10 research outputs found
VoCS : mejora del sistema de almacenamiento voluntario en la nube, sistema de etiquetas
Este documento pretende describir el proyecto “VOCS: Ampliación de Funcionalidades”, el cual consiste en el análisis de un proyecto ya existente para proceder a la implantación de nuevas funcionalidades que lo mejoren, así como retocar el proyecto original para que sea
más intuitivo y sencillo de utilizar.Grado en Ingeniería Informátic
Empirical Comparison of Graph-based Recommendation Engines for an Apps Ecosystem
Recommendation engines (RE) are becoming highly popular, e.g., in the area of e-commerce. A RE offers new items (products or content) to users based on their profile and historical data. The most popular algorithms used in RE are based on collaborative filtering. This technique makes recommendations based on the past behavior of other users and the similarity between users and items. In this paper we have evaluated the performance of several RE based on the properties of the networks formed by users and items. The RE use in a novel way graph theoretic concepts like edges weights or network flow. The evaluation has been conducted in a real environment (ecosystem) for recommending apps to smartphone users. The analysis of the results allows concluding that the effectiveness of a RE can be improved if the age of the data, and if a global view of the data is considered. It also shows that graph-based RE are effective, but more experiments are required for a more accurate characterization of their properties
CPEB alteration and aberrant transcriptome-polyadenylation lead to a treatable SLC19A3 deficiency in Huntington's disease
Huntington’s disease (HD) is a hereditary neurodegenerative disorder of the basal ganglia for which disease-modifying treatments are not yet available. Although gene-silencing therapies are currently being tested, further molecular mechanisms must be explored to identify druggable targets for HD. Cytoplasmic polyadenylation element binding proteins 1 to 4 (CPEB1 to CPEB4) are RNA binding proteins that repress or activate translation of CPE-containing transcripts by shortening or elongating their poly(A) tail. Here, we found increased CPEB1 and decreased CPEB4 protein in the striatum of patients and mouse models with HD. This correlated with a reprogramming of polyadenylation in 17.3% of the transcriptome, markedly affecting neurodegeneration-associated genes including PSEN1, MAPT, SNCA, LRRK2, PINK1, DJ1, SOD1, TARDBP, FUS, and HTT and suggesting a new molecular mechanism in neurodegenerative disease etiology. We found decreased protein content of top deadenylated transcripts, including striatal atrophy–linked genes not previously related to HD, such as KTN1 and the easily druggable SLC19A3 (the ThTr2 thiamine transporter). Mutations in SLC19A3 cause biotin-thiamine–responsive basal ganglia disease (BTBGD), a striatal disorder that can be treated with a combination of biotin and thiamine. Similar to patients with BTBGD, patients with HD demonstrated decreased thiamine in the cerebrospinal fluid. Furthermore, patients and mice with HD showed decreased striatal concentrations of thiamine pyrophosphate (TPP), the metabolically active form of thiamine. High-dose biotin and thiamine treatment prevented TPP deficiency in HD mice and attenuated the radiological, neuropathological, and motor HD-like phenotypes, revealing an easily implementable therapy that might benefit patients with HD
Characterization of the role of the CPEB family of RNA-binding proteins in neurodegeneration
Alzheimer’s disease (AD) is the most common type of dementia in the elderly. It is associated to a progressive loss of memory, problems in learning and behaviour changes. This disease is characterized by the accumulation of extracellular amyloid β (Aβ) aggregates and intracellular deposits of hyperphosphorylated Tau protein. Both aggregates trigger neuronal apoptosis and glial inflammation, leading to the cognitive decline found in AD patients. Interestingly, the serine protease tissue plasminogen activator (tPA), which is induced by Aβ, has been found to play a dual, dose-dependent role in the disease. Physiological levels of tPA confers neuroprotection through plasmin generation and Aβ degradation. In contrast, high doses of tPA activate intracellular signalling pathways in neurons and glial cells, inducing neuronal apoptosis and inflammation. However, the molecular mechanisms that govern the regulation of tPA expression in AD have still not been fully elucidated. In this work, we demonstrate that Aβ-induced tPA expression is regulated by translational control. In particular, our