The investigation of the neuronal network in mouse spinal cord models represents the basis for the research on neurodegenerative diseases. In this framework, the quantitative analysis of the single elements in different districts is a crucial task. However, conventional 3D imaging techniques do not have enough spatial resolution and contrast to allow for a quantitative investigation of the neuronal network. Exploiting the high coherence and the high flux of synchrotron sources, X-ray Phase-Contrast multiscale-Tomography allows for the 3D investigation of the neuronal microanatomy without any aggressive sample preparation or sectioning. We investigated healthy-mouse neuronal architecture by imaging the 3D distribution of the neuronal-network with a spatial resolution of 640 nm. Thanks to the high spatial resolution and large field of view, we were able to perform a detailed quantitative analysis of the neuronal network. In particular, we analyzed the reconstructed volume of the axial section of the spinal cord ventral horn (about 1 mm thick). This region includes groups of cells that form motor nuclei in the Lamina IX . Spatial statistical analysis was employed to obtain quantitative information about motor neurons arrangement at different levels of the spinal cord . To this end, we defined the following parameters, to effectively characterize the neurons spatial distribution: 1)Clustering length and degree, that tell us whether the neurons are aggregated (clustering) or dispersed (anti-clustering) in comparison to a Complete State of Randomness described by a homogenous Poisson process. 2)A regularity factor, given by the Voronoi tessellation, describing whether neurons are located in a more or less uniform way . Since these characteristic parameters of the neuronal microanatomy are expected to change in pathological conditions, we applied the spatial statistical analysis to detect and quantitatively characterize the modification of the motor neurons networks in different pathological system. In conclusion, we developed and applied a spatial statistical analysis on the motor neurons to obtain quantitative information on their 3D arrangement in the healthy-mice spinal cord and in pathological systemfor a comparative investigation of neurodegenerative diseases and therapies.
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