Mathematical and empirical examinations of some epidemiological procedures

In epidemiology literature, it is often required to investigate the relationships between means where the levels of experiment are actually monotone sets forming a partition on the range of sampling values. With this need, the analysis of these group means is generally performed using classical analysis of variance (ANOVA). However, this method has never been challenged. In this dissertation, we will formulate and present our examination of its validity. First, the classical assumptions of normality and constant variance are not always true. Second, under the null hypothesis of equal means, the test statistic for the classical ANOVA technique is still valid. Third, when the hypothesis of equal means is rejected, the classical analysis techniques for hypotheses of contrasts are not valid. Fourth, under the alternative hypothesis, we can show that the monotone property of levels leads to the conclusion that the means are monotone. Fifth, we propose an appropriate method for handing the data in this situation. ^

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

Exploring parental factors and their influence on early adolescent sexual health

Black and Hispanic youth experience the largest burden of sexually transmitted infections, teen pregnancy, and childbirth (Hamilton, Martin, & Ventura, 2011). Minority youth are disporportionately more likely to sexually debut at every age and debut before the age of 13 compared to whites (Centers for Disease Control and Prevention, 2011). However, there is little known about pre-coital sexual activity or protective parental factors in early adolscent minority youth. Parental factors such as parent-child communication and parental monitoring influence adolescent sexual behaviors and pre-coital sexual behaviors in early adolescence. Three distinct methods were used in this dissertation. Study one used qualitative methods, semi-structured, in-depth, individual interviews, to explore parent-child communication in African American mother-early adolescent son dyads. Study two used quantitative methods, secondary data analysis of a cross sectional study, to conduct a moderation analysis. For study three, I conducted a systematic review of parent-based adolescent sexual health interventions. Study one found that mothers feel comfortable talking about sex with adolescents, provide a two-prong sexual health message, and want their sons to tell their when they are thinking of having sex. Study found that parental monitoring moderates the relation between parent-child communication and pre-coital sexual behaviors. Study three found that interventions use a variety of theory, methods, and strategies and that no parent-based programs target faith-based organizations, mother-son or father-daughter dyads, or parents of LGBTQ youth. Adolescent sexual health interventions should consider addressing youth-to-parent disclosure of sexual activity or intentions to debut, addressing both parent-child sexual health communication and parental monitoring, and using a theoretical framework.^

Improving follow-up of abnormal cancer screens using electronic health records: trust but verify test result communication.

BACKGROUND: Early detection of colorectal cancer through timely follow-up of positive Fecal Occult Blood Tests (FOBTs) remains a challenge. In our previous work, we found 40% of positive FOBT results eligible for colonoscopy had no documented response by a treating clinician at two weeks despite procedures for electronic result notification. We determined if technical and/or workflow-related aspects of automated communication in the electronic health record could lead to the lack of response. METHODS: Using both qualitative and quantitative methods, we evaluated positive FOBT communication in the electronic health record of a large, urban facility between May 2008 and March 2009. We identified the source of test result communication breakdown, and developed an intervention to fix the problem. Explicit medical record reviews measured timely follow-up (defined as response within 30 days of positive FOBT) pre- and post-intervention. RESULTS: Data from 11 interviews and tracking information from 490 FOBT alerts revealed that the software intended to alert primary care practitioners (PCPs) of positive FOBT results was not configured correctly and over a third of positive FOBTs were not transmitted to PCPs. Upon correction of the technical problem, lack of timely follow-up decreased immediately from 29.9% to 5.4% (p<0.01) and was sustained at month 4 following the intervention. CONCLUSION: Electronic communication of positive FOBT results should be monitored to avoid limiting colorectal cancer screening benefits. Robust quality assurance and oversight systems are needed to achieve this. Our methods may be useful for others seeking to improve follow-up of FOBTs in their systems.

