Tratamiento por Electrocoagulación para la remoción de índigo carmín presente en agua

En el presente estudio se evaluaron las condiciones óptimas del proceso de electrocoagulación (EC) para su aplicación en la remoción del colorante índigo carmín(IC) presente en agua. Se utilizaron soluciones acuosas de diferentes concentraciones iniciales de 100, 200 y 300 mg/L del colorante. Se determinó la densidad de corriente (DC) óptima para cada una de las concentraciones de partida. Se encontró que, al aumentar la concentración inicial del índigo carmín, la DC óptima utilizada fue mayor, para un tiempo de tratamiento de 40 minutos. Los porcentajes de remoción de color obtenidos fueron 65, 61 y 54% partiendo de concentraciones inicial de 100, 200 y 300 mg/L respectivamente

Indirect DNA Readout by an H-NS Related Protein: Structure of the DNA Complex of the C-Terminal Domain of Ler

Ler, a member of the H-NS protein family, is the master regulator of the LEE pathogenicity island in virulent Escherichia coli strains. Here, we determined the structure of a complex between the DNA-binding domain of Ler (CT-Ler) and a 15-mer DNA duplex. CT-Ler recognizes a preexisting structural pattern in the DNA minor groove formed by two consecutive regions which are narrower and wider, respectively, compared with standard B-DNA. The compressed region, associated with an AT-tract, is sensed by the side chain of Arg90, whose mutation abolishes the capacity of Ler to bind DNA. The expanded groove allows the approach of the loop in which Arg90 is located. This is the first report of an experimental structure of a DNA complex that includes a protein belonging to the H-NS family. The indirect readout mechanism not only explains the capacity of H-NS and other H-NS family members to modulate the expression of a large number of genes but also the origin of the specificity displayed by Ler. Our results point to a general mechanism by which horizontally acquired genes may be specifically recognized by members of the H-NS family

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans – anteaters, sloths, and armadillos – have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with 24 domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, ten anteaters, and six sloths. Our dataset includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data-paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the south of the USA, Mexico, and Caribbean countries at the northern portion of the Neotropics, to its austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n=5,941), and Cyclopes sp. has the fewest (n=240). The armadillo species with the most data is Dasypus novemcinctus (n=11,588), and the least recorded for Calyptophractus retusus (n=33). With regards to sloth species, Bradypus variegatus has the most records (n=962), and Bradypus pygmaeus has the fewest (n=12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other datasets of Neotropical Series which will become available very soon (i.e. Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans dataset

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Impact of Systemic Inflammation and Autoimmune Diseases on apoA-I and HDL Plasma Levels and Functions

The cholesterol of high-density lipoproteins (HDLs) and its major proteic component, apoA-I, have been widely investigated as potential predictors of acute cardiovascular (CV) events. In particular, HDL cholesterol levels were shown to be inversely and independently associated with the risk of acute CV diseases in different patient populations, including autoimmune and chronic inflammatory disorders. Some relevant and direct anti-inflammatory activities of HDL have been also recently identified targeting both immune and vascular cell subsets. These studies recently highlighted the improvement of HDL function (instead of circulating levels) as a promising treatment strategy to reduce inflammation and associated CV risk in several diseases, such as systemic lupus erythematosus and rheumatoid arthritis. In these diseases, anti-inflammatory treatments targeting HDL function might improve both disease activity and CV risk. In this narrative review, we will focus on the pathophysiological relevance of HDL and apoA-I levels/functions in different acute and chronic inflammatory pathophysiological conditions

Clasificación de manzanas utilizando visión artificial y redes neuronales artificiales

The added value in a fruit can be increased with a good postharvest handling. The classification in different parameters is one of the most important operations. In small companies it is done manually, obtaining deficiencies in the quality of the product. These problems could be solved or reduced with the implementation of intelligent algorithms that in this case include artificial vision and artificial neural networks. In this project is presented the classification of apples through an intelligent algorithm, using a convolutional neural network (CNN), which is developed using Open Source libraries (OpenCV, Tensorflow and Keras) in Python with a structure of different convolutional layers and MaxPooling, for a dataset of 2,800 images of 128x128 pixels, of which 80% were used for training and 20% for test of the network, obtaining an accuracy of 98.3% and 95.36%, respectively. After the training a classification was made with a video in real time, obtaining an accuracy of 92.25%. Likewise, the possibility of using it in the industry is explored with the classification by other visual characteristics of the fruit such as size, color, shape, etc.El valor agregado en un fruto puede incrementarse con un buen manejo postcosecha. La clasificación en diferentes parámetros es de las operaciones más importantes. En las pequeñas empresas se realiza de forma manual obteniendo deficiencias en la calidad del producto. Estos problemas se podrían resolver o disminuir con la implementación de algoritmos inteligentes que en este caso incluyen visión artificial y redes neuronales artificiales. En este proyecto se presenta la clasificación de manzanas mediante un algoritmo inteligente, usando una red neuronal convolucional (CNN), la cual se desarrolla utilizando librerías de código abierto (OpenCV, Tensorflow y Keras) en Python con una estructura de diferentes capas convolucionales y MaxPooling, para un conjunto de 2,800 imágenes de 128x128 pixeles, de las cuales el 80% se utilizaron para entrenamiento y el 20% para hacer una prueba de la red, obteniendo una precisión del 98.3% y del 95.36%, respectivamente. Después del entrenamiento, se realizó una clasificación con un video en tiempo real, obteniendo una precisión del 92.25%. Asimismo, se explora la posibilidad de la utilización en la industria con la clasificación por otras características visuales del fruto como tamaño, color, forma, etc