Physical and functional interaction between the dopamine transporter and the synaptic vesicle protein synaptogyrin-3.

Uptake through the dopamine transporter (DAT) represents the primary mechanism used to terminate dopaminergic transmission in brain. Although it is well known that dopamine (DA) taken up by the transporter is used to replenish synaptic vesicle stores for subsequent release, the molecular details of this mechanism are not completely understood. Here, we identified the synaptic vesicle protein synaptogyrin-3 as a DAT interacting protein using the split ubiquitin system. This interaction was confirmed through coimmunoprecipitation experiments using heterologous cell lines and mouse brain. DAT and synaptogyrin-3 colocalized at presynaptic terminals from mouse striatum. Using fluorescence resonance energy transfer microscopy, we show that both proteins interact in live neurons. Pull-down assays with GST (glutathione S-transferase) proteins revealed that the cytoplasmic N termini of both DAT and synaptogyrin-3 are sufficient for this interaction. Furthermore, the N terminus of DAT is capable of binding purified synaptic vesicles from brain tissue. Functional assays revealed that synaptogyrin-3 expression correlated with DAT activity in PC12 and MN9D cells, but not in the non-neuronal HEK-293 cells. These changes were not attributed to changes in transporter cell surface levels or to direct effect of the protein-protein interaction. Instead, the synaptogyrin-3 effect on DAT activity was abolished in the presence of the vesicular monoamine transporter-2 (VMAT2) inhibitor reserpine, suggesting a dependence on the vesicular DA storage system. Finally, we provide evidence for a biochemical complex involving DAT, synaptogyrin-3, and VMAT2. Collectively, our data identify a novel interaction between DAT and synaptogyrin-3 and suggest a physical and functional link between DAT and the vesicular DA system.

A case-control study of hepatitis C virus and its interaction with hepatitis B virus on the development of hepatocellular carcinoma in the USA

Objective. The aim of this study was to assess the independent risk of hepatitis C virus (HCV) infection in the development of hepatocellular carcinoma (HCC). The independent risk of hepatitis B virus (HBV), its interaction with hepatitis C virus and the association with other risk factors were examined.^ Methods. A hospital-based case-control study was conducted between January 1994 and December 1995. We enrolled 115 pathologically confirmed HCC patients and 230 nonliver cancer controls, who were matched by age ($\pm$5 years), gender, and year of diagnosis. Both cases and controls were recruited from The University of Texas M. D. Anderson Cancer Center at Houston. The risk factors were collected through personal interviews and blood samples were tested for HCV and HBV markers. Univariate and multivariate analyses were performed through conditional logistic regression.^ The prevalence of anti-HCV positive is 25.2% in HCC cases compared to 3.0% in controls. The univariate analysis showed that anti-HCV, HBsAg, alcohol drinking and cigarette smoking were significantly associated with HCC, however, family history of cancer, occupational chemical exposure, and use of oral contraceptive were not. Multivariate analysis revealed a matched odds ratio (OR) of 10.1 (95% CI 3.7-27.4) for anti-HCV, and an OR of 11.9 (95% CI 2.5-57.5) for HBsAg. However, dual infection of HCV and HBV had only a thirteen times increase in the risk of HCC, OR = 13.9 (95% CI 1.3-150.6). The estimated population attributable risk percent was 23.4% for HCV, 12.6% for HBV, and 5.3% for both viruses. Ever alcohol drinkers was positively associated with HCC, especially among daily drinkers, matched OR was 5.7 (95% CI 2.1-15.6). However, there was no significant increase in the risk of HCC among smokers as compared to nonsmokers. The mean age of HCC patients was significantly younger among the HBV(+) group and among the HCV(+)/HBV(+) group, when compared to the group of HCC patients with no viral markers. The association between past histories of blood transfusion, acupuncture, tattoo and IVDU was highly significant among the HCV(+) group and the HBV(+)/HCV(+) group, as compared to HCC patients with no viral markers. Forty percent of the HCC patients were pathologically or clinically diagnosed with liver cirrhosis. Anti-HCV(+) (OR = 3.6 95% CI 1.5-8.9) and alcohol drinking (OR = 2.7 95% CI 1.1-6.7), but not HBsAg, are the major risk factors for liver cirrhosis in HCC patients.^ Conclusion. Both hepatitis B virus and hepatitis C virus were independent risk factors for HCC. There was not enough evidence to determine the interaction between both viruses. Only daily alcoholic drinkers showed increasing risk for HCC development, as compared to nondrinkers. ^

