Zur Karbonatsedimentologie, Biofazies und sequenzstratigraphischen Architektur eines fossilen Hochenergie-Schelfs aus dem Neogen der Algarve (Miozän, Südportugal)

Die neogene Lagos-Portimão Formation (Unter- bis Mittelmiozän) bildet einen Teil der Steilküste der Algarve (S-Portugal) und besteht aus einer zyklischen Wechsellagerung von Karbonaten und Sand-steinen. Die vorliegende Arbeit bietet ein Modell zur sedimentologischen, faziellen und stratigraphischen Entwicklung dieser Einheit an. Basierend auf Profilen entlang der gesamten lateralen Erstreckung der Einheit wurden verschiedene Gelände- und Labormethoden angewandt, um ein Modell entwickeln zu können. Messungen des Sr87/86-Isotopenverhältnisses sollten Klarheit bezüglich der stratigraphischen Position bringen. Die laterale Korrelation der Profile erfolgte über lithologische und fazielle Ansprachen. Unterstützend wurden einzelne Profile mit einem tragbaren Gammaray-Spektrometer gemessen. Es wurden vier Leithorizonte etabliert, die sich durch fazielle Merkmale und spezielle Fossilführung defi-nieren lassen. Die Mikrofazies wurde qualitativ und quantitativ analysiert. Als statistisches Verfahren wurde unter anderem eine hierarchische Clusteranalyse durchgeführt, über welche fünf Biofaziestypen des warm-temperierten Klimabereichs unterschieden werden. Die Fossilführung wird von Mollusken, Bryozoen und Rotalgen dominiert. Ausnahmen bilden stratigraphisch isolierte Vorkommen von kolo-nialen Korallen, die jedoch keine Riffkörper aufbauen. Die Ergebnisse aller zuvor erwähnten Untersuchungen deuten auf Ablagerungen eines nicht-tropischen Hochenergie-Schelfs hin. Sedimentäre Zyklen sind oftmals unvollständig, es treten Hartgründe und Auf-arbeitungs- bzw- Kondesationshorizonte auf. Die geochemische Altersdatierung weist Alterssprünge und -inversionen auf. Ein Vergleich mit dem SW-australischen Schelf und dem von James et al. (1994) eingeführten Modell des shaved shelf bietet sich aufgrund der Ähnlichkeit der Sedimentgesteine und des ozeanographischen Settings an. Weiterhin werden zeitgleiche bzw. faziell ähnliche Becken vergleichend diskutiert. Das Sedimentationsgeschehen der Lagos-Portimão Formation wird maßgeblich durch eine halokinetisch bedingte unregelmäßige Subsidenz und Hebung beeinflußt. Der Salzdom von Albufeira war während der Sedimentation der Einheit mehrfach in Bewegung. Rutschungspakete, Entlastungsspalten und Sanddikes zeugen davon. Die sequenzstratigraphische Interpretation bietet einen neuen Ansatz, in dem sie von Hochstand-Sandsteinen und Tiefstand-Karbonaten ausgeht.

Life stage differences in mammary gland gene expression profile in non-human primates

