751 research outputs found

    Model query transformation framework- MQT: from EMF-based model query languages to persistence-spefic query languages

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    Memory problems of XML Metadata Interchange (XMI) (default persistence in Eclipse Modelling Framework (EMF)) when operating large models, have motivated the appearance of alternative mechanisms for persistence of EMF models. Most recent approaches propose using database back-ends. These approaches provide support for querying models using EMF-based model query languages (Plain EMF, Object Constraint Language (OCL), EMF Query, Epsilon Object Language (EOL), etc.). However, these languages commonly require loading in-memory all the model elements that are involved in the query. In the case of queries that traverse models (most commonly used type of queries) they require to load entire model in-memory. This loading strategy causes memory problems when operated models are large. Most database back-ends provide database-specific query languages that leverage capabilities of the database engine (better performance) and without requiring in-memory load of models for query execution (lower memory footprint). For example, Structured Query Language (SQL) is a query language for relational databases and Cypher is for Neo4J databases. In this dissertation we present MQT-Engine, a framework that supports execution of model query languages but with the e ciency (in terms of memory and performance) of a database-specifoc query language. To achieve this, MQT-Engine provides a two-step query transformation mechanism: forst, queries expressed with a model query language are transformed into a Query Language Independent Model (QLI Model); and then QLI Model is transformed into a database-specifoc query that is executed directly over the database. This mechanism provides extensibility and reusability to the framework, since it facilitates the inclusion of new query languages at both sides of the transformation. A prototype of the framework is provided. It supports transformation of EOL queries into SQL queries that are executed directly over a relational Connected Data Objects (CDO) repository. The prototype has been evaluated with two experimental evaluations. First evaluation is based on the reverse engineering domain. It compares time and memory usage required by MQT-Engine and other query languages (EMF API, OCL and SQL) to execute a set of queries over models persisted with CDO. Second evaluation is based on the railway domain, and compares performance results of MQT-Engine and other query languages (EMF API, OCL, IncQuery, SQL, etc.) for executing a set of queries. Obtained results show that MQT-Engine is able to execute successfully all the evaluated experiments. MQT-Engine is one of the evaluated solutions showing best performance results for first execution of model queries. In the case of query languages executed over CDO repositories, it is the faster solution and the one requiring less memory. For example, for the largest model in the reverse engineering case it is up to 162 times faster than a model query language executed at client-side, and it requires 23 times less memory. Additionally, the query transformation overload is constant and small (less than 2 seconds). These results validate the main goal of this dissertation: to provide a framework that gives to the model engineers the ability for specifying queries in a model query language, and then execute them with a performance and memory footprint similar to that of a persistence-specific query language. However, the framework has a set of limitations: the approach should be optimized when queries are subsequently executed; it only supports nonmodification model traversal queries; and the prototype is specific for EOL queries over CDO repositories with DBStore. Therefore, it is planned to extend the framework and address these limitations in a future version.Los problemas de memoria de XMI (mecanismo de persistencia por defecto en EMF) cuando se trabaja con modelos grandes, han motivado la aparición de mecanismos de persistencia alternativos para los modelos EMF. Los enfoques más recientes proponen el uso de bases de datos para la persistencia de los modelos. La mayoría de estos enfoques soportan la ejecución de operaciones usando lenguajes de consulta de modelos basados en EMF (EMF API, OCL, EMF Query, EOL, etc.). Sin embargo, este tipo de lenguajes necesitan almacenar en memoria al menos todos los elementos implicados en la consulta (todos los elementos del modelo en las consultas que recorren completamente el modelo consultado). Esta estrategia de carga de la información para hacer las consultas provoca problemas de memoria cuando los modelos son de gran tamaño. La mayoría de las bases de datos tienen lenguajes específicos que aprovechan las capacidades del motor de la base de datos (mayor rapidez) y sin la necesidad de cargar en memoria los modelos (menor uso de memoria). Por ejemplo, SQL es el lenguaje específico para las bases de datos relacionales y Cypher para las bases de datos Neo4J. Este trabajo propone MQT-Engine, un framework que permite ejecutar lenguajes de consulta para modelos con tiempos de ejecución y uso de memoria similares al de un lenguaje específico de base de datos. MQT-Engine realiza una transformación en dos pasos de las consultas: primero transforma las consultas que han sido escritas con un lenguaje de consulta para modelos en un modelo que es independiente del lenguaje (QLI Model); después, el modelo generado se transforma en una consulta equivalente, pero escrita con un lenguaje específico de base de datos. La transformación en dos pasos proporciona extensibilidad y reusabilidad ya que facilita la inclusión de nuevos lenguajes. Se ha implementado un prototipo de MQT-Engine que transforma consultas EOL en SQL y las ejecuta directamente sobre un repositorio CDO. El prototipo se ha evaluado con dos casos de uso. El primero está basado en el dominio de la ingeniería inversa. Se han comparado los tiempos de ejecución y el uso de memoria que necesitan MQT-Engine y otros lenguajes de consulta (EMF API, OCL y SQL) para ejecutar una serie de consultas sobre modelos persistidos en CDO. El segundo caso de uso está basado en el dominio de los ferrocarriles y compara los tiempos de ejecución que necesitan MQT-Engine y otros lenguajes (EMF API, OCL, IncQuery, etc.) para ejecutar varias consultas. Los resultados obtenidos muestran que MQT-Engine es capaz de ejecutar correctamente todos los experimentos y además es una de las soluciones con mejores tiempos para la primera ejecución de las consultas de modelos. MQTEngine es la opción más rápida y que necesita menos memoria entre los lenguajes ejecutados sobre repositorios CDO. Por ejemplo, en el caso del modelo más grande de ingeniería inversa, MQT-Engine es 162 veces más rápido y necesita 23 veces menos memoria que los lenguajes de consulta de modelos ejecutados al lado del cliente. Además, la sobrecarga de la transformación es pequeña y constante (menos de 2 segundos). Estos resultados prueban el objetivo principal de esta tesis: proporcionar un framework que permite a los ingenieros de modelos definir las consultas con un lenguaje de consulta de modelos y además ejecutarlas con una con tiempos de ejecución y uso de memoria similares a los de un lenguaje específico de bases de datos. Sin embargo, la solución tiene una serie de limitaciones: solo soporta consultas que recorren el modelo completamente y sin modificarlo; el prototipo es específico para consultas en EOL y sobre repositorios CDO (relacionales); y habría que optimizar la ejecución de las consultas cuando estas se ejecutan más de una vez. Se ha planeado resolver estas limitaciones en versiones futuras del trabajo

