894 resultados para Multiple Covariates and Biomarker Interactions


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Cognitive health is of central importance for independent and balanced old age, while memory disorders represent the leading cause of intensive and long-term care among the Finnish elderly. The aims of this study were to analyse the effect of height, body mass index, weight change, metabolic conditions and coffee drinking in midlife on cognitive performance in old age among a sample of 2606 Finnish twins aged 65 years or older who had participated in a telephone interview to assess their cognitive status. Since coffee drinking associates with several metabolic conditions and Finns are known to be the greatest consumers of coffee in the world, the heritability and stability of coffee drinking was analysed in the whole Older Finnish Twin Cohort (n=10716). In order to investigate the association between height and cognitive performance in a population with more supportive childhood living conditions, a total of 2161 Danish twins were included in this study. A greater height was found to clearly associate with better cognitive performance in Finnish subjects, but less so among the Danish sample, which may reflect the childhood environmental differences between these cohorts. In the Finnish subjects, there was greater variance in cognitive performance among shorter subjects, and environmental factors were found to play a greater role in their cognitive performance, whereas the cognitive performance of taller participants was mainly explained by genetic factors. Midlife metabolic variables that were found to be significantly associated with a poorer cognitive performance in old age included a higher body mass index and three metabolic conditions: cardiovascular disease, hypertension and, most significantly of all, diabetes. Moreover, both weight gain and loss, even to a lesser degree than suggested previously, were found to be associated with poorer cognition. Furthermore, evidence of a causal relationship between midlife cardiovascular disease and cognitive performance in old age was demonstrated among discordant twin pairs. Conversely, no effect of coffee drinking in midlife on cognitive performance in old age was observed, although coffee drinking was demonstrated to be stable in the study population. The heritability of coffee drinking was found to differ across sexes and age groups, being 51% in men and 52% in women in the whole study population. This study supports the contention that cognitive performance in old age reflects the effects of multiple genetic and environmental exposures, including their complex interactions during the life-span. The demonstrated associations and evidence of a causal pathway between potentially preventable exposures and poorer cognitive performance highlight the importance of preventive medicine.

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The crystal structure of Flunazirine, an anticonvulsant drug, is analyzed in terms of intermolecular interactions involving fluorine. The structure displays motifs formed by only weak interactions C–H⋯F and C–H⋯π. The motifs thus generated show cavities, which could serve as hosts for complexation. The structure of Flunazirine displays cavities formed by C–H⋯F and C–H⋯π interactions. Haloperidol, an antipsychotic drug, shows F⋯F interactions in the crystalline lattice in lieu of Cl⋯Cl interactions. However, strong O–H⋯N interactions dominate packing. The salient features of the two structures in terms of intermolecular interactions reveal, even though organic fluorine has lower tendency to engage in hydrogen bonding and F⋯F interactions, these interactions could play a significant role in the design of molecular assemblies via crystal engineering.

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Germline mutations in RECQL4 and p53 lead to cancer predisposition syndromes, Rothmund-Thomson syndrome (RTS) and Li-Fraumeni syndrome (LFS), respectively. RECQL4 is essential for the transport of p53 to the mitochondria under unstressed conditions. Here, we show that both RECQL4 and p53 interact with mitochondrial polymerase (Pol gamma A/B2) and regulate its binding to the mitochondrial DNA (mtDNA) control region (D-loop). Both RECQL4 and p53 bind to the exonuclease and polymerase domains of Pol gamma A. Kinetic constants for interactions between Pol gamma A-RECQL4, Pol gamma A-p53 and Pol gamma B-p53 indicate that RECQL4 and p53 are accessory factors for Pol gamma A-Pol gamma B and Pol gamma A-DNA interactions. RECQL4 enhances the binding of Pol gamma A to DNA, thereby potentiating the exonuclease and polymerization activities of Pol gamma A/B2. To investigate whether lack of RECQL4 and p53 results in increased mitochondrial genome instability, resequencing of the entire mitochondrial genome was undertaken from multiple RTS and LFS patient fibroblasts. We found multiple somatic mutations and polymorphisms in both RTS and LFS patient cells. A significant number of mutations and polymorphisms were common between RTS and LFS patients. These changes are associated with either aging and/or cancer, thereby indicating that the phenotypes associated with these syndromes may be due to deregulation of mitochondrial genome stability caused by the lack of RECQL4 and p53. Summary: The biochemical mechanisms by which RECQL4 and p53 affect mtDNA replication have been elucidated. Resequencing of RTS and LFS patients' mitochondrial genome reveals common mutations indicating similar mechanisms of regulation by RECQL4 and p53.

