Surfaces Reconstruction Via Inertial Sensors for Monitoring

International audienceThis document deals with the new capabilities of monitoring via the surface reconstruction of stuctures with sensors' arrays systems. Indeed, we will detail here our new demonstrator composed of a smart textile equipped with inertial sensors and a set of processings allowing to reconstruct the shape of the textile moving along time. We show here how this new tool can provide very useful information from the structures

Passive tomography for elastic waves in solids

In this paper we derive relations between the cross-correlation of ambient noises recorded at two different points and the Green's function of the elastic waves in a medium with viscous damping. The Green's function allows to estimate physical parameters such as speeds or distances. Furthermore, this work is extended by introducing the Green's correlation function proposed by J-L. Lacoume in [Lacoume07]. Some recent works proved the possible reconstruction of the Green's function for scalar waves from the cross-correlation function of ambient noise. In this work, we consider vector waves propagating in a three dimensional solid medium. Two approaches are developed. Firstly, we extend theoretical derivations proposed by Y. Colin de Verdi`ere in [ColinDeVerdiere09], relating cross-correlation of scalar waves to 1D Green's function using linear operator theory. The second approach recasts the three dimensional problem in the framework of Fourier theory. This allows to improve physical understanding of the underlying physical processes as outlined in [Lacoume07].Comment: 24 page

Smooth Interpolation of Curve Networks with Surface Normals

International audienceRecent surface acquisition technologies based on microsensors produce three-space tangential curve data which can be transformed into a network of space curves with surface normals. This paper addresses the problem of surfacing an arbitrary closed 3D curve network with given surface normals.Thanks to the normal vector input, the patch finding problem can be solved unambiguously and an initial piecewise smooth triangle mesh is computed. The input normals are propagated throughout the mesh and used to compute mean curvature vectors. We then introduce a new variational optimization method in which the standard bi-Laplacian is penalized by a term based on the mean curvature vectors. The intuition behind this original approach is to guide the standard Laplacian-based variational methods by the curvature information extracted from the input normals. The normal input increases shape fidelity and allows to achieve globally smooth and visually pleasing shapes

Chemical Optimization of Selective Pseudomonas aeruginosa LasB Elastase Inhibitors and Their Impact on LasB-Mediated Activation of IL-1β in Cellular and Animal Infection Models

LasB elastase is a broad-spectrum exoprotease and a key virulence factor of Pseudomonas aeruginosa, a major pathogen causing lung damage and inflammation in acute and chronic respiratory infections. Here, we describe the chemical optimization of specific LasB inhibitors with druglike properties and investigate their impact in cellular and animal models of P. aeruginosa infection. Competitive inhibition of LasB was demonstrated through structural and kinetic studies. In vitro LasB inhibition was confirmed with respect to several host target proteins, namely, elastin, IgG, and pro-IL-1 beta. Furthermore, inhibition of LasBmediated IL-1 beta activation was demonstrated in macrophage and mouse lung infection models. In mice, intravenous administration of inhibitors also resulted in reduced bacterial numbers at 24 h. These highly potent, selective, and soluble LasB inhibitors constitute valuable tools to study the proinflammatory impact of LasB in P. aeruginosa infections and, most importantly, show clear potential for the clinical development of a novel therapy for life-threatening respiratory infections caused by this opportunistic pathogen

Interpolating sparse scattered data using flow information

Scattered data interpolation and approximation techniques allow for the reconstruction of a scalar field based upon a finite number of scattered samples of the field. In general, the fidelity of the reconstruction with respect to the original scalar field tends to deteriorate as the number of samples decreases. For the situation of very sparse sampling, the results may not be acceptable at all. However, if it is known that the scalar field of interest is correlated with a known flow field - as is the case when the scalar field represents the value of an oceanographic tracer that propagates under the influence of the ocean's flow - then this knowledge can be exploited to enhance the scattered data reconstruction method. One way to exploit flow field information is to use it to construct a modified notion of distance between points. Replacing the standard Euclidean distance metric with a flow-field-aware notion of distance provides a method for extending standard scattered data interpolation methods into flow-based methods that produce superior results for very sparse data. The resulting reconstructions typically have lower root-mean-square errors than reconstructions that do not use the flow information, and qualitatively they often appear physically more realistic

SAR Studies Leading to the Identification of a Novel Series of Metallo-β-lactamase Inhibitors for the Treatment of Carbapenem-Resistant Enterobacteriaceae Infections That Display Efficacy in an Animal Infection Model

The clinical effectiveness of carbapenem antibiotics such as meropenem is becoming increasingly compromised by the spread of both metallo-β-lactamase (MBL) and serine-β-lactamase (SBL) enzymes on mobile genetic elements, stimulating research to find new β-lactamase inhibitors to be used in conjunction with carbapenems and other β-lactam antibiotics. Herein, we describe our initial exploration of a novel chemical series of metallo-β-lactamase inhibitors, from concept to efficacy, in a survival model using an advanced tool compound (ANT431) in conjunction with meropenem

Therapeutic potential of cladribine in combination with STAT3 inhibitor against multiple myeloma

