A generalization of the Moore-Penrose inverse related to matrix subspaces of C(nxm)

[EN]A natural generalization of the classical Moore-Penrose inverse is presented. The so-called S-Moore-Penrose inverse of a m x n complex matrix A, denoted by As, is defined for any linear subspace S of the matrix vector space Cnxm. The S-Moore-Penrose inverse As is characterized using either the singular value decomposition or (for the nonsingular square case) the orthogonal complements with respect to the Frobenius inner product. These results are applied to the preconditioning of linear systems based on Frobenius norm minimization and to the linearly constrained linear least squares problem.

Wound stimulation by growth-arrested human keratinocytes and fibroblasts: HP802-247, a new-generation allogeneic tissue engineering product

HP802-247 is a new-generation, allogeneic tissue engineering product consisting of growth-arrested, human keratinocytes (K) and fibroblasts (F) delivered in a fibrin matrix by a spray device.

Molecular characterization of Neospora caninum MAG1, a dense granule protein secreted into the parasitophorous vacuole, and associated with the cyst wall and the cyst matrix

SUMMARY: In Neospora caninum and Toxoplasma gondii, the parasitophorous vacuole (PV) is synthesized at the time of infection. During tachyzoite-to-bradyzoite stage conversion, the PV is later transformed into a tissue cyst that allows parasites to survive in their host for extended periods of time. We report on the characterization of NcMAG1, the N. caninum orthologue of T. gondii MAG1 (matrix antigen 1; TgMAG1). The 456 amino acid predicted NcMAG1 protein is 54% identical to TgMAG1. By immunoblotting, a rabbit antiserum raised against recombinant NcMAG1 detected a major product of approximately 67 kDa in extracts of N. caninum tachyzoite-infected Vero cells, which was stained more prominently in extracts of infected Vero cells treated to induce in vitro bradyzoite conversion. Immunofluorescence and TEM localized the protein mainly within the cyst wall and the cyst matrix. In both tachyzoites and bradyzoites, NcMAG1 was associated with the parasite dense granules. Comparison between NcMAG1 and TgMAG1 amino acid sequences revealed that the C-terminal conserved regions exhibit 66% identity, while the N-terminal variable regions exhibit only 32% identity. Antibodies against NcMAG1-conserved region cross-reacted with the orthologuous protein in T. gondii but those against the variable region did not. This indicates that the variable region possesses unique antigenic characteristics.

In pneumococcal meningitis a novel water-soluble inhibitor of matrix metalloproteinases and TNF-alpha converting enzyme attenuates seizures and injury of the cerebral cortex

Matrix metalloproteinases (MMPs) and TNF-alpha converting enzyme (TACE) contribute to the pathophysiology of bacterial meningitis. To date, MMP-inhibitors studied in models of meningitis were compromised by their hydrophobic nature. We investigated the pharmacokinetics and the effect of TNF484, a water-soluble hydroxamate-based inhibitor of MMP and TACE, on disease parameters and brain damage in a neonatal rat model of pneumococcal meningitis. At 1 mg/kg q6h TNF484 reduced soluble TNF-alpha and the collagen degradation product hydroxyproline in the cerebrospinal fluid. Clinically, TNF484 attenuated the incidence of seizures and was neuroprotective in the cortex. Water-soluble MMP-inhibitors may hold promise in the therapy of bacterial meningitis.

CYR61, a product of a growth factor-inducible immediate early gene, promotes angiogenesis and tumor growth

CYR61 is a secreted, cysteine-rich, heparin-binding protein encoded by a growth factor-inducible immediate–early gene. Acting as an extracellular, matrix-associated signaling molecule, CYR61 promotes the adhesion of endothelial cells through interaction with the integrin αVβ3 and augments growth factor-induced DNA synthesis in the same cell type. In this study, we show that purified CYR61 stimulates directed migration of human microvascular endothelial cells in culture through an αVβ3-dependent pathway and induces neovascularization in rat corneas. Both the chemotactic and angiogenic activities of CYR61 can be blocked by specific anti-CYR61 antibodies. Whereas most human tumor-derived cell lines tested express CYR61, the gastric adenocarcinoma cell line RF-1 does not. Expression of the CYR61 cDNA under the regulation of a constitutive promoter in RF-1 cells significantly enhances the tumorigenicity of these cells as measured by growth in immunodeficient mice, resulting in tumors that are larger and more vascularized than those produced by control RF-1 cells. Taken together, these results identify CYR61 as an angiogenic inducer that can promote tumor growth and vascularization; the results also suggest potential roles for CYR61 in physiologic and pathologic neovascularization.

