413 resultados para MOLECULAR-PARAMETERS
Resumo:
Bone diseases such as rickets and osteoporosis cause significant reduction in bone quantity and quality, which leads to mechanical abnormalities. However, the precise ultrastructural mechanism by which altered bone quality affects mechanical properties is not clearly understood. Here we demonstrate the functional link between altered bone quality (reduced mineralization) and abnormal fibrillar-level mechanics using a novel, real-time synchrotron X-ray nanomechanical imaging method to study a mouse model with rickets due to reduced extrafibrillar mineralization. A previously unreported N-ethyl-N-nitrosourea (ENU) mouse model for hypophosphatemic rickets (Hpr), as a result of missense Trp314Arg mutation of the phosphate regulating gene with homologies to endopeptidase on the X chromosome (Phex) and with features consistent with X-linked hypophosphatemic rickets (XLHR) in man, was investigated using in situ synchrotron small angle X-ray scattering to measure real-time changes in axial periodicity of the nanoscale mineralized fibrils in bone during tensile loading. These determine nanomechanical parameters including fibril elastic modulus and maximum fibril strain. Mineral content was estimated using backscattered electron imaging. A significant reduction of effective fibril modulus and enhancement of maximum fibril strain was found in Hpr mice. Effective fibril modulus and maximum fibril strain in the elastic region increased consistently with age in Hpr and wild-type mice. However, the mean mineral content was ∼21% lower in Hpr mice and was more heterogeneous in its distribution. Our results are consistent with a nanostructural mechanism in which incompletely mineralized fibrils show greater extensibility and lower stiffness, leading to macroscopic outcomes such as greater bone flexibility. Our study demonstrates the value of in situ X-ray nanomechanical imaging in linking the alterations in bone nanostructure to nanoscale mechanical deterioration in a metabolic bone disease. Copyright
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Endoplasmatic reticulum aminopeptidase 1 (ERAP1) is a multifunctional enzyme involved in trimming of peptides to an optimal length for presentation by major histocompatibility complex (MHC) class I molecules. Polymorphisms in ERAP1 have been associated with chronic inflammatory diseases, including ankylosing spondylitis (AS) and psoriasis, and subsequent in vitro enzyme studies suggest distinct catalytic properties of ERAP1 variants. To understand structure-activity relationships of this enzyme we determined crystal structures in open and closed states of human ERAP1, which provide the first snapshots along a catalytic path. ERAP1 is a zinc-metallopeptidase with typical H-E-X-X-H-(X)18-E zinc binding and G-A-M-E-N motifs characteristic for members of the gluzincin protease family. The structures reveal extensive domain movements, including an active site closure as well as three different open conformations, thus providing insights into the catalytic cycle. A K 528R mutant strongly associated with AS in GWAS studies shows significantly altered peptide processing characteristics, which are possibly related to impaired interdomain interactions.
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This article describes a maximum likelihood method for estimating the parameters of the standard square-root stochastic volatility model and a variant of the model that includes jumps in equity prices. The model is fitted to data on the S&P 500 Index and the prices of vanilla options written on the index, for the period 1990 to 2011. The method is able to estimate both the parameters of the physical measure (associated with the index) and the parameters of the risk-neutral measure (associated with the options), including the volatility and jump risk premia. The estimation is implemented using a particle filter whose efficacy is demonstrated under simulation. The computational load of this estimation method, which previously has been prohibitive, is managed by the effective use of parallel computing using graphics processing units (GPUs). The empirical results indicate that the parameters of the models are reliably estimated and consistent with values reported in previous work. In particular, both the volatility risk premium and the jump risk premium are found to be significant.
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We describe a surprising cooperative adsorption process observed by scanning tunneling microscopy (STM) at the liquid−solid interface. The process involves the association of a threefold hydrogen-bonding unit, trimesic acid (TMA), with straight-chain aliphatic alcohols of varying length (from C7 to C30), which coadsorb on highly oriented pyrolytic graphite (HOPG) to form linear patterns. In certain cases, the known TMA “flower pattern” can coexist temporarily with the linear TMA−alcohol patterns, but it eventually disappears. Time-lapsed STM imaging shows that the evolution of the flower pattern is a classical ripening phenomenon. The periodicity of the linear TMA−alcohol patterns can be modulated by choosing alcohols with appropriate chain lengths, and the precise structure of the patterns depends on the parity of the carbon count in the alkyl chain. Interactions that lead to this odd−even effect are analyzed in detail. The molecular components of the patterns are achiral, yet their association by hydrogen bonding leads to the formation of enantiomeric domains on the surface. The interrelation of these domains and the observation of superperiodic structures (moiré patterns) are rationalized by considering interactions with the underlying graphite surface and within the two-dimensional crystal of the adsorbed molecules. Comparison of the observed two-dimensional structures with the three-dimensional crystal structures of TMA−alcohol complexes determined by X-ray crystallography helps reveal the mechanism of molecular association in these two-component systems.
