Atg5 and Ambra1 differentially modulate neurogenesis in neural stem cells

Neuroepithelial cells undergoing differentiation efficiently remodel their cytoskeleton and shape in an energy-consuming process. The capacity of autophagy to recycle cellular components and provide energy could fulfill these requirements, thus supporting differentiation. However, little is known regarding the role of basal autophagy in neural differentiation. Here we report an increase in the expression of the autophagy genes Atg7, Becn1, Ambra1 and LC3 in vivo in the mouse embryonic olfactory bulb (OB) during the initial period of neuronal differentiation at E15.5, along with a parallel increase in neuronal markers. In addition, we observed an increase in LC3 lipidation and autophagic flux during neuronal differentiation in cultured OB-derived stem/progenitor cells. Pharmacological inhibition of autophagy with 3-MA or wortmannin markedly decreased neurogenesis. These observations were supported by similar findings in two autophagy-deficient genetic models. In Ambra1 loss-of-function homozygous mice (gt/gt) the expression of several neural markers was decreased in the OB at E13.5 in vivo. In vitro, Ambra1 haploinsufficient cells developed as small neurospheres with an impaired capacity for neuronal generation. The addition of methylpyruvate during stem/progenitor cell differentiation in culture largely reversed the inhibition of neurogenesis induced by either 3-MA or Ambra1 haploinsufficiency, suggesting that neural stem/progenitor cells activate autophagy to fulfill their high energy demands. Further supporting the role of autophagy for neuronal differentiation Atg5-null OB cells differentiating in culture displayed decreased TuJ1 levels and lower number of cells with neurites. These results reveal new roles for autophagy-related molecules Atg5 and Ambra1 during early neuronal differentiation of stem/progenitor cells

Vehicle and Pedestrian Detection in Traffic Videos Using Convolutional Neural Networks

One of the major applications of computer vision is the analysis of the traffic scene on the road, and how pedestrian traffic affects traffic in general. Road sizes and traffic signals must constantly adapt. Counting and classifying vehicles and pedestrians at an intersection is an exhausting task, and despite the use of traffic control systems, human interaction is very necessary to perform such a task. The object of study of Deep Learning is to try to solve problems that require artificial intelligence. Artificial intelligence has been working in this field for years, with different approaches and algorithms. It has achieved an important emergence in the recognition of patterns in images and videos using these techniques, to the point of surpassing human capacity in some problems. An important factor in this development is the ability to process large volumes of information in applications, which has resulted in the devices used for this purpose, such as GPU’s and multi-core CPU’s, requiring a large amount of power to operate. For the development of the application of vehicle and pedestrian detection in traffic videos, YOLO V3 was used, which is a neural network model of the latest generation of real-time objects. Keywords: yoloV3, Deep Learning, Convolucional Network. Resumen Una de las mayores aplicaciones de la visión por computadora es el análisis de la escena de tráfico en la carretera, y cómo el tráfico de peatones afecta al tráfico en general. Los tamaños de las carreteras y las señales de tráfico deben adaptarse constantemente. Contar y clasificar vehículos y peatones en una intersección es una tarea agotadora y, a pesar del uso de sistemas de control de tráfico, la interacción humana es muy necesaria para realizar dicha tarea. El objeto de estudio de Deep Learning, es intentar resolver problemas que requieren inteligencia artificial. La inteligencia artificial ha trabajado en este campo durante años, con diferentes enfoques y algoritmos. Ha logrado un surgimiento importante en el reconocimiento de patrones en imágenes y videos usando estas técnicas, hasta el punto de superar la capacidad humana en algunos problemas. Un importante factor de este desarrollo es la capacidad de procesar grandes volúmenes de información en aplicaciones, lo que ha dado como resultado que los dispositivos utilizados para este propósito, como GPU’s y CPU’s multinúcleo, requieran una gran cantidad de energía para operar. Para el desarrollo de la aplicación de Detección de vehículos y peatones en videos de tráfico, fue utilizado YOLO V3, que es un modelo de red neuronal de la última generación de objetos en tiempo real. Palabras Clave: yoloV3, Aprendizaje profundo, Red convoluciona