    The use of mixed collagen-Matrigel matrices of increasing complexity recapitulates the biphasic role of cell adhesion in cancer cell migration: ECM sensing, remodeling and forces at the leading edge of cancer invasion

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    The migration of cancer cells is highly regulated by the biomechanical properties of their local microenvironment. Using 3D scaffolds of simple composition, several aspects of cancer cell mechanosensing (signal transduction, EMC remodeling, traction forces) have been separately analyzed in the context of cell migration. However, a combined study of these factors in 3D scaffolds that more closely resemble the complex microenvironment of the cancer ECM is still missing. Here, we present a comprehensive, quantitative analysis of the role of cell-ECM interactions in cancer cell migration within a highly physiological environment consisting of mixed Matrigel-collagen hydrogel scaffolds of increasing complexity that mimic the tumor microenvironment at the leading edge of cancer invasion. We quantitatively show that the presence of Matrigel increases hydrogel stiffness, which promotes ß1 integrin expression and metalloproteinase activity in H1299 lung cancer cells. Then, we show that ECM remodeling activity causes matrix alignment and compaction that favors higher tractions exerted by the cells. However, these traction forces do not linearly translate into increased motility due to a biphasic role of cell adhesions in cell migration: at low concentration Matrigel promotes migration-effective tractions exerted through a high number of small sized focal adhesions. However, at high Matrigel concentration, traction forces are exerted through fewer, but larger focal adhesions that favor attachment yielding lower cell motility

    Targeting aberrant DNA methylation in mesenchymal stromal cells as a treatment for myeloma bone disease

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    Multiple myeloma (MM) progression and myeloma-associated bone disease (MBD) are highly dependent on bone marrow mesenchymal stromal cells (MSCs). MM-MSCs exhibit abnormal transcriptomes, suggesting the involvement of epigenetic mechanisms governing their tumor-promoting functions and prolonged osteoblast suppression. Here, we identify widespread DNA methylation alterations of bone marrow-isolated MSCs from distinct MM stages, particularly in Homeobox genes involved in osteogenic differentiation that associate with their aberrant expression. Moreover, these DNA methylation changes are recapitulated in vitro by exposing MSCs from healthy individuals to MM cells. Pharmacological targeting of DNMTs and G9a with dual inhibitor CM-272 reverts the expression of hypermethylated osteogenic regulators and promotes osteoblast differentiation of myeloma MSCs. Most importantly, CM-272 treatment prevents tumor-associated bone loss and reduces tumor burden in a murine myeloma model. Our results demonstrate that epigenetic aberrancies mediate the impairment of bone formation in MM, and its targeting by CM-272 is able to reverse MBD. Mesenchymal stromal cells (MSCs) have been shown to support multiple myeloma (MM) development. Here, MSCs isolated from the bone marrow of MM patients are shown to have altered DNA methylation patterns and a methyltransferase inhibitor reverts MM-associated bone loss and reduces tumour burden in MM murine models

