Matrix changes induced by transglutaminase 2 lead to inhibition of angiogenesis and tumor growth

Administration of active TG2 to two different in vitro angiogenesis assays resulted in the accumulation of a complex extracellular matrix (ECM) leading to the suppression of endothelial tube formation without causing cell death. Matrix accumulation was accompanied by a decreased rate of ECM turnover, with increased resistance to matrix metalloproteinase-1. Intratumor injection of TG2 into mice bearing CT26 colon carcinoma tumors demonstrated a reduction in tumor growth, and in some cases tumor regression. In TG2 knockout mice, tumor progression was increased and survival rate reduced compared to wild-type mice. In wild-type mice, an increased presence of TG2 was detectable in the host tissue around the tumor. Analysis of CT26 tumors injected with TG2 revealed fibrotic-like tissue containing increased collagen, TG2-mediated crosslink and reduced organized vasculature. TG2-mediated modulation of cell behavior via changes in the ECM may provide a new approach to solid tumor therapy.

Use of a solvent-free dry matrix coating for quantitative matrix-assisted laser desorption ionization imaging of 4-bromophenyl-1,4-diazabicyclo(3.2.2)nonane-4-carboxylate in rat brain and quantitative analysis of the drug from laser microdissected tissue regions

A dry matrix application for matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) was used to profile the distribution of 4-bromophenyl-1,4-diazabicyclo(3.2.2)nonane-4-carboxylate, monohydrochloride (BDNC, SSR180711) in rat brain tissue sections. Matrix application involved applying layers of finely ground dry alpha-cyano-4-hydroxycinnamic acid (CHCA) to the surface of tissue sections thaw mounted onto MALDI targets. It was not possible to detect the drug when applying matrix in a standard aqueous-organic solvent solution. The drug was detected at higher concentrations in specific regions of the brain, particularly the white matter of the cerebellum. Pseudomultiple reaction monitoring imaging was used to validate that the observed distribution was the target compound. The semiquantitative data obtained from signal intensities in the imaging was confirmed by laser microdissection of specific regions of the brain directed by the imaging, followed by hydrophilic interaction chromatography in combination with a quantitative high-resolution mass spectrometry method. This study illustrates that a dry matrix coating is a valuable and complementary matrix application method for analysis of small polar drugs and metabolites that can be used for semiquantitative analysis.

Using organoclay to promote morphology refinement and co-continuity in high-density polyethylene/polyamide 6 blends - Effect of filler content and polymer matrix composition

We investigate the gradual changes of the microstructure of two blends of high-density polyethylene (HDPE) and polyamide 6 (PA6) at opposite composition filled with increasing amounts of an organomodified clay. The filler locates preferentially inside the polyamide phase, bringing about radical alterations in the micron-scale arrangement of the polymer phases. When the host polyamide represents the major constituent, a sudden reduction of the average sizes of the polyethylene droplets was observed upon addition of even low amounts of organoclay. A morphology refinement was also noticed at low filler contents when the particles distributes inside the minor phase. In this case, however, keep increasing the organoclay content eventually results in a high degree of PA6 phase continuity. Rheological analyses reveal that the filler loading at which the polyamide assembles in a continuous network corresponds to the critical threshold for its rheological transition from a liquid- to a gel-like behaviour, which is indicative of the structuring of the filler inside the host PA6. On the basis of this finding, a schematic mechanism is proposed in which the role of the filler in driving the space arrangement of the polymer phases is discussed. Finally, we show that the synergism between the reinforcing action of the filler and its ability to affect the blend microstructure can be exploited in order to enhance relevant technological properties of the materials, such as their high temperature structural integrity.

Genetic algorithms for discovery of matrix multiplication methods

We present a parallel genetic algorithm for nding matrix multiplication algo-rithms. For 3 x 3 matrices our genetic algorithm successfully discovered algo-rithms requiring 23 multiplications, which are equivalent to the currently best known human-developed algorithms. We also studied the cases with less mul-tiplications and evaluated the suitability of the methods discovered. Although our evolutionary method did not reach the theoretical lower bound it led to an approximate solution for 22 multiplications.

