A network inference method for large-scale unsupervised identification of novel drug-drug interactions

Characterizing interactions between drugs is important to avoid potentially harmful combinations, to reduce off-target effects of treatments and to fight antibiotic resistant pathogens, among others. Here we present a network inference algorithm to predict uncharacterized drug-drug interactions. Our algorithm takes, as its only input, sets of previously reported interactions, and does not require any pharmacological or biochemical information about the drugs, their targets or their mechanisms of action. Because the models we use are abstract, our approach can deal with adverse interactions, synergistic/antagonistic/suppressing interactions, or any other type of drug interaction. We show that our method is able to accurately predict interactions, both in exhaustive pairwise interaction data between small sets of drugs, and in large-scale databases. We also demonstrate that our algorithm can be used efficiently to discover interactions of new drugs as part of the drug discovery process

Missing and spurious interactions and the reconstruction of complex networks

Network analysis is currently used in a myriad of contexts: from identifying potential drug targets to predicting the spread of epidemics and designing vaccination strategies, and from finding friends to uncovering criminal activity. Despite the promise of the network approach, the reliability of network data is a source of great concern in all fields where complex networks are studied. Here, we present a general mathematical and computational framework to deal with the problem of data reliability in complex networks. In particular, we are able to reliably identify both missing and spurious interactions in noisy network observations. Remarkably, our approach also enables us to obtain, from those noisy observations, network reconstructions that yield estimates of the true network properties that are more accurate than those provided by the observations themselves. Our approach has the potential to guide experiments, to better characterize network data sets, and to drive new discoveries