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Dissecting the Interaction between p53 and TRIM24

Dissecting the Interaction of p53 and TRIM24 Aundrietta DeVan Duncan Supervisory Professor, Michelle Barton, Ph.D. p53, the “guardian of the genome”, plays an important role in multiple biological processes including cell cycle, angiogenesis, DNA repair and apoptosis. Because it is mutated in over 50% of cancers, p53 has been widely studied in established cancer cell lines. However, little is known about the function of p53 in a normal cell. We focused on characterizing p53 in normal cells and during differentiation. Our lab recently identified a novel binding partner of p53, Tripartite Motif 24 protein (TRIM24). TRIM24 is a member of the TRIM family of proteins, defined by their conserved RING, B-box, and coiled coil domains. Specifically, TRIM24 is a member of the TIF1 subfamily, which is characterized by PHD and Bromo domains in the C-terminus. Between the Coiled-coil and PHD domain is a linker region, 437 amino acids in length. This linker region houses important functions of TRIM24 including it’s site of interaction with nuclear receptors. TRIM24 is an E3-ubiquitin ligase, recently discovered to negatively regulate p53 by targeting it for degradation. Though it is known that Trim24 and p53 interact, it is not known if the interaction is direct and what effect this interaction has on the function of TRIM24 and p53. My study aims to elucidate the specific interaction domains of p53 and TRIM24. To determine the specific domains of p53 required for interaction with TRIM24, we performed co-immuoprecipitation (Co-IP) with recombinant full-length Flag-tagged TRIM24 protein and various deletion constructs of in vitro translated GST-p53, as well as the reverse. I found that TRIM24 binds both the carboxy terminus and DNA binding domain of p53. Furthermore, my results show that binding is altered when post-translational modifications of p53 are present, suggesting that the interaction between p53 and TRIM24 may be affected by these post-translational modifications. To determine the specific domains of TRIM24 required for p53 interaction, we performed GST pull-downs with in vitro translated, Flag-TRIM24 protein constructs and recombinant GST-p53 protein purified from E. coli. We found that the Linker region is sufficient for interaction of p53 and TRIM24. Taken together, these data indicate that the interaction between p53 and TRIM24 does occur in vitro and that interaction may be influenced by post-translational modifications of the proteins.

Design, Calibration, and Evaluation of Depth-of-Interaction-Capable PET Detector Modules

High-resolution, small-bore PET systems suffer from a tradeoff between system sensitivity, and image quality degradation. In these systems long crystals allow mispositioning of the line of response due to parallax error and this mispositioning causes resolution blurring, but long crystals are necessary for high system sensitivity. One means to allow long crystals without introducing parallax errors is to determine the depth of interaction (DOI) of the gamma ray interaction within the detector module. While DOI has been investigated previously, newly available solid state photomultipliers (SSPMs) well-suited to PET applications and allow new modules for investigation. Depth of interaction in full modules is a relatively new field, and so even if high performance DOI capable modules were available, the appropriate means to characterize and calibrate the modules are not. This work presents an investigation of DOI capable arrays and techniques for characterizing and calibrating those modules. The methods introduced here accurately and reliably characterize and calibrate energy, timing, and event interaction positioning. Additionally presented is a characterization of the spatial resolution of DOI capable modules and a measurement of DOI effects for different angles between detector modules. These arrays have been built into a prototype PET system that delivers better than 2.0 mm resolution with a single-sided-stopping-power in excess of 95% for 511 keV g's. The noise properties of SSPMs scale with the active area of the detector face, and so the best signal-to-noise ratio is possible with parallel readout of each SSPM photodetector pixel rather than multiplexing signals together. This work additionally investigates several algorithms for improving timing performance using timing information from multiple SSPM pixels when light is distributed among several photodetectors.