Resumo:
Trimesic acid (TMA) and alcohols were recently shown to self-assemble into a stable, two-component linear pattern at the solution/highly oriented pyrolytic graphite (HOPG) interface. Away from equilibrium, the TMA/alcohol self-assembled molecular network (SAMN) can coexist with pure-TMA networks. Here, we report on some novel characteristics of these non-equilibrium TMA structures, investigated by scanning tunneling microscopy (STM). We observe that both the chicken-wire and flower-structure TMA phases can host 'guest' C60 molecules within their pores, whereas the TMA/alcohol SAMN does not offer any stable adsorption sites for the C60 molecules. The presence of the C60 molecules at the solution/solid interface was found to improve the STM image quality. We have taken advantage of the high-quality imaging conditions to observe unusual TMA bonding geometries at domain boundaries in the TMA/alcohol SAMN. Boundaries between aligned TMA/alcohol domains can give rise to doubled TMA dimer rows in two different configurations, as well as a tripled-TMA row. The boundaries created between non-aligned domains can create geometries that stabilize TMA bonding configurations not observed on surfaces without TMA/alcohol SAMNs, including small regions of the previously predicted 'super flower' TMA bonding geometry and a tertiary structure related to the known TMA phases. These structures are identified as part of a homologic class of TMA bonding motifs, and we explore some of the reasons for the stabilization of these phases in our multicomponent system.
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The formation of ordered arrays of molecules via self-assembly is a rapid, scalable route towards the realization of nanoscale architectures with tailored properties. In recent years, graphene has emerged as an appealing substrate for molecular self-assembly in two dimensions. Here, the first five years of progress in supramolecular organization on graphene are reviewed. The self-assembly process can vary depending on the type of graphene employed: epitaxial graphene, grown in situ on a metal surface, and non-epitaxial graphene, transferred onto an arbitrary substrate, can have different effects on the final structure. On epitaxial graphene, the process is sensitive to the interaction between the graphene and the substrate on which it is grown. In the case of graphene that strongly interacts with its substrate, such as graphene/Ru(0001), the inhomogeneous adsorption landscape of the graphene moiré superlattice provides a unique opportunity for guiding molecular organization, since molecules experience spatially constrained diffusion and adsorption. On weaker-interacting epitaxial graphene films, and on non-epitaxial graphene transferred onto a host substrate, self-assembly leads to films similar to those obtained on graphite surfaces. The efficacy of a graphene layer for facilitating planar adsorption of aromatic molecules has been repeatedly demonstrated, indicating that it can be used to direct molecular adsorption, and therefore carrier transport, in a certain orientation, and suggesting that the use of transferred graphene may allow for predictible molecular self-assembly on a wide range of surfaces.
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Recently, halogen···halogen interactions have been demonstrated to stabilize two-dimensional supramolecular assemblies at the liquid–solid interface. Here we study the effect of changing the halogen, and report on the 2D supramolecular structures obtained by the adsorption of 2,4,6-tris(4-bromophenyl)-1,3,5-triazine (TBPT) and 2,4,6-tris(4-iodophenyl)-1,3,5-triazine (TIPT) on both highly oriented pyrolytic graphite and the (111) facet of a gold single crystal. These molecular systems were investigated by combining room-temperature scanning tunneling microscopy in ambient conditions with density functional theory, and are compared to results reported in the literature for the similar molecules 1,3,5-tri(4-bromophenyl)benzene (TBPB) and 1,3,5-tri(4-iodophenyl)benzene (TIPB). We find that the substrate exerts a much stronger effect than the nature of the halogen atoms in the molecular building blocks. Our results indicate that the triazine core, which renders TBPT and TIPT stiff and planar, leads to stronger adsorption energies and hence structures that are different from those found for TBPB and TIPB. On the reconstructed Au(111) surface we find that the TBPT network is sensitive to the fcc- and hcp-stacked regions, indicating a significant substrate effect. This makes TBPT the first molecule reported to form a continuous monolayer at room temperature in which molecular packing is altered on the differently reconstructed regions of the Au(111) surface. Solvent-dependent polymorphs with solvent coadsorption were observed for TBPT on HOPG. This is the first example of a multicomponent self-assembled molecular networks involving the rare cyclic, hydrogen-bonded hexamer of carboxylic groups, R66(24) synthon.