earch for new regulators of E3 ubiquitin-ligase Hakai

[Resumen]: El cáncer engloba un conjunto de enfermedades que se originan a partir de alteraciones genéticas que dan lugar a la transformación progresiva de células normales en células cancerosas malignas. Entre ellas, los carcinomas son el tipo de cáncer más frecuente de todos. Estos afectan a las células epiteliales, que pierden sus características epiteliales y adquieren un fenotipo mesenquimal e invasivo, dando lugar a la formación de metástasis. En las primeras etapas de la metástasis tiene lugar la activación del programa de transición epitelio a mesénquima (TEM), un conjunto de procesos biológicos que conducen a la transición de células epiteliales inmóviles hacia células mesenquimales con capacidad de migración e invasión de nuevos tejidos. Durante la TEM, la E3 ubiquitina-ligasa Hakai actúa como regulador posttraduccional de la estabilidad de la E-cadherina presente en las uniones adherentes célula-célula, siendo responsable de su endocitosis y degradación vía lisosomas y promoviendo así el desensamblaje de estas uniones intercelulares y la consiguiente diseminación de las células cancerosas hacia nuevos tejidos a través del torrente circulatorio. El objetivo del presente trabajo consiste en estudiar el efecto de diferentes factores de crecimiento, como son EGF, HGF y TGFβ, sobre la activación de la TEM y determinar si dicha regulación puede ser mediada a través de la regulación posttraduccional de E-cadherina por Hakai. Para ello, se trataron dos líneas tumorales de colon, LoVo y HT29, con los tres estímulos a diferentes tiempos y se analizó el efecto de dichos factores sobre el fenotipo celular mediante microscopía de contraste de fases y sobre la expresión de los marcadores E-cadherina y Hakai, mediante western-blotting, qRTPCR e imunofluorescencia. Los resultados obtenidos indican que los factores de crecimiento EGF, HGF y TGFβ no regulan de forma clara la expresión y localización celular tanto de E-cadherina como de Hakai, en las líneas celulares LoVo y HT-29.[Abstract]: Cancer includes a group of diseases that originate from genetic alterations that lead to the progressive transformation of normal cells into malignant cancer cells. Among them, carcinomas are the most common type of cancer. Carcinoma arise from epithelial cells, which lose their epithelial characteristics and acquire a mesenchymal and invasive phenotype, 7 leading the formation of metastasis. At the early stages of metastasis, the activation of the epithelial to mesenchymal transition (EMT) program takes place. EMT, a biological process that lead to the transition of immobile epithelial cells into mesenchymal cells with the ability to migrate and invade new tissues. During EMT, the E3 ubiquitin-ligase Hakai acts as a post-translational regulator of the stability of E-cadherin, which is present in the adherent cell-cell junctions. Hakai is responsible for E-cadherin endocytosis and degradation via lysosomes, promoting the disassembly of these intercellular junctions and the consequent dissemination of cancer cells into new tissues through the bloodstream. The aim of the present work is to study the effect of different growth factors, such as EGF, HGF and TGFβ, on the activation of EMT. It will be determined wether EMT regulation can be mediated through Hakai posttranslational regulation of E-cadherin. For this purpose, two different colon epithelial tumor lines, LoVo and HT29, were treated with the three stimuli at different times and the effect on the cellular phenotype was analyzed by phase contrast microscopy. Moreover, the expression of the E-cadherin and Hakai, were analyzed by western blotting, qRTPCR and immunofluorescence. The results obtained indicate that EGF, HGF and TGFβ growth factors do not clearly regulate the cellular expression and localization of both E-cadherin and Hakai, in LoVo and HT-29 cell lines.[Resumo]: O cancro engloba a un conxunto de enfermidades que se orixinan a partir de alteracións xenéticas que dan lugar á transformación progresiva de células normais en células cancerosas malignas. Entre elas, os carcinomas son o tipo de cancro máis frecuente de todos. Estos afectan ás células epiteliais, que perden as súas características epiteliais e adquiren un fenotipo mesenquimal e invasivo, dando lugar á formación de metástase. Nas primeiras etapas da metástase, ten lugar a activación do programa de transición epitelio a mesénquima (TEM), un conxunto de procesos biolóxicos que conducen á transición de células epiteliais inmóviles cara células mesenquimais con capacidades de migración e invasión de novos texidos. Durante a TEM, a E3 ubiquitina-ligasa Hakai actúa como reguladora posttraduccional da estabilidade de E-cadherina presente nas unións adherentes célula-célula, sendo responsable da súa endocitose e degradación vía lisosomas e promovendo así a desensamblaxe destas 8 unións intercelulares e a conseguinte diseminación das células cancerosas cara novos texidos a través do torrente circulatorio. O obxectivo do presente traballo consiste en estudar o efecto de diferentes factores de crecemento, como son EGF, HGF e TGFβ, sobre a activación da TEM e determinar se dita regulación pode ser mediada a través da regulación posttraduccional de E-cadherina por Hakai. Para elo, tratáronse dúas líneas tumorais de cancro de colon, LoVo e HT-29, cos tres estímulos a diferentes tempos e analizouse o efecto de ditos factores sobre o fenotipo celular mediante microscopía de contraste de fases e sobre a expresión dos marcadores E-cadherina e Hakai, mediante western-blotting, RT-qPCR e inmunofluorescencia. Os resultados obtidos indican que os factores de crecemento EGF. HGF e TGFβ non regulan de forma clara a expresión e localización celular tanto de E-cadherina como de Hakai nas líneas celulares LoVo e HT-29.Traballo fin de mestrado (UDC.CIE). Bioloxía molecular, celular e xenética. Curso 2017/201

Las neuronas espejo y su aplicación en la recuperación funcional

Introducción: Las neuronas espejo son neuronas que se activan cuando observamos la ejecución de una acción o movimiento de otro individuo, permitiéndonos imitar mentalmente los movimientos de la otra persona, en esto se basa la terapia de la observación de la acción, que persigue las mejoras motrices. Un accidente cerebrovascular (ACV) sucede cuando el flujo de sangre a una parte del cerebro se detiene y el cerebro no puede recibir ni nutrientes ni oxígeno, provocando la muerte de células cerebrales. Si la parte afectada son áreas que controlan el movimiento puede desencadenar alteraciones motoras. Objetivos: Conocer evidencia científica existente sobre la eficacia de la terapia de la observación de la acción en pacientes que sufren una hemiplejia con afectación de extremidades superiores y/o inferiores. Métodos: Se trata de una revisión sistemática, realizada a partir de estudios controlados y aleatorios. Realizados en pacientes mayores de 25 años que sufren de una hemiplejia motora debida a un accidente cerebrovascular (ACV). Realizando una búsqueda en las bases de datos PubMed, PEDro y Biblioteca Cochrane Plus mediante búsqueda simple. Se obtuvo un total de 11 artículos potencialmente interesantes para nuestro propósito. En la adquisición de artículos se descartaron 2 artículos por no ser encontrados en su totalidad y 4 por no cumplir los criterios de selección. Los 9 artículos restantes fueron utilizados para analizar los resultados. Resultados: Todos los artículos analizados que utilizan la terapia de la observación de la acción, solamente 5 coinciden con los criterios de selección empleados y tienen una puntuación mayor a 5/10 en la escala de PEDro (1). Conclusión: Un abordaje mediante la terapia de la observación de la acción unida a la rehabilitación física convencional que realizan estos pacientes puede ayudar al aprendizaje motor en pacientes que hayan sufrido un ACV. Se debería investigar más acerca de esta terapia con muestras mayores y heterogéneasGrado en Fisioterapi