Breast cancer (BC) is the most common malignancy of women in the developed world. To better understand its pathogenesis, knowledge of normal breast development is crucial, as BC is the result of disregulation of physiologic processes. The aim of this study was to investigate the impact of reproductive life stages on the transcriptional profile of the mammary gland in a primate model. Comparative transcriptomic analyses were carried out using breast tissues from 28 female cynomolgus macaques (Macaca fascicularis) at the following life stages: prepubertal (n = 5), adolescent (n = 4), adult luteal (n = 5), pregnant (n = 6), lactating (n = 3), and postmenopausal (n = 5). Mammary gland RNA was hybridized to Affymetrix GeneChip(®) Rhesus Macaque Genome Arrays. Differential gene expression was analyzed using ANOVA and cluster analysis. Hierarchical cluster analysis revealed distinct separation of life stage groups. More than 2,225 differentially expressed mRNAs were identified. Gene families or pathways that changed across life stages included those related to estrogen and androgen (ESR1, PGR, TFF1, GREB1, AR, 17HSDB2, 17HSDB7, STS, HSD11B1, AKR1C4), prolactin (PRLR, ELF5, STAT5, CSN1S1), insulin-like growth factor signaling (IGF1, IGFBP1, IGFBP5), extracellular matrix (POSTN, TGFB1, COL5A2, COL12A1, FOXC1, LAMC1, PDGFRA, TGFB2), and differentiation (CD24, CD29, CD44, CD61, ALDH1, BRCA1, FOXA1, POSTN, DICER1, LIG4, KLF4, NOTCH2, RIF1, BMPR1A, TGFB2). Pregnancy and lactation displayed distinct patterns of gene expression. ESR1 and IGF1 were significantly higher in the adolescent compared to the adult animals, whereas differentiation pathways were overrepresented in adult animals and pregnancy-associated life stages. Few individual genes were distinctly different in postmenopausal animals. Our data demonstrate characteristic patterns of gene expression during breast development. Several of the pathways activated during pubertal development have been implicated in cancer development and metastasis, supporting the idea that other developmental markers may have application as biomarkers for BC.

MicroRNA Expression Array Identifies Novel Diagnostic Markers for Conventional and Oncocytic Follicular Thyroid Carcinomas

Objective:The most difficult thyroid tumors to be diagnosed by cytology and histology are conventional follicular carcinomas (cFTCs) and oncocytic follicular carcinomas (oFTCs). Several microRNAs (miRNAs) have been previously found to be consistently deregulated in papillary thyroid carcinomas; however, very limited information is available for cFTC and oFTC. The aim of this study was to explore miRNA deregulation and find candidate miRNA markers for follicular carcinomas that can be used diagnostically.Design:Thirty-eight follicular thyroid carcinomas (21 cFTCs, 17 oFTCs) and 10 normal thyroid tissue samples were studied for expression of 381 miRNAs using human microarray assays. Expression of deregulated miRNAs was confirmed by individual RT-PCR assays in all samples. In addition, 11 follicular adenomas, two hyperplastic nodules (HNs), and 19 fine-needle aspiration samples were studied for expression of novel miRNA markers detected in this study.Results:The unsupervised hierarchical clustering analysis demonstrated individual clusters for cFTC and oFTC, indicating the difference in miRNA expression between these tumor types. Both cFTCs and oFTCs showed an up-regulation of miR-182/-183/-221/-222/-125a-3p and a down-regulation of miR-542-5p/-574-3p/-455/-199a. Novel miRNA (miR-885-5p) was found to be strongly up-regulated (>40-fold) in oFTCs but not in cFTCs, follicular adenomas, and HNs. The classification and regression tree algorithm applied to fine-needle aspiration samples demonstrated that three dysregulated miRNAs (miR-885-5p/-221/-574-3p) allowed distinguishing follicular thyroid carcinomas from benign HNs with high accuracy.Conclusions:In this study we demonstrate that different histopathological types of follicular thyroid carcinomas have distinct miRNA expression profiles. MiR-885-5p is highly up-regulated in oncocytic follicular carcinomas and may serve as a diagnostic marker for these tumors. A small set of deregulated miRNAs allows for an accurate discrimination between follicular carcinomas and hyperplastic nodules and can be used diagnostically in fine-needle aspiration biopsies.

The Psychosocial Quality of Nursing Home Work

Trained observers used components of the functional job analysis technique to categorize 3,371 tasks performed by 214 nursing assistants in four nursing homes on five occasions over 12 months. The extent to which each task was oriented toward residents versus data or things was coded along with the "level of complexity" of each of these orientations. A psychosocial index was created by multiplying orientation by complexity. Three questions structured the analyses: (a) To what extent do nursing assistants' tasks involve interacting with residents, as opposed to focusing on data or manipulating things? (b) How complex are these tasks? (c) What are the implications of the task analysis data for assessing the quality of psychosocial care? Findings reveal that even among the direct care tasks (69% of total), the orientation was not predominantly toward the resident. Functional complexity of the tasks observed was consistently low. Those task types with the greatest psychosocial quality were those performed least frequently and vice versa. Implications of these results for restructuring nursing assistants' work are discussed.

