Improving the performance of biomass-derived carbons in rechargable lithium batteries

III Encuentro sobre Nanociencia y Nanotecnología de Investigadores y Tecnólogos Andaluce

Molecular Events behind the Selectivity and Inactivation Properties of Model NaK-Derived Ion Channels

Y55W mutants of non-selective NaK and partly K+-selective NaK2K channels have been used to explore the conformational dynamics at the pore region of these channels as they interact with either Na+ or K+. A major conclusion is that these channels exhibit a remarkable pore conformational flexibility. Homo-FRET measurements reveal a large change in W55–W55 intersubunit distances, enabling the selectivity filter (SF) to admit different species, thus, favoring poor or no selectivity. Depending on the cation, these channels exhibit wide-open conformations of the SF in Na+, or tight induced-fit conformations in K+, most favored in the four binding sites containing NaK2K channels. Such conformational flexibility seems to arise from an altered pattern of restricting interactions between the SF and the protein scaffold behind it. Additionally, binding experiments provide clues to explain such poor selectivity. Compared to the K+-selective KcsA channel, these channels lack a high affinity K+ binding component and do not collapse in Na+. Thus, they cannot properly select K+ over competing cations, nor reject Na+ by collapsing, as K+-selective channels do. Finally, these channels do not show C-type inactivation, likely because their submillimolar K+ binding affinities prevent an efficient K+ loss from their SF, thus favoring permanently open channel states.This work was partly supported by grants PGC2018-093505-B-I00 from the Spanish “Ministerio de Ciencia e Innovación”/FEDER, UE, and FCT-Fundação para a Ciência e a Tecnologia, I.P., under the scope of the project UIDB/04565/2020 and UIDP/04565/2020 of the Research Unit Institute for Bioengineering and Biosciences—iBB and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy—i4HB

Efectividad del índice de Brass en la planificación del alta por enfermeras gestoras de casos

Classifying patients according to complexity and frailty during hospitalization allows efficient planning of the scope of care required by the patient at discharge. The aim of this study was to measure the screening validity of the Blaylock Risk Assessment Screening Score and its effectiveness in discharge planning.Methods: We analyzed the variables hospital stay, destination at discharge, use of healthcare resources and mortality in 370 patients. Results: Analysis of the relationship between mortality and the BRASS-Sp index with regard to gender and number of days of stay yielded a hazard ratio of 1.73 (95% CI 1.22-2.46; p=0.002) for male gender and 2.08 (95% CI 1.43-3.04; p<0.001) for the BRASS-Sp score. Patients who continued in case management in Primary Care had a mean BRASS-Sp of 20.97 (standard deviation 6.11), while in the other patients the mean was 19.35 (standard deviation 5.60), p=0.02. Conclusions: The BRASS-Sp proved easy-to-use with verified content validity that is effective for screening hospitalized patients by case management nursesEstratificar a los pacientes en relación con la complejidad y fragilidad durante la hospitalización, nos permite planificar de manera más eficiente los cuidados y el ámbito de atención que precisa al alta. El objetivo de este trabajo es evaluar la efectividad de la traducción al español de índice de BRASS en la planificación del alta hospitalaria por enfermeras gestoras de casos de atención hospitalaria.Método: Se analizaron variables relacionadas con la estancia hospitalaria, destino al alta, utilización de recursos sanitarios y mortalidad en 370 pacientes.. Resultados: La edad media fue 72.6 años (DE 14.05), 191 (51.6%) eran mujeres. Cuando analizamos la relación entre mortalidad e índice de BRASS-Sp en relación al sexo y número de días de ingreso encontramos una HR=1.73 (95% CI de 1.22 a 2.46) con una p=0.002 para sexo masculino y una HR=2.08 (95% CI 1.43 a 3.04) con una p<0.001 para puntuación del índice de BRASS_Sp. Los pacientes que continuaron en gestión de casos en Atención Primaria obtuvieron una media del BRASS-Sp de 20.97 (DE 6.11) mientras que en los demás fue de 19.35 (DE 5.60), p=0.02. Conclusiones: La traducción al español del índice de BRASS se muestra como un instrumento fácil de usar y con validez de contenido y efectividad para cribado de pacientes hospitalizados por enfermeras gestoras de casos. &nbsp

Rehabilitación de pacientes con movilidad reducida usando exoesqueleto y técnicas de gamificación

