Mesenchymal stem cells and their use as cell replacement therapy and disease modelling tool.

Mesenchymal stem cells (MSCs) from adult somatic tissues may differentiate in vitro and in vivo into multiple mesodermal tissues including bone, cartilage, adipose tissue, tendon, ligament or even muscle. MSCs preferentially home to damaged tissues where they exert their therapeutic potential. A striking feature of the MSCs is their low inherent immunogenicity as they induce little, if any, proliferation of allogeneic lymphocytes and antigen-presenting cells. Instead, MSCs appear to be immunosuppressive in vitro. Their multilineage differentiation potential coupled to their immuno-privileged properties is being exploited worldwide for both autologous and allogeneic cell replacement strategies. Here, we introduce the readers to the biology of MSCs and the mechanisms underlying immune tolerance. We then outline potential cell replacement strategies and clinical applications based on the MSCs immunological properties. Ongoing clinical trials for graft-versus-host-disease, haematopoietic recovery after co-transplantation of MSCs along with haematopoietic stem cells and tissue repair are discussed. Finally, we review the emerging area based on the use of MSCs as a target cell subset for either spontaneous or induced neoplastic transformation and, for modelling non-haematological mesenchymal cancers such as sarcomas

Enhancing Coexistence in the Unlicensed Band with Massive MIMO

We consider cellular base stations (BSs) equipped with a large number of antennas and operating in the unlicensed band. We denote such system as massive MIMO unlicensed (mMIMO-U). We design the key procedures required to guarantee coexistence between a cellular BS and nearby Wi-Fi devices. These include: neighboring Wi-Fi channel covariance estimation, allocation of spatial degrees of freedom for interference suppression, and enhanced channel sensing and data transmission phases. We evaluate the performance of the so-designed mMIMO-U, showing that it allows simultaneous cellular and Wi-Fi transmissions by keeping their mutual interference below the regulatory threshold. The same is not true for conventional listen-before-talk (LBT) operations. As a result, mMIMO-U boosts the aggregate cellular-plus-Wi-Fi data rate in the unlicensed band with respect to conventional LBT, exhibiting increasing gains as the number of BS antennas grows.Comment: To appear in Proc. IEEE ICC 201

Carbon materials as template for the preparation of mixed oxides with controlled morphology

Resumen del libro de actas del Congreso: 5th Czech-Italian-Spanish Conference on Molecular Sieves and Catalysis, celebrado en Segovia del 16 al 19 de junio de 2013Bulk mixed oxide catalysts are widely used for many applications, such as catalysts for selective oxidation processes, electrocatalysts for fuel cells, gas sensors, and solid oxide electrolysers for the production of hydrogen. VPO (vanadium and phosphorous oxides) are one of the bulk mixed oxide materials which are of interest nowadays since they are active catalysts for saturated hydrocarbon activation. With the conventional synthesis procedures for preparing bulk mixed oxides is really difficult to control the morphology and the porous structure of these materials. In practice, there are just a few works about the synthesis of mixed oxide materials with controlled morphology. The aim of this work was to describe new approaches for the preparation of VPO mixed oxides materials with spherical morphology. A carbon material was prepared using cellulose as starting material by hydrothermal treatment with phosphoric acid at 200ºC and carbonized at 500ºC. SEM analysis showed that carbon spheres with diameter up to 0.5 m were prepared by this procedure. These phosphorous containing carbon material was impregnated with the appropriate amount of vanadium oxide species in order to obtain a monolayer of VOx species on the surface of the carbon materials following a procedure described previously (1). By this manner, a carbon supported VOx material with spherical morphology was obtained (VPO/Csph). The calcination of this material was optimized in order to obtain VPO spheres with diameter up to 1-2 m and with BET area values close to 100 m2/g. Figure 1 shows a SEM image of this sample (VPOsph). The presence of vanadium pyrophosphate phase, which has been described as the active phase of this catalytic system, was identified by XRD and Raman spectroscopy. Thus, the chemical composition as well as the morphology and porous structure of these new spherical materials makes them quite promising as catalysts

Activated carbons as catalytic support for Cu nanoparticles

There are a wide range of catalytic applications for Cu-based nanoparticles materials, since Cu is an abundant and inexpensive metal and Cu nanoparticles possess unusual electrical, thermal and optical properties. The possible modification of the chemical and physical properties of these nanoparticles using different synthetic strategies and conditions and/or via postsynthetic chemical treatments has been largely responsible for the rapid growth of interest in these nanomaterials and their applications in catalysis. A previous work have explored the possibilities of SBA-15 (1,2) as support for Cu nanoparticles. In the present contribution, those results will be compared with the use of a carbon material as support, since activated carbon present many advantages with respect SBA, as the high surface area.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The coevolution of plants and viruses: Resistance and pathogenicity

Virus infection may damage the plant, and plant defenses are effective against viruses; thus, it is currently assumed that plants and viruses coevolve. However, and despite huge advances in understanding the mechanisms of pathogenicity and virulence in viruses and the mechanisms of virus resistance in plants, evidence in support of this hypothesis is surprisingly scant, and refers almost only to the virus partner. Most evidence for coevolution derives from the study of highly virulent viruses in agricultural systems, in which humans manipulate host genetic structure, what determines genetic changes in the virus population. Studies have focused on virus responses to qualitative resistance, either dominant or recessive but, even within this restricted scenario, population genetic analyses of pathogenicity and resistance factors are still scarce. Analyses of quantitative resistance or tolerance, which could be relevant for plant–virus coevolution, lag far behind. A major limitation is the lack of information on systems in which the host might evolve in response to virus infection, that is, wild hosts in natural ecosystems. It is presently unknown if, or under which circumstances, viruses do exert a selection pressure on wild plants, if qualitative resistance is a major defense strategy to viruses in nature, or even if characterized genes determining qualitative resistance to viruses did indeed evolve in response to virus infection. Here, we review evidence supporting plant–virus coevolution and point to areas in need of attention to understand the role of viruses in plant ecosystem dynamics, and the factors that determine virus emergence in crops

El caballo de bronce de Cancho Roano

Este trabajo da a conocer una pieza excepcional hallada en Cancho Roano durante la campaña de excavación de 1990. Se trata de un caballo de bronce de pequeño tamaño y muy buena factura, que quizá formó parte de un carrito votivo. Formaba parte de un deposito votivo de la estancia w-2, una de las habitaciones contiguas al edificio principal

Improvement of Virtual Screening Predictions using Computational Intelligence Methods

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to improve accuracy of scoring functions used in most VS methods we propose a hybrid novel approach where neural networks (NNET) and support vector machines (SVM) methods are trained with databases of known active (drugs) and inactive compounds, this information being exploited afterwards to improve VS predictions.We thank the Catholic University of Murcia (UCAM) under grant PMAFI/26/12. This work was partially supported by the computing facilities of Extremadura Research Centre for Advanced Technologies (CETA-CIEMAT), funded by the European Regional Development Fund (ERDF). CETA-CIEMAT belongs to CIEMAT and the Government of Spain