Envejecimiento neuronal y transporte de Ca2+ intracelular

El envejecimiento promueve pérdida cognitiva y susceptibilidad a enfermedades neurodegenerativas, lo que se ha relacionado con la dishomeostasis del Ca2+ intracelular. Para investigar esta hipótesis se utiliza el cultivo a largo plazo de neuronas de hipocampo de rata, modelo de envejecimiento neuronal in vitro. Mediante imagen de fluorescencia se han estudiado cambios en transporte de Ca2+ en neuronas a lo largo del envejecimiento in vitro. Las neuronas se han identificado mediante inmunofluorescencia e imagen de Ca2+. Los resultados indican que la entrada de Ca2+ inducida por NMDA y los receptores IP3 aumentan con el envejecimiento lo que favorecería la sobrecarga mitocondrial de Ca2+. Sin embargo, el potencial mitocondrial, la fuerza electromotriz de entrada de Ca2+ a la mitocondria, disminuye con el envejecimiento. Así, el envejecimiento neuronal está asociado a un remodelado del transporte de Ca2+ que favorece el metabolismo energético a expensas de aumentar la susceptibilidad a la muerte neuronal.Grado en Químic

Design and technical evaluation of an enhanced location-awareness service enabler for spatial disorientation management of elderly with mild cognitive impairment

The progressive ageing of population has turned the mild cognitive impairment (MCI) into a prevalent disease suffered by elderly. Consequently, the spatial disorientation has become a significant problem for older people and their caregivers. The ambient-assisted living applications are offering location-based services for empowering elderly to go outside and encouraging a greater independence. Therefore, this paper describes the design and technical evaluation of a location-awareness service enabler aimed at supporting and managing probable wandering situations of a person with MCI. Through the presence capabilities of the IP multimedia subsystem (IMS) architecture, the service will alert patient's contacts if a hazardous situation is detected depending on his location. Furthermore, information about the older person's security areas has been included in the user profile managed by IMS. In doing so, the service enabler introduced contribute to “context-awareness” paradigm allowing the adaptation and personalization of services depending on user's context and specific conditions or preferences

AALUMO: a user model ontology for ambient assisted living services supported in next-generation networks

Ambient Assisted Living (AAL) services are emerging as context-awareness solutions to support elderly people?s autonomy. The context-aware paradigm makes applications more user-adaptive. In this way, context and user models expressed in ontologies are employed by applications to describe user and environment characteristics. The rapid advance of technology allows creating context server to relieve applications of context reasoning techniques. Specifically, the Next Generation Networks (NGN) provides by means of the presence service a framework to manage the current user's state as well as the user's profile information extracted from Internet and mobile context. This paper propose a user modeling ontology for AAL services which can be deployed in a NGN environment with the aim at adapting their functionalities to the elderly's context information and state

Artificial intelligence methodologies and their application to diabetes

In the past decade diabetes management has been transformed by the addition of continuous glucose monitoring and insulin pump data. More recently, a wide variety of functions and physiologic variables, such as heart rate, hours of sleep, number of steps walked and movement, have been available through wristbands or watches. New data, hydration, geolocation, and barometric pressure, among others, will be incorporated in the future. All these parameters, when analyzed, can be helpful for patients and doctors' decision support. Similar new scenarios have appeared in most medical fields, in such a way that in recent years, there has been an increased interest in the development and application of the methods of artificial intelligence (AI) to decision support and knowledge acquisition. Multidisciplinary research teams integrated by computer engineers and doctors are more and more frequent, mirroring the need of cooperation in this new topic. AI, as a science, can be defined as the ability to make computers do things that would require intelligence if done by humans. Increasingly, diabetes-related journals have been incorporating publications focused on AI tools applied to diabetes. In summary, diabetes management scenarios have suffered a deep transformation that forces diabetologists to incorporate skills from new areas. This recently needed knowledge includes AI tools, which have become part of the diabetes health care. The aim of this article is to explain in an easy and plane way the most used AI methodologies to promote the implication of health care providers?doctors and nurses?in this field

Estudio comparativo de técnicas para la detección automática de patrones interictales en señal de EEG de pacientes epilépticos

La epilepsia es una afección neurológica grave que condiciona la calidad de vida de las personas que sufren de ella. Una de las labores de los neurólogos y neurofisiólogos consiste en revisar los Video-EEG de los pacientes epilépticos para analizar la semiología de las crisis epilépticas así como el patrón EEG crítico y los periodos intercríticos que se caracterizan por la aparición de descargas epileptiformes paroxísticas con frecuencia variable. Los registros pueden durar desde minutos hasta días, y la tarea de análisis del EEG por parte del especialista resulta lenta y agotadora. Frente esta problemática es deseable conseguir un programa de detección de eventos relevantes en el EEG que permita acortar el tiempo de análisis de los registros. El presente artículo se centra en definir un primer paso hacia el desarrollo de una aplicación que permita la detección de descargas epileptiformes interictales (DEI) de tipo punta en señales EEG de pacientes epilépticos. El objetivo es realizar un estudio comparativo entre dos métodos de detección: Filtros adaptados y la Transformada Wavelet Continua (CWT) evaluando los resultados con el parámetro de área bajo la curva (AUC) y la curva ROC. Los resultados muestran que el uso de la CWT es más eficiente a la hora de detectar puntas dentro de señales EEG que el Filtro adaptado. A pesar de los buenos resultados obtenidos, es necesario verificar ambos métodos con nuevos registros de datos y mejorar los procesos de automatización para conseguir un programa de detección fiable

