The monoamine neurotransmitter serotonin (5-HT) is an essential component of vertebrate cognitive function and the autonomous nervous system, regulating body temperature, sleep, appetite, and mood. Abnormal 5-HT signaling is implicated in a variety of disorders such as depression, anxiety, alcoholism, and obsessive-compulsive disorder. Synaptic serotonergic activity is primarily regulated by the recycling of 5-HT from the synaptic cleft by the presynaptic 5-HT transporter (SERT), a target for many psychostimulants and anti-depressants such as MDMA (Ecstasy) and Fluoxetine (Prozac). In the model system Caenorhabditis elegans (C. elegans), 5-HT is an active participant in a variety of motor, autonomic, and behavioral functions including egg-laying, pharyngeal pumping, locomotion, male mating, aging, and enhanced slowing. The goal of this work is to use the C. elegans model system to manipulate the SERT homolog (MOD-5) and examine regulatory genes controlling MOD-5 trafficking, localization, and activity. We characterized the behavioral phenotypes of endogenous 5-HT activity in C. elegans and in 5-HT transporter deletion mutants, especially those pertaining to locomotor function. We also describe a novel, food dependent immobilization phenotype and use genetic and pharmacological approaches to establish the role of 5-HT and MOD-5 within this phenotype. These techniques provide the necessary tools for use of this phenotype as the basis for a forward genetic screen which will provide unbiased assessments of transporter regulatory molecules. This work provides the foundation for elucidation of proteins that regulate determinants of serotonin transporter function and support normal serotonin transporter activity.

This dissertation is concerned with the development of a decision making framework which companies and organizations can use in establishing an effective carbon disclosure strategy. This is accomplished by first researching the current practice of carbon disclosure both in theory and in practice. Next, a benchmarking study was conducted analyzing the carbon disclosure efforts of a sample of 83 U.S.-based companies across nine industrial sectors. Finally, a decision making methodology framework for determining carbon information disclosure strategy is presented that was developed as part of this research and validated by peer-review process.

Medical decision making is a complex cognitive process involving multiple stakeholders and factors. The increased amount of information, pace at which information is obtained, source of that information, and the experience of the decision maker, both the physician and the patient can affect the medical decision making process. This research investigated two independent factors that may influence decision making: 1) the usage of a medical registry and 2) the influence of the educational background of the decision makers. This research found that registry users and non-users follow different decision making processes; and that registry users utilize the information attained from the registry in their decision making process. Decision makers of varying educational disciplines are influenced differently when presented with difficult medical decisions, and innumeracy skills are limited even in a highly educated population. Finally as medical registries are shown to impact medical decisions, and medical information is increasingly being requested by the general public, it is vital that an understanding of how the educational background of patients may impact their view of the information provided and what other influences may lead one to follow different decision rules.

This research investigates the organizational and collective impacts of participation in industry technology roadmap (ITR) development; further, characteristics of the roadmapping collective make-up and processes that contribute to these impacts are evaluated. A model is developed, relating roadmapping characteristics to organizational and ITR collective impacts of creating an industry roadmap. The model includes: 1) motivations for organizations to participate in the development of an ITR, 2) industry-related motivations for developing a roadmap, 3) stakeholder-based structure and processes used to create the roadmap, 4) characteristics of the roadmap document, 5) industry clockspeed (pace of change), and 6) organizational impacts from ITR development (e.g. technology planning, pace of innovation, collaborative activities and partnerships, implementation of new technologies, etc.). The model is evaluated using survey data obtained from organizational participants (N=128) in ITR development from six industries (concrete, electronics, forest products, magnesium, metal casting, and powder metallurgy). Findings suggest that motivation of an organization to participate in the roadmapping effort, organizational executive support for the effort, and the research and development (R&D) experiential level of an organizational representative in the ITR collective, impact the individual organization; while the aggregate motivation of participating organizations, aggregate R&D experience of the organizational participants, thoroughness and clarity of the roadmap document, and industry clockspeed, correlate with an increased impact on organizations as a collective.

A novel three dimensional stereoselective descriptor for use in ligand-based computer-aided drug design (CADD) is presented in this thesis. CADD is an important tool for drug discovery and ligand-based CADD involves the computational analysis and representation of known active compounds for the prediction of novel active compounds. Several approaches are available for ligand-based CADD including quantitative structure-activity relationship (QSAR) which seeks to describe molecules numerically using descriptors. Stereochemistry is an important determinant of a molecules biological activity but presents a challenge for QSAR applications. Presented is the novel 3D-QSAR descriptor termed EMAS (Enantio-selective Molecular ASymmetry) that is capable of distinguishing between enantiomers and describing stereochemistry in a physically meaningful way. The descriptor aims to measure the deviation from an overall symmetric shape of the molecule. EMAS showed good predictability when tested with a dataset of thirty-one steroids commonly used to benchmark stereochemistry descriptors (r2=0.89, q2= 0.78). Additionally, EMAS improved enrichment of 4.38 versus 3.94 without EMAS in a simulated virtual high-throughput screening (vHTS) for inhibitors and substrates of cytochrome P450.

