Radiation dose reduction in postoperative computed position control of cochlear implant electrodes in lambs - An experimental study

OBJECTIVE Cochlear implants (CI) are standard treatment for prelingually deafened children and postlingually deafened adults. Computed tomography (CT) is the standard method for postoperative imaging of the electrode position. CT scans accurately reflect electrode depth and position, which is essential prior to use. However, routine CT examinations expose patients to radiation, which is especially problematic in children. We examined whether new CT protocols could reduce radiation doses while preserving diagnostic accuracy. METHODS To investigate whether electrode position can be assessed by low-dose CT protocols, a cadaveric lamb model was used because the inner ear morphology is similar to humans. The scans were performed at various volumetric CT dose-indexes CTDIvol)/kV combinations. For each constant CTDIvol the tube voltage was varied (i.e., 80, 100, 120 and 140kV). This procedure was repeated at different CTDIvol values (21mGy, 11mGy, 5.5mGy, 2.8mGy and 1.8mGy). To keep the CTDIvol constant at different tube voltages, the tube current values were adjusted. Independent evaluations of the images were performed by two experienced and blinded neuroradiologists. The criteria diagnostic usefulness, image quality and artifacts (scaled 1-4) were assessed in 14 cochlear-implanted cadaveric lamb heads with variable tube voltages. RESULTS Results showed that the standard CT dose could be substantially reduced without sacrificing diagnostic accuracy of electrode position. The assessment of the CI electrode position was feasible in almost all cases up to a CTDIvol of 2-3mGy. The number of artifacts did not increase for images within this dose range as compared to higher dosages. The extent of the artifacts caused by the implanted metal-containing CI electrode does not depend on the radiation dose and is not perceptibly influenced by changes in the tube voltage. Summarizing the evaluation of the CI electrode position is possible even at a very low radiation dose. CONCLUSIONS CT imaging of the temporal bone for postoperative electrode position control of the CI is possible with a very low and significantly radiation dose. The tube current-time product and voltage can be reduced by 50% without increasing artifacts. Low-dose postoperative CT scans are sufficient for localizing the CI electrode.

Hypercoagulation and hyperkinetic blood pressure indicative of physiological loss-of-control despite behavioural control in Africans: The SABPA study.

OBJECTIVES A dissociation between behavioural (in-control) and physiological parameters (indicating loss-of-control) is associated with cardiovascular risk in defensive coping (DefS) Africans. We evaluated relationships between DefS, sub-clinical atherosclerosis, low-grade inflammation and hypercoagulation in a bi-ethnic sex cohort. METHODS Black (Africans) and white Africans (Caucasians) (n = 375; aged 44.6 ± 9.7 years) were included. Ambulatory BP, vascular structure (left carotid cross-sectional wall area (L-CSWA) and plaque counts), and markers of coagulation and inflammation were quantified. Ethnicity/coping style interaction was revealed only in DefS participants. RESULTS A hypertensive state, less plaque, low-grade inflammation, and hypercoagulation were more prevalent in DefS Africans (27-84%) than DefS Caucasians (18-41%). Regression analyses demonstrated associations between L-CSWA and 24 hour systolic BP (R(2) = 0.38; β = 0.78; p < 0.05) in DefS African men but not in DefS African women or Caucasians. No associations between L-CSWA and coagulation markers were evident. CONCLUSION Novel findings revealed hypercoagulation, low-grade inflammation and hyperkinetic BP (physiological loss-of-control responses) in DefS African men. Coupled to a self-reported in-control DefS behavioural profile, this reflects dissociation between behaviour and physiology. It may explain changes in vascular structure, increasing cerebrovascular disease risk in a state of hyper-vigilant coping.

Bacillus anthracis Diversity and Geographic Potential across Nigeria, Cameroon and Chad: Further Support of a Novel West African Lineage.

Zoonoses, diseases affecting both humans and animals, can exert tremendous pressures on human and veterinary health systems, particularly in resource limited countries. Anthrax is one such zoonosis of concern and is a disease requiring greater public health attention in Nigeria. Here we describe the genetic diversity of Bacillus anthracis in Nigeria and compare it to Chad, Cameroon and a broader global dataset based on the multiple locus variable number tandem repeat (MLVA-25) genetic typing system. Nigerian B. anthracis isolates had identical MLVA genotypes and could only be resolved by measuring highly mutable single nucleotide repeats (SNRs). The Nigerian MLVA genotype was identical or highly genetically similar to those in the neighboring countries, confirming the strains belong to this unique West African lineage. Interestingly, sequence data from a Nigerian isolate shares the anthrose deficient genotypes previously described for strains in this region, which may be associated with vaccine evasion. Strains in this study were isolated over six decades, indicating a high level of temporal strain stability regionally. Ecological niche models were used to predict the geographic distribution of the pathogen for all three countries. We describe a west-east habitat corridor through northern Nigeria extending into Chad and Cameroon. Ecological niche models and genetic results show B. anthracis to be ecologically established in Nigeria. These findings expand our understanding of the global B. anthracis population structure and can guide regional anthrax surveillance and control planning.

