Eficacia y seguridad de la melatonina para el manejo de los trastornos del sueño en el autismo: meta-análisis

INTRODUCCIÓN: El 80% de los niños y adolescentes con trastornos del espectro autista (TEA) presenta algún trastorno del sueño, en cuya génesis al parecer intervienen alteraciones en la regulación de la melatonina. El objetivo de este metaanálisis fue determinar la eficacia y seguridad de la melatonina para el manejo de ciertos trastornos del sueño en niños con TEA. MÉTODOS: Tres revisores extrajeron los datos relevantes de los ensayos clínicos aleatorizados doble ciego de alta calidad publicados en bases de datos primarias, de ensayos clínicos, de revisiones sistemáticas y de literatura gris; además se realizó búsqueda en bola de nieve. Se analizaron los datos con RevMan 5.3. Se realizó un análisis del inverso de la varianza por un modelo de efectos aleatorios para las diferencias de medias de los desenlaces propuestos: duración del tiempo total, latencia de sueño y número de despertares nocturnos. Se evaluó la heterogeneidad interestudios con el parámetro I2 RESULTADOS: La búsqueda inicial arrojó 355 resultados, de los cuales tres cumplieron los criterios de selección. La melatonina resultó ser un medicamento seguro y eficaz para aumentar la duración total del sueño y disminuir la latencia de sueño en niños y adolescentes con TEA; hasta el momento la evidencia sobre el número de despertares nocturnos no es estadísticamente significativa. DISCUSIÓN: A la luz de la evidencia disponible, la melatonina es una elección segura y eficaz para el manejo de ciertos problemas del sueño en niños y adolescentes con TEA. Es necesario realizar estudios con mayores tamaños muestrales y comparados con otros medicamentos disponibles en el mercado.

Modeling tuition fees in presence of social heterogeneity. 'Como modelar las tasas de matrícula en presencia de la heterogeneidad social'.

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Prediction of the bulking phenomenon in wastewater treatment plants

The control and prediction of wastewater treatment plants poses an important goal: to avoid breaking the environmental balance by always keeping the system in stable operating conditions. It is known that qualitative information — coming from microscopic examinations and subjective remarks — has a deep influence on the activated sludge process. In particular, on the total amount of effluent suspended solids, one of the measures of overall plant performance. The search for an input–output model of this variable and the prediction of sudden increases (bulking episodes) is thus a central concern to ensure the fulfillment of current discharge limitations. Unfortunately, the strong interrelation between variables, their heterogeneity and the very high amount of missing information makes the use of traditional techniques difficult, or even impossible. Through the combined use of several methods — rough set theory and artificial neural networks, mainly — reasonable prediction models are found, which also serve to show the different importance of variables and provide insight into the process dynamics

Optimal management of natural resources. Accounting for heterogeneity

Dynamic optimization methods have become increasingly important over the last years in economics. Within the dynamic optimization techniques employed, optimal control has emerged as the most powerful tool for the theoretical economic analysis. However, there is the need to advance further and take account that many dynamic economic processes are, in addition, dependent on some other parameter different than time. One can think of relaxing the assumption of a representative (homogeneous) agent in macro- and micro-economic applications allowing for heterogeneity among the agents. For instance, the optimal adaptation and diffusion of a new technology over time, may depend on the age of the person that adopted the new technology. Therefore, the economic models must take account of heterogeneity conditions within the dynamic framework. This thesis intends to accomplish two goals. The first goal is to analyze and revise existing environmental policies that focus on defining the optimal management of natural resources over time, by taking account of the heterogeneity of environmental conditions. Thus, the thesis makes a policy orientated contribution in the field of environmental policy by defining the necessary changes to transform an environmental policy based on the assumption of homogeneity into an environmental policy which takes account of heterogeneity. As a result the newly defined environmental policy will be more efficient and likely also politically more acceptable since it is tailored more specifically to the heterogeneous environmental conditions. Additionally to its policy orientated contribution, this thesis aims making a methodological contribution by applying a new optimization technique for solving problems where the control variables depend on two or more arguments --- the so-called two-stage solution approach ---, and by applying a numerical method --- the Escalator Boxcar Train Method --- for solving distributed optimal control problems, i.e., problems where the state variables, in addition to the control variables, depend on two or more arguments. Chapter 2 presents a theoretical framework to determine optimal resource allocation over time for the production of a good by heterogeneous producers, who generate a stock externalit and derives government policies to modify the behavior of competitive producers in order to achieve optimality. Chapter 3 illustrates the method in a more specific context, and integrates the aspects of quality and time, presenting a theoretical model that allows to determine the socially optimal outcome over time and space for the problem of waterlogging in irrigated agricultural production. Chapter 4 of this thesis concentrates on forestry resources and analyses the optimal selective-logging regime of a size-distributed forest.

Real-Time software control of neural stimulation in a closed loop Animat system

A recent area for investigation into the development of adaptable robot control is the use of living neuronal networks to control a mobile robot. The so-called Animat paradigm comprises a neuronal network (the ‘brain’) connected to an external embodiment (in this case a mobile robot), facilitating potentially robust, adaptable robot control and increased understanding of neural processes. Sensory input from the robot is provided to the neuronal network via stimulation on a number of electrodes embedded in a specialist Petri dish (Multi Electrode Array (MEA)); accurate control of this stimulation is vital. We present software tools allowing precise, near real-time control of electrical stimulation on MEAs, with fast switching between electrodes and the application of custom stimulus waveforms. These Linux-based tools are compatible with the widely used MEABench data acquisition system. Benefits include rapid stimulus modulation in response to neuronal activity (closed loop) and batch processing of stimulation protocols.

