187 resultados para Adjacency matrices


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Hindered amine light stabilisers (HALS) are the most effective antioxidants currently available for polymer systems in post-production, in-service applications, yet the mechanism of their action is still not fully understood. Structural characterisation of HALS in polymer matrices, particularly the identification of structural modifications brought about by oxidative conditions, is critical to aid mechanistic understanding of the prophylactic effects of these molecules. In this work, electrospray ionisation tandem mass spectrometry (ESI-MS/MS) was applied to the analysis of a suite of commercially available 2,2,6,6-tetramethylpiperidine-based HALS. Fragmentation mechanisms for the \[M + H](+) ions are proposed, which provide a rationale for the product ions observed in the MS/MS and MS(3) mass spectra of N-H, N-CH(3), N-C(O)CH(3) and N-OR containing HALS (where R is an alkyl substituent). A common product ion at m/z 123 was identified for the group of antioxidants containing N-H, N-CH3 or N-C(0)CH3 functionality, and this product ion was employed in precursor ion scans on a triple quadrupole mass spectrometer to identify the HALS species present in a crude extract from of a polyester-based coil coating. Using MS/MS, two degradation products were unambiguously identified. This technique provides a simple and selective approach to monitoring HALS structures within complex matrices. Copyright (C) 2010 John Wiley & Sons, Ltd.

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Recent developments in mass spectrometry and chromatography provide new possibilities for the identification and in some instances quantification of a wide range of lipids in complex matrices. These advances in analytical technologies have provided a tantalizing glimpse of the true structural diversity of lipids in nature and have reinvigorated interest in the role of lipids in biology. While technological advances have been impressive, difficulties in the ready identification of sites of unsaturation (i.e., double bond position) within these molecules presents a significant impediment to understanding lipid biochemistry. This is of particular importance given the growing body of literature suggesting that the presence of naturally occurring lipid double bond isomers can have a significant influence, both positive and negative, on the development of pathologies such as cancer, cardiovascular disease and type 2 diabetes. This article provides a critical review of the Current suite of analytical approaches to the challenge of identification of the position of carbon-carbon double bonds in intact lipids. Crown Copyright (C) 2009 Published by Elsevier B.V. All rights reserved.

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Background/Aims Biological and synthetic scaffolds play important roles in tissue engineering and are being developed towards human clinical applications. Based on previous work from our laboratory, we propose that extracellular matrices from skeletal muscle could be developed for adipose tissue engineering. Methods Extracellular matrices (Myogels) extracted from skeletal muscle of various species were assessed using biochemical assays including ELISA and Western blotting. Biofunctionality was assessed using an in vitro differentiation assay and a tissue engineering construct model in the rat. Results Myogels were successfully extracted from mice, rats, pigs and humans. Myogels contained significant levels of laminin α4- and α2-subunits and collagen I compared to Matrigel™, which contains laminin 1 (α1β1γ1) and collagen IV. Levels of growth factors such as fibroblast growth factor 2 were significantly higher than Matrigel, vascular endothelial growth factor-A levels were significantly lower and all other growth factors were comparable. Myogels reproducibly stimulated adipogenic differentiation of preadipocytes in vitro and the growth of adipose tissue in the rat. Conclusions We found Myogel induces adipocyte differentiation in vitroand shows strong adipogenic potential in vivo, inducing the growth of well-vascularised adipose tissue. Myogel offers an alternative for current support scaffolds in adipose tissue engineering, allowing the scaling up of animal models towards clinical adipose tissue engineering applications.

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Background Despite a revived interest in fat grafting procedures, clinicians still fail to demonstrate clearly the in vivo behavior of fat grafts as a dynamic tissue substitute. However, the basic principles in cellular biology teach us that cells can survive and develop, provided that a structural matrix exists that directs their behavior. The purpose of this in vitro study was to analyze that behavior of crude fat grafts, cultured on a three-dimensional laminin-rich matrix. Methods Nonprocessed, human fat biopsy specimens (approximately 1 mm) were inoculated on Matrigel-coated wells to which culture medium was added. The control group consisted of fat biopsy specimens embedded in medium alone. The cellular proliferation pattern was followed over 6 weeks. Additional cultures of primary generated cellular spheroids were performed and eventually subjected to adipogenic differentiation media. Results A progressive outgrowth of fibroblast-like cells from the core fat biopsy specimen was observed in both groups. Within the Matrigel group, an interconnecting three-dimensional network of spindle-shaped cells was established. This new cell colony reproduced spheroids that functioned again as solitary sources of cellular proliferation. Addition of differentiation media resulted in lipid droplet deposition in the majority of generated cells, indicating the initial steps of adipogenic differentiation. Conclusions The authors noticed that crude, nonprocessed fat biopsy specimens do have considerable potential for future tissue engineering-based applications, provided that the basic principles of developmental, cellular biology are respected. Spontaneous in vitro expansion of the stromal cells present in fat grafts within autologous and injectable matrices could create "off-the-shelf" therapies for reconstructive procedures.

