Chiral Templating Activity of Tris(bipyridine)ruthenium(II) Cation in the Design of Three-Dimensional (3D) Optically Active Oxalate-Bridged {[Ru(bpy) 3 ][Cu 2 x Ni 2(1 - x ) (C 2 O 4 ) 3 ]} n (0 ≤ x ≤ 1; bpy = 2,2‘-bipyridine): Structural, Optical, and Magnetic Studies

Three-dimensional oxalate-based {[Ru(bpy)3][Cu2xNi2(1-x)(ox)3]}n (0≤ x ≤ 1, ox = C2O42-, bpy = 2,2‘bipyridine) were synthesized. The structure was determined for x = 1 by X-ray diffraction on single crystal. The compound crystallizes in the cubic space group P4132. It shows a three-dimensional 10-gon 3-connected (10,3) anionic network where copper(II) has an unusual tris(bischelated) environment. X-ray powder diffraction patterns and their Rietveld refinement show that all the compounds along the series are isostructural and single-phased. According to X-ray absorption spectroscopy, copper(II) and nickel(II) have an octahedral environment, respectively elongated and trigonally distorted. As shown by natural circular dichroism, the optically active forms of {[Ru(bpy)3][CuxNi2(1-x)(ox)3]}n are obtained starting from resolved Δ- or Λ-[Ru(bpy)3]2+. The Curie−Weiss temperatures range between −55 (x = 1) and −150 K (x = 0). The antiferromagnetic exchange interaction thus decreases when the copper contents increases in agreement with the crystallographic structure of the compounds and the electronic structure of the metal ions. At low temperature, the compounds exhibit complex long-range ordered magnetic behavior.

The Utilization of Classical Spin Monte Carlo Methods to Simulate the Magnetic Behavior of Extended Three-Dimensional Cubic Networks Incorporating M(II) Ions with an S = 5/2 Ground State Spin

The numerical simulations of the magnetic properties of extended three-dimensional networks containing M(II) ions with an S = 5/2 ground-state spin have been carried out within the framework of the isotropic Heisenberg model. Analytical expressions fitting the numerical simulations for the primitive cubic, diamond, together with (10−3) cubic networks have all been derived. With these empirical formulas in hands, we can now extract the interaction between the magnetic ions from the experimental data for these networks. In the case of the primitive cubic network, these expressions are directly compared with those from the high-temperature expansions of the partition function. A fit of the experimental data for three complexes, namely [(N(CH3)4][Mn(N3)] 1, [Mn(CN4)]n 2, and [FeII(bipy)3][MnII2(ox)3] 3, has been carried out. The best fits were those obtained using the following parameters, J = −3.5 cm-1, g = 2.01 (1); J = −8.3 cm-1, g = 1.95 (2); and J = −2.0 cm-1, g = 1.95 (3).

Molecular-Based Magnetism in High-Spin Molecular Clusters and Three-Dimensional Networks Based on Cyanometalate Building Blocks

The field of molecule-based magnets is a relatively new branch of chemistry, which involves the design and study of molecular compounds that exhibit a spontaneous magnetic ordering below a critical temperature, Tc. One major goal involves the design of materials with tuneable Tc's for specific applications in memory storage devices. Molecule-based magnets with high magnetic ordering temperatures have recently been obtained from bimetallic and mixed-valence transition metal μ-cyanide complexes of the Prussian blue family. Since the μ-cyanide linkages permit an interaction between paramagnetic metal ions, cyanometalate building blocks have found useful applications in the field of molecule-based magnets. Our work involves the use of octacyanometalate building blocks for the self-assembly of two new classes of magnetic materials namely, high-spin molecular clusters which exhibit both ferromagnetic intra- and intercluster coupling, and specific extended network topologies which show long-range ferromagnetic ordering.

