). Although this study did not find statistically significant associations, it will expand on the existing knowledge of the relationship between NTD and proximity to hazardous waste sites. ^

G870A polymorphism of cyclin D1 gene influences cancer risk - From epidemiological study to mechanism analysis

Alternate splicing of the cyclin D1 gene gives rise to transcript a and b which encode two protein isoforms cyclin D1a and cyclin D1b. Through testing transcript a and transcript b in a series of human samples, we found that cyclin D1 transcript b is ubiquitously expressed as transcript a but in the lower abundance compared to transcript a. Epidemiological studies have reported that the cyclin D1 gene (CCND1) G870A polymorphism influences the risk for a variety of cancer. In this investigation, we examined the cyclin D1b levels in tumor samples with different genotypes and found that higher levels of cyclin D1b are expressed from the A allele than the G allele. Cyclin D1 is known as a cell cycle regulator facilitating the progression of the cell cycle from G1 to S phase in response to the mitogenic signals. It also interacts with several transcription factors and transcriptional coregulators to modulate their activities. It has been reported that cyclin D1a can substitute for estrogen to activate estrogen receptor α (ERα) mediated transcription and can induce the proliferation of estrogen responsive tissues. However the biological role of cyclin D1b in ERα transcriptional regulation has not been previously explored. In this study, we determined that cyclin D1b antagonizes the action of cyclin D1a on ERα mediated transcription. Cell proliferation assays provided the evidence that cyclin D1b negatively regulates estrogen responsive breast cancer cell growth. Taken together, our findings show that the CCND1 G870A polymorphism is correlated with increased levels of cyclin D1b and that cyclin D1b antagonizes the action of cyclin D1a on ERα mediated transcription providing evidence for the mechanism by which the CCND1 G870A polymorphism may be protective in certain types of breast cancer. ^

A comparative state policy analysis of the adoption of birth defects surveillance legislation

Birth defects are the leading cause of infant mortality in the United States and are a major cause of lifetime disability. However, efforts to understand their causes have been hampered by a lack of population-specific data. During 1990–2004, 22 state legislatures responded to this need by proposing birth defects surveillance legislation (BDSL). The contrast between these states and those that did not pass BDSL provides an opportunity to better understand conditions associated with US public health policy diffusion. ^ This study identifies key state-specific determinants that predict: (1) the introduction of birth defects surveillance legislation (BDSL) onto states' formal legislative agenda, and (2) the successful adoption of these laws. Secondary aims were to interpret these findings in a theoretically sound framework and to incorporate evidence from three analytical approaches. ^ The study begins with a comparative case study of Texas and Oregon (states with divergent BDSL outcomes), including a review of historical documentation and content analysis of key informant interviews. After selecting and operationalizing explanatory variables suggested by the case study, Qualitative Comparative Analysis (QCA) was applied to publically available data to describe important patterns of variation among 37 states. Results from logistic regression were compared to determine whether the two methods produced consistent findings. ^ Themes emerging from the comparative case study included differing budgetary conditions and the significance of relationships within policy issue networks. However, the QCA and statistical analysis pointed to the importance of political parties and contrasting societal contexts. Notably, state policies that allow greater access to citizen-driven ballot initiatives were consistently associated with lower likelihood of introducing BDSL. ^ Methodologically, these results indicate that a case study approach, while important for eliciting valuable context-specific detail, may fail to detect the influence of overarching, systemic variables, such as party competition. However, QCA and statistical analyses were limited by a lack of existing data to operationalize policy issue networks, and thus may have downplayed the impact of personal interactions. ^ This study contributes to the field of health policy studies in three ways. First, it emphasizes the importance of collegial and consistent relationships among policy issue network members. Second, it calls attention to political party systems in predicting policy outcomes. Finally, a novel approach to interpreting state data in a theoretically significant manner (QCA) has been demonstrated.^