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Rich data bearing on the structural and evolutionary principles of protein protein interactions are paving the way to a better understanding of the regulation of function in the cell. This is particularly the case when these interactions are considered in the framework of key pathways. Knowledge of the interactions may provide insights into the mechanisms of crucial `driver' mutations in oncogenesis. They also provide the foundation toward the design of protein protein interfaces and inhibitors that can abrogate their formation or enhance them. The main features to learn from known 3-D structures of protein protein complexes and the extensive literature which analyzes them computationally and experimentally include the interaction details which permit undertaking structure-based drug discovery, the evolution of complexes and their interactions, the consequences of alterations such as post-translational modifications, ligand binding, disease causing mutations, host pathogen interactions, oligomerization, aggregation and the roles of disorder, dynamics, allostery and more to the protein and the cell. This review highlights some of the recent advances in these areas, including design, inhibition and prediction of protein protein complexes. The field is broad, and much work has been carried out in these areas, making it challenging to cover it in its entirety. Much of this is due to the fast increase in the number of molecules whose structures have been determined experimentally and the vast increase in computational power. Here we provide a concise overview. (C) 2014 Elsevier Ltd. All rights reserved.

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Structural information over the entire course of binding interactions based on the analyses of energy landscapes is described, which provides a framework to understand the events involved during biomolecular recognition. Conformational dynamics of malectin's exquisite selectivity for diglucosylated N-glycan (Dig-N-glycan), a highly flexible oligosaccharide comprising of numerous dihedral torsion angles, are described as an example. For this purpose, a novel approach based on hierarchical sampling for acquiring metastable molecular conformations constituting low-energy minima for understanding the structural features involved in a biologic recognition is proposed. For this purpose, four variants of principal component analysis were employed recursively in both Cartesian space and dihedral angles space that are characterized by free energy landscapes to select the most stable conformational substates. Subsequently, k-means clustering algorithm was implemented for geometric separation of the major native state to acquire a final ensemble of metastable conformers. A comparison of malectin complexes was then performed to characterize their conformational properties. Analyses of stereochemical metrics and other concerted binding events revealed surface complementarity, cooperative and bidentate hydrogen bonds, water-mediated hydrogen bonds, carbohydrate-aromatic interactions including CH-pi and stacking interactions involved in this recognition. Additionally, a striking structural transition from loop to beta-strands in malectin CRD upon specific binding to Dig-N-glycan is observed. The interplay of the above-mentioned binding events in malectin and Dig-N-glycan supports an extended conformational selection model as the underlying binding mechanism.

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We present the results of combined experimental and theoretical (molecular dynamics simulations and integral equation theory) studies of the structure and effective interactions of suspensions of polymer grafted nanoparticles (PGNPs) in the presence of linear polymers. Due to the absence of systematic experimental and theoretical studies of PGNPs, it is widely believed that the structure and effective interactions in such binary mixtures would be very similar to those of an analogous soft colloidal material-star polymers. In our study, polystyrene-grafted gold nanoparticles with functionality f = 70 were mixed with linear polystyrene (PS) of two different molecular weights for obtaining two PGNP: PS size ratios, xi = 0.14 and 2.76 (where, xi = M-g/M-m, M-g and M-m being the molecular weights of grafting and matrix polymers, respectively). The experimental structure factor of PGNPs could be modeled with an effective potential (Model-X), which has been found to be widely applicable for star polymers. Similarly, the structure factor of the blends with xi = 0.14 could be modeled reasonably well, while the structure of blends with xi = 2.76 could not be captured, especially for high density of added polymers. A model (Model-Y) for effective interactions between PGNPs in a melt of matrix polymers also failed to provide good agreement with the experimental data for samples with xi = 2.76 and high density of added polymers. We tentatively attribute this anomaly in modeling the structure factor of blends with xi = 2.76 to the questionable assumption of Model-X in describing the added polymers as star polymers with functionality 2, which gets manifested in both polymer-polymer and polymer-PGNP interactions especially at higher fractions of added polymers. The failure of Model-Y may be due to the neglect of possible many-body interactions among PGNPs mediated by matrix polymers when the fraction of added polymers is high. These observations point to the need for a new framework to understand not only the structural behavior of PGNPs but also possibly their dynamics and thermo-mechanical properties as well. (C) 2015 AIP Publishing LLC.