Antibody-induced engagement of beta 2 integrins on adherent human neutrophils triggers activation of p21ras through tyrosine phosphorylation of the protooncogene product Vav.

It is known that beta 2 integrins are crucial for leukocyte cell-cell and cell-matrix interactions, and accumulating evidence now suggests that integrins serve not only as a structural link but also as a signal-transducing unit that controls adhesion-induced changes in cell functions. In the present study, we plated human neutrophils on surface-bound anti-beta 2 (CD18) antibodies and found that the small GTP-binding protein p21ras is activated by beta 2 integrins. Pretreatment of the cells with genistein, a tyrosine kinase inhibitor, led to a complete block of p21ras activation, an effect that was not achieved with either U73122, which abolishes the beta 2 integrin-induced Ca2+ signal, or wortmannin, which totally inhibits the phosphatidylinositol 3-kinase activity. Western blot analysis revealed that antibody-induced engagement of beta 2 integrins causes tyrosine phosphorylation of several proteins in the cells. One of these tyrosine-phosphorylated proteins had an apparent molecular mass of 95 kDa and was identified as the protooncogene product Vav, a p21ras guanine nucleotide exchange factor that is specifically expressed in cells of hematopoietic lineage. A role for Vav in the activation of p21ras is supported by the observations that antibody-induced engagement of beta 2 integrins causes an association of Vav with p21ras and that the effect of genistein on p21ras activation coincided with its ability to inhibit both the tyrosine phosphorylation of Vav and the Vav-p21ras association. Taken together, these results indicate that antibody-induced engagement of beta 2 integrins on neutrophils triggers tyrosine phosphorylation of Vav and, possibly through its association, a downstream activation of p21ras.

A disaccharide that inhibits tumor necrosis factor alpha is formed from the extracellular matrix by the enzyme heparanase.

The activation of T cells by antigens or mitogens leads to the secretion of cytokines and enzymes that shape the inflammatory response. Among these molecular mediators of inflammation is a heparanase enzyme that degrades the heparan sulfate scaffold of the extracellular matrix (ECM). Activated T cells use heparanase to penetrate the ECM and gain access to the tissues. We now report that among the breakdown products of the ECM generated by heparanase is a trisulfated disaccharide that can inhibit delayed-type hypersensitivity (DTH) in mice. This inhibition of T-cell mediated inflammation in vivo was associated with an inhibitory effect of the disaccharide on the production of biologically active tumor necrosis factor alpha (TNF-alpha) by activated T cells in vitro; the trisulfated disaccharide did not affect T-cell viability or responsiveness generally. Both the in vivo and in vitro effects of the disaccharide manifested a bell-shaped dose-response curve. The inhibitory effects of the trisulfated disaccharide were lost if the sulfate groups were removed. Thus, the disaccharide, which may be a natural product of inflammation, can regulate the functional nature of the response by the T cell to activation. Such a feedback control mechanism could enable the T cell to assess the extent of tissue degradation and adjust its behavior accordingly.

Inhibition of transglutaminase activity reduces extracellular matrix accumulation induced by high glucose levels in proximal tubular epithelial cells

