The role of biological extracellular matrix scaffolds in vascularized three-dimensional tissue growth in vivo

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.

Association of MMP-2 activation potential with metastatic progression in human breast cancer cell lines independent of MMP-2 production

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.

Models for studying cellular invasion of basement membranes

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.

The influence of extracellular matrix on the generation of vascularized, engineered, transplantable tissue

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.

Optimising the cell source and biomaterials for the generation of vascularized adipose tissue in vivo

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.

The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection. II. Two-way data with mixed data types

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.

Mixed data types and the use of pattern analysis on the Australian groundnut germplasm data

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.

A finite volume scheme with preconditioned Lanczos method for two-dimensional space-fractional reaction–diffusion equations

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.

Ultra sensitive label free surface enhanced Raman spectroscopy method for the detection of biomolecules

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.

Ideal threshold schemes from orthogonal arrays

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.

Silica nanoparticles treated by cold atmospheric-pressure plasmas improve the dielectric performance of organic–inorganic nanocomposites

We report on the application of cold atmospheric-pressure plasmas to modify silica nanoparticles to enhance their compatibility with polymer matrices. Thermally nonequilibrium atmospheric-pressure plasma is generated by a high-voltage radio frequency power source operated in the capacitively coupled mode with helium as the working gas. Compared to the pure polymer and the polymer nanocomposites with untreated SiO2, the plasma-treated SiO2–polymer nanocomposites show higher dielectric breakdown strength and extended endurance under a constant electrical stress. These improvements are attributed to the stronger interactions between the SiO2 nanoparticles and the surrounding polymer matrix after the plasma treatment. Our method is generic and can be used in the production of high-performance organic–inorganic functional nanocomposites.

JK1 (FAM134B) represses cell migration in colon cancer : a functional study of a novel gene

Background JK1 is a novel cancer-related gene with unknown functional role in carcinogenesis. The aim of this study is to investigate the role of JK1 gene in carcinogenesis in an in vitro cell proliferation and migration analysis model. Methods Small hairpin RNAs (shRNA) were designed to knock-down JK1 expression in colon cancer cell line (SW480) using transduction ready lentiviral particles. Cell proliferation and cell migration assays were performed on multiple extracellular matrices to investigate the cellular effects of JK1 in colon cancer cells. A non-cancer colonic epithelial cell line (FHC) was used to compare the expression of JK1 in cancer cell line. Results JK1 knock-down did not affect cellular proliferation or survival in colon cancer. However, the manipulation increased cancer cell migration rates on collagen and fibronectin substrates. Conclusions JK1 was shown for the first time to have a functional role in the pathogenesis of colon cancer. The results imply that JK1 represses the capacity of cancer cells to migrate within their tissue. They also concurred with the previous findings of JK1 activity correlations with clinical and pathological features in colon cancer. The capacity may have utility as a means to prevent cancer cells forming metastases.

Optimizing I/O cost and managing memory for composition vector method based on correlation matrix calculation in bioinformatics

The generation of a correlation matrix for set of genomic sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. Each sequence may be millions of bases long and there may be thousands of such sequences which we wish to compare, so not all sequences may fit into main memory at the same time. Each sequence needs to be compared with every other sequence, so we will generally need to page some sequences in and out more than once. In order to minimize execution time we need to minimize this I/O. This paper develops an approach for faster and scalable computing of large-size correlation matrices through the maximal exploitation of available memory and reducing the number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different bioinformatics problems with different correlation matrix sizes. The significant performance improvement of the approach over previous work is demonstrated through benchmark examples.

Pyridine-incorporated dihexylquaterthiophene : a novel blue emitter for organic light emitting diodes (OLEDs)

The synthesis and characterisation of 2,5-bis(5′-hexyl-[2,2′- bithiophen]-5-yl)pyridine (Th4PY) and its use as a blue emitter in organic light emitting diodes (OLEDs) is reported. Th4PY was synthesised in high yield using a straightforward Suzuki coupling route with commercially available starting materials. As Th4PY is both soluble and has low molecular weight, blue OLEDs were fabricated using both spin-coating and vacuum deposition thin film processing techniques to study the effect of processing on device performance. OLED devices using a spin-coated layer consisting of 4′,4′′- tris(N-carbazolyl)triphenylamine (TCTA) and 2-(4-biphenylyl)-5-(4-tert- butylphenyl)-1,3,4-oxadiazole (PBD) as a host matrix together with Th4PY as emitter exhibited highly efficient sky-blue emission with a low turn-on voltage of 3V, a maximum brightness close to 15000cdm-2 at 8V, and a maximum luminous efficiency of 7.4cdA -1 (6.3lmW -1) with CIE coordinates of x≤0.212, y≤0.320. The device performance characteristics are compared using various matrices and processing techniques. The promising sky-blue OLED performance, solution processability, and ambient stability make Th4PY a promising blue emitter for application in OLEDs.

Engineered microenvironments provide new insights into ovarian and prostate cancer progression and drug responses

Tissue engineering technologies, which have originally been designed to reconstitute damaged tissue structure and function, can mimic not only tissue regeneration processes but also cancer development and progression. Bioengineered approaches allow cell biologists to develop sophisticated experimentally and physiologically relevant cancer models to recapitulate the complexity of the disease seen in patients. Tissue engineering tools enable three-dimensionality based on the design of biomaterials and scaffolds that re-create the geometry, chemistry, function and signalling milieu of the native tumour microenvironment. Three-dimensional (3D) microenvironments, including cell-derived matrices, biomaterial-based cell culture models and integrated co-cultures with engineered stromal components, are powerful tools to study dynamic processes like proteolytic functions associated with cancer progression, metastasis and resistance to therapeutics. In this review, we discuss how biomimetic strategies can reproduce a humanised niche for human cancer cells, such as peritoneal or bone-like microenvironments, addressing specific aspects of ovarian and prostate cancer progression and therapy response.