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Diagnosis and adaptive management can help improve the ability of small-scale fisheries (SSF) in the developing world to better cope with and adapt to both external drivers and internal sources of uncertainty. This paper presents a framework for diagnosis and adaptive management and discusses ways of implementing the first two phases of learning: diagnosis and mobilising an appropriate management constituency. The discussion addresses key issues and suggests suitable approaches and tools as well as numerous sources of further information. Diagnosis of a SSF defines the system to be managed, outlines the scope of the management problem in terms of threats and opportunities, and aims to construct realistic and desired future projections for the fishery. These steps can clarify objectives and lead to development of indicators necessary for adaptive management. Before management, however, it is important to mobilize a management constituency to enact change. Ways of identifying stakeholders and understanding both enabling and obstructive interactions and management structures are outlined. These preliminary learning phases for adaptive SSF management are expected to work best if legitimised by collaborative discussion among fishery stakeholders drawing on multiple knowledge systems and participatory approaches to assessment. (PDF contains 33 pages)

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This dissertation primarily describes chemical-scale studies of G protein-coupled receptors and Cys-loop ligand-gated ion channels to better understand ligand binding interactions and the mechanism of channel activation using recently published crystal structures as a guide. These studies employ the use of unnatural amino acid mutagenesis and electrophysiology to measure subtle changes in receptor function.

In chapter 2, the role of a conserved aromatic microdomain predicted in the D3 dopamine receptor is probed in the closely related D2 and D4 dopamine receptors. This domain was found to act as a structural unit near the ligand binding site that is important for receptor function. The domain consists of several functionally important noncovalent interactions including hydrogen bond, aromatic-aromatic, and sulfur-π interactions that show strong couplings by mutant cycle analysis. We also assign an alternate interpretation for the linear fluorination plot observed at W6.48, a residue previously thought to participate in a cation-π interaction with dopamine.

Chapter 3 outlines attempts to incorporate chemically synthesized and in vitro acylated unnatural amino acids into mammalian cells. While our attempts were not successful, method optimizations and data for nonsense suppression with an in vivo acylated tRNA are included. This chapter is aimed to aid future researchers attempting unnatural amino acid mutagenesis in mammalian cells.

Chapter 4 identifies a cation-π interaction between glutamate and a tyrosine residue on loop C in the GluClβ receptor. Using the recently published crystal structure of the homologous GluClα receptor, other ligand-binding and protein-protein interactions are probed to determine the similarity between this invertebrate receptor and other more distantly related vertebrate Cys-loop receptors. We find that many of the interactions previously observed are conserved in the GluCl receptors, however care must be taken when extrapolating structural data.

Chapter 5 examines inherent properties of the GluClα receptor that are responsible for the observed glutamate insensitivity of the receptor. Chimera synthesis and mutagenesis reveal the C-terminal portion of the M4 helix and the C-terminus as contributing to formation of the decoupled state, where ligand binding is incapable of triggering channel gating. Receptor mutagenesis was unable to identify single residue mismatches or impaired protein-protein interactions within this domain. We conclude that M4 helix structure and/or membrane dynamics are likely the cause of ligand insensitivity in this receptor and that the M4 helix has an role important in the activation process.

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The investigations presented in this thesis use various in vivo techniques to understand how trans-acting factors control gene expression. The first part addresses the transcriptional regulation of muscle creatine kinase (MCK). MCK expression is activated during the course of development and is found only in differentiated muscle. Several in vivo footprints are observed at the enhancer of this gene, but all of these interactions are limited to cell types that express MCK. This is interesting because two of the footprints appear to represent muscle specific use of general transcription factors, while the other two correspond to sites that can bind the myogenic regulator, MyoD1, in vitro. MyoD1 and these general factors are present in myoblasts, but can bind to the enhancer only in myocytes. This suggests that either the factors themselves are post-translationally modified (phosphorylation or protein:protein interactions), or the accessibility of the enhancer to the factors is limited (changes in chromatin structure). The in vivo footprinting study of MCK was performed with a new ligation mediated, single-sided PCR (polymerase chain reaction) technique that I have developed.