Diabetic nephropathy affects 30-40% of diabetics leading to end-stage kidney failure through progressive scarring and fibrosis. Previous evidence suggests that tissue transglutaminase (tTg) and its protein cross-link product epsilon(gamma-glutamyl)lysine contribute to the expanding renal tubulointerstitial and glomerular basement membranes in this disease. Using an in vitro cell culture model of renal proximal tubular epithelial cells we determined the link between elevated glucose levels with changes in expression and activity of tTg and then, by using a highly specific site directed inhibitor of tTg (1,3-dimethyl-2[(oxopropyl)thio]imidazolium), determined the contribution of tTg to glucose-induced matrix accumulation. Exposure of cells to 36 mm glucose over 96 h caused an mRNA-dependent increase in tTg activity with a 25% increase in extracellular matrix (ECM)-associated tTg and a 150% increase in ECM epsilon(gamma-glutamyl)lysine cross-linking. This was paralleled by an elevation in total deposited ECM resulting from higher levels of deposited collagen and fibronectin. These were associated with raised mRNA for collagens III, IV, and fibronectin. The specific site-directed inhibitor of tTg normalized both tTg activity and ECM-associated epsilon(gamma-glutamyl)lysine. Levels of ECM per cell returned to near control levels with non-transcriptional reductions in deposited collagen and fibronectin. No changes in transforming growth factor beta1 (expression or biological activity) occurred that could account for our observations, whereas incubation of tTg with collagen III indicated that cross-linking could directly increase the rate of collagen fibril/gel formation. We conclude that Tg inhibition reduces glucose-induced deposition of ECM proteins independently of changes in ECM and transforming growth factor beta1 synthesis thus opening up its possible application in the treatment other fibrotic and scarring diseases where tTg has been implicated.

Leveraging product adopter information from online reviews for product recommendation

The availability of the sheer volume of online product reviews makes it possible to derive implicit demographic information of product adopters from review documents. This paper proposes a novel approach to the extraction of product adopter mentions from online reviews. The extracted product adopters are the ncategorise into a number of different demographic user groups. The aggregated demographic information of many product adopters can be used to characterize both products and users, which can be incorporated into a recommendation method using weighted regularised matrix factorisation. Our experimental results on over 15 million reviews crawled from JINGDONG, the largest B2C e-commerce website in China, show the feasibility and effectiveness of our proposed frame work for product recommendation.

Connecting social media to e-commerce:cold-start product recommendation using microblogging information

In recent years, the boundaries between e-commerce and social networking have become increasingly blurred. Many e-commerce websites support the mechanism of social login where users can sign on the websites using their social network identities such as their Facebook or Twitter accounts. Users can also post their newly purchased products on microblogs with links to the e-commerce product web pages. In this paper, we propose a novel solution for cross-site cold-start product recommendation, which aims to recommend products from e-commerce websites to users at social networking sites in 'cold-start' situations, a problem which has rarely been explored before. A major challenge is how to leverage knowledge extracted from social networking sites for cross-site cold-start product recommendation. We propose to use the linked users across social networking sites and e-commerce websites (users who have social networking accounts and have made purchases on e-commerce websites) as a bridge to map users' social networking features to another feature representation for product recommendation. In specific, we propose learning both users' and products' feature representations (called user embeddings and product embeddings, respectively) from data collected from e-commerce websites using recurrent neural networks and then apply a modified gradient boosting trees method to transform users' social networking features into user embeddings. We then develop a feature-based matrix factorization approach which can leverage the learnt user embeddings for cold-start product recommendation. Experimental results on a large dataset constructed from the largest Chinese microblogging service Sina Weibo and the largest Chinese B2C e-commerce website JingDong have shown the effectiveness of our proposed framework.

Mining product adopter information from online reviews for improving product recommendation

We present in this article an automated framework that extracts product adopter information from online reviews and incorporates the extracted information into feature-based matrix factorization formore effective product recommendation. In specific, we propose a bootstrapping approach for the extraction of product adopters from review text and categorize them into a number of different demographic categories. The aggregated demographic information of many product adopters can be used to characterize both products and users in the form of distributions over different demographic categories. We further propose a graphbased method to iteratively update user- and product-related distributions more reliably in a heterogeneous user-product graph and incorporate them as features into the matrix factorization approach for product recommendation. Our experimental results on a large dataset crawled from JINGDONG, the largest B2C e-commerce website in China, show that our proposed framework outperforms a number of competitive baselines for product recommendation.

On Queueinginventory Models – product form solution; reservation, Cancellation and common life time

Queueing theory is the mathematical study of ‘queue’ or ‘waiting lines’ where an item from inventory is provided to the customer on completion of service. A typical queueing system consists of a queue and a server. Customers arrive in the system from outside and join the queue in a certain way. The server picks up customers and serves them according to certain service discipline. Customers leave the system immediately after their service is completed. For queueing systems, queue length, waiting time and busy period are of primary interest to applications. The theory permits the derivation and calculation of several performance measures including the average waiting time in the queue or the system, mean queue length, traffic intensity, the expected number waiting or receiving service, mean busy period, distribution of queue length, and the probability of encountering the system in certain states, such as empty, full, having an available server or having to wait a certain time to be served.