Gene expression profiling reveals consistent differences between clinical samples of human leukaemias and their model cell lines

Microarray gene expression profiles of fresh clinical samples of chronic myeloid leukaemia in chronic phase, acute promyelocytic leukaemia and acute monocytic leukaemia were compared with profiles from cell lines representing the corresponding types of leukaemia (K562, NB4, HL60). In a hierarchical clustering analysis, all clinical samples clustered separately from the cell lines, regardless of leukaemic subtype. Gene ontology analysis showed that cell lines chiefly overexpressed genes related to macromolecular metabolism, whereas in clinical samples genes related to the immune response were abundantly expressed. These findings must be taken into consideration when conclusions from cell line-based studies are extrapolated to patients.

Simulation in training: one-year experience using an efficiency index to assess interventional radiology fellow training status

PURPOSE: To compare objective fellow and expert efficiency indices for an interventional radiology renal artery stenosis skill set with the use of a high-fidelity simulator. MATERIALS AND METHODS: The Mentice VIST simulator was used for three different renal artery stenosis simulations of varying difficulty, which were used to grade performance. Fellows' indices at three intervals throughout 1 year were compared to expert baseline performance. Seventy-four simulated procedures were performed, 63 of which were captured as audiovisual recordings. Three levels of fellow experience were analyzed: 1, 6, and 12 months of dedicated interventional radiology fellowship. The recordings were compiled on a computer workstation and analyzed. Distinct measurable events in the procedures were identified with task analysis, and data regarding efficiency were extracted. Total scores were calculated as the product of procedure time, fluoroscopy time, tools, and contrast agent volume. The lowest scores, which reflected efficient use of tools, radiation, and time, were considered to indicate proficiency. Subjective analysis of participants' procedural errors was not included in this analysis. RESULTS: Fellows' mean scores diminished from 1 month to 12 months (42,960 at 1 month, 18,726 at 6 months, and 9,636 at 12 months). The experts' mean score was 4,660. In addition, the range of variance in score diminished with increasing experience (from a range of 5,940-120,156 at 1 month to 2,436-85,272 at 6 months and 2,160-32,400 at 12 months). Expert scores ranged from 1,450 to 10,800. CONCLUSIONS: Objective efficiency indices for simulated procedures can demonstrate scores directly comparable to the level of clinical experience.

Generierung von Konstruktionsmerkmalen zur Entwicklung eines bio-inspirierten Kommissionier- Greifers für die Intralogistik mittels Clusteranalyse

Kurzbeschreibung: In der Automatisierung von intralogistischen Kommissioniervorgängen ist ein großes Zukunftspotential erkennbar. Elementarer Bestandteil des Automatisierungsprozesses ist der Einsatz von Industrierobotern, die mit einem geeigneten Endeffektor, dem Greifer, ausgestattet werden müssen. Die Robotik ist in der Lage schneller, präziser und ausdauernder als die menschlichen Kommissionierer zu arbeiten und trägt damit entscheidend zur Effizienzsteigerung bei. Eine wesentliche Herausforderung für diesen Entwicklungsschritt zur Substitution der manuellen Kommissionierung ist die Konstruktion und Bereitstellung eines geeigneten Greifsystems. Am Lehrstuhl für Maschinenelemente und Technische Logistik der Helmut-Schmidt-Universität wurde mit der Erfahrung aus einem vorangegangenen Forschungsprojekt die Methode der Clusteranalyse erstmalig zur Untersuchung von Greifobjekten zur Entwicklung eines bionischen Universalgreifers für die Kommissionierung von Drogerieartikeln verwendet. Diese Abhandlung beschreibt einen Beitrag zur Entwicklung dieses Greifers am Beispiel handelsüblicher Drogerieartikel, die aktuell manuell kommissioniert werden. Diese werden hinsichtlich der für das Greifen relevanten Objektmerkmale geclustert und die daraus resultierenden Erkenntnisse in Form von Konstruktionsmerkmalen abgeleitet. Nach einer Analyse und Festlegung der greifrelevanten Merkmale der Greifobjekte wird eine Objektdatenbasis erstellt. Mit Hilfe geeigneter Methoden wird die gewonnene Datenbasis aufbereitet und reduziert. Im Anschluss werden die Greifobjekte bzw. deren Merkmalsausprägungen einer hierarchischen Clusteranalyse unterzogen. Hierbei werden die Grenzen der gebildeten Cluster mittels der zugehörigen Greifobjekte festgelegt und analysiert. Abschließend werden bestimmte greiferspezifische Merkmale auf die Anwendbarkeit in den Clustern überprüft und bewertet. Diese Betrachtungen ermöglichen es, dass spezielle Anforderungen an den Greifer, die direkt aus den Eigenschaften der Greifobjekte herrühren, zuverlässig erkannt und konstruktiv berücksichtigt werden können.