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In this paper, we present an approach for image-based surface classification using multi-class Support Vector Machine (SVM). Classifying surfaces in aerial images is an important step towards an increased aircraft autonomy in emergency landing situations. We design a one-vs-all SVM classifier and conduct experiments on five data sets. Results demonstrate consistent overall performance figures over 88% and approximately 8% more accurate to those published on multi-class SVM on the KTH TIPS data set. We also show per-class performance values by using normalised confusion matrices. Our approach is designed to be executed online using a minimum set of feature attributes representing a feasible and ready-to-deploy system for onboard execution.

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An in vivo murine vascularized chamber model has been shown to generate spontaneous angiogenesis and new tissue formation. This experiment aimed to assess the effects of common biological scaffolds on tissue growth in this model. Either laminin-1, type I collagen, fibrin glue, hyaluronan, or sea sponge was inserted into silicone chambers containing the epigastric artery and vein, one end was sealed with adipose tissue and the other with bone wax, then incubated subcutaneously. After 2, 4, or 6 weeks, tissue from chambers containing collagen I, fibrin glue, hyaluronan, or no added scaffold (control) had small amounts of vascularized connective tissue. Chambers containing sea sponge had moderate connective tissue growth together with a mild "foreign body" inflammatory response. Chambers containing laminin-1, at a concentration 10-fold lower than its concentration in Matrigel™, resulted in a moderate adipogenic response. In summary, (1) biological hydrogels are resorbed and gradually replaced by vascularized connective tissue; (2) sponge-like matrices with large pores support connective tissue growth within the pores and become encapsulated with granulation tissue; (3) laminin-containing scaffolds facilitate adipogenesis. It is concluded that the nature and chemical composition of the scaffold exerts a significant influence on the amount and type of tissue generated in this in vivo chamber model.

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Background: Expression of matrix metalloproteinase-2 (MMP-2), the 72-kd type IV collagenase/gelatinase, by cancer cells has been implicated in metastasis through cancer cell invasion of basement membranes mediated by degradation of collagen IV. However, the abundance of this latent proenzyme in normal tissues and fluids suggests that MMP-2 proenzyme utilization is limited by its physiological activation rather than expression alone. We previously reported activation of this proenzyme by normal and malignant fibroblastoid cells cultured on collagen I (vitrogen) gels. Purpose: Our purposes in this study were 1) to determine whether MMP-2 activation is restricted to the more invasive human breast cancer cell lines and 2) to localize the activating mechanism. Methods: Zymography was used to monitor MMP-2 activation through detection of latent MMP-2 (72 kd) and mature species of smaller molecular weight (59 or 62 kd). Human breast cancer cell lines cultured on plastic, vitrogen, and other matrices were thus screened for MMP- 2 activation. Collagen I-cultured cells were exposed to cycloheximide, a protein synthesis inhibitor, or to protease inhibitors to determine the nature of the MMP-2-activating mechanism. Triton X-114 (TX-114) detergent extracts from cells cultured on collagen I or plastic were incubated with latent MMP-2 and analyzed by zymography to localize the MMP-2 activator. Results: MMP-2 activation was only induced by collagen I culture in the more aggressive, highly invasive estrogen receptor-negative, vimentin-positive human breast cancer cell lines (Hs578T, MDA-MB-436, BT549, MDA-MB-231, MDA- MB-435, MCF-7(ADR)) and was independent of MMP-2 production. MMP-2 activation was detected in cells cultured on collagen I gels but not in those cultured on gelatin gels, Matrigel, or thin layers of collagen I or IV, gelatin, or fibronectin. Collagen-induced activation was specific for the enzyme species MMP-2, since MMP-9, the 92-kd type IV collagenase/gelatinase, was not activatable under similar conditions. MMP-2 activation was inhibited by cycloheximide and was sensitive to a metalloproteinase inhibitor but not to aspartyl, serine, or cysteinyl protease inhibitors. MMP-2 activation was detected in the hydrophobic, plasma membrane-enriched, TX-114 extracts from invasive collagen I-cultured cells. Conclusion: Collagen I-induced MMP-2 activation is restricted to highly invasive estrogen receptor-negative, vimentin-positive human breast cancer cell lines, is independent of MMP-2 production, and is associated with metastatic potential. Our findings are consistent with plasma membrane localization of the activator. Implications: The MMP-2 activation mechanism may represent a new target for diagnosis, prognosis, and treatment of human breast cancer.