    Plastic debris in the open ocean

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    There is a rising concern regarding the accumulation of floating plastic debris in the open ocean. However, the magnitude and the fate of this pollution are still open questions. Using data from the Malaspina 2010 circumnavigation, regional surveys, and previously published reports, we show a worldwide distribution of plastic on the surface of the open ocean, mostly accumulating in the convergence zones of each of the five subtropical gyres with comparable density. However, the global load of plastic on the open ocean surface was estimated to be on the order of tens of thousands of tons, far less than expected. Our observations of the size distribution of floating plastic debris point at important size-selective sinks removing millimeter-sized fragments of floating plastic on a large scale. This sink may involve a combination of fast nano-fragmentation of the microplastic into particles of microns or smaller, their transference to the ocean interior by food webs and ballasting processes, and processes yet to be discovered. Resolving the fate of the missing plastic debris is of fundamental importance to determine the nature and significance of the impacts of plastic pollution in the ocean

    Targeting aberrant DNA methylation in mesenchymal stromal cells as a treatment for myeloma bone disease

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    © The Author(s) 2021.Multiple myeloma (MM) progression and myeloma-associated bone disease (MBD) are highly dependent on bone marrow mesenchymal stromal cells (MSCs). MM-MSCs exhibit abnormal transcriptomes, suggesting the involvement of epigenetic mechanisms governing their tumor-promoting functions and prolonged osteoblast suppression. Here, we identify widespread DNA methylation alterations of bone marrow-isolated MSCs from distinct MM stages, particularly in Homeobox genes involved in osteogenic differentiation that associate with their aberrant expression. Moreover, these DNA methylation changes are recapitulated in vitro by exposing MSCs from healthy individuals to MM cells. Pharmacological targeting of DNMTs and G9a with dual inhibitor CM-272 reverts the expression of hypermethylated osteogenic regulators and promotes osteoblast differentiation of myeloma MSCs. Most importantly, CM-272 treatment prevents tumor-associated bone loss and reduces tumor burden in a murine myeloma model. Our results demonstrate that epigenetic aberrancies mediate the impairment of bone formation in MM, and its targeting by CM-272 is able to reverse MBD.We thank CERCA Program/Generalitat de Catalunya and the Josep Carreras Foundation for institutional support. E.B. was funded by the Spanish Ministry of Science and Innovation (grant numbers SAF2014-55942-R and SAF2017-88086-R), co-funded by FEDER funds/European Regional Development Fund (ERDF)—a way to build Europe, and a Senior Research Award from the Multiple Myeloma Research Foundation (MMRF). C.O.-d.-S. was funded by the Spanish Ministry of Science, Innovation and Universities, under grant RTI2018-094494-B-C22 (MCIU/AEI/FEDER, UE). M.G. received financial support from the Spanish FIS-ISCIII (PI15/02156 and PI19/01384) and FEDER. A.G.G is funded by a postdoctoral contract of the Asociación Española Contra el Cáncer (AECC). F.P. was funded by grants from Instituto de Salud Carlos III (ISCIII), PI17/00701 and PI19/01352, TRASCAN (EPICA and Immunocell), Fundació La Marató de TV3, the Accelerator award CRUK/AIRC/AECC joint funder-partnership, CIBERONC (CB16/12/00489) and co-financed with FEDER funds and Fundación Ramón Areces (PREMAMM)

    Barcelona City Council ICT Public Procurement Guide

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    Les mencions de responsabilitat s'han basat en els crèdits facilitats per l'àrea responsablePodeu consultar la versió en català a: http://hdl.handle.net/11703/106505Podeu consultar la versió en castellà a: http://hdl.handle.net/11703/115663Directrius per a definir el nou model de relació amb els proveïdors de tecnologia basat en el Codi de Pràctiques Tecnològique

    Role of age and comorbidities in mortality of patients with infective endocarditis

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    [Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

    Plastic accumulation in the Mediterranean Sea

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    Concentrations of floating plastic were measured throughout the Mediterranean Sea to assess whether this basin can be regarded as a great accumulation region of plastic debris. We found that the average density of plastic (1 item per 4 m2), as well as its frequency of occurrence (100% of the sites sampled), are comparable to the accumulation zones described for the five subtropical ocean gyres. Plastic debris in the Mediterranean surface waters was dominated by millimeter-sized fragments, but showed a higher proportion of large plastic objects than that present in oceanic gyres, reflecting the closer connection with pollution sources. The accumulation of floating plastic in the Mediterranean Sea (between 1,000 and 3,000 tons) is likely related to the high human pressure together with the hydrodynamics of this semi-enclosed basin, with outflow mainly occurring through a deep water layer. Given the biological richness and concentration of economic activities in the Mediterranean Sea, the affects of plastic pollution on marine and human life are expected to be particularly frequent in this plastic accumulation region
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