6 resultados para action potential

em Universidad Politécnica de Madrid


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Axonal outgrowth and the formation of the axon initial segment (AIS) are early events in the acquisition of neuronal polarity. The AIS is characterized by a high concentration of voltage-dependent sodium and potassium channels. However, the specific ion channel subunits present and their precise localization in this axonal subdomain vary both during development and among the types of neurons, probably determining their firing characteristics in response to stimulation. Here, we characterize the developmental expression of different subfamilies of voltage-gated potassium channels in the AISs of cultured mouse hippocampal neurons, including subunits Kv1.2, Kv2.2 and Kv7.2. In contrast to the early appearance of voltage-gated sodium channels and the Kv7.2 subunit at the AIS, Kv1.2 and Kv2.2 subunits were tethered at the AIS only after 10 days in vitro. Interestingly, we observed different patterns of Kv1.2 and Kv2.2 subunit expression, with each confined to distinct neuronal populations. The accumulation of Kv1.2 and Kv2.2 subunits at the AIS was dependent on ankyrin G tethering, it was not affected by disruption of the actin cytoskeleton and it was resistant to detergent extraction, as described previously for other AIS proteins. This distribution of potassium channels in the AIS further emphasizes the heterogeneity of this structure in different neuronal populations, as proposed previously, and suggests corresponding differences in action potential regulation.