The impact of the position effect on the factorial structure of the Culture Fair Test (CFT)

The Culture Fair Test (CFT) is a psychometric test of fluid intelligence consisting of four subtests; Series, Classification, Matrices, and Topographies. The four subtests are only moderately intercorrelated, doubting the notion that they assess the same construct (i.e., fluid intelligence). As an explanation of these low correlations, we investigated the position effect. This effect is assumed to reflect implicit learning during testing. By applying fixed-links modeling to analyze the CFT data of 206 participants, we identified position effects as latent variables in the subtests; Classification, Matrices, and Topographies. These position effects were disentangled from a second set of latent variables representing fluid intelligence inherent in the four subtests. After this separation of position effect and basic fluid intelligence, the latent variables representing basic fluid intelligence in the subtests Series, Matrices, and Topographies could be combined to one common latent variable which was highly correlated with fluid intelligence derived from the subtest Classification (r=.72). Correlations between the three latent variables representing the position effects in the Classification, Matrices, and Topographies subtests ranged from r=.38 to r=.59. The results indicate that all four CFT subtests measure the same construct (i.e., fluid intelligence) but that the position effect confounds the factorial structure

Situational adaptiveness of control orientation mediates relation between fixed-world view and youth well-being in three cultures

When proposing primary control (changing the world to fit self)/secondary control (changing self to fit the world) theory, Weisz et al. (1984) argued for the importance of the “serenity to accept the things I cannot change, the courage to change the things I can” (p. 967), and the wisdom to choose the right control strategy that fits the context. Although the dual processes of control theory generated hundreds of empirical studies, most of them focused on the dichotomy of PC and SC, with none of these tapped into the critical concept: individuals’ ability to know when to use what. This project addressed this issue by using scenario questions to study the impact of situationally adaptive control strategies on youth well-being. To understand the antecedents of youths’ preference for PC or SC, we also connected PCSC theory with Dweck’s implicit theory about the changeability of the world. We hypothesized that youths’ belief about the world’s changeability impacts how difficult it was for them to choose situationally adaptive control orientation, which then impacts their well-being. This study included adolescents and emerging adults between the ages of 18 and 28 years (Mean = 20.87 years) from the US (n = 98), China (n = 100), and Switzerland (n = 103). Participants answered a questionnaire including a measure of implicit theories about the fixedness of the external world, a scenario-based measure of control orientation, and several measures of well-being. Preliminary analyses of the scenario-based control orientation measures showed striking cross-cultural similarity of preferred control responses: while for three of the six scenarios primary control was the predominately chosen control response in all cultures, for the other three scenarios secondary control was the predominately chosen response. This suggested that youths across cultures are aware that some situations call for primary control, while others demand secondary control. We considered the control strategy winning the majority of the votes to be the strategy that is situationally adaptive. The results of a multi-group structural equation mediation model with the extent of belief in a fixed world as independent variable, the difficulties of carrying out the respective adaptive versus non-adaptive control responses as two mediating variables and the latent well-being variable as dependent variable showed a cross-culturally similar pattern of effects: a belief in a fixed world was significantly related to higher difficulties in carrying out the normative as well as the non-normative control response, but only the difficulty of carrying out the normative control response (be it primary control in situations where primary control is normative or secondary control in situations where secondary control is normative) was significantly related to a lower reported well-being (while the difficulty of carrying out the non-normative response was unrelated to well-being). While previous research focused on cross-cultural differences on the choice of PC or SC, this study shed light on the universal necessity of applying the right kind of control to fit the situation.

Evidence for Emergency Vaccination Having Played a Crucial Role to Control the 1965/66 Foot-and-Mouth Disease Outbreak in Switzerland.