Effect of thermal residual stresses on fatigue crack opening and propagation behavior in an Al/SiCp metal matrix composite

The effects of a thermal residual stress field on fatigue crack growth in a silicon carbide particle-reinforced aluminum alloy have been measured. Stress fields were introduced into plates of material by means of a quench from a solution heat-treatment temperature. Measurements using neutron diffraction have shown that this introduces an approximately parabolic stress field into the plates, varying from compressive at the surfaces to tensile in the center. Long fatigue cracks were grown in specimens cut from as-quenched plates and in specimens which were given a stress-relieving overaging heat treatment prior to testing. Crack closure levels for these cracks were determined as a function of the position of the crack tip in the residual stress field, and these are shown to differ between as-quenched and stress-relieved samples. By monitoring the compliance of the specimens during fatigue cycling, the degree to which the residual stresses close the crack has been evaluated. © 1995 The Minerals, Metals & Material Society.

Comparison of the ageing behaviour of PM 2124 Al alloy and Al-SiCp metal-matrix composite

The ageing response of 2124 Al-SiC particulate metal-matrix composite (MMC) and unreinforced alloy has been examined using hardness measurements and Arrhenius analysis. The formation of phases during precipitation has been studied using differential scanning calorimetry (DSC). The MMC exhibits accelerated ageing compared to unreinforced alloy, due to enhanced S′ formation. The activation energy for diffusion is lower in the MMC than in the unreinforced alloy. DSC scans show Guinier-Preston B (GPB) zone nucleation to occur at a lower temperature in the MMC, whilst the total volume of GPB zones formed is smaller than in the unreinforced alloy. A model has been proposed to explain the GPB zone formation behaviour, in which ease of GPB zone nucleation varies within the MMC, as a function of ageing time and of position within the matrix. S′ formation is enhanced in the MMC because of improved diffusion and a large increase in density of heterogeneous nucleation sites compared to the unreinforced alloy. © 1994 Chapman & Hall.

Application of excitation emission matrix fluorescence monitoring in the assessment of spatial and seasonal drivers of dissolved organic matter composition: Sources and physical disturbance controls

The environmental dynamics of dissolved organic matter (DOM) were characterized for a shallow, subtropical, seagrass-dominated estuarine bay, namely Florida Bay, USA. Large spatial and seasonal variations in DOM quantity and quality were assessed using dissolved organic C (DOC) measurements and spectrophotometric properties including excitation emission matrix (EEM) fluorescence with parallel factor analysis (PARAFAC). Surface water samples were collected monthly for 2 years across the bay. DOM characteristics were statistically different across the bay, and the bay was spatially characterized into four basins based on chemical characteristics of DOM as determined by EEM-PARAFAC. Differences between zones were explained based on hydrology, geomorphology, and primary productivity of the local seagrass community. In addition, potential disturbance effects from a very active hurricane season were identified. Although the overall seasonal patterns of DOM variations were not significantly affected on a bay-wide scale by this disturbance, enhanced freshwater delivery and associated P and DOM inputs (both quantity and quality) were suggested as potential drivers for the appearance of algal blooms in high impact areas. The application of EEM-PARAFAC proved to be ideally suited for studies requiring high sample throughput methods to assess spatial and temporal ecological drivers and to determine disturbance-induced impacts in aquatic ecosystems.

Immunohistochemical expression of nuclear factor B, matrix metalloproteinase 9, and endoglin (CD105) in odontogenic keratocysts, dentigerous cysts, and radicular cysts

OBJECTIVE: The aim of this study was to compare the immunohistochemical expression of nuclear factor κB (NF-κB), matrix metalloproteinase 9 (MMP-9), and CD105 in odontogenic keratocysts (OKCs), dentigerous cysts (DCs), and radicular cysts (RCs). STUDY DESIGN: Twenty cases of OKCs, 20 DCs, and 20 RCs were analyzed. A labeling index (LI), which expresses the percentage of NF-κB-stained nuclei, was calculated for the analysis of NF-κB expression. Expression of MMP-9 in the epithelium and in the capsule of each lesion was scored as 0 (<10% stained cells), 1 (10%-50% stained cells), or 2 (>50% stained cells). In addition, MMP-9 immunostaining was analyzed in endothelial cells of vessels with a conspicuous lumen. The angiogenic index was determined based on the number of anti-CD105 antibody-stained microvessels. RESULTS: In the epithelial component, the NF-κB LI was higher in OKCs than in DCs and RCs (P < .001). Analysis of MMP-9 expression in the epithelial component showed a predominance of score 2 in OKCs (90%), DCs (70%), and RCs (65%; P = .159). Evaluation of the NF-κB LI according to the expression of MMP-9 in the epithelial lining revealed no significant difference between lesions (P = .282). In the fibrous capsule, the highest percentage of MMP-9-stained cells (score 2) was observed in OKCs (P = .100). Analysis of the expression of MMP-9 in the vessels of odontogenic cysts showed a predominance of score 2 in OKCs (80%) and RCs (50%) and of score 1 in DCs (75%; P = .002). Mean microvessel count was high in RCs (16.9), followed by DCs (12.1) and OKCs (10.0; P = .163). No significant difference in microvessel count according to the expression of MMP-9 was observed between groups (P = .689). CONCLUSIONS: The results suggest that the more aggressive biologic behavior of OKCs is related to the higher expression of MMP-9 and NF-κB in those lesions. The differences in the biologic behavior of the lesions studied do not seem to be associated with the angiogenic index.