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Situado en el límite entre Ingeniería, Informática y Biología, la mecánica computacional de las neuronas aparece como un nuevo campo interdisciplinar que potencialmente puede ser capaz de abordar problemas clínicos desde una perspectiva diferente. Este campo es multiescala por naturaleza, yendo desde la nanoescala (como, por ejemplo, los dímeros de tubulina) a la macroescala (como, por ejemplo, el tejido cerebral), y tiene como objetivo abordar problemas que son complejos, y algunas veces imposibles, de estudiar con medios experimentales. La modelización computacional ha sido ampliamente empleada en aplicaciones Neurocientíficas tan diversas como el crecimiento neuronal o la propagación de los potenciales de acción compuestos. Sin embargo, en la mayoría de los enfoques de modelización hechos hasta ahora, la interacción entre la célula y el medio/estímulo que la rodea ha sido muy poco explorada. A pesar de la tremenda importancia de esa relación en algunos desafíos médicos—como, por ejemplo, lesiones traumáticas en el cerebro, cáncer, la enfermedad del Alzheimer—un puente que relacione las propiedades electrofisiológicas-químicas y mecánicas desde la escala molecular al nivel celular todavía no existe. Con ese objetivo, esta investigación propone un marco computacional multiescala particularizado para dos escenarios respresentativos: el crecimiento del axón y el acomplamiento electrofisiológicomecánico de las neuritas. En el primer caso, se explora la relación entre los constituyentes moleculares del axón durante su crecimiento y sus propiedades mecánicas resultantes, mientras que en el último, un estímulo mecánico provoca deficiencias funcionales a nivel celular como consecuencia de sus alteraciones electrofisiológicas-químicas. La modelización computacional empleada en este trabajo es el método de las diferencias finitas, y es implementada en un nuevo programa llamado Neurite. Aunque el método de los elementos finitos es también explorado en parte de esta investigación, el método de las diferencias finitas tiene la flexibilidad y versatilidad necesaria para implementar mode los biológicos, así como la simplicidad matemática para extenderlos a simulaciones a gran escala con un coste computacional bajo. Centrándose primero en el efecto de las propiedades electrofisiológicas-químicas sobre las propiedades mecánicas, una versión adaptada de Neurite es desarrollada para simular la polimerización de los microtúbulos en el crecimiento del axón y proporcionar las propiedades mecánicas como función de la ocupación de los microtúbulos. Después de calibrar el modelo de crecimiento del axón frente a resultados experimentales disponibles en la literatura, las características mecánicas pueden ser evaluadas durante la simulación. Las propiedades mecánicas del axón muestran variaciones dramáticas en la punta de éste, donde el cono de crecimiento soporta las señales químicas y mecánicas. Bansándose en el conocimiento ganado con el modelo de diferencias finitas, y con el objetivo de ir de 1D a 3D, este esquema preliminar pero de una naturaleza innovadora allana el camino a futuros estudios con el método de los elementos finitos. Centrándose finalmente en el efecto de las propiedades mecánicas sobre las propiedades electrofisiológicas- químicas, Neurite es empleado para relacionar las cargas mecánicas macroscópicas con las deformaciones y velocidades de deformación a escala microscópica, y simular la propagación de la señal eléctrica en las neuritas bajo carga mecánica. Las simulaciones fueron calibradas con resultados experimentales publicados en la literatura, proporcionando, por tanto, un modelo capaz de predecir las alteraciones de las funciones electrofisiológicas neuronales bajo cargas externas dañinas, y uniendo lesiones mecánicas con las correspondientes deficiencias funcionales. Para abordar simulaciones a gran escala, aunque otras arquitecturas avanzadas basadas en muchos núcleos integrados (MICs) fueron consideradas, los solvers explícito e implícito se implementaron en unidades de procesamiento central (CPU) y unidades de procesamiento gráfico (GPUs). Estudios de escalabilidad fueron llevados acabo para ambas implementaciones mostrando resultados prometedores para casos de simulaciones extremadamente grandes con GPUs. Esta tesis abre la vía para futuros modelos mecánicos con el objetivo de unir las propiedades electrofisiológicas-químicas con las propiedades mecánicas. El objetivo general es mejorar el conocimiento de las comunidades médicas y de bioingeniería sobre la mecánica de las neuronas y las deficiencias funcionales que aparecen de los daños producidos por traumatismos mecánicos, como lesiones traumáticas en el cerebro, o enfermedades neurodegenerativas como la enfermedad del Alzheimer. ABSTRACT Sitting at the interface between Engineering, Computer Science and Biology, Computational Neuron Mechanics appears as a new interdisciplinary field potentially able to tackle clinical problems from a new perspective. This field is multiscale by nature, ranging from the nanoscale (e.g., tubulin dimers) to the macroscale (e.g., brain tissue), and aims at tackling problems that are complex, and sometime impossible, to study through experimental means. Computational modeling has been widely used in different Neuroscience applications as diverse as neuronal growth or compound action potential propagation. However, in the majority of the modeling approaches done in this field to date, the interactions between the cell and its surrounding media/stimulus have been rarely explored. Despite of the tremendous importance of such relationship in several medical challenges—e.g., traumatic brain injury (TBI), cancer, Alzheimer’s disease (AD)—a bridge between electrophysiological-chemical and mechanical properties of neurons from the molecular scale to the cell level is still lacking. To this end, this research proposes a multiscale computational framework particularized for two representative scenarios: axon growth and electrophysiological-mechanical coupling of neurites. In the former case, the relation between the molecular constituents of the axon during its growth and its resulting mechanical properties is explored, whereas in the latter, a mechanical stimulus provokes functional deficits at cell level as a consequence of its electrophysiological-chemical alterations. The computational modeling approach chosen in this work is the finite difference method (FDM), and was implemented in a new program called Neurite. Although the finite element method (FEM) is also explored as part of this research, the FDM provides the necessary flexibility and versatility to implement biological models, as well as the mathematical simplicity to extend them to large scale simulations with a low computational cost. Focusing first on the effect of electrophysiological-chemical properties on the mechanical proper ties, an adaptation of Neurite was developed to simulate microtubule polymerization in axonal growth and provide the axon mechanical properties as a function of microtubule occupancy. After calibrating the axon growth model against experimental results available in the literature, the mechanical characteristics can be tracked during the simulation. The axon mechanical properties show dramatic variations at the tip of the axon, where the growth cone supports the chemical and mechanical signaling. Based on the knowledge gained from the FDM scheme, and in order to go from 1D to 3D, this preliminary yet novel scheme paves the road for future studies with FEM. Focusing then on the effect of mechanical properties on the electrophysiological-chemical properties, Neurite was used to relate macroscopic mechanical loading to microscopic strains and strain rates, and simulate the electrical signal propagation along neurites under mechanical loading. The simulations were calibrated against experimental results published in the literature, thus providing a model able to predict the alteration of neuronal electrophysiological function under external damaging load, and linking mechanical injuries to subsequent acute functional deficits. To undertake large scale simulations, although other state-of-the-art architectures based on many integrated cores (MICs) were considered, the explicit and implicit solvers were implemented for central processing units (CPUs) and graphics processing units (GPUs). Scalability studies were done for both implementations showing promising results for extremely large scale simulations with GPUs. This thesis opens the avenue for future mechanical modeling approaches aimed at linking electrophysiological- chemical properties to mechanical properties. Its overarching goal is to enhance the bioengineering and medical communities knowledge on neuronal mechanics and functional deficits arising from damages produced by direct mechanical insults, such as TBI, or neurodegenerative evolving illness, such as AD.