Detection of Parkinson’s disease tremor-onset with a frequency analysing artificial neural network

Deep Brain Stimulator devices are becoming widely used for therapeutic benefits in movement disorders such as Parkinson's disease. Prolonging the battery life span of such devices could dramatically reduce the risks and accumulative costs associated with surgical replacement. This paper demonstrates how an artificial neural network can be trained using pre-processing frequency analysis of deep brain electrode recordings to detect the onset of tremor in Parkinsonian patients. Implementing this solution into an 'intelligent' neurostimulator device will remove the need for continuous stimulation currently used, and open up the possibility of demand-driven stimulation. Such a methodology could potentially decrease the power consumption of a deep brain pulse generator.

The effects of scene heterogeneity on soil moisture retrieval from passive microwave data

The s–x model of microwave emission from soil and vegetation layers is widely used to estimate soil moisture content from passive microwave observations. Its application to prospective satellite-based observations aggregating several thousand square kilometres requires understanding of the effects of scene heterogeneity. The effects of heterogeneity in soil surface roughness, soil moisture, water area and vegetation density on the retrieval of soil moisture from simulated single- and multi-angle observing systems were tested. Uncertainty in water area proved the most serious problem for both systems, causing errors of a few percent in soil moisture retrieval. Single-angle retrieval was largely unaffected by the other factors studied here. Multiple-angle retrievals errors around one percent arose from heterogeneity in either soil roughness or soil moisture. Errors of a few percent were caused by vegetation heterogeneity. A simple extension of the model vegetation representation was shown to reduce this error substantially for scenes containing a range of vegetation types.

Effects of sub-pixel heterogeneity on the retrieval of soil moisture from passive microwave radiometry

A simple formulation relating the L-band microwave brightness temperature detected by a passive microwave radiometer to the near surface soil moisture was developed using MICRO-SWEAT, a coupled microwave emission model and soil-vegetation-atmosphere-transfer (SVAT) scheme. This simple model provides an ideal tool with which to explore the impact of sub-pixel heterogeneity on the retrieval of soil moisture from microwave brightness temperatures. In the case of a bare soil pixel, the relationship between apparent emissivity and surface soil moisture is approximately linear, with the clay content of the soil influencing just the intercept of this relationship. It is shown that there are no errors in the retrieved soil moisture from a bare soil pixel that is heterogeneous in soil moisture and texture. However, in the case of a vegetated pixel, the slope of the relationship between apparent emissivity and surface soil moisture decreases with increasing vegetation. Therefore for a pixel that is heterogeneous in vegetation and soil moisture, errors can be introduced into the retrieved soil moisture. Generally, under moderate conditions, the retrieved soil moisture is within 3% of the actual soil moisture. Examples illustrating this discussion use data collected during the Southern Great Plains '97 Experiment (SGP97).

Influence of host plant heterogeneity on the distribution of a birch aphid

1. The spatial and temporal abundance of the aphid Euceraphis betulae was investigated in relation to heterogeneity in host plant ( Betula pendula) vigour and pathogenic stress. The performance of aphids feeding on vigorous and stressed foliage was also examined. 2. The plant stress and plant vigour hypotheses have been suggested as opposing ways in which foliage quality influences herbivore abundance. In many plants, however, vigorous growing foliage co-exists with stressed or damaged foliage. 3. There was a negative correlation between branch growth ( vigour) and branch stress ( leaf chlorosis), with the most vigorous branches displaying little or no stress, and the most stressed branches achieving poor growth. There was a similar negative correlation between vigour and stress at the level of individual trees, which themselves represented a continuum in quality. 4. At the beginning of the season, E. betulae were intermittently more abundant on vigorous branches than on branches destined to become stressed, but aphids became significantly more abundant on stressed branches later in the season, when symptoms of stress became apparent. Similar patterns of aphid abundance were seen on vigorous and stressed trees in the following year. 5. Euceraphis betulae performance was generally enhanced when feeding on naturally stressed B. pendula leaves, but there was some evidence for elevated potential reproduction when feeding on vigorous leaves too. 6. Overall, plant stress probably influences E. betulae distribution more than plant vigour, but the temporal and spatial variability in plant quality suggests that plant vigour could play a role in aphid distribution early in the season.

Perceived controllability modulates the neural response to pain

The response to painful stimulation depends not only on peripheral nociceptive input but also on the cognitive and affective context in which pain occurs. One contextual variable that affects the neural and behavioral response to nociceptive stimulation is the degree to which pain is perceived to be controllable. Previous studies indicate that perceived controllability affects pain tolerance, learning and motivation, and the ability to cope with intractable pain, suggesting that it has profound effects on neural pain processing. To date, however, no neuroimaging studies have assessed these effects. We manipulated the subjects' belief that they had control over a nociceptive stimulus, while the stimulus itself was held constant. Using functional magnetic resonance imaging, we found that pain that was perceived to be controllable resulted in attenuated activation in the three neural areas most consistently linked with pain processing: the anterior cingulate, insular, and secondary somatosensory cortices. This suggests that activation at these sites is modulated by cognitive variables, such as perceived controllability, and that pain imaging studies may therefore overestimate the degree to which these responses are stimulus driven and generalizable across cognitive contexts. [References: 28]