Macromolecular interaction studies on FF1-3 of human CA150 and STAT1-importin alpha5 using biophysical and biochemical methods

Macromolecular interactions, such as protein-protein interactions and protein-DNA interactions, play important roles in executing biological functions in cells. However the complexity of such interactions often makes it very challenging to elucidate the structural details of these subjects. In this thesis, two different research strategies were applied on two different two macromolecular systems: X-ray crystallography on three tandem FF domains of transcription regulator CA150 and electron microscopy on STAT1-importin α5 complex. The results from these studies provide novel insights into the function-structure relationships of transcription coupled RNA splicing mediated by CA150 and the nuclear import process of the JAK-STAT signaling pathway. ^ The first project aimed at the protein-protein interaction module FF domain, which often occurs as tandem repeats. Crystallographic structure of the first three FF domains of human CA150 was determined to 2.7 Å resolution. This is the only crystal structure of an FF domain and the only structure on tandem FF domains to date. It revealed a striking connectivity between an FF domain and the next. Peptide binding assay with the potential binding ligand of FF domains was performed using fluorescence polarization. Furthermore, for the first time, FF domains were found to potentially interact with DNA. DNA binding assays were also performed and the results were supportive to this newly proposed functionality of an FF domain. ^ The second project aimed at understanding the molecular mechanism of the nuclear import process of transcription factor STAT1. The first structural model of pSTAT1-importin α5 complex in solution was built from the images of negative staining electron microscopy. Two STAT1 molecules were observed to interact with one molecule of importin α5 in an asymmetric manner. This seems to imply that STAT1 interacts with importin α5 with a novel mechanism that is different from canonical importin α-cargo interactions. Further in vitro binding assays were performed to obtain more details on the pSTAT1-importin α5 interaction. ^

Performance tiers: Implementing comparative effectiveness analysis in the health care setting through operations research and spatial methods

This dissertation develops and tests a comparative effectiveness methodology utilizing a novel approach to the application of Data Envelopment Analysis (DEA) in health studies. The concept of performance tiers (PerT) is introduced as terminology to express a relative risk class for individuals within a peer group and the PerT calculation is implemented with operations research (DEA) and spatial algorithms. The analysis results in the discrimination of the individual data observations into a relative risk classification by the DEA-PerT methodology. The performance of two distance measures, kNN (k-nearest neighbor) and Mahalanobis, was subsequently tested to classify new entrants into the appropriate tier. The methods were applied to subject data for the 14 year old cohort in the Project HeartBeat! study.^ The concepts presented herein represent a paradigm shift in the potential for public health applications to identify and respond to individual health status. The resultant classification scheme provides descriptive, and potentially prescriptive, guidance to assess and implement treatments and strategies to improve the delivery and performance of health systems. ^

SOCIO-ENVIRONMENTAL FACTORS ASSOCIATED WITH THE DISTRIBUTION OF DRACUNCULUS MEDINENSIS (GUINEA WORM DISEASE) AND SUGGESTED METHODS FOR CONTROL, IBARAPA, NIGERIA, 1982 (AFRICA)

A population-based cross-sectional survey of socio-environmental factors associated with the prevalence of Dracunculus medinensis (guinea worm disease) was conducted in Idere, a rural agricultural community in Ibarapa, Oyo state, Nigeria, during 1982.^ The epidemiologic data were collected by household interview of all 501 households. The environmental data were collected by analysis of water samples collected from all domestic water sources and rainfall records.^ The specific objectives of this research were to: (a) Describe the prevalence of guinea worm disease in Idere during 1982 by age, sex, area of residence, drinking water source, religion and weekly amount of money spent by the household to collect potable drinking water. (b) Compare the characteristics of cases with non-cases of guinea worm in order to identify factors associated with high risk of infection. (c) Investigate domestic water sources for the distribution of Cyclops. (d) Determine the extent of potable water shortage with a view to identifying factors responsible for such shortage in the community. (e) Describe the effects of guinea worm on school attendance during 1980/1982 school years by class and location of school from piped water supply.^ The findings of this research indicate that during 1982, 31.8 percent of Idere's 6,527 residents experienced guinea worm infection, with higher prevalence of infection recorded in males in their most productive years and females in their teenage years. The role of sex and age to risk of higher infection rate was explained in the context of water related exposure and water intake due to dehydration from physical occupational actitives of subgroups.^ Potable water available to residents was considerably below the minimum recommended by WHO for tropical climates, with sixty-eight percent of water needs of the residents coming from unprotected surface water which harbour Cyclops, the obligatory intermediate host of Dracunculus medinensis. An association was found between periods of relative high density of Cyclops in domestic water and rainfall.^ Impact of guinea worm infection on educational activities was considerable and its implications were discussed, including the implications of the research findings in relation to control of guinea worm disease in Ibarapa. ^