Luminescence and Energy Transfer of [Ru(bpy) 3 ] 2+ , [Cr(ox) 3 ] 3- , and [Os(bpy) 3 ] 2+ in Three-Dimensional Oxalato-Networks

Luminescence and energy transfer in [Zn1-xRux(bpy)3][NaAl1-yCry(ox)3] (x ≈ 0.01, y = 0.006 − 0.22; bpy = 2,2‘-bipyridine, ox = C2O42-) and [Zn1-x-yRuxOsy(bpy)3][NaAl(ox)3] (x ≈ 0.01, y = 0.012) are presented and discussed. Surprisingly, the luminescence of the isolated luminophores [Ru(bpy)3]2+ and [Os(bpy)3]2+ in [Zn(bpy)3][NaAl(ox)3] is hardly quenched at room temperature. Steady-state luminescence spectra and decay curves show that energy transfer occurs between [Ru(bpy)3]2+ and [Cr(ox)3]3- and between [Ru(bpy)3]2+ and [Os(bpy)3]2+ in [Zn1-xRux(bpy)3][NaAl1-yCry(ox)3] and [Zn1-x-yRuxOsy(bpy)3] [NaAl(ox)3], respectively. For a quantitative investigation of the energy transfer, a shell type model is developed, using a Monte Carlo procedure and the structural parameters of the systems. A good description of the experimental data is obtained assuming electric dipole−electric dipole interaction between donors and acceptors, with a critical distance Rc for [Ru(bpy)3]2+ to [Cr(ox)3]3- energy transfer of 15 Å and for [Ru(bpy)3]2+ to [Os(bpy)3]2+ energy transfer of 33 Å. These values are in good agreement with those derived using the Förster−Dexter theory.

Interaction of the Trinuclear Triangular Secondary Building Unit [Cu 3 (μ 3 -OH)(μ-pz) 3 ] 2+ with 4,4′-Bipyridine. Structural Characterizations of New Coordination Polymers and Hexanuclear Cu II Clusters. 2°

By reacting 4,4′-bipyridine (bpy) with selected trinuclear triangular CuII complexes, [Cu3(μ3-OH)(μ-pz)3(RCOO)2(LL′)] [pz = pyrazolate anion; R = CH3, CH3CH2, CH2═CH, CH2═C(CH3); L, L′ = Hpz, H2O, MeOH] in MeOH, the substitution of monotopic ligands by ditopic bpy was observed. Depending on the stoichiometric reaction ratios, different compounds were isolated and structurally characterized. One- and two-dimensional coordination polymers (CPs), as well as two hexanuclear CuII clusters were identified. One of the hexanuclear clusters self-assembles into a supramolecular three-dimensional structure, and its crystal packing shows the presence of two intersecting channels, one of which is almost completely occupied by guest bpy, while in the second one guest water molecules are present. This compound also shows a reversible, thermally induced, single-crystal-to-single-crystal transition.

Exploring the emotional brain: Neural correlates of homeostatic and sensory-evoked emotions and their interaction in emotional rivalry

Human emotions are essential for survival. They are vital for the satisfaction of basic needs, the regulation of personal life and successful integration into social structures. Depending on which aspect of an emotion is used in its definition, many different theories offer possible answers to the questions of what emotions are and how they can be distinguished. The systematic investigation of emotions in cognitive neuroscience is relatively new, and neuroimaging studies specifically focussing on the neural correlates of different categories of emotions are still lacking. Therefore, the current thesis aimed at investigating the behavioural and neurophysiological correlates of different human emotional levels and their interaction in healthy subjects. We differentiated between emotions according to their cerebral entry site and neural processing pathways: homeostatic emotions, which are elicited by metabolic changes and processed by the interoceptive system (such as thirst, hunger, and need for air), and sensory-evoked emotions, which are evoked by external inputs via the eyes, ears or nose, or their corresponding mental representations and processed in the brain as sensory perception (e.g. fear, disgust, or pride). Using functional magnetic resonance imaging (fMRI) and behavioural parameters, we examined both the specific neural underpinnings of a homeostatic emotion (thirst) and a sensory-evoked emotion (disgust), and their interaction in a situation of emotional rivalry when both emotions were perceived simultaneously. This thesis comprises three research articles reporting the results of this research. The first paper presents disgust-related brain imaging data in a thirsty and a satiated condition. We found that disgust mainly activated the anterior insular cortex. In the thirsty condition, however, we observed an interaction effect between disgust and thirst: when thirsty, the subjects rated the disgusting stimulus as less repulsive. On the neurobiological level, this reduction of subjective disgust was accompanied by significantly reduced neural activity in the insular cortex. These results provide new neurophysiological evidence for a hierarchical organization among homeostatic and sensory-evoked emotions, revealing that in a situation of emotional conflict, homeostatic emotions are prioritized over sensory-evoked emotions. In the second paper, findings on brain perfusion over four different thirst stages are reported, with a special focus on the parametric progression of thirst. Cerebral perfusion differences over all thirst stages were found in the posterior insular cortex. Taking this result together with the findings of the first paper, the insular cortex seems to be a key player in human emotional processing, since it comprises specific representations of homeostatic and sensory-evoked emotions and also represents the site of cortical interaction between the two levels of emotions. Finally, although this thesis focussed on the homeostatic modulation of disgust, we were also interested in whether dehydration modulates taste perception. The results of this behavioural experiment are described in the third paper, where we show that dehydration alters the perception of neutral taste stimuli.

