Transplantation of glial progenitor cells results in transplant-derived myelination and improved function in rodents with genetic dysmyelination or chemical demyelination. However, glial cell transplantation in adult CNS inflammatory demyelinating models has not been well studied. Here we transplanted human glial-restricted progenitor (hGRP) cells into the spinal cord of adult rats with inflammatory demyelination, and monitored cell fate in chemically immunosuppressed animals. We found that hGRPs migrate extensively, expand within inflammatory spinal cord lesions, do not form tumors, and adopt a mature glial phenotype, albeit at a low rate. Human GRPtransplanted rats, but not controls, exhibited preserved electrophysiological conduction across the spinal cord, though no differences in behavioral improvement were noted between the two groups. Although these hGRPs myelinated extensively after implantation into neonatal shiverer mouse brain, only marginal remyelination was observed in the inflammatory spinal cord demyelination model. The low rate of transplant-derived myelination in adult rat spinal cord may reflect host age, species, transplant environment/location, and/or immune suppression regime differences. We conclude that hGRPs have the capacity to myelinate dysmyelinated neonatal rodent brain and preserve conduction in the inflammatory demyelinated adult rodent spinal cord. The latter benefit is likely dependent on trophic support and suggests further exploration of potential of glial progenitors in animal models of chronic inflammatory demyelination.

A technique is introduced for estimating unknown parameters when time series of only one variable from a multivariate nonlinear dynamical system is given. The technique employs a combination of two different control methods, a linear feedback for synchronizing system variables and an adaptive control, and is based on dynamic minimization of synchronization error. The technique is shown to work even when the unknown parameters appear in the evolution equations of the variables other than the one for which the time series is given.The technique not only establishes that explicit detailed information about all system variables and parameters is contained in a scalar time series, but also gives a way to extract it out under suitable conditions. Illustrations are presented for Lorenz and Rössler systems and a nonlinear dynamical system in plasma physics. Also it is found that the technique is reasonably stable against noise in the given time series and the estimated value of a parameter fluctuates around the correct value, with the error of estimation growing linearly with the noise strength, for small noise.PACS number(s): 05.45+b,47.52.+j Typeset using REVT E X

We investigate the dynamics of peeling of an adhesive tape subjected to a constant pull speed. We derive the equations of motion for the angular speed of the roller tape, the peel angle and the pull force used in earlier investigations using a Lagrangian. Due to the constraint between the pull force, peel angle and the peel force, it falls into the category of differential-algebraic equations requiring an appropriate algorithm for its numerical solution. Using such a scheme, we show that stick-slip jumps emerge in a purely dynamical manner. Our detailed numerical study shows that these set of equations exhibit rich dynamics hitherto not reported. In particular, our analysis shows that inertia has considerable influence on the nature of the dynamics. Following studies in the Portevin-Le Chatelier effect, we suggest a phenomenological peel force function which includes the influence of the pull speed. This reproduces the decreasing nature of the rupture force with the pull speed observed in experiments. This rich dynamics is made transparent by using a set of approximations valid in different regimes of the parameter space. The approximate solutions capture major features of the exact numerical solutions and also produce reasonably accurate values for the various quantities of interest.