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

Single-stranded DNA-binding proteins regulate the abundance of LIM domain and LIM domain-binding proteins.

The LIM domain-binding protein Ldb1 is an essential cofactor of LIM-homeodomain (LIM-HD) and LIM-only (LMO) proteins in development. The stoichiometry of Ldb1, LIM-HD, and LMO proteins is tightly controlled in the cell and is likely a critical determinant of their biological actions. Single-stranded DNA-binding proteins (SSBPs) were recently shown to interact with Ldb1 and are also important in developmental programs. We establish here that two mammalian SSBPs, SSBP2 and SSBP3, contribute to an erythroid DNA-binding complex that contains the transcription factors Tal1 and GATA-1, the LIM domain protein Lmo2, and Ldb1 and binds a bipartite E-box-GATA DNA sequence motif. In addition, SSBP2 was found to augment transcription of the Protein 4.2 (P4.2) gene, a direct target of the E-box-GATA-binding complex, in an Ldb1-dependent manner and to increase endogenous Ldb1 and Lmo2 protein levels, E-box-GATA DNA-binding activity, and P4.2 and beta-globin expression in erythroid progenitors. Finally, SSBP2 was demonstrated to inhibit Ldb1 and Lmo2 interaction with the E3 ubiquitin ligase RLIM, prevent RLIM-mediated Ldb1 ubiquitination, and protect Ldb1 and Lmo2 from proteasomal degradation. These results define a novel biochemical function for SSBPs in regulating the abundance of LIM domain and LIM domain-binding proteins.

Phototaxis signaling by the membrane complex of archaeal sensory rhodopsins and their transducers

Sensory rhodopsins I and II (SRI and SRII) are visual pigment-like phototaxis receptors in the archaeon Halobacterium salinarum. The receptor proteins each consist of a single polypeptide that folds into 7 $\alpha$-helical membrane-spanning segments forming an internal pocket where the chromophore retinal is bound. They transmit signals to their tightly bound transducer proteins, HtrI and HtrII, respectively, which in turn control a phosphotransfer pathway modulating the flagellar motors. SRI-HtrI mediates attractant responses to orange-light and repellent responses to UV light, while SRII-HtrII mediates repellent response to blue light. Experiments were designed to analyze the molecular processes in the SR-Htr complexes responsible for receptor activation, which previously had been shown by our laboratory to involve proton transfer reactions of the retinylidene Schiff base in the photoactive site, transfer of signals from receptor to transducer, and signaling specificity by the receptor-transducer complex.^ Site-directed mutagenesis and laser-flash kinetic spectroscopy revealed that His-166 in SRI (i) plays a role in the proton transfers both to and from the Schiffbase, either as a structurally critical residue or possibly as a direct participant, (ii) is involved in the modulation of SIU photoreaction kinetics by HtrI, and (iii) modulates the pKa of Asp-76, an important residue in the photoactive site, through a long-distance electrostatic interaction. Computerized cell tracking and motion analysis demonstrated that (iv) His-166 is crucial in phototaxis signaling: a spectrum of substitutions either eliminate signaling or greatly perturb the activation process that produces attractant and repellent signaling states of the receptor.^ The signaling states of SRI are communicated to HtrI, whose oligomeric structure and conformational changes were investigated by engineered sulfhydryl probes. It was found that signaling by the SRI-HtrI complex involves reversible conformational changes within a preexisting HtrI dimer, which is likely accomplished through a slight winding or unwinding of the two HtrT monomers via their loose coiled coil association. To elucidate which domains of the Htr dimers confer specificity for interaction with SRI or SRII, chimeras of HtrI and HtrII were constructed. The only determinant needed for functional and specific interaction with SRI or SRII was found to be the four transmembrane segments of the HtrI or HtrII dimers, respectively. The entire cytoplasmic parts of HtrI and HtrII, which include the functionally important signaling and adaptation domains, were interchangeable.^ These observations support a model in which SRI and SRII undergo conformational changes coupled to light-induced proton transfers in their photoactive sites, and that lateral helix-helix interactions with their cognate transducers' 4-helix bundle in the membrane relay these conformational changes into different states of the Htr proteins which regulate the down-stream phosphotransfer pathway. ^

