980 resultados para fiber matrix


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The repair of bone defects that result from periodontal diseases remains a clinical challenge for periodontal therapy. β-tricalcium phosphate (β-TCP) ceramics are biodegradable inorganic bone substitutes with inorganic components that are similar to those of bone. Demineralized bone matrix (DBM) is an acid-extracted organic matrix derived from bone sources that consists of the collagen and matrix proteins of bone. A few studies have documented the effects of DBM on the proliferation and osteogenic differentiation of human periodontal ligament cells (hPDLCs). The aim of the present study was to investigate the effects of inorganic and organic elements of bone on the proliferation and osteogenic differentiation of hPDLCs using three-dimensional porous β-TCP ceramics and DBM with or without osteogenic inducers. Primary hPDLCs were isolated from human periodontal ligaments. The proliferation of the hPDLCs on the scaffolds in the growth culture medium was examined using a Cell‑Counting kit‑8 (CCK-8) and scanning electron microscopy (SEM). Alkaline phosphatase (ALP) activity and the osteogenic differentiation of the hPDLCs cultured on the β-TCP ceramics and DBM were examined in both the growth culture medium and osteogenic culture medium. Specific osteogenic differentiation markers were examined using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). SEM images revealed that the cells on the β-TCP were spindle-shaped and much more spread out compared with the cells on the DBM surfaces. There were no significant differences observed in cell proliferation between the β-TCP ceramics and the DBM scaffolds. Compared with the cells that were cultured on β-TCP ceramics, the ALP activity, as well as the Runx2 and osteocalcin (OCN) mRNA levels in the hPDLCs cultured on DBM were significantly enhanced both in the growth culture medium and the osteogenic culture medium. The organic elements of bone may exhibit greater osteogenic differentiation effects on hPDLCs than the inorganic elements.

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Feminist research on girlhood has drawn extensively on Butler's conceptual work in order to theorise the normative forces of heterosexuality in the everyday construction of gender. This chapter explores girlhood by drawing on memories and artwork generated in a collective biography workshop held in Australian on the topic of girlhood and sexuality. We are interested in thinking through Butler's notion of the heterosexual matrix. Following Renold and Ringrose (2008) we do so with the help of Deleuze and Guattari, who invite us to think about difference as differenciation or continuous becoming, where difference is an evolutionary multiplicity.

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The Haddon Matrix was developed in the 1960s road safety arena, and has since been used in many public health settings. The literature and two specific case studies are reviewed to describe the background to the Haddon Matrix, identify how it has been critiqued and developed over time and practical applications in the work-related road safety context. Haddon’s original focus on the road, vehicle and driver has been extended and applied to include organisational safety culture, journey management and wider issues in society that affect occupational drivers and the communities in which they work. The paper shows that the Haddon Matrix has been applied in many projects and contexts. Practical work-related road safety applications include providing a comprehensive systems-based safety management framework to inform strategy. It has also been used to structure the review or gap analysis of current programs and processes, identify and develop prevention measures and as a tool for effective post-event investigations.

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This study investigated interactions of protein-cleaving enzymes (or proteases) that promote prostate cancer progression. It provides the first evidence of a novel regulatory network of protease activity at the surface of cells. The proteases kallikrein-related peptidases 4 and 14, and matrix metalloproteinases 3 and 9 are cleaved at the cell surface by the cell surface proteases hepsin and TMPRSS2. These cleavage events potentially regulate activation of downstream targets of kallikrein 4 and 14 such as cell surface signalling via the protease-activated receptors (PARs) and cell growth-promoting factors such as hepatocyte-growth factor.

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Welcome to the Evaluation of course matrix. This matrix is designed for highly qualified discipline experts to evaluate their course, major or unit in a systemic manner. The primary purpose of the Evaluation of course matrix is to provide a tool that a group of academic staff at universities can collaboratively review the assessment within a course, major or unit annually. The annual review will result in you being ready for an external curricula review at any point in time. This tool is designed for use in a workshop format with one, two or more academic staff, and will lead to an action plan for implementation. I hope you find this tool useful in your assessment review.

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Traditional sensitivity and elasticity analyses of matrix population models have been used to inform management decisions, but they ignore the economic costs of manipulating vital rates. For example, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously. These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency. ©2006 Society for Conservation Biology.

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By taking the advantage of the excellent mechanical properties and high specific surface area of graphene oxide (GO) sheets, we develop a simple and effective strategy to improve the interlaminar mechanical properties of carbon fiber reinforced plastic (CFRP) laminates. With the incorporation of graphene oxide reinforced epoxy interleaf into the interface of CFRP laminates, the Mode-I fracture toughness and resistance were greatly increased. The experimental results of double cantilever beam (DCB) tests demonstrated that, with 2 g/m2 addition of GO, the Mode-I fracture toughness and resistance of the specimen increase by 170.8% and 108.0%, respectively, compared to those of the plain specimen. The improvement mechanisms were investigated by the observation of fracture surface with scanning electron microscopies. Moreover, finite element analyses were performed based on the cohesive zone model to verify the experimental fracture toughness and to predict the interfacial tensile strength of CFRP laminates.