The role of substance abuse treatment in preventing human immunodeficiency virus transmission among injecting drug users

This exploratory study assesses the utility of substance abuse treatment as a strategy for preventing human immunodeficiency virus (HIV) transmission among injecting drug users (IDUs). Data analyzed in this study were collected in San Antonio, TX, 1989 through 1995 using both qualitative and quantitative methods. Qualitative data included ethnographic interviews with 234 active IDUs; quantitative data included baseline risk assessments and HIV screening plus interviews follow-up interviews administered approximately six months later to 823 IDUs participating in a Federally-funded AIDS community outreach demonstration project.^ Findings that have particularly important implications for substance abuse treatment as an HIV prevention strategy for IDUs are listed below. (1) IDUs who wanted treatment were significantly more likely to be daily heroin users. (2) IDUs who want treatment were significantly more likely to have been to treatment previously. (3) IDUs who wanted treatment at baseline reported significantly higher levels of HIV risk than IDUs who did not want treatment. (4) IDUs who went to treatment between their baseline and follow-up interviews reported significantly higher levels of HIV risk at baseline than IDUs who did not go to treatment. (5) IDUs who went to treatment between their baseline and follow-up interviews reported significantly greater decreases in injection-related HIV risk behaviors. (6) IDUs who went to treatment reported significantly greater decreases in sexual HIV risk behaviors than IDUs who did not go to treatment.^ This study also noted a number of factors that may limit the effectiveness of substance abuse treatment in reducing HIV risk among IDUs. Findings suggest that the impact of methadone maintenance on HIV risk behaviors among opioid dependent IDUs may be limited by the negative manner in which it is perceived by IDUs as well as other elements of society. One consequence of the negative perception of methadone maintenance held by many elements of society may be an unwillingness to provide public funding for an adequate number of methadone maintenance slots. Thus many IDUs who would be willing to enter methadone maintenance are unable to enter it and many IDUs who do enter it are forced to drop out prematurely. ^

Use of short term test systems for the prediction of the hazard represented by potential chemical carcinogens

It has been hypothesized that results from the short term bioassays will ultimately provide information that will be useful for human health hazard assessment. Although toxicologic test systems have become increasingly refined, to date, no investigator has been able to provide qualitative or quantitative methods which would support the use of short term tests in this capacity.^ Historically, the validity of the short term tests have been assessed using the framework of the epidemiologic/medical screens. In this context, the results of the carcinogen (long term) bioassay is generally used as the standard. However, this approach is widely recognized as being biased and, because it employs qualitative data, cannot be used in the setting of priorities. In contrast, the goal of this research was to address the problem of evaluating the utility of the short term tests for hazard assessment using an alternative method of investigation.^ Chemical carcinogens were selected from the list of carcinogens published by the International Agency for Research on Carcinogens (IARC). Tumorigenicity and mutagenicity data on fifty-two chemicals were obtained from the Registry of Toxic Effects of Chemical Substances (RTECS) and were analyzed using a relative potency approach. The relative potency framework allows for the standardization of data "relative" to a reference compound. To avoid any bias associated with the choice of the reference compound, fourteen different compounds were used.^ The data were evaluated in a format which allowed for a comparison of the ranking of the mutagenic relative potencies of the compounds (as estimated using short term data) vs. the ranking of the tumorigenic relative potencies (as estimated from the chronic bioassays). The results were statistically significant (p $<$.05) for data standardized to thirteen of the fourteen reference compounds. Although this was a preliminary investigation, it offers evidence that the short term test systems may be of utility in ranking the hazards represented by chemicals which may be human carcinogens. ^

DETERMINING THE GENOTYPE-PHENOTYPE CONNECTION IN SYNTHETIC INDUCIBLE GENE EXPRESSION SYSTEMS

Introduction Gene expression is an important process whereby the genotype controls an individual cell’s phenotype. However, even genetically identical cells display a variety of phenotypes, which may be attributed to differences in their environment. Yet, even after controlling for these two factors, individual phenotypes still diverge due to noisy gene expression. Synthetic gene expression systems allow investigators to isolate, control, and measure the effects of noise on cell phenotypes. I used mathematical and computational methods to design, study, and predict the behavior of synthetic gene expression systems in S. cerevisiae, which were affected by noise. Methods I created probabilistic biochemical reaction models from known behaviors of the tetR and rtTA genes, gene products, and their gene architectures. I then simplified these models to account for essential behaviors of gene expression systems. Finally, I used these models to predict behaviors of modified gene expression systems, which were experimentally verified. Results Cell growth, which is often ignored when formulating chemical kinetics models, was essential for understanding gene expression behavior. Models incorporating growth effects were used to explain unexpected reductions in gene expression noise, design a set of gene expression systems with “linear” dose-responses, and quantify the speed with which cells explored their fitness landscapes due to noisy gene expression. Conclusions Models incorporating noisy gene expression and cell division were necessary to design, understand, and predict the behaviors of synthetic gene expression systems. The methods and models developed here will allow investigators to more efficiently design new gene expression systems, and infer gene expression properties of TetR based systems.