Overview of the CRISPR-Cas system and design of sgRNAs ("single guide RNAs") for genomic DNA editing in yeast

Traballo fin de grao (UDC.CIE). Bioloxía. Curso 2016/2017[Resumen] El descubrimiento de los sistemas CRISPR-Cas y concretamente del sistema CRISPR-Cas9 ha supuesto una revolución en el campo de la ingeniería genómica y la biotecnología, puesto que permite editar cualquier región del genoma de cualquier organismo de manera altamente eficaz, precisa y económica. Así, desde su descubrimiento como un sistema natural de inmunidad adaptativa en organismos procariotas, sus características estructurales y funcionales han sido estudiadas y redefinidas hasta obtener variantes de CRISPR-Cas9 que incrementan la versatilidad de esta maquinaria para su empleo en investigación e industria. En el presente trabajo se realiza una revisión teórica de las características generales, estructura y función de CRISPR-Cas9 en la naturaleza así como de las funciones y aplicaciones que lo perfilan como una de las más novedosas y eficaces herramientas biotecnológicas conocidas. Además, para ejemplificar su empleo como mecanismo de edición genómica, se llevará a cabo el diseño de un proyecto experimental mediante el diseño de un oligonucleótido que permitirá la introducción y expresión de la proteína GFP (Green Fluorescent Protein) en el organismo eucariota Saccharomyces cerevisiae.[Abstract] The discovery of CRISPR-Cas systems and specifically the CRISPR-Cas9 system has led to a revolution in the field of genomic engineering and biotechnology, since it allows to edit any region of the genome of any organism in a highly effective, precise and economical way. Thus, since its discovery as a natural system of adaptive immunity in prokaryotic organisms, its structural and functional characteristics have been studied and redefined until obtaining variants of CRISPR-Cas9 that increase the versatility of this machinery for its use in research and industry. In the present work a theoretical review of the general characteristics, structure and function of CRISPR-Cas9 in the nature as well as of the functions and applications that profile it as one of the most novel and effective known biotechnological tools. In addition, to exemplify its use as a genomic editing mechanism, the design of an experimental project will be carried out by designing an oligonucleotide that will allow the introduction and expression of the GFP (Green Fluorescent Protein) protein in the eukaryotic organism Saccharomyces cerevisiae.[Resumo] O descubrimento dos sistemas CRISPR-Cas e concretamente do sistema CRISPRCas9 supuxo unha revolución no campo da inxeniería xenómica e a biotecnoloxía, posto que permite editar calquera rexión do xenoma de calquera organismo de maneira altamente eficaz, precisa e económica. Así, dende o seu descubrimento como un sistema natural de inmunidade adaptativa en organismos procariotas, a súas características estructurais e funcionais foron estudadas e redefinidas ata obter variantes de CRISPRCas9 que incrementan a versatilidades desta maquinaria para o seu emprego en investigación e industria. No presente traballo realízase unha revisión teórica das características xerais, estructura e función de CRISPR-Cas9 na natureza así como das funcións e aplicacións que o perfilan como unha das máis novedosas e eficaces ferramentas biotecnolóxicas coñecidas. Ademáis, para exemplificar o seu emprego como mecanismo de edición xenómica, levaráse a cabo o deseño dun proxecto experimental mediante o deseño dun oligonucleótido que permitirá a introducción e expresión da proteína GFP (Green Fluorescent Protein) no organsimo eucariota Saccharomyces cerevisiae

Predicting human preferences using the block structure of complex social networks