Structural Modeling of Straw Bale Loadbearing Wall

In Ecuador, there are qualitative and quantitative housing deficits that must be covered with materials that produce seismic-resistant, energy-efficient buildings that do not require a large amount of energy to be produced. Several studies indicate that the answer lies in straw bale structures. However, for these to be considered by designers, aids are needed to facilitate their structural modeling in specialized computer programs. Through literature reviews, the present research proposes a model that adapts the specific structural considerations of straw bale buildings to the tools available in a design program. Keywords: structure, bales, straw, model, program, design. Resumen En el Ecuador existe un déficit cualitativo y cuantitativo de viviendas que debe ser cubierto con materiales que produzcan edificaciones sismo resistentes, energéticamente eficientes y a la vez que no requieran gran cantidad de energía para ser producidos. Varios estudios señalan que la respuesta está en las estructuras elaboradas con fardos de paja. Sin embargo, para que éstas sean consideradas por los diseñadores son necesarias ayudas para facilitar su modelamiento estructural en programas informáticos especializados. La presente investigación, a través de revisiones bibliográficas, propone un modelo que adapta las consideraciones estructurales específicas de las construcciones con fardos de paja a las herramientas disponibles en un programa de diseño. Palabras Clave: estructura, fardos, paja, modelo, programa, diseñ

Enhancing Regression Models for Complex Systems using Evolutionary Techniques for Feature Engineering

Abstract This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an optimal set of features that take part of a linear and convex model. This technique provides both Feature Engineering and Symbolic Regression in order to infer accurate models with no effort or designer's expertise requirements. As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. These facilities consume from 10 to 100 times more power per square foot than typical office buildings. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. For this case study, our methodology minimizes error in power prediction. This work has been tested using real Cloud applications resulting on an average error in power estimation of 3.98%. Our work improves the possibilities of deriving Cloud energy efficient policies in Cloud data center

Microglia activation in a model of retinal degeneration and TUDCA neuroprotective effects

Background: Retinitis pigmentosa is a heterogeneous group of inherited neurodegenerative retinal disorders characterized by a progressive peripheral vision loss and night vision difficulties, subsequently leading to central vision impairment. Chronic microglia activation is associated with various neurodegenerative diseases including retinitis pigmentosa. The objective of this study was to quantify microglia activation in the retina of P23H rats, an animal model of retinitis pigmentosa, and to evaluate the therapeutic effects of TUDCA (tauroursodeoxycholic acid), which has been described as a neuroprotective compound. Methods: For this study, homozygous P23H line 3 and Sprague-Dawley (SD) rats were injected weekly with TUDCA (500 mg/kg, ip) or vehicle (saline) from 20 days to 4 months old. Vertical retinal sections and whole-mount retinas were immunostained for specific markers of microglial cells (anti-CD11b, anti-Iba1 and anti-MHC-II). Microglial cell morphology was analyzed and the number of retinal microglial was quantified. Results: Microglial cells in the SD rat retinas were arranged in regular mosaics homogenously distributed within the plexiform and ganglion cell layers. In the P23H rat retina, microglial cells increased in number in all layers compared with control SD rat retinas, preserving the regular mosaic distribution. In addition, a large number of amoeboid CD11b-positive cells were observed in the P23H rat retina, even in the subretinal space. Retinas of TUDCA-treated P23H animals exhibited lower microglial cell number in all layers and absence of microglial cells in the subretinal space. Conclusions: These results report novel TUDCA anti-inflammatory actions, with potential therapeutic implications for neurodegenerative diseases, including retinitis pigmentosa.This research was supported by grants from the Spanish Ministry of Economy and Competitiveness-FEDER (BFU2012-36845), Instituto de Salud Carlos III (RETICS RD12/0034/0010), Organización Nacional de Ciegos Españoles (ONCE), FUNDALUCE, Asociación Retina Asturias and Fundación Jesús de Gangoiti