The long arm of time pressure at work: Cognitive failure and commuting near-accidents

This study tests whether cognitive failures mediate effects of work-related time pressure and time control on commuting accidents and near-accidents. Participants were 83 employees (56% female) who each commuted between their regular place of residence and place of work using vehicles. The Workplace Cognitive Failure Scale (WCFS) asked for the frequency of failure in memory function, failure in attention regulation, and failure in action execution. Time pressure and time control at work were assessed by the Instrument for Stress Oriented Task Analysis (ISTA). Commuting accidents in the last 12 months were reported by 10% of participants, and half of the sample reported commuting near-accidents in the last 4 weeks. Cognitive failure significantly mediated the influence of time pressure at work on near-accidents even when age, gender, neuroticism, conscientiousness, commuting duration, commuting distance, and time pressure during commuting were controlled for. Time control was negatively related to cognitive failure and neuroticism, but no association with commuting accidents or near-accidents was found. Time pressure at work is likely to increase cognitive load. Time pressure might, therefore, increase cognitive failures during work and also during commuting. Hence, time pressure at work can decrease commuting safety. The result suggests a reduction of time pressure at work should improve commuting safety.

Comprehensive MicroRNA expression profiling identifies novel markers in follicular variant of papillary thyroid carcinoma

BACKGROUND Follicular variant of papillary thyroid carcinoma (FVPTC) shares features of papillary (PTC) and follicular (FTC) thyroid carcinomas on a clinical, morphological, and genetic level. MicroRNA (miRNA) deregulation was extensively studied in PTCs and FTCs. However, very limited information is available for FVPTC. The aim of this study was to assess miRNA expression in FVPTC with the most comprehensive miRNA array panel and to correlate it with the clinicopathological data. METHODS Forty-four papillary thyroid carcinomas (17 FVPTC, 27 classic PTC) and eight normal thyroid tissue samples were analyzed for expression of 748 miRNAs using Human Microarray Assays on the ABI 7900 platform (Life Technologies, Carlsbad, CA). In addition, an independent set of 61 tumor and normal samples was studied for expression of novel miRNA markers detected in this study. RESULTS Overall, the miRNA expression profile demonstrated similar trends between FVPTC and classic PTC. Fourteen miRNAs were deregulated in FVPTC with a fold change of more than five (up/down), including miRNAs known to be upregulated in PTC (miR-146b-3p, -146-5p, -221, -222 and miR-222-5p) and novel miRNAs (miR-375, -551b, 181-2-3p, 99b-3p). However, the levels of miRNA expression were different between these tumor types and some miRNAs were uniquely dysregulated in FVPTC allowing separation of these tumors on the unsupervised hierarchical clustering analysis. Upregulation of novel miR-375 was confirmed in a large independent set of follicular cell derived neoplasms and benign nodules and demonstrated specific upregulation for PTC. Two miRNAs (miR-181a-2-3p, miR-99b-3p) were associated with an adverse outcome in FVPTC patients by a Kaplan-Meier (p < 0.05) and multivariate Cox regression analysis (p < 0.05). CONCLUSIONS Despite high similarity in miRNA expression between FVPTC and classic PTC, several miRNAs were uniquely expressed in each tumor type, supporting their histopathologic differences. Highly upregulated miRNA identified in this study (miR-375) can serve as a novel marker of papillary thyroid carcinoma, and miR-181a-2-3p and miR-99b-3p can predict relapse-free survival in patients with FVPTC thus potentially providing important diagnostic and predictive value.