The second half of the thesis concerns the regulation of mouse metallothionein (MT). Metallothioneins are a family of highly conserved housekeeping genes whose expression can be induced by heavy metals, steroids, and other stresses. By adapting a primer extension method of genomic sequencing to in vivo footprinting, I've observed both metal inducible and noninducible interactions at the promoter of MT-I. From these results I've been able to limit the possible mechanisms by which metal responsive trans-acting factors induce transcription. These interpretations correlate with a second line of experiments involving the stable titration of positive acting factors necessary for induction of MT. I've amplified the promoter of MT to 10^2-10^3 copies per cell by fusing the 5' and 3' ends of the MT gene to the coding region of DHFR and selecting cells for methotrexate resistance. In these cells, there is a metal-specific titration effect, and although it acts at the level of transcription, it appears to be independent of direct DNA binding factors.

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Immunoglobulin G (IgG) is central in mediating host defense due to its ability to target and eliminate invading pathogens. The fragment antigen binding (Fab) regions are responsible for antigen recognition; however the effector responses are encoded on the Fc region of IgG. IgG Fc displays considerable glycan heterogeneity, accounting for its complex effector functions of inflammation, modulation and immune suppression. Intravenous immunoglobulin G (IVIG) is pooled serum IgG from multiple donors and is used to treat individuals with autoimmune and inflammatory disorders such as rheumatoid arthritis and Kawasaki’s disease, respectively. It contains all the subtypes of IgG (IgG1-4) and over 120 glycovariants due to variation of an Asparagine 297-linked glycan on the Fc. The species identified as the activating component of IVIG is sialylated IgG Fc. Comparisons of wild type Fc and sialylated Fc X-ray crystal structures suggests that sialylation causes an increase in conformational flexibility, which may be important for its anti-inflammatory properties.

Although glycan modifications can promote the anti-inflammatory properties of the Fc, there are amino acid substitutions that cause Fcs to initiate an enhanced immune response. Mutations in the Fc can cause up to a 100-fold increase in binding affinity to activating Fc gamma receptors located on immune cells, and have been shown to enhance antibody dependent cell-mediated cytotoxicity. This is important in developing therapeutic antibodies against cancer and infectious diseases. Structural studies of mutant Fcs in complex with activating receptors gave insight into new protein-protein interactions that lead to an enhanced binding affinity.

Together these studies show how dynamic and diverse the Fc region is and how both protein and carbohydrate modifications can alter structure, leading to IgG Fc’s switch from a pro-inflammatory to an anti-inflammatory protein.

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Distribution, movements, and habitat use of small (<46 cm, juveniles and individuals of unknown maturity) striped bass (Morone saxatilis) were investigated with multiple techniques and at multiple spatial scales (surveys and tag-recapture in the estuary and ocean, and telemetry in the estuary) over multiple years to determine the frequency and duration of use of non-natal estuaries. These unique comparisons suggest, at least in New Jersey, that smaller individuals (<20 cm) may disperse from natal estuaries and arrive in non-natal estuaries early in life and take up residence for several years. During this period of estuarine residence, individuals spend all seasons primarily in the low salinity portions of the estuary. At larger sizes, they then leave these non-natal estuaries to begin coastal migrations with those individuals from nurseries in natal estuaries. These composite observations of frequency and duration of habitat use indicate that non-natal estuaries may provide important habitat for a portion of the striped bass population.