Transcription factor SEF: Purification and functional characterization

Cytokine-induced transcription of the serum amyloid A3 (SAA3) gene promoter requires a transcriptional enhancer that contains three functional elements: two C/EBP-binding sites and a third site that interacts with a constitutively expressed transcription factor, SAA3 enhancer factor (SEF). Deletion or site-specific mutations in the SEF-binding site drastically reduced SAA3 promoter activity, strongly suggesting that SEF is important in SAA3 promoter function. To further elucidate its role in the regulation of the SAA3 gene, we purified SEF from HeLa cell nuclear extracts to near homogeneity by using conventional liquid chromatography and DNA-affinity chromatography. Ultraviolet cross-linking and Southwestern experiments indicated that SEF consisted of a single polypeptide with an apparent molecular mass of 65 kDa. Protein sequencing, oligonucleotide competition and antibody supershift experiments identified SEF as transcription factor LBP-1c/CP2/LSF. Cotransfection of SEF expression plasmid with SAA3-luciferase reporter resulted in 3- to 5-fold activation of SAA3 promoter. Interestingly, when SEF-transfected cells were treated with either conditioned medium (CM) or interleukin (IL) 1, the SAA3 promoter was synergistically activated in a dose-dependent manner. Furthermore, when SEF-binding site was mutated, the response of SAA3 promoter to IL-1 or CM stimulation was abolished or drastically decreased, suggesting that SEF may functionally cooperate with an IL-1-inducible transcription factor. Indeed, our functional studies showed that NFκB is a key transcription factor that mediates the IL-1-induced expression of SAA3 gene, and that SEF can synergize with NFκBp65 to activate SAA3 promoter. By coimmunoprecipitation experiments, we found that SEF could specifically interact with NFκBp65, and that the association of these two factors was enhanced upon IL-1 and CM stimulation. This suggests that the molecular basis for the functional synergy between SEF and NFκB may be due to the ability of SEF to physically interact with NPκB. In addition to its interaction with SEF, NFκB-dependent activation also requires the weak κB site in the C element and its interaction with C/EBP. Besides its role in regulating SAA3 gene expression, we provide evidence that SEF could also bind in a sequence-specific manner to the promoters of α2-macroglobulin, Aα fibrinogen, and 6–16 genes and to an intronic enhancer of the human Wilm's tumor 1 gene, suggesting a functional role in the regulation of these genes. By coimmunoprecipitation experiments, we determined that SEF could specifically associate with both Stat3 and Stat2 upon cytokine stimulation. To examine the functional roles of such interactions, we evaluated the effects of SEF on the transcriptional regulation of two reporter genes: Aα fibrinogen and 6–16, which are IL-6- and interferon-α-responsive, respectively. Our results showed that cotransfection of SEF expression plasmid can activate the expression of Aα fibrinogen gene and 6–16 gene. Moreover, SEF can dramatically enhance the interferon-α-induced expression of 6–16 gene and IL-6-induced expression of Aα fibrinogen gene, suggesting that SEF may functionally cooperate with ISGF3 and Stat3 to mediate interferon-α and IL-6 signaling. ^ Our findings that SEF can interact with multiple cytokine-inducible transcription factors to mediate the expression of target genes open a new avenue of investigation of cooperative transcriptional regulation of gene expression, and should further our understanding of differential gene expression in response to a specific stimulus. In summary, our data provide evidence that SEF can mediate the signaling of different cytokines by interacting with various cytokine-inducible transcription factors. ^

Changes in blood lipids and their associations with changes in measures of height, weight and body mass index from age 8 to 18 years: Project Heartbeat!