Regional differences in trait-like characteristics of the waking EEG in early adolescence

BACKGROUND The human waking EEG spectrum shows high heritability and stability and, despite maturational cortical changes, high test-retest reliability in children and teens. These phenomena have also been shown to be region specific. We examined the stability of the morphology of the wake EEG spectrum in children aged 11 to 13 years recorded over weekly intervals and assessed whether the waking EEG spectrum in children may also be trait-like. Three minutes of eyes open and three minutes of eyes closed waking EEG was recorded in 22 healthy children once a week for three consecutive weeks. Eyes open and closed EEG power density spectra were calculated for two central (C3LM and C4LM) and two occipital (O1LM and O2LM) derivations. A hierarchical cluster analysis was performed to determine whether the morphology of the waking EEG spectrum between 1 and 20 Hz is trait-like. We also examined the stability of the alpha peak using an ANOVA. RESULTS The morphology of the EEG spectrum recorded from central derivations was highly stable and unique to an individual (correctly classified in 85% of participants), while the EEG recorded from occipital derivations, while stable, was much less unique across individuals (correctly classified in 42% of participants). Furthermore, our analysis revealed an increase in alpha peak height concurrent with a decline in the frequency of the alpha peak across weeks for occipital derivations. No changes in either measure were observed in the central derivations. CONCLUSIONS Our results indicate that across weekly recordings, power spectra at central derivations exhibit more "trait-like" characteristics than occipital derivations. These results may be relevant for future studies searching for links between phenotypes, such as psychiatric diagnoses, and the underlying genes (i.e., endophenotypes) by suggesting that such studies should make use of more anterior rather than posterior EEG derivations.

Teacher emotions in the classroom: Associations with students’ engagement, classroom discipline and the interpersonal teacher-student relationship

The present study explores teacher emotions, in particular how they are predicted by students’ behaviour and the interpersonal aspect of the teacher-student relationship (TSR). One hundred thirty-two secondary teachers participated in a quantitative study relying on self-report questionnaire data. Based on the model of teacher emotions by Frenzel (2014), teachers rated their experienced joy, anger and anxiety during classroom instruction (dependent variable). Students’ motivational behaviour (= engagement), socio-emotional behaviour (= discipline in class) and relational behaviour (= closeness; interpersonal TSR) were assessed as the independent variables. Teachers’ self-efficacy beliefs served as a control variable. Hierarchical regression analysis revealed that the interpersonal relationship formed between teachers and students was the strongest predictor for teachers’ joy (positive relation) and anxiety (negative relation), whereas lack of discipline in class best predicted teachers’ anger experiences. Students’ engagement also proved a significant predictor of teacher emotions. The results suggest that interpersonal TSR plays a particularly important role in teachers’ emotional experiences in class.

Biochemical MRI predicts hip osteoarthritis in an experimental ovine femoroacetabular impingement model

