Relationship of glycosaminoglycan and matrix changes to vascular smooth cell phenotype modulation in rabbit arteries after acute injury

Purpose: The phenotype of vascular smooth muscle cells (SMCs) is altered in several arterial pathologies, including the neointima formed after acute arterial injury. This study examined the time course of this phenotypic change in relation to changes in the amount and distribution of matrix glycosaminoglycans. Methods: The immunochemical staining of heparan sulphates (HS) and chondroitin sulphates (CS) in the extracellular matrix of the arterial wall was examined at early points after balloon catheter injury of the rabbit carotid artery. SMC phenotype was assessed by means of ultrastructural morphometry of the cytoplasmic volume fraction of myofilaments. The proportions of cell and matrix components in the media were analyzed with similar morphometric techniques. Results: HS and CS were shown in close association with SMCs of the uninjured arterial media as well as being more widespread within the matrix. Within 6 hours after arterial injury, there was loss of the regular pericellular distribution of both HS and CS, which was associated with a significant expansion in the extracellular space. This preceded the change in ultrastructural phenotype of the SMCs. The glycosaminoglycan loss was most exaggerated at 4 days, after which time the HS and CS reappeared around the medial SMCs. SMCs of the recovering media were able to rapidly replace their glycosaminoglycans, whereas SMCs of the developing neointima failed to produce HS as readily as they produced CS. Conclusions: These studies indicate that changes in glycosaminoglycans of the extracellular matrix precede changes in SMC phenotype after acute arterial injury. In the recovering arterial media, SMCs replace their matrix glycosaminoglycans rapidly, whereas the newly established neointima fails to produce similar amounts of heparan sulphates.

Fitting a mixture model to three-mode three-way data with missing information

When the data consist of certain attributes measured on the same set of items in different situations, they would be described as a three-mode three-way array. A mixture likelihood approach can be implemented to cluster the items (i.e., one of the modes) on the basis of both of the other modes simultaneously (i.e,, the attributes measured in different situations). In this paper, it is shown that this approach can be extended to handle three-mode three-way arrays where some of the data values are missing at random in the sense of Little and Rubin (1987). The methodology is illustrated by clustering the genotypes in a three-way soybean data set where various attributes were measured on genotypes grown in several environments.

Noise-free scattering of the quantized electromagnetic field from a dispersive linear dielectric

We study the scattering of the quantized electromagnetic field from a linear, dispersive dielectric using the scattering formalism for quantum fields. The medium is modeled as a collection of harmonic oscillators with a number of distinct resonance frequencies. This model corresponds to the Sellmeir expansion, which is widely used to describe experimental data for real dispersive media. The integral equation for the interpolating field in terms of the in field is solved and the solution used to find the out field. The relation between the ill and out creation and annihilation operators is found that allows one to calculate the S matrix for this system. In this model, we find that there are absorption bands, but the input-output relations are completely unitary. No additional quantum-noise terms are required.

Lanczos subspace filter diagonalization: Homogeneous recursive filtering and a low-storage method for the calculation of matrix elements

We develop a new iterative filter diagonalization (FD) scheme based on Lanczos subspaces and demonstrate its application to the calculation of bound-state and resonance eigenvalues. The new scheme combines the Lanczos three-term vector recursion for the generation of a tridiagonal representation of the Hamiltonian with a three-term scalar recursion to generate filtered states within the Lanczos representation. Eigenstates in the energy windows of interest can then be obtained by solving a small generalized eigenvalue problem in the subspace spanned by the filtered states. The scalar filtering recursion is based on the homogeneous eigenvalue equation of the tridiagonal representation of the Hamiltonian, and is simpler and more efficient than our previous quasi-minimum-residual filter diagonalization (QMRFD) scheme (H. G. Yu and S. C. Smith, Chem. Phys. Lett., 1998, 283, 69), which was based on solving for the action of the Green operator via an inhomogeneous equation. A low-storage method for the construction of Hamiltonian and overlap matrix elements in the filtered-basis representation is devised, in which contributions to the matrix elements are computed simultaneously as the recursion proceeds, allowing coefficients of the filtered states to be discarded once their contribution has been evaluated. Application to the HO2 system shows that the new scheme is highly efficient and can generate eigenvalues with the same numerical accuracy as the basic Lanczos algorithm.

Exploratory spatial data analysis techniques for examining urban crime

Regional planners, policy makers and policing agencies all recognize the importance of better understanding the dynamics of crime. Theoretical and application-oriented approaches which provide insights into why and where crimes take place are much sought after. Geographic information systems and spatial analysis techniques, in particular, are proving to be essential or studying criminal activity. However, the capabilities of these quantitative methods continue to evolve. This paper explores the use of geographic information systems and spatial analysis approaches for examining crime occurrence in Brisbane, Australia. The analysis highlights novel capabilities for the analysis of crime in urban regions.

Probabilistic modelling of CO2 corrosion laboratory data using neural networks

The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.