results show that CPEB1 and CPEB4, two members of the cytoplasmic polyadenylation element binding protein (CPEB) family of RNA-binding proteins, control local tPA synthesis in response to Aβ. Specifically, Aβ promotes tPA mRNA translation in the dendritic spines through synaptic polyadenylation and synaptic cleavage and polyadenylation, a mechanism that is impaired in the absence of CPEB1 or CPEB4. Our results also demonstrate that the pre-mRNA 3'-end processing machinery required for the efficient cleavage and polyadenylation of mRNAs is also present in the synaptic terminals. Finally, we have found that, similarly to tPA, CPEB4 is upregulated in the synaptic terminals in response Aβ and in vivo in the brain of AD patients.La enfermedad de Alzheimer (EA) es la demencia más común en la tercera edad. Está asociada a una pérdida progresiva de memoria, problemas de aprendizaje y cambios de comportamiento. Esta enfermedad se caracteriza por la acumulación de agregados extracelulares de proteína β-amiloide (Aβ) y depósitos intracelulares de proteína Tau hiperfosforilada. Ambos agregados inducen apoptosis neuronal e inflamación mediada por las células de la glia, lo cual desencadena el declive cognitivo característico de los enfermos de EA. En este sentido, se ha demostrado que una serina proteasa, el activador del plasminógeno tisular (del inglés "tissue plasminogen activator", tPA), cuya expresión se induce por Aβ, juega un doble papel clave en la enfermedad en función de sus niveles. Por un lado, unos niveles fisiológicos de tPA pueden ser neuroprotectores a través de la generación de plasmina, con la consiguiente degradación del Aβ. Por otro lado, unos niveles altos de tPA activan cascadas de señalización intracelular en neuronas y células de la glia, lo que induce apoptosis neuronal e inflamación. Los mecanismos moleculares que rigen la regulación de la expresión de tPA en la EA no se conocen con claridad. En este trabajo, demostramos que la expresión de tPA inducida por Aβ está regulada por control traducional. En concreto, nuestros resultados muestran que CPEB1 y CPEB4, dos miembros de la familia CPEB de proteínas de unión a RNA (del inglés "cytoplasmic polyadenylation element binding, CPEB), controlan la síntesis de tPA en respuesta a Aβ. Concretamente, el Aβ promueve la traducción del ARNm de tPA en las espinas sinápticas a través de poliadenilación sináptica, y procesamiento y poliadenilación alternativos sinápticos, un mecanismo que se ve interrumpido en ausencia de CPEB1 o CPEB4. Nuestros resultados también demuestran que la maquinaria de procesamiento de los extremos 3' del pre-ARNm necesaria para llevar a cabo este proceso está presente en los terminales sinápticos. Por último, hemos encontrado que, al igual que tPA, CPEB4 se sobreexpresa en los terminales sinápticos en respuesta a Aβ, así como en el cerebro de pacientes con EA
Empirical Comparison of Graph-based Recommendation Engines for an Apps Ecosystem
Recommendation engines (RE) are becoming highly popular, e.g., in the area of e-commerce. A RE offers new items (products or content) to users based on their profile and historical data. The most popular algorithms used in RE are based on collaborative filtering. This technique makes recommendations based on the past behavior of other users and the similarity between users and items. In this paper we have evaluated the performance of several RE based on the properties of the networks formed by users and items. The RE use in a novel way graph theoretic concepts like edges weights or network flow. The evaluation has been conducted in a real environment (ecosystem) for recommending apps to smartphone users. The analysis of the results allows concluding that the effectiveness of a RE can be improved if the age of the data, and if a global view of the data is considered. It also shows that graph-based RE are effective, but more experiments are required for a more accurate characterization of their properties
Empirical Comparison of Graph-based Recommendation Engines for an Apps Ecosystem
Recommendation engines (RE) are becoming
highly popular, e.g., in the area of e-commerce. A RE offers new
items (products or content) to users based on their profile and
historical data. The most popular algorithms used in RE are
based on collaborative filtering. This technique makes
recommendations based on the past behavior of other users and
the similarity between users and items. In this paper we have
evaluated the performance of several RE based on the properties
of the networks formed by users and items. The RE use in a novel
way graph theoretic concepts like edges weights or network flow.