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The efficient computation of matrix function vector products has become an important area of research in recent times, driven in particular by two important applications: the numerical solution of fractional partial differential equations and the integration of large systems of ordinary differential equations. In this work we consider a problem that combines these two applications, in the form of a numerical solution algorithm for fractional reaction diffusion equations that after spatial discretisation, is advanced in time using the exponential Euler method. We focus on the efficient implementation of the algorithm on Graphics Processing Units (GPU), as we wish to make use of the increased computational power available with this hardware. We compute the matrix function vector products using the contour integration method in [N. Hale, N. Higham, and L. Trefethen. Computing Aα, log(A), and related matrix functions by contour integrals. SIAM J. Numer. Anal., 46(5):2505–2523, 2008]. Multiple levels of preconditioning are applied to reduce the GPU memory footprint and to further accelerate convergence. We also derive an error bound for the convergence of the contour integral method that allows us to pre-determine the appropriate number of quadrature points. Results are presented that demonstrate the effectiveness of the method for large two-dimensional problems, showing a speedup of more than an order of magnitude compared to a CPU-only implementation.

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The matrix of volcaniclastic kimberlite (VK) from the Muskox pipe (Northern Slave Province, Nunavut, Canada) is interpreted to represent an overprint of an original clastic matrix. Muskox VK is subdivided into three different matrix mineral assemblages that reflect differences in the proportions of original primary matrix constituents, temperature of formation and nature of the altering fluids. Using whole rock X-ray fluorescence (XRF), whole rock X-ray diffraction (XRD), microprobe analyses, back-scatter electron (BSE) imaging, petrography and core logging, we find that most matrix minerals (serpentine, phlogopite, chlorite, saponite, monticellite, Fe-Ti oxides and calcite) lack either primary igneous or primary clastic textures. The mineralogy and textures are most consistent with formation through alteration overprinting of an original clastic matrix that form by retrograde reactions as the deposit cools, or, in the case of calcite, by precipitation from Ca-bearing fluids into a secondary porosity. The first mineral assemblage consists largely of serpentine, phlogopite, calcite, Fe-Ti oxides and monticellite and occurs in VK with relatively fresh framework clasts. Alteration reactions, driven by deuteric fluids derived from the juvenile constituents, promote the crystallisation of minerals that indicate relatively high temperatures of formation (> 400 °C). Lower-temperature minerals are not present because permeability was occluded before the deposit cooled to low temperatures, thus shielding the facies from further interaction with fluids. The other two matrix mineral assemblages consist largely of serpentine, phlogopite, calcite, +/- diopside, and +/- chlorite. They form in VK that contains more country rock, which may have caused the deposit to be cooler upon emplacement. Most framework components are completely altered, suggesting that larger volumes of fluids drove the alteration reactions. These fluids were likely of meteoric provenance and became heated by the volcaniclastic debris when they percolated into the VK infill. Most alteration reactions ceased at temperatures > 200 °C, as indicated by the absence or paucity of lower-temperature phases in most samples, such as saponite. Recognition that Muskox VK contains an original clastic matrix is a necessary first step for evaluating the textural configuration, which is important for reconstructing the physical processes responsible for the formation of the deposit.

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We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject's DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.

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We developed an analysis pipeline enabling population studies of HARDI data, and applied it to map genetic influences on fiber architecture in 90 twin subjects. We applied tensor-driven 3D fluid registration to HARDI, resampling the spherical fiber orientation distribution functions (ODFs) in appropriate Riemannian manifolds, after ODF regularization and sharpening. Fitting structural equation models (SEM) from quantitative genetics, we evaluated genetic influences on the Jensen-Shannon divergence (JSD), a novel measure of fiber spatial coherence, and on the generalized fiber anisotropy (GFA) a measure of fiber integrity. With random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects' intelligence quotient (IQ). Fiber complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied spatially. Our methods show promise for discovering genes affecting fiber connectivity in the brain.

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We report the first 3D maps of genetic effects on brain fiber complexity. We analyzed HARDI brain imaging data from 90 young adult twins using an information-theoretic measure, the Jensen-Shannon divergence (JSD), to gauge the regional complexity of the white matter fiber orientation distribution functions (ODF). HARDI data were fluidly registered using Karcher means and ODF square-roots for interpol ation; each subject's JSD map was computed from the spatial coherence of the ODFs in each voxel's neighborhood. We evaluated the genetic influences on generalized fiber anisotropy (GFA) and complexity (JSD) using structural equation models (SEM). At each voxel, genetic and environmental components of data variation were estimated, and their goodness of fit tested by permutation. Color-coded maps revealed that the optimal models varied for different brain regions. Fiber complexity was predominantly under genetic control, and was higher in more highly anisotropic regions. These methods show promise for discovering factors affecting fiber connectivity in the brain.

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Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scale-free topology, that influences white matter integrity over multiple brain regions.