The Role of EphA4 in Glial Scar Formation Following Injury

Although many areas of the brain lose their regenerative capacity with age, stem cell niches have been identified in both the subventricular zone (SVZ) along the lateral walls of the lateral ventricles and the subgranular zone (SGZ) of the dentate gyrus (Gage, 2000; Alvarez-Buylla et al., 2001; Alvarez-Buylla and Lim, 2004). The SVZ niche utilizes many mechanisms to determine the migration patterns of neuroblasts along the RMS into the olfactory bulb, one being Eph/ephrin signaling (Conover et al., 2000; Holmberg et al., 2005). EphA4-mediated signaling is necessary for axon guidance during development, and its continued expression in the SVZ niche suggests a regulatory role throughout adulthood. Previous studies have suggested that EphA4 plays a role in the regulation of astrocytic gliosis and glial scar formation, which inhibits axonal regeneration in these areas following spinal cord injury (Goldshmit et al., 2004). Blood vessels may also play an important role in SVZ cell proliferation and neuroblast migration following injury (Tavazoie et al., 2008; Yamashita et al., 2006). The goal of this project is to examine glial scar formation as well as the relationship between SVZ vasculature, neuroblasts, and neural stem cells in EphA4 +/+, EphA4 +/-, and EphA4 -/- mice following a needle stick injury in the cortex or striatum. The outcome of these experiments will determine whether invasive procedures such as injections will affect neuroblast migration and/or the organization of the SVZ.

Modeling the Volatility of Real GDP Growth: The Case of Japan Revisited

Previous studies (e.g., Hamori, 2000; Ho and Tsui, 2003; Fountas et al., 2004) find high volatility persistence of economic growth rates using generalized autoregressive conditional heteroskedasticity (GARCH) specifications. This paper reexamines the Japanese case, using the same approach and showing that this finding of high volatility persistence reflects the Great Moderation, which features a sharp decline in the variance as well as two falls in the mean of the growth rates identified by Bai and Perronâs (1998, 2003) multiple structural change test. Our empirical results provide new evidence. First, excess kurtosis drops substantially or disappears in the GARCH or exponential GARCH model that corrects for an additive outlier. Second, using the outlier-corrected data, the integrated GARCH effect or high volatility persistence remains in the specification once we introduce intercept-shift dummies into the mean equation. Third, the time-varying variance falls sharply, only when we incorporate the break in the variance equation. Fourth, the ARCH in mean model finds no effects of our more correct measure of output volatility on output growth or of output growth on its volatility.