A variety of studies indicate that the process of athrosclerosis begins in childhood. There was limited information on the association of the changes in anthropometric variables to blood lipids in school age children and adolescents. Previous longitudinal studies of children typically with insufficient frequency of observation could not provide sound inference on the dynamics of change in blood lipids. The aims of this analysis are (1) to document the sex- and ethnic-specific trajectory and velocity curves of blood lipids (TC, LDL-C, HDL-C and TG); (2) to evaluate the relationship of changes in anthropometric variables, such as height, weight and BMI, to blood lipids from age 8 to 18 years. ^ Project HeartBeat! is a longitudinal study designed to examine the patterns of serial change in major cardiovascular risk factors. Cohort of three different age levels, 8, 11 and 14 years at baseline, with a total of 678 participants were enrolled. Each member of these cohorts was examined three times per year for up to four years. ^ Sex- and ethnic-specific trajectory and velocity curves of blood lipids; demonstrated the complex and polyphasic changes in TC, LDL-C, HDL-C and TG longitudinally. The trajectory curves of TC, LDL-C and HDL-C with age showed curvilinear patterns of change. The velocity change in TC, HDL-C and LDL-C showed U-shaped curves for non-Blacks, and nearly linear lines in velocity of TG for both Blacks and non-Blacks. ^ The relationship of changes in anthropometric variables to blood lipids was evaulated by adding height, weight, or BMI and associated interaction terms separately to the basic age-sex models. Height or height gain had a significant negative association with changes in TC, LDL-C and HDL-C. Weight or BMI gain showed positive associations with TC, LDL-C and TC, and a negative relationship with HDL-C. ^ Dynamic changes of blood lipids in school age children and adolescents observed from this analysis suggested that using fixed screening criteria under the current NCEP guidelines for all ages 2–19 may not be appropriate for this age group. The association of increasing BMI or weight to an adverse blood lipid profile found in this analysis also indicated that weight or BMI monitoring could be a future intervention to be implemented in the pediatric population. ^

TH and XFKBP12 interact and regulate proliferation and differentiation in neural ectoderm through the TOR signaling pathway

During development, embryos must carefully integrate the processes of cell proliferation and differentiation. TH has been identified in Xenopus laevis as a gene product that functions in regulating differentiation of the neural ectoderm through its effect on cell proliferation. However, the mechanism and molecular pathway through which TH functions are not known. We identified the Xenopus FK506 binding protein homolog (XFKBP12) as a protein that interacted with TH in a yeast two-hybrid screen with TH as the bait. The direct and specific interaction between TH and XFKBP12 was supported by several tests including CO-IP, drug competence assay and mutagenesis analysis. To investigate the function of XFKBP12 during embryogenesis, we created an XFKBP12 loss of function embryo using antisense morpholino oligonucleotides (MO). XFKBP12 MO injected embryos displayed similar phenotypes as TH depleted embryos. We also demonstrated that both TH and XFKBP12 functioned through the TOR signaling pathway which is a target for cancer therapies. The interaction between TH and XFKBP 12 was required to regulate the proliferation of neural cells. Therefore, our study indicates that TH represents the endogenous ligand of XFKBP12 and together they coordinate neural cell proliferation and differentiation through the conserved rapamycin sensitive TOR pathway. Thus, understanding how this pathway functions in development will not only provide us important insights into the relationship between proliferation and differentiation, but help design rational cancer therapies targeting this pathway. ^

Molecular and genetic analyses of Fgf signaling during cardiac outflow tract development

