Bitcoin ha supuesto una revolución en las transacciones digitales y la economía mundial. Propone un modelo descentralizado de confianza para realizar transacciones basadas en una criptomoneda. Miles de seguidores defienden su descentralización e independencia, su seguridad y versatilidad. Sus detractores lo tachan de burbuja especulativa, medio para fomentar la ciberdelincuencia o pseudotimo piramidal, además de construirse entorno a una tecnología no escalable e ineficiente. Pero, ¿y si fuera posible aprovechar las bondades de la tecnología subyacente a Bitcoin, el Blockchain, para revolucionar la gestión digital de datos de historial clínico, de diagnósticos y consultas a expertos y especialistas? ¿Y si en lugar de transacciones económicas se gestionan transacciones de información clínica, opiniones, pruebas médicas o procesos de tratamiento/diagnóstico de enfermedades, evaluadas por consenso por médicos expertos de todo el mundo? En esta ponencia se presenta un modelo basado en Blockchain para resolver los retos actuales de la educación superior, cada vez más dispersa, abierta y ubicua, y se trata de esgrimir la línea de actuación para aplicar este mismo modelo y tecnología al mundo de la medicina. El modelo propuesto puede implantarse en cualquier entidad, y adecuar su sistema y actores a las necesidades concretas de cualquier dominio o sector, como es el dominio médico. Se ha validado dicho modelo por medio de un prototipo con resultados muy esperanzadores.

Abstract

The increasing use of hydrocarbons has generated several environmental problems due to accidents during the extraction, transportation, refining, storage and use of said compounds. Diesel is a complex mixture of alkanes and aromatics, which due to its wide use has become a very frequent pollutant of water and soil.
Therefore, it is necessary to explore alternatives for the degradation of said pollutants. The purpose of this work is to analyze the optimal conditions for the degradation of diesel by bacterial consortiums from polluted soils, as well as to evaluate the production of surfactants. The bacterial consortiums (J3 and S3) were obtained from soil samples and selected in diesel as the sole carbon source, in addition, the data of the growth kinetics obtained to date in different concentrations of diesel indicate that the two bacterial consortiums use it more at 3 and 4%. On the other hand, at a pH of 7 and 8 in the presence of 3% of diesel, better bacterial growth was observed. Also, the S3 consortium showed good growth at NaCl levels of 4%. For the case of the production of surfactants only the J3 consortium, production was produced with an E24 emulsion index of 38%, which was also recorded by the hemolytic activity of the bacterial supernatant and by the collapse of the oil drop. On the other hand, the consortia are able to grow in pentadecane and citronellol, while they do not grow in naphthalene and pyrene as the sole source of carbon. Although they are partial results, they reflect the potential of these consortiums for the degradation of linear hydrocarbons, so studies are being conducted to quantify diesel degradation, identify the members of each consortium and characterize the surfactants produced.

Several natural products are currently available as chemotherapeutic agents against frequently occurring cancer. This review reports terpenes from plants that have showed chemotherapeutic activity against lung cancer. In this review, 40 references were found in the period from 1998 to 2018. Terpenes were compiled according to their chemical structures and pharmacological data obtained from different experimental models. From consulted references, 31 terpenes had chemotherapeutic activity in cells of lung cancer, and among them, the triterpenes were the most studied. The MTT assay was the most utilized method in order to evaluate pharmacological activity. According to the specialized literature, terpenes are a great promise as chemotherapeutic agents in the treatment of lung cancer. Some of them are remarkably active, and further research on its anticancer activity seems to be promising.

Studies relating the consumption of food and their nutritional properties have a great contribution in the field of health. Intake of bioactive compounds, such as proteins, vitamins, minerals and other molecules present in foods can also present substances considered antinutritives or toxic, such as cyanide, polyphenols, nitrate, saponins, protease inhibitors and lectins. The tubers are rich in carbohydrates, proteins, vitamins, organic acids, anthocyanins, phytosterols, glycolipids, antioxidants, besides presenting low lipid content. Experimental analyzes of dioscorine, the main protein present in several varieties of yams (Dioscorea spp.) has been performed over the years, demonstrating several biological activities. The present study aims to isolate the protein fraction dioscorine present in tubers of Dioscorea cayennensis and to perform its phytochemical characterization by determining the presence of secondary compounds. The tubers underwent the process of separating the mucilage and obtaining the ultrafine flour, the protein extraction was performed in buffer solution: Tris HCl 0.05M pH 8.3, the total extract was submitted to protein precipitation with ammonium sulfate in the fraction 45-75% (F_45-75). The material underwent dialysis with molecular exclusion cutoff of 8 kDa, and lyophilization for sample concentration. Phytochemical determination was performed using specific techniques such as: saponins (foam-stirring test); tannins (reaction with ferric chloride/lead acetate/gelatin); carbohydrates (Molisch test); starch (iodine test); anthocyanins, anthocyanidins and flavonoids (pH variation test/heating); catechins (reaction with hydrochloric acid/heating), flavonols and xanthones (reaction with granulated magnesium/hydrochloric acid/heating). The chemical compounds identified in the total extract were: tannins, carbohydrates, saponins, flavones, flavonols and xanthones, the protein fraction did not show any phytochemical compound. Therefore, the isolated protein fraction of tubers of D. cayennensis showed no influence of secondary metabolites on their biological activities, being a target for the synthesis of natural products, considering their biotechnological and pharmaceutical importance.

