Respiratory rhythm generation: A modeling study of the respiratory central pattern generator and the phrenic motor neuron

The respiratory central pattern generator is a collection of medullary neurons that generates the rhythm of respiration. The respiratory central pattern generator feeds phrenic motor neurons, which, in turn, drive the main muscle of respiration, the diaphragm. The purpose of this thesis is to understand the neural control of respiration through mathematical models of the respiratory central pattern generator and phrenic motor neurons. ^ We first designed and validated a Hodgkin-Huxley type model that mimics the behavior of phrenic motor neurons under a wide range of electrical and pharmacological perturbations. This model was constrained physiological data from the literature. Next, we designed and validated a model of the respiratory central pattern generator by connecting four Hodgkin-Huxley type models of medullary respiratory neurons in a mutually inhibitory network. This network was in turn driven by a simple model of an endogenously bursting neuron, which acted as the pacemaker for the respiratory central pattern generator. Finally, the respiratory central pattern generator and phrenic motor neuron models were connected and their interactions studied. ^ Our study of the models has provided a number of insights into the behavior of the respiratory central pattern generator and phrenic motor neurons. These include the suggestion of a role for the T-type and N-type calcium channels during single spikes and repetitive firing in phrenic motor neurons, as well as a better understanding of network properties underlying respiratory rhythm generation. We also utilized an existing model of lung mechanics to study the interactions between the respiratory central pattern generator and ventilation. ^

Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.

Modeling survival and the development of second primary tumors among Hodgkin's disease patients

Hodgkin's disease (HD) is a cancer of the lymphatic system. Survivors of HD face varieties of consequent adverse effects, in which secondary primary tumors (SPT) is one of the most serious consequences. This dissertation is aimed to model time-to-SPT in the presence of death and HD relapses during follow-up.^ The model is designed to handle a mixture phenomenon of SPT and the influence of death. Relapses of HD are adjusted as a covariate. Proportional hazards framework is used to define SPT intensity function, which includes an exponential term to estimate explanatory variables. Death as a competing risk is considered according to different scenarios, depending on which terminal event comes first. Newton-Raphson method is used to estimate the parameter estimates in the end.^ The proposed method is applied to a real data set containing a group of HD patients. Several risk factors for the development of SPT are identified and the findings are noteworthy in the development of healthcare guidelines that may lead to the early detection or prevention of SPT.^

Molecular studies of human high grade B cell non -Hodgkin's lymphomas

The non-Hodgkin's B cell lymphomas are a diverse group of neoplastic diseases. The incidence rate of the malignant tumors has been rising rapidly over the past twenty years in the United States and worldwide. The lack of insight to pathogenesis of the disease poses a significant problem in the early detection and effective treatment of the human malignancies. These studies attempted to investigate the molecular basis of pathogenesis of the human high grade B cell non-Hodgkin's lymphomas with a reverse genetic approach. The specific objective was to clone gene(s) which may play roles in development and progression of human high grade B cell non-Hodgkin's lymphomas.^ The messenger RNAs from two high grade B cell lymphoma lines, CJ and RR, were used for construction of cDNA libraries. Differential screening of the derived cDNA libraries yielded a 1.4 kb cDNA clone. The gene, designated as NHL-B1.4, was shown to be highly amplified and over-expressed in the high grade B cell lymphoma lines. It was not expressed in the peripheral blood lymphoid cells from normal donors. However, it was inducible in peripheral blood T lymphocytes by a T cell mitogen, PHA, but could not be activated in normal B cells by B cell mitogen PMA. Further molecular characterization revealed that the gene may have been rearranged in the RR and some other B cell lymphoma lines. The coding capacity of the cDNA has been confirmed by a rabbit reticulocyte lysate and wheat germ protein synthesis system. A recombinant protein with a molecular weight of approximate 30 kDa was visualized in autoradiogram. Polyclonal antisera have been generated by immunization of two rabbits with the NHL-B1.4 recombinant protein produced in the E. coli JM109. The derived antibody can recognize a natural protein with molecular weight of 49 kDa in cell lysate of activated peripheral T lymphocytes of normal donors and both the cell lysate and supernatant of RR B cell lymphoma lines. The possible biologic functions of the molecule has been tested preliminarily in a B lymphocyte proliferation assay. It was found that the Q-sepharose chromatograph purified supernatant of COS cell transfection could increase tritiated thymidine uptake by B lymphocytes but not by T lymphocytes. The B cell stimulatory activity of the supernatant of COS cell tranfection could be neutralized by the polyclonal antisera, indicating that the NHL-B1.4 gene product may be a molecule with BCGF-like activity.^ The expression profiles of NHL-B1.4 in normal and neoplastic lymphoid cells were consistent with the current B lymphocyte activation model and autocrine hypothesis of high grade B cell lymphomagenesis. These results suggested that the NHL-B1.4 cDNA may be a disease-related gene of human high grade B cell lymphomas, which may codes for a postulated B cell autocrine growth factor. ^