Foot-and-mouth disease (FMD) is a highly contagious disease that caused several large outbreaks in Europe in the last century. The last important outbreak in Switzerland took place in 1965/66 and affected more than 900 premises and more than 50,000 animals were slaughtered. Large-scale emergency vaccination of the cattle and pig population has been applied to control the epidemic. In recent years, many studies have used infectious disease models to assess the impact of different disease control measures, including models developed for diseases exotic for the specific region of interest. Often, the absence of real outbreak data makes a validation of such models impossible. This study aimed to evaluate whether a spatial, stochastic simulation model (the Davis Animal Disease Simulation model) can predict the course of a Swiss FMD epidemic based on the available historic input data on population structure, contact rates, epidemiology of the virus, and quality of the vaccine. In addition, the potential outcome of the 1965/66 FMD epidemic without application of vaccination was investigated. Comparing the model outcomes to reality, only the largest 10% of the simulated outbreaks approximated the number of animals being culled. However, the simulation model highly overestimated the number of culled premises. While the outbreak duration could not be well reproduced by the model compared to the 1965/66 epidemic, it was able to accurately estimate the size of the area infected. Without application of vaccination, the model predicted a much higher mean number of culled animals than with vaccination, demonstrating that vaccination was likely crucial in disease control for the Swiss FMD outbreak in 1965/66. The study demonstrated the feasibility to analyze historical outbreak data with modern analytical tools. However, it also confirmed that predicted epidemics from a most carefully parameterized model cannot integrate all eventualities of a real epidemic. Therefore, decision makers need to be aware that infectious disease models are useful tools to support the decision-making process but their results are not equal valuable as real observations and should always be interpreted with caution.

Environmental control on the occurrence of high-coercivity magnetic minerals and formation of iron sulfides in a 640 ka sediment sequence from Lake Ohrid (Balkans)

The bulk magnetic mineral record from Lake Ohrid, spanning the past 637 kyr, reflects large-scale shifts in hydrological conditions, and, superimposed, a strong signal of environmental conditions on glacial–interglacial and millennial timescales. A shift in the formation of early diagenetic ferrimagnetic iron sulfides to siderites is observed around 320 ka. This change is probably associated with variable availability of sulfide in the pore water. We propose that sulfate concentrations were significantly higher before  ∼  320 ka, due to either a higher sulfate flux or lower dilution of lake sulfate due to a smaller water volume. Diagenetic iron minerals appear more abundant during glacials, which are generally characterized by higher Fe / Ca ratios in the sediments. While in the lower part of the core the ferrimagnetic sulfide signal overprints the primary detrital magnetic signal, the upper part of the core is dominated by variable proportions of high- to low-coercivity iron oxides. Glacial sediments are characterized by high concentration of high-coercivity magnetic minerals (hematite, goethite), which relate to enhanced erosion of soils that had formed during preceding interglacials. Superimposed on the glacial–interglacial behavior are millennial-scale oscillations in the magnetic mineral composition that parallel variations in summer insolation. Like the processes on glacial–interglacial timescales, low summer insolation and a retreat in vegetation resulted in enhanced erosion of soil material. Our study highlights that rock-magnetic studies, in concert with geochemical and sedimentological investigations, provide a multi-level contribution to environmental reconstructions, since the magnetic properties can mirror both environmental conditions on land and intra-lake processes.

Knowledge-Based Task Structure Planning for an Information Gathering Agent

An effective solution to model and apply planning domain knowledge for deliberation and action in probabilistic, agent-oriented control is presented. Specifically, the addition of a task structure planning component and supporting components to an agent-oriented architecture and agent implementation is described. For agent control in risky or uncertain environments, an approach and method of goal reduction to task plan sets and schedules of action is presented. Additionally, some issues related to component-wise, situation-dependent control of a task planning agent that schedules its tasks separately from planning them are motivated and discussed.

Multiple imputation for missing continuous and dichotomous data: The effects of patterns of missingness and variable correlations on type I error with small samples

The purpose of this study is to investigate the effects of predictor variable correlations and patterns of missingness with dichotomous and/or continuous data in small samples when missing data is multiply imputed. Missing data of predictor variables is multiply imputed under three different multivariate models: the multivariate normal model for continuous data, the multinomial model for dichotomous data and the general location model for mixed dichotomous and continuous data. Subsequent to the multiple imputation process, Type I error rates of the regression coefficients obtained with logistic regression analysis are estimated under various conditions of correlation structure, sample size, type of data and patterns of missing data. The distributional properties of average mean, variance and correlations among the predictor variables are assessed after the multiple imputation process. ^ For continuous predictor data under the multivariate normal model, Type I error rates are generally within the nominal values with samples of size n = 100. Smaller samples of size n = 50 resulted in more conservative estimates (i.e., lower than the nominal value). Correlation and variance estimates of the original data are retained after multiple imputation with less than 50% missing continuous predictor data. For dichotomous predictor data under the multinomial model, Type I error rates are generally conservative, which in part is due to the sparseness of the data. The correlation structure for the predictor variables is not well retained on multiply-imputed data from small samples with more than 50% missing data with this model. For mixed continuous and dichotomous predictor data, the results are similar to those found under the multivariate normal model for continuous data and under the multinomial model for dichotomous data. With all data types, a fully-observed variable included with variables subject to missingness in the multiple imputation process and subsequent statistical analysis provided liberal (larger than nominal values) Type I error rates under a specific pattern of missing data. It is suggested that future studies focus on the effects of multiple imputation in multivariate settings with more realistic data characteristics and a variety of multivariate analyses, assessing both Type I error and power. ^