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Pesticide applications are still one of the most common control methods against the main olive grove pests and diseases: the olive fruit fly, Bactrocera oleae (Rossi), the olive moth, Prays oleae (Bernard), the black scale, Saissetia oleae (Olivier), and the olive leaf spot, caused by the fungus Spilocaea oleagina Fries. However, and because the new pesticide legislation is aimed at an integrated pest and disease management, it is still important to evaluate and to know the ecotoxicology of pesticides on the natural enemies of the different agrosystems. A part of this work has been focusses on evaluating the direct and indirect effects of kaolin particle films and two copper-based products (Bordeaux mixture and copper oxychloride) through different laboratory, extended laboratory and semi-field experiments. Two natural enemies have been chosen: Psyttalia concolor (Szèpligeti), a parasitoid of the olive fruit fly, and Chilocorus nigritus (F.), predator of Diaspididae. This predator has been used instead of C. bipustulatus (L.), which is the species found in olive orchards. Kaolin mainly acts as a repellent of insects and/or as an oviposition deterrent. It is used in olive groves to control the olive fruit fly and the olive moth. Copper is applied against fungal and bacterial diseases. In olive groves it is used against the olive leaf spot and other diseases. No statistical differences were found in any of the experiments performed, compared to the controls, except when the oral toxicity of the products was evaluated on P. concolor females. In this case, kaolin and copper oxychloride caused a higher mortality 72 hours after the treatments, and both kaolin and the two copper formulations decreased females’ life span. Reproductive parameters were only negatively affected when kaolin was ingested. Apart from these experiments, due to the uncommon mode of action of kaolin, two extra experiments were carried out: a dual choice and a no-choice experiment. In this case, both P. concolor females and C. nigritus adults showed a clear preference for the untreated surfaces when they had the possibility of choosing between a treated surface and an untreated one. When there was no choice, no statistical differences were found between the treatments and the controls. Furthermore, the efficacy and the selectivity of three insect growth regulators (methoxyfenozide, tebufenozide and RH-5849) on B. oleae and P. concolor, respectively, have also been evaluated. In addition to laboratory experiments to evaluate the toxicity of the insecticides, also molecular approaches were used. RNA of both insects was isolated. cDNA was subsequently synthesized and the complete sequences of the ligand biding domain (LBD) of the ecdysone receptor of each insect were then determined. Afterwards the three dimensional structures of both LBDs were constructed. Finally, the docking of the insecticide molecules in the cavity delineated by the 12 α-helix that composed the LBD was performed. Both toxicity assays and molecular docking approaches showed that either methoxyfenozide or tebufenozide had no negative effects nor on B. oleae nor on P. concolor. In contrast, RH-5849 had no deleterious effect to the parasitoid but decreased olive fruit fly adults’ life span, especially when they were in contact with the fresh residue of the insecticide applied on a glass surface. The docking study of RH-5849 molecule has shown a very light hindrance with the wall of the LBD pocket. This means that this molecule could more or less adjust in the cavity. Thus, searching of new insecticides for controlling the olive fruit fly could be based on the basic lead structure of RH-5849 molecule.

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Phenomenal states are generally considered the ultimate sources of intrinsic motivation for autonomous biological agents. In this article, we will address the issue of the necessity of exploiting these states for the design and implementation of robust goal-directed artificial systems. We will provide an analysis of consciousness in terms of a precise definition of how an agent "understands" the informational flows entering the agent and its very own action possibilities. This abstract model of consciousness and understanding will be based in the analysis and evaluation of phenomenal states along potential future trajectories in the state space of the agents. This implies that a potential strategy to follow in order to build autonomous but still customer-useful systems is to embed them with the particular, ad hoc phenomenality that captures the system-external requirements that define the system usefulness from a customer-based, requirements-strict engineering viewpoint.

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The third Training School of the Action took place in Vitoria-Gasteiz (Basque country, Spain) from 24th to 26th September 2014. Vitoria-Gateiz has experimented an important urban outgrowth in the last decade, mainly through the planning and development of two new neighborhoods, Zabalgana and Salburúa, situated at the eastern and western border of the city, by the Greenbelt. These new development are well-equipped and designed according to sustainability principles. Nevertheless, among the main problems they present is their over-dimensioned public space, which creates some areas lacking enough density and mix of uses. On the other hand it is very expensive for the municipality to maintain these public space with the high Vitorian urban standards for public space. The proposed solution for this problem is a strategy of "re-densification" through the insertion of new uses The debate has arisen about which are the most adequate uses to insert in order to get an increasing of urban vitality, specially considering that housing has reached its peak and that Vitoria-Gasteiz is well served with social and sport amenities. The main goal of the TS was to offer an opportunity for the reflection about how urban agriculture might be an optimal alternative for the re-qualifying of this over-dimensioned public space in the new neighbourhoods, especially considering it synergic potential as a tool for production, leisure and landscaping, including the possibility of energy crops within the limits of urban space. Continuity with rural and natural surrounding area through alternatives for urban fringe at the small scale is a relevant issue to be considered as well within the reflection. Taking Zabalgana neighbourhood as a practical field for experiment, the Training School is conceived as a practical and intensive design charrette to be held during a whole day after two days of local knowledge-deepening through field visits and presentations.

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Biomass has always been associated with the development of the population in the Canary Islands as the first source of elemental energy that was in the archipelago and the main cause of deforestation of forests, which over the years has been replaced by forest fossil fuels. The Canary Islands store a large amount of energy in the form of biomass. This may be important on a small scale for the design of small power plants with similar fuels from agricultural activities, and these plants could supply rural areas that could have self-sufficiency energy. The problem with the Canary Islands for a boost in this achievement is to ensure the supply to the consumer centers or power plants for greater efficiency that must operate continuously, allowing them to have a resource with regularity, quality and at an acceptable cost. In the Canary Islands converge also a unique topography with a very rugged terrain that makes it greater difficult to use and significantly more expensive. In this work all these aspects are studied, giving conclusions, action paths and theoretical potentials.