Comparing global land cover datasets through the Eagle matrix land cover components for continental Portugal

Global land cover maps play an important role in the understanding of the Earth's ecosystem dynamic. Several global land cover maps have been produced recently namely, Global Land Cover Share (GLC-Share) and GlobeLand30. These datasets are very useful sources of land cover information and potential users and producers are many times interested in comparing these datasets. However these global land cover maps are produced based on different techniques and using different classification schemes making their interoperability in a standardized way a challenge. The Environmental Information and Observation Network (EIONET) Action Group on Land Monitoring in Europe (EAGLE) concept was developed in order to translate the differences in the classification schemes into a standardized format which allows a comparison between class definitions. This is done by elaborating an EAGLE matrix for each classification scheme, where a bar code is assigned to each class definition that compose a certain land cover class. Ahlqvist (2005) developed an overlap metric to cope with semantic uncertainty of geographical concepts, providing this way a measure of how geographical concepts are more related to each other. In this paper, the comparison of global land cover datasets is done by translating each land cover legend into the EAGLE bar coding for the Land Cover Components of the EAGLE matrix. The bar coding values assigned to each class definition are transformed in a fuzzy function that is used to compute the overlap metric proposed by Ahlqvist (2005) and overlap matrices between land cover legends are elaborated. The overlap matrices allow the semantic comparison between the classification schemes of each global land cover map. The proposed methodology is tested on a case study where the overlap metric proposed by Ahlqvist (2005) is computed in the comparison of two global land cover maps for Continental Portugal. The study resulted with the overlap spatial distribution among the two global land cover maps, Globeland30 and GLC-Share. These results shows that Globeland30 product overlap with a degree of 77% with GLC-Share product in Continental Portugal.

Interrelated product design activities sequencing with efficient tabu search algorithms

This paper proposes and investigates a metaheuristic tabu search algorithm (TSA) that generates optimal or near optimal solutions sequences for the feedback length minimization problem (FLMP) associated to a design structure matrix (DSM). The FLMP is a non-linear combinatorial optimization problem, belonging to the NP-hard class, and therefore finding an exact optimal solution is very hard and time consuming, especially on medium and large problem instances. First, we introduce the subject and provide a review of the related literature and problem definitions. Using the tabu search method (TSM) paradigm, this paper presents a new tabu search algorithm that generates optimal or sub-optimal solutions for the feedback length minimization problem, using two different neighborhoods based on swaps of two activities and shifting an activity to a different position. Furthermore, this paper includes numerical results for analyzing the performance of the proposed TSA and for fixing the proper values of its parameters. Then we compare our results on benchmarked problems with those already published in the literature. We conclude that the proposed tabu search algorithm is very promising because it outperforms the existing methods, and because no other tabu search method for the FLMP is reported in the literature. The proposed tabu search algorithm applied to the process layer of the multidimensional design structure matrices proves to be a key optimization method for an optimal product development.

Interrelated product design activities sequencing with efficient tabu search algorithms

This paper proposes and investigates a metaheuristic tabu search algorithm (TSA) that generates optimal or near optimal solutions sequences for the feedback length minimization problem (FLMP) associated to a design structure matrix (DSM). The FLMP is a non-linear combinatorial optimization problem, belonging to the NP-hard class, and therefore finding an exact optimal solution is very hard and time consuming, especially on medium and large problem instances. First, we introduce the subject and provide a review of the related literature and problem definitions. Using the tabu search method (TSM) paradigm, this paper presents a new tabu search algorithm that generates optimal or sub-optimal solutions for the feedback length minimization problem, using two different neighborhoods based on swaps of two activities and shifting an activity to a different position. Furthermore, this paper includes numerical results for analyzing the performance of the proposed TSA and for fixing the proper values of its parameters. Then we compare our results on benchmarked problems with those already published in the literature. We conclude that the proposed tabu search algorithm is very promising because it outperforms the existing methods, and because no other tabu search method for the FLMP is reported in the literature. The proposed tabu search algorithm applied to the process layer of the multidimensional design structure matrices proves to be a key optimization method for an optimal product development.