Hierarchical spatial segregation of two Mediterranean vole species : the role of patch-network structure and matrix composition

Acknowledgments This study was financed by FEDER funds through the Programa Operacional Factores de Competitividade— COMPETE, and National funds through the Portuguese Foundation for Science and Technology—FCT, within the scope of the projects PERSIST (PTDC/BIA-BEC/105110/2008), NETPERSIST (PTDC/ AAG-MAA/3227/2012), and MateFrag (PTDC/BIA-BIC/6582/2014). RP was supported by the FCT grant SFRH/BPD/73478/2010 and SFRH/BPD/109235/2015. PB was supported by EDP Biodiversity Chair. We thank Rita Brito and Marta Duarte for help during field work. We thank Chris Sutherland, Douglas Morris, William Morgan, and Richard Hassall for critical reviews of early versions of the paper. We also thank two anonymous reviewers for helpful comments to improve the paper.

First-principles calculation of P-type alloy scattering in Si1-xGex

The p-type carrier scattering rate due to alloy disorder in Si1-xGex alloys is obtained from first principles. The required alloy scattering matrix elements are calculated from the energy splitting of the valence bands, which arise when one average host atom is replaced by a Ge or Si atom in supercells containing up to 128 atoms. Alloy scattering within the valence bands is found to be characterized by a single scattering parameter. The hole mobility is calculated from the scattering rate using the Boltzmann transport equation in the relaxation time approximation. The results are in good agreement with experiments on bulk, unstrained alloys..

Cumulon: Simplified Matrix-Based Data Analytics in the Cloud

Cumulon is a system aimed at simplifying the development and deployment of statistical analysis of big data in public clouds. Cumulon allows users to program in their familiar language of matrices and linear algebra, without worrying about how to map data and computation to specific hardware and cloud software platforms. Given user-specified requirements in terms of time, monetary cost, and risk tolerance, Cumulon automatically makes intelligent decisions on implementation alternatives, execution parameters, as well as hardware provisioning and configuration settings -- such as what type of machines and how many of them to acquire. Cumulon also supports clouds with auction-based markets: it effectively utilizes computing resources whose availability varies according to market conditions, and suggests best bidding strategies for them. Cumulon explores two alternative approaches toward supporting such markets, with different trade-offs between system and optimization complexity. Experimental study is conducted to show the efficiency of Cumulon's execution engine, as well as the optimizer's effectiveness in finding the optimal plan in the vast plan space.

Ground and Electronic Excited States from Pairing Matrix Fluctuation and Particle-Particle Random Phase Approximation

The accurate description of ground and electronic excited states is an important and challenging topic in quantum chemistry. The pairing matrix fluctuation, as a counterpart of the density fluctuation, is applied to this topic. From the pairing matrix fluctuation, the exact electron correlation energy as well as two electron addition/removal energies can be extracted. Therefore, both ground state and excited states energies can be obtained and they are in principle exact with a complete knowledge of the pairing matrix fluctuation. In practice, considering the exact pairing matrix fluctuation is unknown, we adopt its simple approximation --- the particle-particle random phase approximation (pp-RPA) --- for ground and excited states calculations. The algorithms for accelerating the pp-RPA calculation, including spin separation, spin adaptation, as well as an iterative Davidson method, are developed. For ground states correlation descriptions, the results obtained from pp-RPA are usually comparable to and can be more accurate than those from traditional particle-hole random phase approximation (ph-RPA). For excited states, the pp-RPA is able to describe double, Rydberg, and charge transfer excitations, which are challenging for conventional time-dependent density functional theory (TDDFT). Although the pp-RPA intrinsically cannot describe those excitations excited from the orbitals below the highest occupied molecular orbital (HOMO), its performances on those single excitations that can be captured are comparable to TDDFT. The pp-RPA for excitation calculation is further applied to challenging diradical problems and is used to unveil the nature of the ground and electronic excited states of higher acenes. The pp-RPA and the corresponding Tamm-Dancoff approximation (pp-TDA) are also applied to conical intersections, an important concept in nonadiabatic dynamics. Their good description of the double-cone feature of conical intersections is in sharp contrast to the failure of TDDFT. All in all, the pairing matrix fluctuation opens up new channel of thinking for quantum chemistry, and the pp-RPA is a promising method in describing ground and electronic excited states.