The evaluation has been conducted in a real environment
(ecosystem) for recommending apps to smartphone users. The
analysis of the results allows concluding that the effectiveness of a
RE can be improved if the age of the data, and if a global view of
the data is considered. It also shows that graph-based RE are
effective, but more experiments are required for a more accurate
characterization of their properties
Autism-like phenotype and risk gene mRNA deadenylation by CPEB4 mis-splicing
Common genetic contributions to autism spectrum disorder (ASD) reside in risk gene variants that individually have minimal effect sizes. As environmental factors that perturb neurodevelopment also underlie idiopathic ASD, it is crucial to identify altered regulators that can orchestrate multiple ASD risk genes during neurodevelopment. Cytoplasmic polyadenylation element binding proteins 1–4 (CPEB1–4) regulate the translation of specific mRNAs by modulating their poly(A)-tails and thereby participate in embryonic development and synaptic plasticity. Here we find that CPEB4 binds transcripts of most high-confidence ASD risk genes. The brains of individuals with idiopathic ASD show imbalances in CPEB4 transcript isoforms that result from decreased inclusion of a neuron-specific microexon. In addition, 9% of the transcriptome shows reduced poly(A)-tail length. Notably, this percentage is much higher for high-confidence ASD risk genes, correlating with reduced expression of the protein products of ASD risk genes. An equivalent imbalance in CPEB4 transcript isoforms in mice mimics the changes in mRNA polyadenylation and protein expression of ASD risk genes and induces ASD-like neuroanatomical, electrophysiological and behavioural phenotypes. Together, these data identify CPEB4 as a regulator of ASD risk genesThis work was supported by grants: ISCIII-CiberNed-PI2013/09-
412 &PI2015-2/06 (J.J.L., R.F.-C), -FEDER-PI14/00125&PI17/00199 (P.N.); MINECO413
SAF2012-34177&SAF2015-65371-R (J.J.L.) -FEDER-BFU2014-54122-P (R.M.) -
414 BFU2014-55076-P (M.I.) -BFU2016-76050-P (R.F.-C.), -SEV-2012-0208 to CRG by
415 European Union FEDER (M.I.); NIMH 5R37 MH060233, 5R01 MH09714 and 5R01
416 MH100027 (D.H.G.); Junta de Andalucía-P12-CTS-2232&CTS-600 (R.F.-C.); Generalitat
417 de Catalunya-2014/SGR/143 (P.N.); ERC-StG-LS2-637591 (M.I.); and by Fundación
418 Botín-Banco Santander/Santander Universities Global Division, Fundación BBVA, and
419 Fundación Ramón Areces; A.P. was recipient of a MICINN FPI-fellowship; N.N.P. (NRSA
420 F30 MH099886, UCLA Medical Scientist Training Program) and V.S. (Larry Hillblom
421 Postdoctoral Fellowship
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Autism-like phenotype and risk gene mRNA deadenylation by CPEB4 mis-splicing.
Common genetic contributions to autism spectrum disorder (ASD) reside in risk gene variants that individually have minimal effect sizes. As environmental factors that perturb neurodevelopment also underlie idiopathic ASD, it is crucial to identify altered regulators that can orchestrate multiple ASD risk genes during neurodevelopment. Cytoplasmic polyadenylation element binding proteins 1-4 (CPEB1-4) regulate the translation of specific mRNAs by modulating their poly(A)-tails and thereby participate in embryonic development and synaptic plasticity. Here we find that CPEB4 binds transcripts of most high-confidence ASD risk genes. The brains of individuals with idiopathic ASD show imbalances in CPEB4 transcript isoforms that result from decreased inclusion of a neuron-specific microexon. In addition, 9% of the transcriptome shows reduced poly(A)-tail length. Notably, this percentage is much higher for high-confidence ASD risk genes, correlating with reduced expression of the protein products of ASD risk genes. An equivalent imbalance in CPEB4 transcript isoforms in mice mimics the changes in mRNA polyadenylation and protein expression of ASD risk genes and induces ASD-like neuroanatomical, electrophysiological and behavioural phenotypes. Together, these data identify CPEB4 as a regulator of ASD risk genes
Determinants of Severity in Acute Pancreatitis : A Nation-wide Multicenter Prospective Cohort Study
OBJECTIVE: The aim of this study was to compare and validate the different classifications of severity in acute pancreatitis (AP) and to investigate which characteristics of the disease are associated with worse outcomes. SUMMARY OF BACKGROUND DATA: AP is a heterogeneous disease, ranging from uneventful cases to patients with considerable morbidity and high mortality rates. Severity classifications based on legitimate determinants of severity are important to correctly describe the course of disease. METHODS: A prospective multicenter cohort study involving patients with AP from 23 hospitals in Spain. The Atlanta Classification (AC), Revised Atlanta Classification (RAC), and Determinant-based Classification (DBC) were compared. Binary logistic multivariate analysis was performed to investigate independent determinants of severity. RESULTS: A total of 1655 patients were included; 70 patients (4.2%) died. RAC and DBC were equally superior to AC for describing the clinical course of AP. Although any kind of organ failure was associated with increased morbidity and mortality, persistent organ failure (POF) was the most significant determinant of severity. All local complications were associated with worse outcomes. Infected pancreatic necrosis correlated with high morbidity, but in the presence of POF, it was not associated to higher mortality when compared with sterile necrotizing pancreatitis. Exacerbation of previous comorbidity was associated with increased morbidity and mortality. CONCLUSION: The RAC and DBC both signify an advance in the description and differentiation of AP patients. Herein, we describe the complications of the disease independently associated to morbidity and mortality. Our findings are valuable not only when designing future studies on AP but also for the improvement of current classifications