Epithelial-mesenchymal tissue interactions regulate the development of derivatives of the caudal pharyngeal arches (PAs) to govern the ultimate morphogenesis of the aortic arch and outflow tract (OFT) of the heart. Disruption of these signaling pathways is thought to contribute to the pathology of a significant proportion of congenital cardiovascular defects in humans. In this study, I tested whether Fibroblast Growth Factor 15 (Fgf15), a secreted signaling molecule expressed within the PAs, is an extracellular mediator of tissue interactions during PA and OFT development. Analyses of Fgf15−/− mouse embryonic hearts revealed abnormalities primarily localized to the OFT, correlating with aberrant cardiac neural crest cell behavior. The T-box-containing transcription factor Tbx1 has been implicated in the cardiovascular defects associated with the human 22q11 Deletion Syndromes, and regulates the expression of other Fgf family members within the mouse PAs. However, expression and genetic interaction studies incorporating mice deficient for Tbx1, its upstream regulator, Sonic Hedgehog (Shh), or its putative downstream effector, Fgf8, indicated that Fgf15 functions during OFT development in a manner independent of these factors. Rather, analyses of compound mutant mice indicated that Fgf15 and Fgf9, an additional Fgf family member expressed within the PAs, genetically interact, providing insight into the factors acting in conjunction with Fgf15 during OFT development. Finally, in an effort to further characterize this Fgf15-mediated developmental pathway, promoter deletion analyses were employed to isolate a 415bp sequence 7.1Kb 5′ to the Fgf15 transcription start site both necessary and sufficient to drive reporter gene expression within the epithelium of the PAs. Sequence comparisons among multiple mammalian species facilitated the identification of evolutionarily conserved potential trans-acting factor binding sites within this fragment. Subsequent studies will investigate the molecular pathway(s) through which Fgf15 functions via identification of factors that bind to this element to govern Fgf15 gene expression. Furthermore, targeted deletion of this element will establish the developmental requirement for pharyngeal epithelium-derived Fgf15 signaling function. Taken as a whole, these data demonstrate that Fgf15 is a component of a novel, Tbx1-independent molecular pathway, functioning within the PAs in a manner cooperative with Fgf9, required for proper development of the cardiac OFT. ^

Molecular mechanisms by which p53/LSD1 and ERalpha/Trim24 complexes mediate gene regulation

In this dissertation, I identify two molecular mechanisms by which transcription factors cooperate with their co-regulators to mediate gene regulation. In the first part, I demonstrate that p53 directly recruits LSD1, a histone demethylase, to AFP chromatin to demethylate methylated H3K4 and actively mediate transcription repression. Loss of p53 and LSD1 interaction at chromatin leads to derepression of AFP in hepatic cells. In the second part, I reveal that Trim24 functions as an important co-activator in ERα-mediated gene activation in response to estrogen stimulation. Trim24 is recruited by ligand-bound ERα to chromatin and stabilizes ERα-chromatin interactions by binding to histone H3 via its PHD finger, which preferentially recognizes unmethylated H3K4. ^

A study to determine the association between medical decision-making and the performance of an institutional ethics committee

This study developed proxy measures to test the independent effects of medical specialty, institutional ethics committee (IEC) and the interaction between the two, upon a proxy for the dependent variable of the medical decision to withhold/withdraw care for the dying--the resuscitation index (R-index). Five clinical vignettes were constructed and validated to convey the realism and contextual factors implicit in the decision to withhold/withdraw care. A scale was developed to determine the range of contact by an IEC in terms of physician knowledge and use of IEC policy.^ This study was composed of a sample of 215 physicians in a teaching hospital in the Southwest where proxy measures were tested for two competing influences, medical specialty and IEC, which alternately oppose and support the decision to withhold/withdraw care for the dying. A sub-sample of surgeons supported the hypothesis that an IEC is influential in opposing the medical training imperative to prolong life.^ Those surgeons with a low IEC score were 326 percent more likely to continue care than were surgeons with a high IEC score when compared to all other specialties. IEC alone was also found to significantly predict the decision to withhold/withdraw care. Interaction of IEC with the specialty of surgery was found to be the best predictor for a decision to withhold/withdraw care for the dying. ^

Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^