Comparing the factorial structure, invariance, and predictive validity of transtheoretical model constructs for alcohol use across restricted and unrestricted settings

With substance abuse treatment expanding in prisons and jails, understanding how behavior change interacts with a restricted setting becomes more essential. The Transtheoretical Model (TTM) has been used to understand intentional behavior change in unrestricted settings, however, evidence indicates restrictive settings can affect the measurement and structure of the TTM constructs. The present study examined data from problem drinkers at baseline and end-of-treatment from three studies: (1) Project CARE (n = 187) recruited inmates from a large county jail; (2) Project Check-In (n = 116) recruited inmates from a state prison; (3) Project MATCH, a large multi-site alcohol study had two recruitment arms, aftercare (n = 724 pre-treatment and 650 post-treatment) and outpatient (n = 912 pre-treatment and 844 post-treatment). The analyses were conducted using cross-sectional data to test for non-invariance of measures of the TTM constructs: readiness, confidence, temptation, and processes of change (Structural Equation Modeling, SEM) across restricted and unrestricted settings. Two restricted (jail and aftercare) and one unrestricted group (outpatient) entering treatment and one restricted (prison) and two unrestricted groups (aftercare and outpatient) at end-of-treatment were contrasted. In addition TTM end-of-treatment profiles were tested as predictors of 12 month drinking outcomes (Profile Analysis). Although SEM did not indicate structural differences in the overall TTM construct model across setting types, there were factor structure differences on the confidence and temptation constructs at pre-treatment and in the factor structure of the behavioral processes at the end-of-treatment. For pre-treatment temptation and confidence, differences were found in the social situations factor loadings and in the variance for the confidence and temptation latent factors. For the end-of-treatment behavioral processes, differences across the restricted and unrestricted settings were identified in the counter-conditioning and stimulus control factor loadings. The TTM end-of-treatment profiles were not predictive of drinking outcomes in the prison sample. Both pre and post-treatment differences in structure across setting types involved constructs operationalized with behaviors that are limited for those in restricted settings. These studies suggest the TTM is a viable model for explicating addictive behavior change in restricted settings but calls for modification of subscale items that refer to specific behaviors and caution in interpreting the mean differences across setting types for problem drinkers. ^

Does parental monitoring influence the use of alcohol and drugs among inner city 7th grade students?

Objective. To examine associations between parental monitoring and adolescent alcohol/drug use. ^ Methods. 981 7th grade students from 10 inner-city middle schools were surveyed at the 3 month follow-up of an HIV, STD, and pregnancy prevention program. Data from 549 control subjects were used for analyses. Multinomial logistic regression was used to examine associations between five parental monitoring variables and substance use, coded as: low risk [never drank alcohol or used drugs (0)], moderate risk [drank alcohol, no drug use (1)], and high risk [both drank alcohol and used drugs or just used drugs (2)]. ^ Results. Participants were 58.3% female, 39.6% African American, 43.8% Hispanic, mean age 13.3 years. Lifetime alcohol use was 47.9%. Lifetime drug use was 14.9%. Adjusted for gender, age, race, and family structure, each individual parental monitoring variable (perceived parental monitoring, less permissive parental monitoring, greater supervision (public places), greater supervision (teen clubs), and less time spent with older teens) was significant and protective for the moderate and high risk groups. When all 5 variables were entered into a single model, only perceived parental monitoring was significantly associated (OR=0.40, 95% CI 0.29-0.55) for the moderate risk group. For the high risk group, 3 variables were significantly protective (perceived parental monitoring OR=0.28, CI 0.18-0.42, less time spent with older teens OR=0.75, CI 0.60-0.93, and greater supervision (public places) OR=0.79, CI 0.64-0.99). ^ Conclusion. The association between parental monitoring and substance abuse is complex and varied for different risk levels. Implications for intervention development are addressed. ^

