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Contralateral C7 (cC7) root transfer to the healthy side is the main method for the treatment of brachial plexus root injury. A relatively new modification of this method involves cC7 root transfer to the lower trunk via the prespinal route. In the current study, we examined the effectiveness of this method using electrophysiological and histological analyses. To this end, we used a rat model of total brachial plexus injury, and cC7 root transfer was performed to either the lower trunk via the prespinal route or the median nerve via a subcutaneous tunnel to repair the injury. At 4, 8 and 12 weeks, the grasping test was used to measure the changes in grasp strength of the injured forepaw. Electrophysiological changes were examined in the flexor digitorum superficialis muscle. The change in the wet weight of the forearm flexor was also measured. Atrophy of the flexor digitorum superficialis muscle was assessed by hematoxylin-eosin staining. Toluidine blue staining was used to count the number of myelinated nerve fibers in the injured nerves. Compared with the traditional method, cC7 root transfer to the lower trunk via the prespinal route increased grasp strength of the injured forepaw, increased the compound muscle action potential maximum amplitude, shortened latency, substantially restored tetanic contraction of the forearm flexor muscles, increased the wet weight of the muscle, reduced atrophy of the flexor digitorum superficialis muscle, and increased the number of myelinated nerve fibers. These findings demonstrate that for finger flexion functional recovery in rats with total brachial plexus injury, transfer of the cC7 root to the lower trunk via the prespinal route is more effective than transfer to the median nerve via subcutaneous tunnel.
Pubmed ID: 30233071
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Software package used for interactive, or batched, statistical analysis in social science, health sciences and marketing. Software platform offers advanced statistical analysis, a library of machine-learning algorithms, text analysis, open-source extensibility, integration with big data and deployment into applications.Versions that were produced by SPSS Inc. before the IBM acquisition (Versions 18 and earlier) would be given origin or publisher of SPSS Inc. in Chicago.
View all literature mentionsNeuroMatic is a collection of Igor Pro functions for analyzing electrophysiological data. By allowing users to organize their data into Sets and Groups, NeuroMatic makes it relatively easy to compute transformations and statistical analyses on their data, including scaling, alignment averaging, baseline subtraction, spike detection, stationarity analysis, rise-time computations, etc. Being open source and modular designed, NeuroMatic also allows users to develop their own analysis functions that can be easily incorporated into NeuroMatic's framework. Note, if you have reached this page in search of a freeware tool for neuronal reconstructions, you are more likely to be interested in Neuromantic, a software package that sounds like NeuroMatic, but is not quite the same. Features of NeuroMatic Include * Sorting, Scaling, Averaging, Interpolation * Max / Min / Mean / Level / Rise Time / FWHM / Slope Measurements * Stability / Stationarity Analysis * Event Detection * Waveform Template Matching * Spike Raster Plots * Interspike-Interval and Peri-Stimulus Time (PST) Histograms * Compact Easy-to-Use Interface * Modular design as a basis for your own procedures * Extra space for your own buttons and controls * Import functions for Axograph and Pclamp data * Automatic macro generation for batch processing Supporting Agencies: MRC, Wellcome Trust Spike, Event, Fit, NClamp, Acquisition, spike train, EPSP, IPSP, IPSC, EPSC
View all literature mentionsWelcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
