Pre- and postsynaptic localization of RC3/neurogranin in the adult rat spinal cord:An immunohistochemical study

RC3 (neurogranin; BICKS) is a neuron-specific calmodulin-binding protein kinase C substrate. Thus far, immunohistochemical studies on the localization of RC3 revealed its presence in all neuronal phenotypes, which were restricted to specific areas in the neostriatum, the neocortex, and the hippocampus. RC3 was mostly found in cell bodies and dendrites, with some infrequent presence in axonal profiles, i.e. in the internal capsule. Until now, RC3 expression was reported to be absent in the adult rat spinal cord. RC3 might, however, act as an intermediate of protein kinase C-mediated signaling pathways during synaptic development and plasticity. We hypothesized a role for this 78-amino-acid protein in dendritic plasticity occurring after spinal cord injury. To our surprise, an immunohistological analysis of the uninjured adult rat spinal cord revealed the presence of RC3-positive cell bodies and dendrites in specific regions in the gray matter. Interestingly, axon-containing structures, such as the dorsal and ventral corticospinal tract, were also found to be RCS-positive. This axonal labeling was confirmed by preembedding electron microscopy. In conclusion, we demonstrate here that RC3 is present in the adult rat spinal cord in pre- and postsynaptic structures. J. Neurosci. Res. 59: 750-759, 2000. (C) 2000 Wiley-Liss, Inc.</p

Automated extraction and validation of children\u27s gait parameters with the Kinect

Background: Gait analysis for therapy regimen prescription and monitoring requires patients to physically access clinics with specialized equipment. The timely availability of such infrastructure at the right frequency is especially important for small children. Besides being very costly, this is a challenge for many children living in rural areas. This is why this work develops a low-cost, portable, and automated approach for in-home gait analysis, based on the Microsoft Kinect. Methods: A robust and efficient method for extracting gait parameters is introduced, which copes with the high variability of noisy Kinect skeleton tracking data experienced across the population of young children. This is achieved by temporally segmenting the data with an approach based on coupling a probabilistic matching of stride template models, learned offline, with the estimation of their global and local temporal scaling. A preliminary study conducted on healthy children between 2 and 4 years of age is performed to analyze the accuracy, precision, repeatability, and concurrent validity of the proposed method against the GAITRite when measuring several spatial and temporal children’s gait parameters. Results: The method has excellent accuracy and good precision, with segmenting temporal sequences of body joint locations into stride and step cycles. Also, the spatial and temporal gait parameters, estimated automatically, exhibit good concurrent validity with those provided by the GAITRite, as well as very good repeatability. In particular, on a range of nine gait parameters, the relative and absolute agreements were found to be good and excellent, and the overall agreements were found to be good and moderate. Conclusion: This work enables and validates the automated use of the Kinect for children’s gait analysis in healthy subjects. In particular, the approach makes a step forward towards developing a low-cost, portable, parent-operated in-home tool for clinicians assisting young children