Este proyecto denominado consiste en la creación de un prototipo de exoesqueleto para su utilización en personas con movilidad reducida en brazos y manos. Está enfocado en entrenar al paciente con distintos grados de ejercicios y esfuerzos para ayudar en las tareas de recuperación del movimiento y aumentar así la movilidad de estas partes del cuerpo ante mencionadas. Para realizar estas funciones, el prototipo está formado por: una exo-mano que permite mover los dedos del usuario gracias al uso de motores, un exo-brazo que cuenta con un motor en el codo que ayuda al movimiento del brazo y una aplicación software con el que el usuario interactúa con el exoesqueleto y permite el entrenamiento y recolección de datos de éste. La exo-mano es capaz de imitar los movimientos de la mano del usuario a partir de un sen- sor que mide el grado de actividad del músculo de la mano, mientras que el exo-brazo calcula el grado de curvatura en función de su posición. Los componentes hardware del prototipo se interconectan con las aplicaciones software gracias al microcontrolador conectado al puerto serie del PC. La aplicación software esta´ formado por dos juegos en los que cada uno entrena una parte diferente: un juego estilo Pong con el que el usuario entrena el movimiento del brazo y en función de su grado de movilidad, el exo-brazo se adapta para ofrecer mayor o menor ayuda, y un juego con el que entrenar el movimiento tanto del brazo como de la mano, en el que la exo-mano se adapta al grado de movilidad de la mano.This project called ExoKit consists on the creation of a prototype of exoskeleton for its use in people with reduced mobility in arms and hands. It’s focused on training the patient with different types of exercises and efforts to help in the tasks of recovery of movement and thus increase the mobility of these parts of the body mentioned above. To perform these functions, the prototype consists of: an exohand that allows the user’s fingers to move thanks to the use of motors, an exo-arm that has a motor in the elbow that helps arm movement and a software application with the one that the user interacts with the exoskeleton and allows the training and data collection of the same. The exo-hand can imitate the movements of the user’s hand from a sensor that measures the degree of activity of the hand muscle, while the exo-arm calculates the degree of curvature as a function of its position. The hardware components of the prototype are interconnected with the software applications thanks to the microcontroller connected to the serial port of the PC. The software application consists of two games in which each of them trains a different part: a Pong style game with which the user trains the movement of the arm and depending on their degree of mobility, the exo-arm is adapted to offer more or less help, and a game with which to train the movement of the arm as well as the hand, in which the exo-hand adapts to the degree of mobility of the user’s hand.Universidad de Sevilla. TEP- 108: Robótica y Tecnología de Computadore

Estimación de distancias mediante un sistema de estéreo-visión basado en retinas DVS

La estimación de distancias es uno de los objetivos más importantes en todo sistema de visión artificial. Para poder llevarse a cabo, es necesaria la presencia de más de un sensor de visión para poder enfocar los objetos desde más de un punto de vista y poder aplicar la geometría de la escena con tal fin. El uso de sensores DVS supone una diferencia notable, puesto que la información recibida hace referencia únicamente a los objetos que se encuentren en movimiento dentro de la escena. Este aspecto y la codificación de la información utilizada hace necesario el uso de un sistema de procesamiento especializado que, en busca de la autonomía y la paralelización, se integra en una FGPA. Esta demostración integra un escenario fijo, donde un objeto móvil realiza un movimiento continuo acercándose y alejándose del sistema de visión estéreo; tras el procesamiento de esta información, se aporta una estimación cualitativa de la posición del objeto.Image processing in digital computer systems usually considers the visual information as a sequence of frames. Digital video processing has to process each frame in order to obtain a result or detect a feature. In stereo vision, existing algorithms used for distance estimation use frames from two digital cameras and process them pixel by pixel to obtain similarities and differences from both frames; after that, it is calculated an estimation about the distance of the different objects of the scene. Spike-based processing implements the processing by manipulating spikes one by one at the time they are transmitted, like human brain. The mammal nervous system is able to solve much more complex problems, such as visual recognition by manipulating neuron’s spikes. The spike-based philosophy for visual information processing based on the neuro-inspired Address-Event- Representation (AER) is achieving nowadays very high performances. In this work, it is proposed a two-DVS-retina connected to a Virtex5 FPGA framework, which allows us to obtain a distance approach of the moving objects in a close environment. It is also proposed a Multi Hold&Fire algorithm in VHDL that obtains the differences between the two retina output streams of spikes; and a VHDL distance estimator.Plan Propio de la Universidad de Sevilla Proyecto: 2017/00000962Ministerio de Industria, Competitividad e Innovación (España) COFNET TEC2016-77785-