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Biotechnology has the potential to improve sugar cane, one of the world's major crops for food and fuel. This research describes the detailed characterisation of introns and their potential for enhancing transgene expression in sugar cane via intron-mediated enhancement (IME). IME is a phenomenon whereby an intron enhances gene expression from a promoter. Current knowledge on the mechanism of IME or its potential for enhancing gene expression in sugar cane is limited. A better understanding of the factors responsible for IME will help develop new molecular tools that facilitate high levels of constitutive and tissue-specific gene expression in this crop.
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There is an urgent need to develop crops that can withstand future climates. Results from this thesis demonstrated that a native Australian resurrection grass exhibits structural, physiological and metabolic strategies to tolerate drying. These strategies may be utilized for the generation of stress tolerant crops.
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The extended recruitment season for short-lived species such as prawns biases the estimation of growth parameters from length-frequency data when conventional methods are used. We propose a simple method for overcoming this bias given a time series of length-frequency data. The difficulties arising from extended recruitment are eliminated by predicting the growth of the succeeding samples and the length increments of the recruits in previous samples. This method requires that some maximum size at recruitment can be specified. The advantages of this multiple length-frequency method are: it is simple to use; it requires only three parameters; no specific distributions need to be assumed; and the actual seasonal recruitment pattern does not have to be specified. We illustrate the new method with length-frequency data on the tiger prawn Penaeus esculentus from the north-western Gulf of Carpentaria, Australia.
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Prostate cancer is a leading contributor to male cancer-related deaths worldwide. Kallikrein-related peptidases (KLKs) are serine proteases that exhibit deregulated expression in prostate cancer, with KLK3, or prostate specific antigen (PSA), being the widely-employed clinical biomarker for prostate cancer. Other KLKs, such as KLK2, show promise as prostate cancer biomarkers and, additionally, their altered expression has been utilised for the design of KLK-targeted therapies. There is also a large body of in vitro and in vivo evidence supporting their role in cancer-related processes. Here, we review the literature on studies to date investigating the potential of other KLKs, in addition to PSA, as biomarkers and in therapeutic options, as well as their current known functional roles in cancer progression. Increased knowledge of these KLK-mediated functions, including degradation of the extracellular matrix, local invasion, cancer cell proliferation, interactions with fibroblasts, angiogenesis, migration, bone metastasis and tumour growth in vivo, may help define new roles as prognostic biomarkers and novel therapeutic targets for this cancer.
Resumo:
This article develops a method for analysis of growth data with multiple recaptures when the initial ages for all individuals are unknown. The existing approaches either impute the initial ages or model them as random effects. Assumptions about the initial age are not verifiable because all the initial ages are unknown. We present an alternative approach that treats all the lengths including the length at first capture as correlated repeated measures for each individual. Optimal estimating equations are developed using the generalized estimating equations approach that only requires the first two moment assumptions. Explicit expressions for estimation of both mean growth parameters and variance components are given to minimize the computational complexity. Simulation studies indicate that the proposed method works well. Two real data sets are analyzed for illustration, one from whelks (Dicathais aegaota) and the other from southern rock lobster (Jasus edwardsii) in South Australia.
Resumo:
James (1991, Biometrics 47, 1519-1530) constructed unbiased estimating functions for estimating the two parameters in the von Bertalanffy growth curve from tag-recapture data. This paper provides unbiased estimating functions for a class of growth models that incorporate stochastic components and explanatory variables. a simulation study using seasonal growth models indicates that the proposed method works well while the least-squares methods that are commonly used in the literature may produce substantially biased estimates. The proposed model and method are also applied to real data from tagged rack lobsters to assess the possible seasonal effect on growth.
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We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock when there is individual variability in the von Bertalanffy growth parameter L-infinity and investigate the possible bias in the estimates when the individual variability is ignored. Three methods are examined: (i) the regression method based on the Beverton and Holt's (1956, Rapp. P.V. Reun. Cons. Int. Explor. Mer, 140: 67-83) equation; (ii) the moment method of Powell (1979, Rapp. PV. Reun. Int. Explor. Mer, 175: 167-169); and (iii) a generalization of Powell's method that estimates the individual variability to be incorporated into the estimation. It is found that the biases in the estimates from the existing methods are, in general, substantial, even when individual variability in growth is small and recruitment is uniform, and the generalized method performs better in terms of bias but is subject to a larger variation. There is a need to develop robust and flexible methods to deal with individual variability in the analysis of length-frequency data.