Characterisation of templated xerogels for molecular sieve application

This paper presents the results of the characterisation of templated silica xerogels as precursor material for molecular sieve silica membranes for gas separation. The template agent integrated in the xerogel matrix is a methyl ligand covalently bended to the siloxane network in the form of methyltriethoxysilane (MTES). Several surface and microstructural characterisation techniques such as TGA, FTIR, NMR, and nitrogen adsorption have been employed to obtain information on the reaction mechanisms involved in the sol-gel processing of such molecular sieves. The characterisation results show the effects of processing parameters such as heat treatment temperature, and the concentration of the covalently bonded template on the development of the pore structure. It was found that calcination temperature significantly enhanced the condensation reactions thus resulted in more Si-O-Si groups being formed. This was also confirmed with the data of FTIR characterisation showing enhanced silicon bands at higher heat treatment temperatures. As a result of the promoted densification and shrinkable pore network the micropore volume also reduced with increasing methyl ligand molar ratio. However, the mean pore diameter does not change significantly with calcination temperature. While the contribution of the templates towards controlling pore size is less precise, increasing the methyl ligand molar ratio results in the broadening of the pore size distribution and lower pore volume. Higher template concentration induces the collapse of the xerogel matrix due to capillary stress promoting dense xerogels with low pore volume (C) 2001 Elsevier Science B.V. All rights reserved.

Exploring through cover - the integrated interpretation of high resolution aeromagnetic, airborne electromagnetic and ground gravity data from the Grant's Patch area, Eastern Goldfields Province, Archaean Yigarn Craton Part B; Gravity inversion as a

The cost and risk associated with mineral exploration in Australia increases significantly as companies move into deeper regolith-covered terrain. The ability to map the bedrock and the depth of weathering within an area has the potential to decrease this risk and increase the effectiveness of exploration programs. This paper is the second in a trilogy concerning the Grant's Patch area of the Eastern Goldfields. The recent development of the VPmg potential field inversion program in conjunction with the acquisition of high-resolution gravity data over an area with extensive drilling provided an opportunity to evaluate three-dimensional gravity inversion as a bedrock and regolith mapping tool. An apparent density model of the study area was constructed, with the ground represented as adjoining 200 m by 200 m vertical rectangular prisms. During inversion VPmg incrementally adjusted the density of each prism until the free-air gravity response of the model replicated the observed data. For the Grant's Patch study area, this image of the apparent density values proved easier to interpret than the Bouguer gravity image. A regolith layer was introduced into the model and realistic fresh-rock densities assigned to each basement prism according to its interpreted lithology. With the basement and regolith densities fixed, the VPmg inversion algorithm adjusted the depth to fresh basement until the misfit between the calculated and observed gravity response was minimised. The resulting geometry of the bedrock/regolith contact largely replicated the base of weathering indicated by drilling with predicted depth of weathering values from gravity inversion typically within 15% of those logged during RAB and RC drilling.

Investigating technical and scale efficiencies of Australian universities through data envelopment analysis

Performance indicators in the public sector have often been criticised for being inadequate and not conducive to analysing efficiency. The main objective of this study is to use data envelopment analysis (DEA) to examine the relative efficiency of Australian universities. Three performance models are developed, namely, overall performance, performance on delivery of educational services, and performance on fee-paying enrolments. The findings based on 1995 data show that the university sector was performing well on technical and scale efficiency but there was room for improving performance on fee-paying enrolments. There were also small slacks in input utilisation. More universities were operating at decreasing returns to scale, indicating a potential to downsize. DEA helps in identifying the reference sets for inefficient institutions and objectively determines productivity improvements. As such, it can be a valuable benchmarking tool for educational administrators and assist in more efficient allocation of scarce resources. In the absence of market mechanisms to price educational outputs, which renders traditional production or cost functions inappropriate, universities are particularly obliged to seek alternative efficiency analysis methods such as DEA.

Proteomic analysis reveals that 14-3-3 sigma in downregulated in human breast cancer cells

The class of molecular chaperones known as 14-3-3 is involved in the control of cellular growth by virtue of its apparent regulation of various signaling pathways, including the Raf/mitogen-activated protein kinase pathway. In breast cancer cells, the sigma form of 14-3-3 has been shown to interact with cyclin-dependent kinases and to control the rate of entry into mitosis. To test for a direct role for 14-3-3 in breast epithelial cell neoplasia, me have quantitated 14-3-3 protein levels using a proteomic approach based on two-dimensional electrophoresis and matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF). We show here that 14-3-3 sigma protein is strongly down-regulated in the prototypic breast cancer cell lines MCF-7 and MDA-MB-231 and in primary breast carcinomas as compared with normal breast epithelial cells. In contrast, levels of the alpha, beta, delta, or zeta isoforms of 14-3-3 mere the same in both normal and transformed cells. The data support the idea that 14-3-3 sigma is involved in the neoplastic transition of breast epithelial cells by virtue of its role as a tumor suppressor; as such, it may constitute a robust marker with clinical efficacy for this pathology.

Freeform fabrication of aluminum metal-matrix composites

A series of metal-matrix composites were formed by extrusion freeform, fabrication of a sinterable aluminum alloy in combination with silicon carbide particles and whiskers, carbon fibers, alumina particles, and hollow flyash cenospheres. Silicon carbide particles were most successful in that the composites retained high density with up to 20 vol% of reinforcement and the strength approximately doubles over the strength of the metal matrix alone. Comparison with simple models suggests that this unexpectedly high degree of reinforcement can be attributed to the concentration of small silicon carbide particles around the larger metal powder. This fabrication method also allows composites to be formed with hollow spheres that cannot be formed by other powder or melt methods.