Host risk factors for rifamycin-resistant clostridium difficile infection: A case control study

Objective. To evaluate the host risk factors associated with rifamycin-resistant Clostridium difficile (C. diff) infection in hospitalized patients compared to rifamycin-susceptible C.diff infection.^ Background. C. diff is the most common definable cause of nosocomial diarrhea affecting elderly hospitalized patients taking antibiotics for prolonged durations. The epidemiology of Clostridium difficile associated disease is now changing with the reports of a new hypervirulent strain causing hospital outbreaks. This new strain is associated with increased disease severity and mortality. The conventional therapy for C. diff includes metronidazole and vancomycin but high recurrence rates and treatment failures are now becoming a major concern. Rifamycin antibiotics are being developed as a new therapeutic option to treat C. diff infection after their efficacy was established in a few in vivo and in vitro studies. There are some recent studies that report an association between the hypervirulent strain and emerging rifamycin resistance. These findings assess the need for clinical studies to better understand the efficacy of rifamycin drugs against C. diff.^ Methods. This is a hospital-based, matched case-control study using de-identified data drawn from two prospective cohort studies involving C. diff patients at St Luke's Hospital. The C. diff isolates from these patients are screened for rifamycin resistance using agar dilution methods for minimum inhibitory concentrations (MIC) as part of Dr Zhi-Dong Jiang's study. Twenty-four rifamycin-rifamycin resistant C. diff cases were identified and matched with one rifamycin susceptible C. diff control on the basis of ± 10 years of age and hospitalization 30 days before or after the case. De-identified data for the 48 subjects was obtained from Dr Kevin Garey's clinical study at St Luke's Hospital enrolling C. diff patients. It was reviewed to gather information about host risk factors, outcome variables and relevant clinical characteristic.^ Results. Medical diagnosis at the time of admission (p = 0.0281) and history of chemotherapy (p = 0.022) were identified as a significant risk factor while hospital stay ranging from 1 week to 1 month and artificial feeding were identified as an important outcome variable (p = 0.072 and p = 0.081 respectively). Horn's Index assessing the severity of underlying illness and duration of antibiotics for cases and controls showed no significant difference.^ Conclusion. The study was a small project designed to identify host risk factors and understand the clinical implications of rifamycin-resistance. The study was underpowered and a larger sample size is needed to validate the results.^

Multivariate methods for correlated effects sizes

Current statistical methods for estimation of parametric effect sizes from a series of experiments are generally restricted to univariate comparisons of standardized mean differences between two treatments. Multivariate methods are presented for the case in which effect size is a vector of standardized multivariate mean differences and the number of treatment groups is two or more. The proposed methods employ a vector of independent sample means for each response variable that leads to a covariance structure which depends only on correlations among the $p$ responses on each subject. Using weighted least squares theory and the assumption that the observations are from normally distributed populations, multivariate hypotheses analogous to common hypotheses used for testing effect sizes were formulated and tested for treatment effects which are correlated through a common control group, through multiple response variables observed on each subject, or both conditions.^ The asymptotic multivariate distribution for correlated effect sizes is obtained by extending univariate methods for estimating effect sizes which are correlated through common control groups. The joint distribution of vectors of effect sizes (from $p$ responses on each subject) from one treatment and one control group and from several treatment groups sharing a common control group are derived. Methods are given for estimation of linear combinations of effect sizes when certain homogeneity conditions are met, and for estimation of vectors of effect sizes and confidence intervals from $p$ responses on each subject. Computational illustrations are provided using data from studies of effects of electric field exposure on small laboratory animals. ^

HEAD OF HOUSEHOLD STRUCTURE: ITS INFLUENCE ON THE DIETARY QUALITY OF U.S. HOUSEHOLDS, 1977-78 (UNITED STATES, NATIONWIDE FOOD CONSUMPTION SURVEY)

Using analysis of variance, household data collected in the Spring portion of the 1977-78 Nationwide Food Consumption Survey conducted by the United States Department of Agriculture were analyzed to examine the relationship between household characteristics and dietary quality of the household food supply. Results indicated that head of household structure was a statistically significant variable, with female headed households having higher dietary quality.^ Further analysis indicated that neither race, degree of urbanization, regional location, the education level of the female head, nor her employment status were significant variables in influencing dietary quality. The influence of head of household structure remained significant when these variables were controlled. However, income, household size, and family life cycle stage had statistically significant effects on dietary quality, and when individually controlled, the influence of head of household structure disappeared. ^

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.