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The intersection of social and environmental forces is complex in coastal communities. The well-being of a coastal community is caught up in the health of its environment, the stability of its economy, the provision of services to its residents, and a multitude of other factors. With this in mind, the project investigators sought to develop an approach that would enable researchers to measure these social and environmental interactions. The concept of well-being proved extremely useful for this purpose. Using the Gulf of Mexico as a regional case study, the research team developed a set of composite indicators to be used for monitoring well-being at the county-level. The indicators selected for the study were: Social Connectedness, Economic Security, Basic Needs, Health, Access to Social Services, Education, Safety, Governance, and Environmental Condition. For each of the 37 sample counties included in the study region, investigators collected and consolidated existing, secondary data representing multiple aspects of objective well-being. To conduct a longitudinal assessment of changing wellbeing and environmental conditions, data were collected for the period of 2000 to 2010. The team focused on the Gulf of Mexico because the development of a baseline of well-being would allow NOAA and other agencies to better understand progress made toward recovery in communities affected by the Deepwater Horizon oil spill. However, the broader purpose of the project was to conceptualize and develop an approach that could be adapted to monitor how coastal communities are doing in relation to a variety of ecosystem disruptions and associated interventions across all coastal regions in the U.S. and its Territories. The method and models developed provide substantial insight into the structure and significance of relationships between community well-being and environmental conditions. Further, this project has laid the groundwork for future investigation, providing a clear path forward for integrated monitoring of our nation’s coasts. The research and monitoring capability described in this document will substantially help counties, local organizations, as well state and federal agencies that are striving to improve all facets of community well-being.

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We investigate solitary excitations in a model of a one-dimensional antiferromagnet including a single-ion anisotropy and a Dzyaloshinsky-Moriya antisymmetric exchange interaction term. We employ the Holstein-Primakoff transformation, the coherent state ansatz and the time variational principle. We obtain two partial differential equations of motion by using the method of multiple scales and applying perturbation theory. By so doing, we show that the motion of the coherent amplitude must satisfy the nonlinear Schrodinger equation. We give the single-soliton solution.

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An investigation into the interactions between thiamine monophosphate (TMP) and anions has resulted in the preparation and X-ray characterization of the compounds (TMP)(Hg2Br5).0.5H(2)O (1) and (TMP)(2)(Hg3I8) (2). In each compound the TMP molecule exists as a monovalent cation in the usual F conformation. The halogenomercurate anions occur in two-dimensional (2-D) network in 1 or one-dimensional (1-D) chain in 2. In both 1 and 2, the structures consist of alternating cationic sheets of the hydrogen-bonded TMP molecules and anionic sheets of the polymeric halogenomercurate anions. The TMP molecule binds to the polymeric anions through the characteristic 'anion bridge I', C(2)-H..X...pyrimidinium (X = Br in 1 and 1 in 2), and electrostatic interactions between electropositive S(1) and halogen atoms. The 'anion bridge II' of the type N(4'1)-H...X...thiazolium (X = phosphate group) plays a role in stabilizing the molecular conformation. The biological implication of the host-guest-like complexation between TMP and polymeric anions is discussed.

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This article develops the Synchronous Matching Adaptive Resonance Theory (SMART) neural model to explain how the brain may coordinate multiple levels of thalamocortical and corticocortical processing to rapidly learn, and stably remember, important information about a changing world. The model clarifies how bottom-up and top-down processes work together to realize this goal, notably how processes of learning, expectation, attention, resonance, and synchrony are coordinated. The model hereby clarifies, for the first time, how the following levels of brain organization coexist to realize cognitive processing properties that regulate fast learning and stable memory of brain representations: single cell properties, such as spiking dynamics, spike-timing-dependent plasticity (STDP), and acetylcholine modulation; detailed laminar thalamic and cortical circuit designs and their interactions; aggregate cell recordings, such as current-source densities and local field potentials; and single cell and large-scale inter-areal oscillations in the gamma and beta frequency domains. In particular, the model predicts how laminar circuits of multiple cortical areas interact with primary and higher-order specific thalamic nuclei and nonspecific thalamic nuclei to carry out attentive visual learning and information processing. The model simulates how synchronization of neuronal spiking occurs within and across brain regions, and triggers STDP. Matches between bottom-up adaptively filtered input patterns and learned top-down expectations cause gamma oscillations that support attention, resonance, and learning. Mismatches inhibit learning while causing beta oscillations during reset and hypothesis testing operations that are initiated in the deeper cortical layers. The generality of learned recognition codes is controlled by a vigilance process mediated by acetylcholine.