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Invasion of extracellular matrices is crucial to a number of physiological and pathophysiological states, including tumor cell metastasis, arthritis, embryo implantation, wound healing, and early development. To isolate invasion from the additional complexities of these scenarios a number of in vitro invasion assays have been developed over the years. Early studies employed intact tissues, like denuded amniotic membrane (1) or embryonic chick heart fragments (2), however recently, purified matrix components or complex matrix extracts have been used to provide more uniform and often more rapid analyses (for examples, see the following integrin studies). Of course, the more holistic view of invasion offered in the earlier assays is valuable and cannot be fully reproduced in these more rapid assays, but advantages of reproducibility among replicates, ease of preparation and analysis, and overall high throughput favor the newer assays. In this chapter, we will focus on providing detailed protocols for Matrigel-based assays (Matrigel=reconstituted basement membrane; reviewed in ref. (3)). Matrigel is an extract from the transplantable Engelbreth-Holm-Swarm murine sarcoma that deposits a multilammelar basement membrane. Matrigel is available commercially (Becton Dickinson, Bedford, MA), and can be manipulated as a liquid at 4°C into a variety of different formats. Alternatively, cell culture inserts precoated with Matrigel can be purchased for even greater simplicity.

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In a recently described model for tissue engineering, an arteriovenous loop comprising the femoral artery and vein with interposed vein graft is fabricated in the groin of an adult male rat, placed inside a polycarbonate chamber, and incubated subcutaneously. New vascularized granulation tissue will generate on this loop for up to 12 weeks. In the study described in this paper three different extracellular matrices were investigated for their ability to accelerate the amount of tissue generated compared with a no-matrix control. Poly-D,L-lactic-co-glycolic acid (PLGA) produced the maximal weight of new tissue and vascularization and this peaked at two weeks, but regressed by four weeks. Matrigel was next best. It peaked at four weeks but by eight weeks it also had regressed. Fibrin (20 and 80 mg/ml), by contrast, did not integrate with the generating vascularized tissue and produced less weight and volume of tissue than controls without matrix. The limiting factors to growth appear to be the chamber size and the capacity of the neotissue to integrate with the matrix. Once the sides of the chamber are reached or tissue fails to integrate, encapsulation and regression follow. The intrinsic position of the blood supply within the neotissue has many advantages for tissue and organ engineering, such as ability to seed the construct with stem cells and microsurgically transfer new tissue to another site within the individual. In conclusion, this study has found that PLGA and Matrigel are the best matrices for the rapid growth of new vascularized tissue suitable for replantation or transplantation.

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We initially described a rat chamber model with an inserted arteriovenous pedicle which spontaneously generates 3-dimensional vascularized connective tissue (Tanaka Y et al., Br J Plast Surg 2000; 53: 51-7). More recently we have developed a murine chamber model containing reconstituted basement membrane (Matrigel®) and FGF-2 that generates vascularized adipose tissue in vivo (Cronin K et al., Plast Reconstr Surg 2004; in press). We have extended this work to assess the cellular and matrix requirements for the Matrigel®- induced neo-adipogenesis. We found that chambers sealed to host fat were unable to grow new adipose tissue. In these chambers the Matrigel® became vascularized with maximal outgrowth of vessels extending to the periphery at 6 weeks. A small amount of adipose tissue was found adjacent to the vessels, most likely arising from periadventitial adipose tissue. In contrast, chambers open to interaction with endogenous adipose tissue showed abundant new fat, and partial exposure to adjacent adipose tissue clearly showed neo-adipogenesis only in this area. Addition of small amounts of free fat to the closed chamber containing Matrigel® was able to induce neo-adipogenesis. Addition of small pieces of human fat also caused neo-adipogenesis in immunocompromised (SCID) mice. Also, we found Matrigel® to induce adipogenesis of Lac-Z-tagged (Rosa-26) murine bone marrow-derived mesenchymal stem cells, and cells similar to these have been isolated from human adipose tissue. Given that Matrigel® is a mouse product and cannot be used in humans, we have started investigating alternative matrix scaffolds for adipogenesis such as the PDA-approved PLGA, collagen and purified components derived from Matrigel®, such as laminin-1. The optimal conditions for adipogenesis with these matrices are still being elucidated. In conclusion, we have demonstrated that a precursor cell source inside the chamber is essential for the generation of vascularized adipose tissue in vivo. This technique offers unique potential for the reconstruction of soft tissue defects and may enable the generation of site-specific tissue using the correct microenvironment.

