2-Arakidonilglizerol endokannabinoidearen sintesi- eta degradazio-makineria neuronaren nukleoan: Diazilglizerol Lipasa alfa-ren konpartimentazioa eta aktibitate entzimatikoa

182 p.Ikerketa lan honetan, zatikapen azpizelularra, Western blot eta fluoreszentzia mikroskopia bidez, diazilglizerol lipasa ¿-ren (DAGL¿) presentzia frogatu dugu arratoi helduaren garun-kortexetik isolatutako nukleoetan. Kromatografia likidoa eta masa-espektrometria erabiliz, DAGL¿ aktibitatea eta 2-arakidonilglizerol (2-AG; garuneko endokannabinoiderik nagusiena) sintesia agerian jarri dugu isolatutako nukleo osoetan. Gure datuen arabera, 2-AG emari nuklearrerako, DAGL¿-k fosfatidilinositol fosfolipasa C isozimek sintetizatutako diazilglizerola (DAG) erabiltzen du. Segidan, 2-AG ekoizpenaren (DAGL aktibitatea) eta degradazioaren (monoazilglizerol lipasa aktibitatea) kontstante entzimatikoak definitu ditugu. Halaber, 2-AG degrada dezaketen entzima naugisen lokalizazioa eta konpartimentazioa deskribatu dugu; hots, monoazilglizerol lipasa (MGL), gantz-azidoen amida hidrolasa (FAAH), ¿/ß hidrolasa domeinudun proteina 12 (ABHD12) eta ziklooxigenasa-2 (COX-2). Horien artean, ABHD12 baino ez genuen aurkitu nukleoen matrizean. Are gehiago, soilik ABHD familiko isozimen inhibitzaileek (baina ez MGL inhibitzaileek) saihesten zuten 2-AG hidrolisia. Hala ere, ABDH aktibitate hidrolitikoak ez zuen eraginik DAGLk bultzatutako 2-AG emaria. Oro har, gure emaitzek DAGL neuronalaren banaketa azpizelularrari buruzko ezagutza zabaltzen dute, eta ebidentzia biokimiko eta morfologikoak eskaintzen dituzte zalantarik gabe ziurtatzeko 2-AG nukleo neuronalaren matrizean ekoizten dela. Hala, lan honek bidea ematen du nukleo neuronaletan ekoiztutako 2-AGren zereginaren inguruko lan-hipotesiak mahai gainean jartzeko

Security Architecture for Swarms of Autonomous Vehicles in Smart Farming

Nowadays, autonomous vehicles are incorporated into farms to facilitate manual labour. Being connected vehicles, as IoT systems, they are susceptible to cyber security attacks that try to cause damage to hardware, software or even living beings. Therefore, it is important to provide sufficient security mechanisms to protect both the communications and the data, mitigating any possible risk or harm to farmers, livestock or crops. Technology providers are aware of the importance of ensuring security, and more and more secure solutions can be found on the market today. However, generally, these particular solutions are not sufficient when they are part of complex hybrid systems, since there is no single global solution proposal. In addition, as the number of technologies and protocols used increases, the number of security threats also increases. This article presents a cyber-security architecture proposal for swarms of heterogeneous vehicles in smart farming, which covers all of the aspects recommended by the ISO 7798-2 specification in terms of security. As a result of this analysis, a detailed summary of the possible solutions and available technologies for each of the communication channels of the target system as well as some recommendations are presented.ECSEL JU (H2020–EU.2.1.1.7.–ECSEL RIA) and the Spanish Ministry of Economic Affairs and Digital Transformatio

The AFarCloud ECSEL Project

Farming is facing many economic challenges in terms of productivity and cost-effectiveness. Labor shortage partly due to depopulation of rural areas, especially in Europe, is another challenge. Domain specific problems such as accurate identification and proper quantification of pathogens affecting plant and animal health are key factors for minimizing economical risks, and not risking human health. The ECSEL AFarCloud (Aggregate FARming in the CLOUD) project will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labour costs. This platform will be integrated with farm management software and will support monitoring and decision-making solutions based on big data and real-time data mining techniques.The AFarCloud project is funded from the ECSEL Joint Undertaking under grant agreement n° 783221, and from National funding

Aggregate Farming in the Cloud: The AFarCloud ECSEL project

Farming is facing many economic challenges in terms of productivity and cost-effectiveness. Labor shortage partly due to depopulation of rural areas, especially in Europe, is another challenge. Domain specific problems such as accurate monitoring of soil and crop properties and animal health are key factors for minimizing economical risks, and not risking human health. The ECSEL AFarCloud (Aggregate Farming in the Cloud) project will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labor costs. Moreover, such a platform can be integrated with farm management software to support monitoring and decision-making solutions based on big data and real-time data mining techniques.publishedVersio

Centrales. Historia y patrimonio de Cuba

Peer reviewe

Genes Differentially Expressed in Conidia and Hyphae of Aspergillus fumigatus upon Exposure to Human Neutrophils