Bargaining for power and information : an experimental and theoretical analysis of the interaction between institutions, externalities and adverse selection

Bargaining is the building block of many economic interactions, ranging from bilateral to multilateral encounters and from situations in which the actors are individuals to negotiations between firms or countries. In all these settings, economists have been intrigued for a long time by the fact that some projects, trades or agreements are not realized even though they are mutually beneficial. On the one hand, this has been explained by incomplete information. A firm may not be willing to offer a wage that is acceptable to a qualified worker, because it knows that there are also unqualified workers and cannot distinguish between the two types. This phenomenon is known as adverse selection. On the other hand, it has been argued that even with complete information, the presence of externalities may impede efficient outcomes. To see this, consider the example of climate change. If a subset of countries agrees to curb emissions, non-participant regions benefit from the signatories’ efforts without incurring costs. These free riding opportunities give rise to incentives to strategically improve ones bargaining power that work against the formation of a global agreement. This thesis is concerned with extending our understanding of both factors, adverse selection and externalities. The findings are based on empirical evidence from original laboratory experiments as well as game theoretic modeling. On a very general note, it is demonstrated that the institutions through which agents interact matter to a large extent. Insights are provided about which institutions we should expect to perform better than others, at least in terms of aggregate welfare. Chapters 1 and 2 focus on the problem of adverse selection. Effective operation of markets and other institutions often depends on good information transmission properties. In terms of the example introduced above, a firm is only willing to offer high wages if it receives enough positive signals about the worker’s quality during the application and wage bargaining process. In Chapter 1, it will be shown that repeated interaction coupled with time costs facilitates information transmission. By making the wage bargaining process costly for the worker, the firm is able to obtain more accurate information about the worker’s type. The cost could be pure time cost from delaying agreement or cost of effort arising from a multi-step interviewing process. In Chapter 2, I abstract from time cost and show that communication can play a similar role. The simple fact that a worker states to be of high quality may be informative. In Chapter 3, the focus is on a different source of inefficiency. Agents strive for bargaining power and thus may be motivated by incentives that are at odds with the socially efficient outcome. I have already mentioned the example of climate change. Other examples are coalitions within committees that are formed to secure voting power to block outcomes or groups that commit to different technological standards although a single standard would be optimal (e.g. the format war between HD and BlueRay). It will be shown that such inefficiencies are directly linked to the presence of externalities and a certain degree of irreversibility in actions. I now discuss the three articles in more detail. In Chapter 1, Olivier Bochet and I study a simple bilateral bargaining institution that eliminates trade failures arising from incomplete information. In this setting, a buyer makes offers to a seller in order to acquire a good. Whenever an offer is rejected by the seller, the buyer may submit a further offer. Bargaining is costly, because both parties suffer a (small) time cost after any rejection. The difficulties arise, because the good can be of low or high quality and the quality of the good is only known to the seller. Indeed, without the possibility to make repeated offers, it is too risky for the buyer to offer prices that allow for trade of high quality goods. When allowing for repeated offers, however, at equilibrium both types of goods trade with probability one. We provide an experimental test of these predictions. Buyers gather information about sellers using specific price offers and rates of trade are high, much as the model’s qualitative predictions. We also observe a persistent over-delay before trade occurs, and this mitigates efficiency substantially. Possible channels for over-delay are identified in the form of two behavioral assumptions missing from the standard model, loss aversion (buyers) and haggling (sellers), which reconcile the data with the theoretical predictions. Chapter 2 also studies adverse selection, but interaction between buyers and sellers now takes place within a market rather than isolated pairs. Remarkably, in a market it suffices to let agents communicate in a very simple manner to mitigate trade failures. The key insight is that better informed agents (sellers) are willing to truthfully reveal their private information, because by doing so they are able to reduce search frictions and attract more buyers. Behavior observed in the experimental sessions closely follows the theoretical predictions. As a consequence, costless and non-binding communication (cheap talk) significantly raises rates of trade and welfare. Previous experiments have documented that cheap talk alleviates inefficiencies due to asymmetric information. These findings are explained by pro-social preferences and lie aversion. I use appropriate control treatments to show that such consideration play only a minor role in our market. Instead, the experiment highlights the ability to organize markets as a new channel through which communication can facilitate trade in the presence of private information. In Chapter 3, I theoretically explore coalition formation via multilateral bargaining under complete information. The environment studied is extremely rich in the sense that the model allows for all kinds of externalities. This is achieved by using so-called partition functions, which pin down a coalitional worth for each possible coalition in each possible coalition structure. It is found that although binding agreements can be written, efficiency is not guaranteed, because the negotiation process is inherently non-cooperative. The prospects of cooperation are shown to crucially depend on i) the degree to which players can renegotiate and gradually build up agreements and ii) the absence of a certain type of externalities that can loosely be described as incentives to free ride. Moreover, the willingness to concede bargaining power is identified as a novel reason for gradualism. Another key contribution of the study is that it identifies a strong connection between the Core, one of the most important concepts in cooperative game theory, and the set of environments for which efficiency is attained even without renegotiation.