BACKGROUND Cam-type femoroacetabular impingement (FAI) resulting from an abnormal nonspherical femoral head shape leads to chondrolabral damage and is considered a cause of early osteoarthritis. A previously developed experimental ovine FAI model induces a cam-type impingement that results in localized chondrolabral damage, replicating the patterns found in the human hip. Biochemical MRI modalities such as T2 and T2* may allow for evaluation of the cartilage biochemistry long before cartilage loss occurs and, for that reason, may be a worthwhile avenue of inquiry. QUESTIONS/PURPOSES We asked: (1) Does the histological grading of degenerated cartilage correlate with T2 or T2* values in this ovine FAI model? (2) How accurately can zones of degenerated cartilage be predicted with T2 or T2* MRI in this model? METHODS A cam-type FAI was induced in eight Swiss alpine sheep by performing a closing wedge intertrochanteric varus osteotomy. After ambulation of 10 to 14 weeks, the sheep were euthanized and a 3-T MRI of the hip was performed. T2 and T2* values were measured at six locations on the acetabulum and compared with the histological damage pattern using the Mankin score. This is an established histological scoring system to quantify cartilage degeneration. Both T2 and T2* values are determined by cartilage water content and its collagen fiber network. Of those, the T2* mapping is a more modern sequence with technical advantages (eg, shorter acquisition time). Correlation of the Mankin score and the T2 and T2* values, respectively, was evaluated using the Spearman's rank correlation coefficient. We used a hierarchical cluster analysis to calculate the positive and negative predictive values of T2 and T2* to predict advanced cartilage degeneration (Mankin ≥ 3). RESULTS We found a negative correlation between the Mankin score and both the T2 (p < 0.001, r = -0.79) and T2* values (p < 0.001, r = -0.90). For the T2 MRI technique, we found a positive predictive value of 100% (95% confidence interval [CI], 79%-100%) and a negative predictive value of 84% (95% CI, 67%-95%). For the T2* technique, we found a positive predictive value of 100% (95% CI, 79%-100%) and a negative predictive value of 94% (95% CI, 79%-99%). CONCLUSIONS T2 and T2* MRI modalities can reliably detect early cartilage degeneration in the experimental ovine FAI model. CLINICAL RELEVANCE T2 and T2* MRI modalities have the potential to allow for monitoring the natural course of osteoarthrosis noninvasively and to evaluate the results of surgical treatments targeted to joint preservation.

Resilience as a correlate of acute stress disorder symptoms in patients with acute myocardial infarction

OBJECTIVES Myocardial infarction (MI) may be experienced as a traumatic event causing acute stress disorder (ASD). This mental disorder has an impact on the daily life of patients and is associated with the development of post-traumatic stress disorder. Trait resilience has been shown to be a protective factor for post-traumatic stress disorder, but its association with ASD in patients with MI is elusive and was examined in this study. METHODS We investigated 71 consecutive patients with acute MI within 48 h of having stable haemodynamic conditions established and for 3 months thereafter. All patients completed the Acute Stress Disorder Scale and the Resilience Scale to self-rate the severity of ASD symptoms and trait resilience, respectively. RESULTS Hierarchical regression analysis showed that greater resilience was associated with lower symptoms of ASD independent of covariates (b=-0.22, p<0.05). Post hoc analysis revealed resilience level to be inversely associated with the ASD symptom clusters of re-experiencing (b=-0.05, p<0.05) and arousal (b=-0.09, p<0.05), but not with dissociation and avoidance. CONCLUSIONS The findings suggest that patients with acute MI with higher trait resilience experience relatively fewer symptoms of ASD during MI. Resilience was particularly associated with re-experiencing and arousal symptoms. Our findings contribute to a better understanding of resilience as a potentially important correlate of ASD in the context of traumatic situations such as acute MI. These results emphasise the importance of identifying patients with low resilience in medical settings and to offer them adequate support.

Does Trauma Impair Self-Control? Differences in Delaying Gratification Between Former Indentured Child Laborers and Nontraumatized Controls.

Traumatic experiences may affect an individual's ability to exercise self-control, which is an essential characteristic for successfully managing life. As a measure of self-control, we used the delay discounting paradigm, that is, the extent to which a person devalues delayed gratification. The aim of this study was to investigate the relationship between childhood trauma and delay discounting using a control group design with elderly participants with a mean age of 76.2 years. Swiss former indentured child laborers (n=103) who had been exposed to trauma during their childhood were compared with nontraumatized controls (n=50). The trauma exposure group showed a considerably higher preference for immediate smaller rewards than the controls, indicating their lower self-control. A hierarchical regression analysis revealed that a history of abuse, current self-efficacy, and education were significantly associated with delay discounting. Implications for future research are discussed.

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.