La información más relevante de las angiografías coronarias se extrae empleando técnicas de segmentación, que pueden ser automáticas, semiautomáticas o manuales. Existen numerosos algoritmos de segmentación vascular, obteniendo mejores resultados, por normal general, aquellos que emplean múltiples técnicas e imágenes a diferentes escalas para proporcionar los resultados requeridos. Se presenta un nuevo método de segmentación automatizado basado en el método manual de Hamarneh incluyendo un estudio estadístico que demuestra su idoneidad para el problema.

The objective of the prototype is to eliminate the polluting contamination of water sources, due to the leak of industrial waste without any kind of treatment, mainly generated by the industries and home sector. In this project, a prototype of water purification by plasma technology has been designed. The prototype will convert contaminated water into the plasma stream and eliminate the pathogens from the water by exposing it to ultraviolet radiation and plasma sterilisation. The polluted water will be accelerated at high speed using a water pump in order to convert it into a liquid-gas mixture for ease plasma generation. This process will be achieved when the electric supply from a source of alternating current (AC) is applied to the water by means of high voltage electrodes. After which, the mixture slows down to return into liquid form and the clean water is obtained. The whole process takes place without significantly raising the temperature also knows as non-thermal plasma. The device also has an automatic flow and pressure control system. Finally, a short feasibility study has been conducted on the water samples collected and report obtained from Chennai Metropolitan Water Supply and Sewage boards are reported. It has been concluded that this new plasma-based water treatment system will be more efficient and cheaper than the current wastewater treatment techniques and can be used in the future as the replacement of current secondary and tertiary treatments of industrial wastewater.

El análisis del transcriptoma juega un rol principal en el entendendimiento de enfermedades complejas, heterogéneas y multifactoriales como el cáncer. Es utilizado como una herramienta para la caracterización y entendimiento de alteraciones fenotípicas y la biología molecular. Perfiles transcriptómicos son utilizados para la búsqueda de genes que muestran diferencias en sus niveles de expresión asociados con una respuesta particular. Los datos RNA-seq permiten a los investigadores estudiar millones de lecturas cortas provenientes de muestras de mRNA secuenciados a través de plataformas Next Generation Sequencing (NGS). En términos generales, tales cantidades de datos son difíciles de interpretar y no hay un protocolo de análisis óptimo para cada análisis individual. Por una parte, enfoques estadísticos clásicos están disponibles en diferentes paquetes de R (como por ejemplo los paquetes DESeq o edgeR, entre otros). Por otra parte, en medicina somos capaces de utilizar algoritmos de Machine Learning para el análisis de expresión diferencial de una particular variable respuesta (por ejemplo, sano frente a enfermo) seleccionando los genes que son más relevantes y que discriminan de mejor manera ambas categorías, considerando así, información de rutas biológicas, relación de gene o usando enfoques integrativos con el fin de incluir toda la información disponible de diferentes fuentes de datos. El principal objetivo de esta presentación será introducir un enfoque basado en Machine Learning para el análisis de expresión génica con RNA-seq en el estudio del cáncer.

One of the main retoes in Artificial Intelligence is to do creative tasks such us creating music, art or novel ideas. But, even more "simple" task such us have aesthetic taste is very hard to a computer system. In this paper we will present some steps into the building of a system that learn to predict the aesthetic and quality value. We will also show preliminar results into a experiment where human evaluate different images based on its quality and aesthetic value. Finally we will show some of the posibilities of this tecnology.

We have developed theoretically a generalized least squared fitting, using as fitting function the exponential of a cubic polynomial, and as data, the efficiency ratios between different wavelengths in the vacuum ultraviolet spectral range. The fitting function is suggested by the linear interpolation of efficiency ratios whose wavelengths are nearby. We have tested the fitting proposed for data given by different authors in the literature, obtaining a determination coefficient above 98%.

Today, the cosmetics segment has become one of the most successful areas in the world. Among the most varied types of cosmetics on the market, hydrogels are highlighted because they have characteristics similar to those of biological fluids. Hydrogels are structures with three-dimensional polymer chains that can act as carriers of active principles, including substances with antioxidant activity, that can be used to prevent premature aging of the skin. Recent research has shown good results for hydrogels formed with chitosan, which is a naturally occurring, nontoxic and biodegradable polymer. Thus, the objective of this study was to perform the interaction of the phenolic compounds vitamin E (tocopherol), gallic acid, ferulic acid, artemetin and quercetin, which possess antioxidant activity, with the chitosan, aiming at hydrogel planning with antioxidant activity. The study was performed by molecular docking. The phenolic compounds were obtained by PUBCHEM, while chitosan was obtained through the PolySac3DB.For molecular docking, polar hydrogen and gasteiger charges were added to the chitosan molecule and to the ligands.The method used was the genetic algorithm Lamarckian in 100 runs. All compounds interacted with chitosan attractively but quercetin was the most stable interacting compound with energy expenditure at -3.92 kcal / mol, whereas gallic acid, ferulic acid, caffeic acid , vitamin E (tocopherol) and artemetin had energy expenditure at -2.25 kcal / mol, -2.12 kcal / mol, -2.59 kcal / mol, -2.44 kcal / mol and -2.73 kcal / mol, respectively. The study showed that both compounds have molecular conditions for interacting with chitosan-based hydrogels, but for faster releases, compounds with less stable interactions (higher energy) can be used, while for longer releases, quercetin may be used, since its interaction stability is greater.