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Optimal, minimax, and Bayesian two-stage designs in two-dose phase II clinical trials

Background: For most cytotoxic and biologic anti-cancer agents, the response rate of the drug is commonly assumed to be non-decreasing with an increasing dose. However, an increasing dose does not always result in an appreciable increase in the response rate. This may especially be true at high doses for a biologic agent. Therefore, in a phase II trial the investigators may be interested in testing the anti-tumor activity of a drug at more than one (often two) doses, instead of only at the maximum tolerated dose (MTD). This way, when the lower dose appears equally effective, this dose can be recommended for further confirmatory testing in a phase III trial under potential long-term toxicity and cost considerations. A common approach to designing such a phase II trial has been to use an independent (e.g., Simon's two-stage) design at each dose ignoring the prior knowledge about the ordering of the response probabilities at the different doses. However, failure to account for this ordering constraint in estimating the response probabilities may result in an inefficient design. In this dissertation, we developed extensions of Simon's optimal and minimax two-stage designs, including both frequentist and Bayesian methods, for two doses that assume ordered response rates between doses. ^ Methods: Optimal and minimax two-stage designs are proposed for phase II clinical trials in settings where the true response rates at two dose levels are ordered. We borrow strength between doses using isotonic regression and control the joint and/or marginal error probabilities. Bayesian two-stage designs are also proposed under a stochastic ordering constraint. ^ Results: Compared to Simon's designs, when controlling the power and type I error at the same levels, the proposed frequentist and Bayesian designs reduce the maximum and expected sample sizes. Most of the proposed designs also increase the probability of early termination when the true response rates are poor. ^ Conclusion: Proposed frequentist and Bayesian designs are superior to Simon's designs in terms of operating characteristics (expected sample size and probability of early termination, when the response rates are poor) Thus, the proposed designs lead to more cost-efficient and ethical trials, and may consequently improve and expedite the drug discovery process. The proposed designs may be extended to designs of multiple group trials and drug combination trials.^

Complications of misoprostol and other abortion induction methods in the developing world: A systematic review

OBJECTIVE: To systematically review published literature to examine the complications associated with the use of misoprostol and compare these complications to those associated with other forms of abortion induction. ^ DATA SOURCES: Studies were identified through searches of medical literature databases including Medline (Ovid), PubMed (NLM), LILACS, sciELO, and AIM (AFRO), and review of references of relevant articles. ^ STUDY SELECTION AND METHODS: A descriptive systematic review that included studies reported in English and published before December 2012. Eligibility criteria included: misoprostol (with or without other methods) and any other method of abortion in a developing country, as well as quantitative data on the complication of each method. The following is information extracted from each study: author/year, country/city, study design/study sample, age range, setting of data collection, sample size, the method of abortion induction, the number of cases for each method, and the percentage of complications with each method. RESULTS: A total of 4 studies were identified (all in Latin America) describing post-abortion complications of misoprostol and other methods in countries where abortion is generally considered unsafe and/or illegal. The four studies reported on a range of complications including: bleeding, infection, incomplete abortion, intense pelvic pain, uterine perforation, headache, diarrhea, nausea, mechanical lesions, and systemic collapse. The most prevalent complications of misoprostol-induced abortion reported were: bleeding (7-82%), incomplete abortion (33-70%), and infection (0.8-67%). The prevalence of these complications reported from other abortion methods include: bleeding (16-25%), incomplete abortion (15-82%), and infection (13-50%). ^ CONCLUSION: The literature identified by this systematic review is inadequate for determining the complications of misoprostol used in unsafe settings. Abortion is considered an illicit behavior in these countries, therefore making it difficult to investigate the details needed to conduct a study on abortion complications. Given the differences between the reviewed studies as well as a variety of study limitations, it is not possible to draw firm conclusions about the rates of specific-abortion related complications.^