2 resultados para Motoneurons

em CentAUR: Central Archive University of Reading - UK


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The lymph heart is a sac-like structure on either side of avian tail. In some adult birds, it empties the lymph from the copulatory organ; however, during embryonic development, it is thought to circulate extra-embryonic lymph. Very little is known about the origin, innervation and the cellular changes it undergoes during development. Using immunohistochemistry and gene expression profiling we show that the musculature of the lymph heart is initially composed solely of striated skeletal muscle but later develops an additional layer composed of smooth myofibroblasts. Chick-quail fate-mapping demonstrates that the lymph heart originates from the hypaxial compartments of somites 34-41. The embryonic lymph heart is transiently innervated by somatic motoneurons with no autonomic input. In comparison to body muscles, the lymph heart has different sensitivity to neuromuscular junction blockers (sensitive only to decamethonium). Furthermore, its abundant bungarotoxin-positive acetylcholinesterase receptors are unique as they completely lack specific acetylcholinesterase activity. Several lines of evidence suggest that the lymph heart may possess an intrinsic pacing mechanism. Finally, we assessed the function of the lymph heart during embryogenesis and demonstrate that it is responsible for preventing embryonic oedema in birds, a role previously thought to be played by body skeletal muscle contractions.

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An important goal in computational neuroanatomy is the complete and accurate simulation of neuronal morphology. We are developing computational tools to model three-dimensional dendritic structures based on sets of stochastic rules. This paper reports an extensive, quantitative anatomical characterization of simulated motoneurons and Purkinje cells. We used several local and global algorithms implemented in the L-Neuron and ArborVitae programs to generate sets of virtual neurons. Parameters statistics for all algorithms were measured from experimental data, thus providing a compact and consistent description of these morphological classes. We compared the emergent anatomical features of each group of virtual neurons with those of the experimental database in order to gain insights on the plausibility of the model assumptions, potential improvements to the algorithms, and non-trivial relations among morphological parameters. Algorithms mainly based on local constraints (e.g., branch diameter) were successful in reproducing many morphological properties of both motoneurons and Purkinje cells (e.g. total length, asymmetry, number of bifurcations). The addition of global constraints (e.g., trophic factors) improved the angle-dependent emergent characteristics (average Euclidean distance from the soma to the dendritic terminations, dendritic spread). Virtual neurons systematically displayed greater anatomical variability than real cells, suggesting the need for additional constraints in the models. For several emergent anatomical properties, a specific algorithm reproduced the experimental statistics better than the others did. However, relative performances were often reversed for different anatomical properties and/or morphological classes. Thus, combining the strengths of alternative generative models could lead to comprehensive algorithms for the complete and accurate simulation of dendritic morphology.