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As a sequel to a paper that dealt with the analysis of two-way quantitative data in large germplasm collections, this paper presents analytical methods appropriate for two-way data matrices consisting of mixed data types, namely, ordered multicategory and quantitative data types. While various pattern analysis techniques have been identified as suitable for analysis of the mixed data types which occur in germplasm collections, the clustering and ordination methods used often can not deal explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions) with incomplete information. However, it is shown that the ordination technique of principal component analysis and the mixture maximum likelihood method of clustering can be employed to achieve such analyses. Germplasm evaluation data for 11436 accessions of groundnut (Arachis hypogaea L.) from the International Research Institute of the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the post-rainy season and five ordered multicategory descriptors were used. Pattern analysis results generally indicated that the accessions could be distinguished into four regions along the continuum of growth habit (or plant erectness). Interpretation of accession membership in these regions was found to be consistent with taxonomic information, such as subspecies. Each growth habit region contained accessions from three of the most common groundnut botanical varieties. This implies that within each of the habit types there is the full range of expression for the other descriptors used in the analysis. Using these types of insights, the patterns of variability in germplasm collections can provide scientists with valuable information for their plant improvement programs.

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Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these data, the pattern analysis methods of classification and ordination have been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification and ordination techniques, is often specific to particular data types. The use of a combined resemblance matrix has an advantage over data type specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descriptors are partitioned into their data types and an appropriate proximity measure is used on each. The separate proximity matrices, after range standardisation, are added as a weighted average and the combined resemblance matrix is then used for classification and ordination. Germplasm evaluation data for 831 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for four binary, five ordered multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal weighting of data types to obtain a combined resemblance matrix - was investigated by using principal co-ordinate analysis (ordination) and hierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater insight into the patterns of variability available in the Australian groundnut germplasm collection. The complementary nature of pattern analysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This additional information may provide plant breeders with a more defined entry point into the germplasm collection for identifying sources of variability for their plant improvement program, thus improving the utilisation of germplasm resources.

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Fractional differential equations have been increasingly used as a powerful tool to model the non-locality and spatial heterogeneity inherent in many real-world problems. However, a constant challenge faced by researchers in this area is the high computational expense of obtaining numerical solutions of these fractional models, owing to the non-local nature of fractional derivatives. In this paper, we introduce a finite volume scheme with preconditioned Lanczos method as an attractive and high-efficiency approach for solving two-dimensional space-fractional reaction–diffusion equations. The computational heart of this approach is the efficient computation of a matrix-function-vector product f(A)bf(A)b, where A A is the matrix representation of the Laplacian obtained from the finite volume method and is non-symmetric. A key aspect of our proposed approach is that the popular Lanczos method for symmetric matrices is applied to this non-symmetric problem, after a suitable transformation. Furthermore, the convergence of the Lanczos method is greatly improved by incorporating a preconditioner. Our approach is show-cased by solving the fractional Fisher equation including a validation of the solution and an analysis of the behaviour of the model.

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We present a proof of concept for a novel nanosensor for the detection of ultra-trace amounts of bio-active molecules in complex matrices. The nanosensor is comprised of gold nanoparticles with an ultra-thin silica shell and antibody surface attachment, which allows for the immobilization and direct detection of bio-active molecules by surface enhanced Raman spectroscopy (SERS) without requiring a Raman label. The ultra-thin passive layer (~1.3 nm thickness) prevents competing molecules from binding non-selectively to the gold surface without compromising the signal enhancement. The antibodies attached on the surface of the nanoparticles selectively bind to the target molecule with high affinity. The interaction between the nanosensor and the target analyte result in conformational rearrangements of the antibody binding sites, leading to significant changes in the surface enhanced Raman spectra of the nanoparticles when compared to the spectra of the un-reacted nanoparticles. Nanosensors of this design targeting the bio-active compounds erythropoietin and caffeine were able to detect ultra-trace amounts the analyte to the lower quantification limits of 3.5×10−13 M and 1×10−9 M, respectively.

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The work investigates the design of ideal threshold secret sharing in the context of cheating prevention. We showed that each orthogonal array is exactly a defining matrix of an ideal threshold scheme. To prevent cheating, defining matrices should be nonlinear so both the cheaters and honest participants have the same chance of guessing of the valid secret. The last part of the work shows how to construct nonlinear secret sharing based on orthogonal arrays.