Three-year efficacy and safety of new- versus early-generation drug-eluting stents for unprotected left main coronary artery disease insights from the ISAR-LEFT MAIN and ISAR-LEFT MAIN 2 trials.

BACKGROUND In percutaneous coronary intervention (PCI) patients new-generation drug-eluting stent (DES) has reduced adverse events in comparison to early-generation DES. The aim of the current study was to investigate the long-term clinical efficacy and safety of new-generation DES versus early-generation DES for PCI of unprotected left main coronary artery (uLMCA) disease. METHODS The patient-level data from the ISAR-LEFT MAIN and ISAR-LEFT MAIN 2 randomized trials were pooled. The clinical outcomes of PCI patients assigned to new-generation DES (everolimus- or zotarolimus-eluting stent) versus early-generation DES (paclitaxel- or sirolimus-eluting stent) were studied. The primary endpoint was the composite of death, myocardial infarction (MI), target lesion revascularization and stroke (MACCE, major adverse cardiac and cerebrovascular event). RESULTS In total, 1257 patients were available. At 3 years, the risk of MACCE was comparable between patients assigned to new-generation DES or early-generation DES (28.2 versus 27.5 %, hazard ratio-HR 1.03, 95 % confidence intervals-CI 0.83-1.26; P = 0.86). Definite/probable stent thrombosis was low and comparable between new-generation DES and early-generation DES (0.8 versus 1.6 %, HR 0.52, 95 % CI 0.18-1.57; P = 0.25); in patients treated with new-generation DES no cases occurred beyond 30 days. Diabetes increased the risk of MACCE in patients treated with new-generation DES but not with early-generation DES (P interaction = 0.004). CONCLUSIONS At 3-year follow-up, a PCI with new-generation DES for uLMCA disease shows comparable efficacy to early-generation DES. Rates of stent thrombosis were low in both groups. Diabetes significantly impacts the risk of MACCE at 3 years in patients treated with new-generation DES for uLMCA disease. ClinicalTrials.gov Identifiers: NCT00133237; NCT00598637.

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

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

Gene-gene interaction and gene-pathway analysis of genome-wide association for schizophrenia

Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^

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.

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.