Congenital heart disease (CHD) is the most common type of birth defect affecting eight out of every 1,000 newborns, causing more deaths in the first year of life than any other birth defect. A significant fraction of CHD is associated with abnormal valve structure and function. A detailed understanding of the early signaling events that regulate and guide cardiac valve formation is required to identify new therapeutic targets. Here, I focus on the role of Type III Transforming Growth Factor β Receptor (TGFβR3) in Endocardial epithelial to mesenchymal transformation (EMT), a critical step in valvular development. Using an in vitro assay of endocardial EMT I used small molecule inhibitors to establish that ALK2 and ALK3 are both required for endocardial EMT. Specifically, I demonstrated that ALK2 and ALK3 are downstream of TGFβR3. Finally, I used small molecule inhibitors of the NF-κB pathway to implicate this signaling system in endocardial EMT. These studies identify and clarify the role of specific pathways endocardial EMT which furthers our understanding of TGFβR3 signaling and early valve formation.

Studying population isolates with large, complex pedigrees has many advantages for discovering genetic susceptibility loci; however, statistical analyses can be computationally challenging. Allelic association tests need to be corrected for relatedness among study participants, and linkage analyses require subdividing and simplifying the pedigree structures. In this thesis work I simulated SNP (single nucleotide polymorphism) data in complex pedigree structures based on an Amish pedigree. I evaluated type 1 error rates and power when performing two-point and multipoint linkage after dividing the pedigree into subpedigrees. I also ran MQLS (modified likelihood score test) to test for allelic association in the subpedigrees and in the unified pedigree.

Type 2 diabetes (T2D) is a complex metabolic disease that disproportionately affects African Americans. Obesity is a major risk factor for T2D, and it is postulated that chronic inflammation possibly stemming from adipose tissue macrophages and T cells plays a key role. Genome-wide association studies (GWAS) have identified over 20 disease loci that contribute to T2D in European Americans but few studies have been performed in admixed populations. We first performed a GWAS of 1,563 African Americans from the Vanderbilt Genome-Electronic Records Project and Northwestern University NUgene Project as part of the electronic Medical Records and Genomics (eMERGE) network. We successfully replicate an association in TCF7L2, previously identified by GWAS in our African American dataset. We were unable to identify novel associations at p<5.0x10-8 by GWAS. Admixture mapping disease loci in recently admixed populations is a powerful method used to identify disease loci in African Americans. Using admixture mapping, we sought to identify novel disease loci in the genome with T2D. Our admixture scan revealed multiple candidate genes with T2D, including TCIRG1, a T-cell immune regulator expressed in the pancreas and liver and not previously implicated in T2D. We performed a subsequent fine-mapping analysis to further assess the association with TCIRG1 and T2D in >5,000 African Americans. We successfully identified 13 independent associations in TCIRG1, CHKA, and ALDH3B1 genes on chromosome 11. Our results suggest a novel region on chromosome 11 identified by admixture mapping associated with T2D in African Americans and warrants additional replication and validation in this region.

Angelman Syndrome (AS) is a devastating neurodevelopmental disorder characterized by developmental delay, speech impairment, movement disorder, sleep disorders and refractory epilepsy. AS is caused by loss of the Ube3a protein encoded for by the imprinted Ube3a gene. Ube3a is expressed nearly exclusively from the maternal chromosome in mature neurons. Mouse models have helped determine the molecular defects in AS, however findings have been inconsistent across laboratories. Work in our laboratory suggested that environmental factors may play a role in the phenotypes observed in AS model mice. As a result, we evaluated the possibility of non-genomic causes of variation in phenotypes observed in AS model mice. Here we demonstrate that maternal status and diet play a large role in the magnitude of a hypomyelination phenotype observed in these mice.

The Department of Energy (DOE) is responsible for the cleanup of nuclear waste at former nuclear weapons sites across the United States. Cleanup activities of particular interest include the containment of waste in near surface disposal facilities. There is a need to build confidence in the predictive nature of long-term cover performance models, particularly when considering long-term impacts from climate change. This research aimed to develop an approach to assessing long-term performance of near surface disposal facilities under climate change impacts. This was accomplished by: (1) defining a methodology using historical precipitation and temperature data; (2) using a Monte Carlo approach to assess performance based on past events; (3) performing a proof of concept application; and (4) developing and assessing future climate change scenarios relative to percolation thresholds. From this research, it was determined that the HELP model is a useful tool to assess the hydrological performance of near surface disposal facilities in humid climates when degradation of designs is considered by modifying various hydraulic inputs. In addition, changes in both precipitation and temperature have been found to influence landfill cover performance; in many cases, the potential negative effects of additional precipitation on landfill cover performance can be offset by warmer temperatures. These developments and findings can have meaningful implications on future regulatory policies and guidelines when considering naturally occurring climatic change and anthropogenic forcing.