Influence of the ripening chamber's geographical location on dry-cured Iberian ham's key odorants

Olfactometric and sensory analyses have been applied to study the possible influence of the ripening chamber’s geographical location on the aroma sensory profiles and key odorants of Iberian ham. Dry-cured Iberian ham was obtained from 3 acorn-fed pigs and, for the first time, both of the participating production facilities, located in two different Andalusian municipalities with different altitudes above mean sea level, processed one of the two hind legs from each pig. The descriptive sensory profile of orthonasal and retronasal odours was determined by trained panellists, while odour-active compounds were determined by gas chromatography/mass spectrometry-olfactometry (GC/MS-O). The results obtained showed that, separately, both techniques enable Iberian ham samples to be differentiated by their ripening chamber’s geographical location. For sensory analysis, retronasal sensory analysis appeared to be the most suitable for this goal, highlighting the “meat broth odour” and “roasted nuts odour” descriptors which presented significant differences between geographical locations for samples from all pigs. Moreover, ripening chamber’s geographical location characteristics and the initial composition of the raw material seemed to influence the content of some odour-active compounds. The odour-active compound identified as octane/acetone and isobutanol were conditioned by the ripening chamber’s geographical location, while decanal/2-ethyl-1-hexanol, 1-undecanol, 2-furanmethanol and cis-2-nonenal were also influenced by the individual pig itself. This study showed that slight climatological differences due to the location of the ripening chamber seem to have somewhat of an influence on the aromatic profile.Universidad de Sevilla VIPPIT-2019-I

Accessibility of Cations to the Selectivity Filter of KcsA in the Inactivated State: An Equilibrium Binding Study

Cation binding under equilibrium conditions has been used as a tool to explore the accessibility of permeant and nonpermeant cations to the selectivity filter in three different inactivated models of the potassium channel KcsA. The results show that the stack of ion binding sites (S1 to S4) in the inactivated filter models remain accessible to cations as they are in the resting channel state. The inactivated state of the selectivity filter is therefore “resting-like” under such equilibrium conditions. Nonetheless, quantitative differences in the apparent KD’s of the binding processes reveal that the affinity for the binding of permeant cations to the inactivated channel models, mainly K+, decreases considerably with respect to the resting channel. This is likely to cause a loss of K+ from the inactivated filter and consequently, to promote nonconductive conformations. The most affected site by the affinity loss seems to be S4, which is interesting because S4 is the first site to accommodate K+ coming from the channel vestibule when K+ exits the cell. Moreover, binding of the nonpermeant species, Na+, is not substantially affected by inactivation, meaning that the inactivated channels are also less selective for permeant versus nonpermeant cations under equilibrium conditions.This work was partly supported by the grant BFU2015-66612-P from the Spanish MINECO/FEDER, UE. CD-G acknowledges support from Medical Biochemistry and Biophysics Doctoral Programme (M2B-PhD) and FCT Portugal (SFRH/PD/BD/135154/2017)

Clasificación de tumores en cáncer de mama basado en redes neuronales de convolución

El cáncer de mama es una de las causas más frecuentes de mortalidad en las mujeres. Con la llegada de los sistemas inteligentes, la detección automática de tumores en mamografías se ha convertido en un gran reto y puede jugar un papel crucial para mejorar el diagnóstico médico. En este trabajo, se propone un sistema de diagnóstico asistido por ordenador basado en técnicas de Deep Learning, específicamente en redes neuronales de convolución (CNN). El sistema está dividido en dos partes: en primer lugar, se realiza un preprocesamiento sobre las mamografías extraídas de una base de datos pública; posteriormente, las CNNs extraen características de las imágenes preprocesadas para finalmente clasificarlas en función de los dos tipos de tumores existentes: benignos y malignos. Los resultados de este estudio muestran que el sistema tiene una precisión del 80% en clasificación de tumores.Breast cancer is one of the most frequent causes of mortality in women. With the arrival of the artificial intelligent, the automatic detection of tumors in mammograms has become a big challenge and can play a crucial role in improving medical diagnosis. In this work, a computer-aided diagnosis system based on Deep Learning techniques, specifically in Convolutional Neural Networks (CNN), is proposed. The system is divided into two parts: first, a preprocessing is performed on mammograms taken from a public database; then, the CNN extracts features of the preprocessed images to finally classify them accordingly to the type of tissue. The results of this study show that the system has an accuracy of 80% in the classification