With ever-increasing available data, predicting individuals' preferences and helping them locate the most relevant information has become a pressing need. Understanding and predicting preferences is also important from a fundamental point of view, as part of what has been called a "new" computational social science. Here, we propose a novel approach based on stochastic block models, which have been developed by sociologists as plausible models of complex networks of social interactions. Our model is in the spirit of predicting individuals' preferences based on the preferences of others but, rather than fitting a particular model, we rely on a Bayesian approach that samples over the ensemble of all possible models. We show that our approach is considerably more accurate than leading recommender algorithms, with major relative improvements between 38% and 99% over industry-level algorithms. Besides, our approach sheds light on decision-making processes by identifying groups of individuals that have consistently similar preferences, and enabling the analysis of the characteristics of those groups

Warmer temperatures and their effect on East-African malaria

Malaria has been an issue worldwide for a long time, having a huge social, economic, and health burden. This disease occurs mostly in tropical and subtropical areas of the world, in countries where the levels of poverty are higher. In this work we will focus our study of malaria in Kenya. Because it has been an issue in this region for a long time. Due to insecticide and cool temperatures the disease was eradicated from Kenya s highlands in the 1960 s. However, the disease has returned in recent years, as some researchers believe that it is produced by subtle changes in the region s climate. We have strongly based our work in the paper done by David Alonso, Menno and Mercedes Pascual called "Epidemic malaria and warmer temperatures in recent decades in an East African highland." . But, while they focus their study on the influence of climate change in the spread of malaria, we give a more qualitative approach of the model and present some feasible applications to other geographical regions. Moreover we introduce different rates to analyse the impact of a pandemic, like the basic reproduction rate R0

The Impact of Physical Activity on Executive Function and Health-Related Quality of Life in Youth with Type 1 Diabetes Mellitus

Greater levels of physical activity (PA) in youth with type 1 diabetes mellitus (T1DM) has been shown to positively impact quality of life (QoL) in addition to improving physiologic and psychological outcomes. In adults with diabetes, greater levels of PA have also been positively associated with executive functioning (EF), though this relationship remains relatively unexplored in youth. Little is known about the relationship between health-related quality of life (HRQoL) and EF. Health status and psychosocial variables have been implicated as possible mediators in the relationship between PA and EF, though research with children is sparse. While studies with older adults have shown improvements in QoL and EF with PA interventions, the interrelationship between PA, HRQoL, and EF has not yet been investigated. Using a sample of 116 youth with T1DM recruited from a large tertiary care children’s hospital in the southern United States, this study analyzed if engagement in PA was related to age, sex, EF, and HRQoL. It also investigated if HRQoL was related to EF. Relationships were explored using regression analyses, controlling for time since diabetes diagnosis and socioeconomic status. The study also sought to test HRQoL as a mediator in the relationship between PA and EF. Results did not demonstrate that age or sex alone predicted PA, but age, sex, TSD, and SES explained significantly predicted PA level. PA was not found to significantly predict HRQoL or EF in any capacity, nor did HRQoL predict EF. Sans significant results between PA, EF, and HRQoL, a mediational relationship could not be explored. Future studies may seek to use a broader range of ages, a more accurate measure of PA to draw conclusions, and limit the length of the study protocol to maintain participant motivation and manage fatigue. Furthermore, increasing sample size may lead to finding signify significant results

Detection of node group membership in networks with group overlap

Most networks found in social and biochemical systems have modular structures. An important question prompted by the modularity of these networks is whether nodes can be said to belong to a single group. If they cannot, we would need to consider the role of "overlapping communities." Despite some efforts in this direction, the problem of detecting overlapping groups remains unsolved because there is neither a formal definition of overlapping community, nor an ensemble of networks with which to test the performance of group detection algorithms when nodes can belong to more than one group. Here, we introduce an ensemble of networks with overlapping groups. We then apply three group identification methods--modularity maximization, k-clique percolation, and modularity-landscape surveying--to these networks. We find that the modularity-landscape surveying method is the only one able to detect heterogeneities in node memberships, and that those heterogeneities are only detectable when the overlap is small. Surprisingly, we find that the k-clique percolation method is unable to detect node membership for the overlapping case.Comment: 12 pages, 6 figures. To appear in Euro. Phys. J