<p>Abstract</p> <p>Background</p> <p>Cladribine or 2-chlorodeoxyadenosine (2-CDA) is a well-known purine nucleoside analog with particular activity against lymphoproliferative disorders, such as hairy cell leukemia (HCL). Its benefits in multiple myeloma (MM) remain unclear. Here we report the inhibitory effects of cladribine on MM cell lines (U266, RPMI8226, MM1.S), and its therapeutic potential in combination with a specific inhibitor of the signal transducer and activator of transcription 3 (STAT3).</p> <p>Methods</p> <p>MTS-based proliferation assays were used to determine cell viability in response to cladribine. Cell cycle progression was examined by flow cytometry analysis. Cells undergoing apoptosis were evaluated with Annexin V staining and a specific ELISA to quantitatively measure cytoplasmic histone-associated DNA fragments. Western blot analyses were performed to determine the protein expression levels and activation.</p> <p>Results</p> <p>Cladribine inhibited cell proliferation of MM cells in a dose-dependent manner, although the three MM cell lines exhibited a remarkably different responsiveness to cladribine. The IC50 of cladribine for U266, RPMI8226, or MM1.S cells was approximately 2.43, 0.75, or 0.18 μmol/L, respectively. Treatment with cladribine resulted in a significant G1 arrest in U266 and RPMI8226 cells, but only a minor increase in the G1 phase for MM1.S cells. Apoptosis assays with Annexin V-FITC/PI double staining indicated that cladribine induced apoptosis of U266 cells in a dose-dependent manner. Similar results were obtained with an apoptotic-ELISA showing that cladribine dramatically promoted MM1.S and RPMA8226 cells undergoing apoptosis. On the molecular level, cladribine induced PARP cleavage and activation of caspase-8 and caspase-3. Meanwhile, treatment with cladribine led to a remarkable reduction of the phosphorylated STAT3 (P-STAT3), but had little effect on STAT3 protein levels. The combinations of cladribine and a specific STAT3 inhibitor as compared to either agent alone significantly induced apoptosis in all three MM cell lines.</p> <p>Conclusions</p> <p>Cladribine exhibited inhibitory effects on MM cells <it>in vitro</it>. MM1.S is the only cell line showing significant response to the clinically achievable concentrations of cladribine-induced apoptosis and inactivation of STAT3. Our data suggest that MM patients with the features of MM1.S cells may particularly benefit from cladribine monotherapy, whereas cladribine in combination with STAT3 inhibitor exerts a broader therapeutic potential against MM.</p

Inhibition of IGF-1 Signalling Enhances the Apoptotic Effect of AS602868, an IKK2 Inhibitor, in Multiple Myeloma Cell Lines

Multiple myeloma (MM) is a B cell neoplasm characterized by bone marrow infiltration with malignant plasma cells. IGF-1 signalling has been explored as a therapeutic target in this disease. We analyzed the effect of the IKK2 inhibitor AS602868, in combination with a monoclonal antibody targeting IGF-1 receptor (anti-IGF-1R) in human MM cell lines. We found that anti-IGF-1R potentiated the apoptotic effect of AS602868 in LP1 and RPMI8226 MM cell lines which express high levels of IGF-1R. Anti-IGF-1R enhanced the inhibitory effect of AS602868 on NF-κB pathway signalling and potentiated the disruption of mitochondrial membrane potential caused by AS602868. These results support the role of IGF-1 signalling in MM and suggest that inhibition of this pathway could sensitize MM cells to NF-κB inhibitors

Growth factors in multiple myeloma: a comprehensive analysis of their expression in tumor cells and bone marrow environment using Affymetrix microarrays

<p>Abstract</p> <p>Background</p> <p>Multiple myeloma (MM) is characterized by a strong dependence of the tumor cells on their microenvironment, which produces growth factors supporting survival and proliferation of myeloma cells (MMC). In the past few years, many myeloma growth factors (MGF) have been described in the literature. However, their relative importance and the nature of the cells producing MGF remain unidentified for many of them.</p> <p>Methods</p> <p>We have analysed the expression of 51 MGF and 36 MGF receptors (MGFR) using Affymetrix microarrays throughout normal plasma cell differentiation, in MMC and in cells from the bone marrow (BM) microenvironment (CD14, CD3, polymorphonuclear neutrophils, stromal cells and osteoclasts).</p> <p>Results</p> <p>4/51 MGF and 9/36 MGF-receptors genes were significantly overexpressed in plasmablasts (PPC) and BM plasma cell (BMPC) compared to B cells whereas 11 MGF and 11 MGFR genes were overexpressed in BMPC compared to PPC. 3 MGF genes (AREG, NRG3, Wnt5A) and none of the receptors were significantly overexpressed in MMC versus BMPC. Furthermore, 3/51 MGF genes were overexpressed in MMC compared to the the BM microenvironment whereas 22/51 MGF genes were overexpressed in one environment subpopulation compared to MMC.</p> <p>Conclusions</p> <p>Two major messages arise from this analysis 1) The majority of MGF genes is expressed by the bone marrow environment. 2) Several MGF and their receptors are overexpressed throughout normal plasma cell differentiation. This study provides an extensive and comparative analysis of MGF expression in plasma cell differentiation and in MM and gives new insights in the understanding of intercellular communication signals in MM.</p