Mechanism of subunit interaction and DNA binding of the heterotrimeric CCAAT binding factor CBF

Many eukaryotic promoters contain a CCAAT element at a site close ($-$80 to $-$120) to the transcription initiation site. CBF (CCAAT Binding Factor), also called NF-Y and CP1, was initially identified as a transcription factor binding to such sites in the promoters of the Type I collagen, albumin and MHC class II genes. CBF is a heteromeric transcription factor and purification and cloning of two of the subunits, CBF-A and CBF-B revealed that it was evolutionarily conserved with striking sequence identities with the yeast polypeptides HAP3 and HAP2, which are components of a CCAAT binding factor in yeast. Recombinant CBF-A and CBF-B however failed to bind to DNA containing CCAAT sequences. Biochemical experiments led to the identification of a third subunit, CBF-C which co-purified with CBF-A and complemented the DNA binding of recombinant CBF-A and CBF-B. We have recently isolated CBF-C cDNAs and have shown that bacterially expressed purified CBF-C binds to CCAAT containing DNA in the presence of recombinant CBF-A and CBF-B. Our experiments also show that a single molecule each of all the three subunits are present in the protein-DNA complex. Interestingly, CBF-C is also evolutionarily conserved and the conserved domain between CBF-C and its yeast homolog HAP5 is sufficient for CBF-C activity. Using GST-pulldown experiments we have demonstrated the existence of protein-protein interaction between CBF-A and CBF-C in the absence of CBF-B and DNA. CBF-B on other hand, requires both CBF-A and CBF-C to form a ternary complex which then binds to DNA. Mutational studies of CBF-A have revealed different domains of the protein which are involved in CBF-C interaction and CBF-B interaction. In addition, CBF-A harbors a domain which is involved in DNA recognition along with CBF-B. Dominant negative analogs of CBF-A have also substantiated our initial observation of assembly of CBF subunits. Our studies define a novel DNA binding structure of heterotrimeric CBF, where the three subunits of CBF follow a particular pathway of assembly of subunits that leads to CBF binding to DNA and activating transcription. ^

Anelastic strain recovery and elastic properties of ODP Leg 123 oceanic basalt samples

A knowledge of rock stress is fundamental for improving our understanding of oceanic crustal mechanisms and lithospheric dynamic processes. However, direct measurements of stress in the deep oceans, and in particular stress magnitudes, have proved to be technically difficult. Anelastic strain recovery measurements were conducted on 15 basalt core samples from Sites 765 and 766 during Leg 123. Three sets of experiments were performed: anelastic strain recovery monitoring, dynamic elastic property measurements, and thermal azimuthal anisotropy observations. In addition, a range of other tests and observations were recorded to characterize each of the samples. One common feature of the experimental results and observations is that apparently no consistent orientation trend exists, either between the different measurements on each core sample or between the same sets of measurements on the various core samples. However, some evidence of correspondence between velocity anisotropy and anelastic strain recovery exists, but this is not consistent for all the core samples investigated. Thermal azimuthal anisotropy observations, although showing no conclusive correlations with the other results, were of significant interest in that they clearly exhibited anisotropic behavior. The apparent reproducibility of this behavior may point toward the possibility of rocks that retain a "memory" of their stress history, which could be exploited to derive stress orientations from archived core. Anelastic strain recovery is a relatively new technique. Because use of the method has extended to a wider range of rock types, the literature has begun to include examples of rocks that contracted with time. Strong circumstantial evidence exists to suggest that core-sample contractions result from the slow diffusion of pore fluids from a preexisting microcrack structure that permits the rock to deflate at a greater rate than the expansion caused by anelastic strain recovery. Both expansions and contractions of the Leg 123 cores were observed. The basalt cores have clearly been intersected by an abundance of preexisting fractures, some of which pass right through the samples, but many are intercepted or terminate within the rock matrix. Thus, the behavior of the core samples will be influenced not only by the properties of the rock matrix between the fractures, but also by how these macro- and micro-scale fractures mutually interact. The strain-recovery curves recorded during Leg 123 for each of the 15 basalt core samples may reflect the result of two competing time dependent processes: anelastic strain recovery and pore pressure recovery. Were these the only two processes to influence the gauge responses, then one might expect that given the additional information required, established theoretical models might be used to determine consistent stress orientations and reliable stress magnitudes. However, superimposed upon these competing processes is their respective interaction with the preexisting fractures that intersect each core. Evidence from our experiments and observations suggests that these fractures have a dominating influence on the characteristics of the recovery curves and that their effects are complex.

Comparing the quality of three models of postabortion care in public hospitals in Mexico City

artículo publicado en la revista Int Fam Plan Perspect. 2003 Sep;29(3):112-20