TRHIOS: Trust and reputation in hierarchical and quality-oriented societies

In this paper we present TRHIOS: a Trust and Reputation system for HIerarchical and quality-Oriented Societies. We focus our work on hierarchical medical organizations. The model estimates the reputation of an individual, RTRHIOS, taking into account information from three trust dimensions: the hierarchy of the system; the source of information; and the quality of the results. Besides the concrete reputation value, it is important to know how reliable that value is; for each of the three dimensions we calculate the reliability of the assessed reputations; and aggregating them, the reliability of the reputation of an individual. The modular approach followed in the definition of the different types of reputations provides the system with a high flexibility that allows adapting the model to the peculiarities of each society

Determinación del estado metabólico de pacientes con diabetes gestacional mediante autómatas finitos

Los nuevos criterios de diagnóstico de la diabetes gestacional recomendados por la IADPSGC disminuyen los efectos adversos de la hiperglucemia tanto en la madre como en el recién nacido, pero su aplicación supondría un aumento de la prevalencia llegando a triplicar el número de casos actual. Para que los Servicios de Endocrinología y Nutrición puedan hacer frente a la carga que supondría este aumento de prevalencia es necesario emplear nuevos procesos asistenciales que incluyan el uso de las TICs. Este trabajo presenta una herramienta de análisis automático de datos de monitorización que determina el estado metabólico de las pacientes con diabetes gestacional a partir de sus datos de glucemia, dieta y cetonuria. Su diseño se basa en dos autómatas finitos, uno para el análisis de la glucemia y de la dieta y el otro para el análisis de la cetonuria. La salida de ambos autómatas se combina para determinar el estado metabólico de la paciente a lo largo del tiempo. La herramienta se ha evaluado con datos retrospectivos de 25 pacientes pertenecientes al Hospital Parc Taulí de Sabadell comparando los 1288 estados metabólicos resultantes con los 47 ajustes de terapia realizados por el equipo médico. Se observó que el 91,49% de los cambios de tratamiento coincidieron con estados metabólicos deficientes determinados por la herramienta de análisis. La herramienta ayuda a diferenciar pacientes complejas que requieren una evaluación exhaustiva y un ajuste de terapia de las que tienen buen control metabólico y no necesitan ser evaluadas por el personal médico

How Continuous Monitoring Changes the Interaction of Patients with a Mobile Telemedicine System

The use of continuous glucose monitor changes the way patients manage their diabetes, as observed in the increased number of daily insulin bolus, the increased number of daily BG measurements, and the differences in the distribution of BG measurements throughout the day. Continuous monitoring also increases the interaction of patients with the information system and modifies their patterns of use

Glucose-Insulin regulator for type 1 diabetes using high order neural networks

In this paper a Glucose-Insulin regulator for Type 1 Diabetes using artificial neural networks (ANN) is proposed. This is done using a discrete recurrent high order neural network in order to identify and control a nonlinear dynamical system which represents the pancreas? beta-cells behavior of a virtual patient. The ANN which reproduces and identifies the dynamical behavior system, is configured as series parallel and trained on line using the extended Kalman filter algorithm to achieve a quickly convergence identification in silico. The control objective is to regulate the glucose-insulin level under different glucose inputs and is based on a nonlinear neural block control law. A safety block is included between the control output signal and the virtual patient with type 1 diabetes mellitus. Simulations include a period of three days. Simulation results are compared during the overnight fasting period in Open-Loop (OL) versus Closed- Loop (CL). Tests in Semi-Closed-Loop (SCL) are made feedforward in order to give information to the control algorithm. We conclude the controller is able to drive the glucose to target in overnight periods and the feedforward is necessary to control the postprandial period

Quantifying the acute changes in glucose with exercise in type 1 Diabetes: a systematic review and meta-analysis

Background The acute impact of different types of physical activity on glycemic control in type 1 diabetes has not been well quantified. Objectives Our objective was to estimate the rate of change (RoC) in glucose concentration induced acutely during the performance of structured exercise and at recovery in subjects with type 1 diabetes. Methods We searched for original articles in the PubMed, MEDLINE, Scopus, and Cochrane databases. Search terms included type 1 diabetes, blood glucose, physical activity, and exercise. Eligible studies (randomized controlled trials and non-randomized experiments) encompassed controlled physical activity sessions (continuous moderate [CONT], intermittent high intensity [IHE], resistance [RESIST