Transcriptional correlates of the pathological phenotype in a Huntington’s disease mouse model

Huntington disease (HD) is a fatal neurodegenerative disorder without a cure that is caused by an aberrant expansion of CAG repeats in exon 1 of the huntingtin (HTT) gene. Although a negative correlation between the number of CAG repeats and the age of disease onset is established, additional factors may contribute to the high heterogeneity of the complex manifestation of symptoms among patients. This variability is also observed in mouse models, even under controlled genetic and environmental conditions. To better understand this phenomenon, we analysed the R6/1 strain in search of potential correlates between pathological motor/cognitive phenotypical traits and transcriptional alterations. HD-related genes (e.g., Penk, Plk5, Itpka), despite being downregulated across the examined brain areas (the prefrontal cortex, striatum, hippocampus and cerebellum), exhibited tissue-specific correlations with particular phenotypical traits that were attributable to the contribution of the brain region to that trait (e.g., striatum and rotarod performance, cerebellum and feet clasping). Focusing on the striatum, we determined that the transcriptional dysregulation associated with HD was partially exacerbated in mice that showed poor overall phenotypical scores, especially in genes with relevant roles in striatal functioning (e.g., Pde10a, Drd1, Drd2, Ppp1r1b). However, we also observed transcripts associated with relatively better outcomes, such as Nfya (CCAAT-binding transcription factor NF-Y subunit A) plus others related to neuronal development, apoptosis and differentiation. In this study, we demonstrated that altered brain transcription can be related to the manifestation of HD-like symptoms in mouse models and that this can be extrapolated to the highly heterogeneous population of HD patients

Muros estructurales y diafragmas

Como respuesta a los severos daños sufridos por muchas edificaciones durante al sismo de 16 de abril de 2016 se presenta una alternativa de construcción diferente a la tradicionalmente aceptada en el país. Esta alternativa da gran importancia a los muros estructurales para que junto con pórticos produzcan estructuras más seguras ante las cargas sísmicas. Se desarrolla un ejemplo de aplicación que resalta el prediseño orientado al control de derivas y cargas y luego, el diseño de diafragmas y elementos tales como cordones y colectores de esfuerzos. Se concluye que la construcción de estructuras duales con muros y diafragmas es una opción prometedor

Structural Modeling of Straw Bale Load-bearing WallModelación estructural de muro portante de fardos de paja

Abstract In Ecuador, there are qualitative and quantitative housing deficits that must be covered with materials that produce seismic-resistant, energy-efficient buildings that do not require a large amount of energy to be produced. Several studies indicate that the answer lies in straw bale structures. However, for these to be considered by designers, aids are needed to facilitate their structural modeling in specialized computer programs. Through literature reviews, the present research proposes a model that adapts the specific structural considerations of straw bale buildings to the tools available in a design program

Vibro-Tactile Enrichment Improves Blind User Interaction with Mobile Touchscreens

Abstract. Interaction via mobile devices is a challenge for blind users, who often encounter severe accessibility and usability problems. The main issues are due to the lack of hardware keys, making it difficult to quickly reach an area or activate functions, and to the new way of interacting via touchscreen. A touchscreen has no specific reference points detectable by feel, so a blind user cannot easily understand exactly where (s)he is positioned on the interface nor readily find a specific item/function. Alternative ways to provide content are mainly vocal and may be inadequate in some situations, e.g., noisy environments. In this study we investigate enriching the user interfaces of touchscreen mobile devices to facilitate blind users ' orientation. We propose a possible solution for improving interaction based on the vibro-tactile channel. After introducing the idea behind our approach, two implemented Android Apps including the enriched user interfaces are shown and discussed