Distributed Feature Selection in Large n and Large p Regression Problems

Fitting statistical models is computationally challenging when the sample size or the dimension of the dataset is huge. An attractive approach for down-scaling the problem size is to first partition the dataset into subsets and then fit using distributed algorithms. The dataset can be partitioned either horizontally (in the sample space) or vertically (in the feature space), and the challenge arise in defining an algorithm with low communication, theoretical guarantees and excellent practical performance in general settings. For sample space partitioning, I propose a MEdian Selection Subset AGgregation Estimator ({\em message}) algorithm for solving these issues. The algorithm applies feature selection in parallel for each subset using regularized regression or Bayesian variable selection method, calculates the `median' feature inclusion index, estimates coefficients for the selected features in parallel for each subset, and then averages these estimates. The algorithm is simple, involves very minimal communication, scales efficiently in sample size, and has theoretical guarantees. I provide extensive experiments to show excellent performance in feature selection, estimation, prediction, and computation time relative to usual competitors.

While sample space partitioning is useful in handling datasets with large sample size, feature space partitioning is more effective when the data dimension is high. Existing methods for partitioning features, however, are either vulnerable to high correlations or inefficient in reducing the model dimension. In the thesis, I propose a new embarrassingly parallel framework named {\em DECO} for distributed variable selection and parameter estimation. In {\em DECO}, variables are first partitioned and allocated to m distributed workers. The decorrelated subset data within each worker are then fitted via any algorithm designed for high-dimensional problems. We show that by incorporating the decorrelation step, DECO can achieve consistent variable selection and parameter estimation on each subset with (almost) no assumptions. In addition, the convergence rate is nearly minimax optimal for both sparse and weakly sparse models and does NOT depend on the partition number m. Extensive numerical experiments are provided to illustrate the performance of the new framework.

For datasets with both large sample sizes and high dimensionality, I propose a new "divided-and-conquer" framework {\em DEME} (DECO-message) by leveraging both the {\em DECO} and the {\em message} algorithm. The new framework first partitions the dataset in the sample space into row cubes using {\em message} and then partition the feature space of the cubes using {\em DECO}. This procedure is equivalent to partitioning the original data matrix into multiple small blocks, each with a feasible size that can be stored and fitted in a computer in parallel. The results are then synthezied via the {\em DECO} and {\em message} algorithm in a reverse order to produce the final output. The whole framework is extremely scalable.

Extracellular matrix sub-types and mechanical stretch impact human cardiac fibroblast responses to transforming growth factor beta

Understanding the impact of extracellular matrix sub-types and mechanical stretch on cardiac fibroblast activity is required to help unravel the pathophysiology of myocardial fibrotic diseases. Therefore, the purpose of this study was to investigate pro-fibrotic responses of primary human cardiac fibroblast cells exposed to different extracellular matrix components, including collagen sub-types I, III, IV, VI and laminin. The impact of mechanical cyclical stretch and treatment with transforming growth factor beta 1 (TGFβ1) on collagen 1, collagen 3 and alpha smooth muscle actin mRNA expression on different matrices was assessed using quantitative real-time PCR. Our results revealed that all of the matrices studied not only affected the expression of pro-fibrotic genes in primary human cardiac fibroblast cells at rest but also affected their response to TGFβ1. In addition, differential cellular responses to mechanical cyclical stretch were observed depending on the type of matrix the cells were adhered to. These findings may give insight into the impact of selective pathological deposition of extracellular matrix proteins within different disease states and how these could impact the fibrotic environment.