Aspergillus fumigatus is the most common etiologic agent of invasive aspergillosis in immunocompromised patients. Several studies have addressed the mechanism involved in host defense but only few have investigated the pathogen's response to attack by the host cells. To our knowledge, this is the first study that investigates the genes differentially expressed in conidia vs hyphae of A. fumigatus in response to neutrophils from healthy donors as well as from those with chronic granulomatous disease (CGD) which are defective in the production of reactive oxygen species.Transcriptional profiles of conidia and hyphae exposed to neutrophils, either from normal donors or from CGD patients, were obtained by using the genome-wide microarray. Upon exposure to either normal or CGD neutrophils, 244 genes were up-regulated in conidia but not in hyphae. Several of these genes are involved in the degradation of fatty acids, peroxisome function and the glyoxylate cycle which suggests that conidia exposed to neutrophils reprogram their metabolism to adjust to the host environment. In addition, the mRNA levels of four genes encoding proteins putatively involved in iron/copper assimilation were found to be higher in conidia and hyphae exposed to normal neutrophils compared to those exposed to CGD neutrophils. Deletants in several of the differentially expressed genes showed phenotypes related to the proposed functions, i.e. deletants of genes involved in fatty acid catabolism showed defective growth on fatty acids and the deletants of iron/copper assimilation showed higher sensitivity to the oxidative agent menadione. None of these deletants, however, showed reduced resistance to neutrophil attack.This work reveals the complex response of the fungus to leukocytes, one of the major host factors involved in antifungal defense, and identifies fungal genes that may be involved in establishing or prolonging infections in humans

Particles for Local Delivery of Proteins Using Intra-Articular Route

Designing a vehicle for local delivery of proteins using intra-articular route is an attractive option to minimize the adverse effects associated with systemic exposure and to maximize the efficacy. Slowly dissolving silylated microparticles are designed with specific size and shape that are capable of extending the retention time of a model protein (bovine serum albumin) in the murine knee joint. No cytotoxicity is observed for the reconstituted formulation when tested against synovial fibroblasts and RAW 264.7 macrophages

La huella de la Diosa en lo popular: "La Llorona" mexicana

The legend of The Weeping Woman intertwines with mythical pre-Hispanic referents, although it is during the colonial times where its plot is established and gets a major anguished charge. The fundamental core of the story of The Weeping Woman would consist of the Terrible Mother who kills her own children.La leyenda de La Llorona se entrelaza con referentes míticos prehispánicos, aunque es en la época colonial donde se instaura su trama y se le confiere una mayor carga angustiosa. El núcleo fundamental de la historia de La Llorona consistiría en la manifestación de la Madre Terrible1 que mata a los hijos. Palabras clave: La Llorona. Madre Terrible. Leyendas coloniales mexicanas. Chavel

Evaluación del rendimiento de Facenet

Este trabajo presenta una evaluación de la variación del rendimiento de la red neuronal para reconocimiento de caras Facenet cuando varían algunas condiciones de la imagen de entrada. Facenet fue introducida en 2015 por un equipo de Google como evolución del modelo Inception y fue entrenada usando un esquema de tripletas (imagen base, imagen de la misma identidad, imagen de distinta identidad) y una función de pérdida que favorecía distancias pequeñas entre los descriptores generados para imágenes de la misma identidad y distancias grandes entre los descriptores de imágenes de distinta identidad. Se presentaba Facenet como una red con resultados asombrosamente invariantes ante aspectos como la posición, la iluminación, la oclusión o la edad del individuo que variaba de manera significativa el estado del arte en reconocimiento de caras. La evaluación se ha llevado a cabo utilizando el dataset de estudio Multi-Pie para evaluar la variación en rendimiento de Facenet cuando se modifican las condiciones de iluminación, gesto y posición de cámara, y un conjunto de imágenes generadas sintéticamente a partir de una selección de imágenes del dataset VGGFace2 para evaluar la variación del rendimiento cuando se modifican aspectos como la resolución de la imagen, el área de recorte de la cara, la tonalidad, la saturación, la intensidad o el ángulo de giro de la imagen. Se ha podido valorar también la variación de rendimiento en relación con el género de la persona.---ABSTRACT---This works presents a performance evaluation of the face recognition neural network Facenet when some conditions of the input image are modified. Facenet was introduced in 2015 by a team from Google as an a evolution of the Inception model and was trained using a scheme of triplets (anchor image, same identity image, different identity image) and a loss function that favored small distances between descriptors generated from same identity images and larger distances between descriptors generated from images of different identity. Facenet was presented as a network with incredible invariance to aspects such as position, lighting, occlusion or the age of the individual. It significantly varied the state of the art in face recognition. The evaluation has been carried out using the Multi-Pie studio dataset to evaluate the variation in performance of Facenet when the lighting, gesture or camera position conditions are modified, and using a set of synthetically generated images from a selection of images from the VGGFace2 dataset to evaluate the performance variation when aspects such as the resolution of the image, the cropping of the face, the hue, the saturation, the intensity or the angle of rotation of the image are modified. It has also been possible to assess the performance variation regarding the gender of the person