Search results for "Matrix"

Type-II Transmembrane Prolyl Dipeptidases and Matrix Metalloproteinases in Membrane Vesicles of Active Endothelial Cells

2006

Endothelia cells in sparse culture are migratory and increase the production of gelatinases of serine- and metallo-classes in membrane vesicles. Collectively, proteases associated with membrane vesicles degrade extracellular matrix components including type-I and type-IV collagens, laminin and fibronectin. Inhibitor studies suggest the existence of small gelatinases that were derived from these serine- and metallo-proteases. Thus, further studies are warranted to demonstrate the cooperative action of metallo- and serine proteases on cell surfaces and in extracellular vesicles during endothelial cell migration in 3D collagenous matrices, and potential proteolytic activation mechanism for the…

Systemic Development of Service Innovation

2015

This chapter explores the intrinsic characteristics of services and service systems and presents systemic approach to produce service innovations. The chapter consists of elaborating the characteristics of services and the principles of systemic development, discussing service matrixes, service systems, service strategies and business models, and special challenges related to the development of services and service innovations. Services are always produced in service systems consisting of combination of service personnel and information systems. Customers are involved in these systems by interacting with the front end of service organization. The key issue in service development and innovat…

Spectral properties of correlation matrices for some hierarchically nested factor models

2007

We show that spectral methods, such as Principal Component Analysis and Random Matrix Theory, are unable to reveal the hierarchical (or nested) structure of a set of mutivariate data. We consider the method introduced in M. Tumminello et al., EPL 78, 30006 (2007) to associate a hierarchical factor model with a set of data by making use of clustering algorithms. This is done by proving the existence of a bijective correspondence between a hierarchical tree and a factor model.

About Combining Metric Learning and Prototype Generation

2014

Distance metric learning has been a major research topic in recent times. Usually, the problem is formulated as finding a Mahalanobis-like metric matrix that satisfies a set of constraints as much as possible. Different ways to introduce these constraints and to effectively formulate and solve the optimization problem have been proposed. In this work, we start with one of these formulations that leads to a convex optimization problem and generalize it in order to increase the efficiency by appropriately selecting the set of constraints. Moreover, the original criterion is expressed in terms of a reduced set of representatives that is learnt together with the metric. This leads to further im…

Discrete-time static output-feedback semi-decentralized H<inf>∞</inf> controller design: An application to structural vibratio…

2012

In this work, we present a new and effective method to design discrete-time static output-feedback H ∞ controllers. This new method, based on a Linear Matrix Inequality (LMI) formulation, introduces a suitable transformation of the LMI variables that allows to obtain an explicit expression for the output-feedback gain matrix. Moreover, for problems involving a set of subsystems with information exchange constraints, a convenient structure on the LMI variables can be imposed in order to design semi-decentralized controllers, where the corresponding output-feedback gain matrix has a prescribed zero-nonzero structure. To illustrate the proposed methodology, discrete-time static velocity-feedba…

Zymographic Analysis of Matrix Metalloproteinases (MMP-2 and MMP-9) in Cerebrospinal Fluid and Sera from Patients with Multiple Sclerosis

2023

The challenge of tumor microenvironment

2008

Functional investigations of matrix metalloproteinases in breast cancer: focus on MMP9 and MMP2

2021

Melanoma cells release extracellular vesicles which contain RNA-binding proteins able to bind the mRNA encoding histone H1°

2015

Extracellular vesicles (EVs) are produced by most prokaryotic and eukaryotic cells; tumour cells, however, release much higher amounts of EVs, which contain cancer-specific proteins and RNAs. Molecules carried by EVs are captured by surrounding cells, which then undergo profound phenotypic modifications. G26/24 oligodendroglioma cells release, for example, EVs containing FasL and TRAIL, which induce apoptosis in rat cortical neurons and astrocytes in culture. By metabolic labelling of cells, EV-mediated horizontal transfer of radioactive proteins was clearly demonstrated. Among the proteins present in EVs produced by oligodendroglioma cells, extracellular matrix remodelling proteases, and t…

RNA as a carrier of epigenetic information

2017

Both prokaryotic and eukaryotic cells release into the extracellular matrix membrane-bound structures of different sizes, origin and composition, collectively called extracellular vesicles (EVs) [1]. Tumor cells, in particular, use EVs to transfer both nucleic acids and proteins to the surrounding normal cells, thus inducing in them transformed behaviours or killing them. G26/24 oligodendroglioma cells, for example, transfer by EVs pro-apoptotic proteins, such as TRAIL and Fas-Ligand [2], extracellular matrix remodelling proteases (such as ADAMTS) [3], and even the H1.0 histone protein [4]. Another tumour cell line, with a different tissue origin (A375 melanoma cells) releases into the medi…