Increased migration of olfactory ensheathing cells secreting the Nogo receptor ectodomain over inhibitory substrates and lesioned spinal cord

Olfactory ensheathing cell (OEC) transplantation emerged some years ago as a promising therapeutic strategy to repair injured spinal cord. However, inhibitory molecules are present for long periods of time in lesioned spinal cord, inhibiting both OEC migration and axonal regrowth. Two families of these molecules, chondroitin sulphate proteoglycans (CSPG) and myelin-derived inhibitors (MAIs), are able to trigger inhibitory responses in lesioned axons. Mounting evidence suggests that OEC migration is inhibited by myelin. Here we demonstrate that OEC migration is largely inhibited by CSPGs and that inhibition can be overcome by the bacterial enzyme Chondroitinase ABC. In parallel, we have generated a stable OEC cell line overexpressing the Nogo receptor (NgR) ectodomain to reduce MAI-associated inhibition in vitro and in vivo. Results indicate that engineered cells migrate longer distances than unmodified OECs over myelin or oligodendrocyte-myelin glycoprotein (OMgp)-coated substrates. In addition, they also show improved migration in lesioned spinal cord. Our results provide new insights toward the improvement of the mechanisms of action and optimization of OEC-based cell therapy for spinal cord lesion.     

Probability distributions,trading strategies and leverage: an application of Gaussian mixture models

The purpose of this paper is twofold. Firstly, to assess the merit of estimating probability density functions rather than level or classification estimations on a one‐day‐ahead forecasting task of the EUR/USD time series. This is implemented using a Gaussian mixture model neural network, benchmarking the results against standard forecasting models, namely a naïve model, a moving average convergence divergence technical model (MACD), an autoregressive moving average model (ARMA), a logistic regression model (LOGIT) and a multi‐layer perceptron network (MLP). Secondly, to examine the possibilities of improving the trading performance of those models with confirmation filters and leverage. While the benchmark models perform best without confirmation filters and leverage, the Gaussian mixture model outperforms all of the benchmarks when taking advantage of the possibilities offered by a combination of more sophisticated trading strategies and leverage. This might be due to the ability of the Gaussian mixture model to identify successfully trades with a high Sharpe ratio. Copyright © 2004 John Wiley & Sons, Ltd.     

A record of Permian subaqueous vent activity in southeastern Brazil

The remarkable occurrence of more than 4,500 conical siliceous mounds in an area of less than 1.5 square kilometres has been reported in the Paraná basin, near Anhembi, S?o Paulo, in southeastern Brazil. These structures, which are up to two metres high, are thought to have been formed at the margin of a very shallow, broad but waning internal sea, and it was originally suggested that they are stromatolites. Yet their restricted occurrence, unusual abundance and nearly pure siliceous composition have never been satisfactorily explained by this hypothesis. Here we report field and laboratory observations on their shape, construction, composition and mineralogy. On the basis of our data we suggest that the conical mounds are the result of subaqueous Late Permian vent activity in southwestern Gondwana. The present siliceous cone field differs considerably from other Palaeozoic siliceous hot spring deposits, such as those at Rhynie, Scotland, and the Drummond basin, Australia, and therefore represents an unusual occurrence of vent activity.