Induction and regulation of differentiation in neural stem cells on ultra-nanocrystalline diamond films

100學年度研究獎補助論文[[abstract]]The interaction of ultra-nanocrystalline diamond (UNCD) with neural stem cells (NSCs) has been studied in order to evaluate its potential as a biomaterial. Hydrogen-terminated UNCD (H-UNCD) films were compared with standard grade polystyrene in terms of their impact on the differentiation of NSCs. When NSCs were cultured on these substrates in medium supplemented with low concentration of serum and without any differentiating factors, H-UNCD films spontaneously induced neuronal differentiation on NSCs. By direct suppression of mitogen-activated protein kinase/extracellular signaling-regulated kinase1/2 (MAPK/Erk1/2) signaling pathway in NSCs using U0126, known to inhibit the activation of Erk1/2, we demonstrated that the enhancement of Erk1/2 pathway is one of the effects of H-UNCD-induced NSCs differentiation. Moreover, functional-blocking antibody directed against integrin β1 subunit inhibited neuronal differentiation on H-UNCD films. This result demonstrated the involvement of integrin β1 in H-UNCD-mediated neuronal differentiation. Mechanistic studies revealed the cell adhesion to H-UNCD films associated with focal adhesion kinase (Fak) and initiated MAPK/Erk1/2 signaling. Our study demonstrated that H-UNCD films-mediated NSCs differentiation involves fibronectin-integrin β1 and Fak–MAPK/Erk signaling pathways in the absence of differentiation factors. These observations raise the potential for the use of UNCD as a biomaterial for central nervous system transplantation and tissue engineering.[[incitationindex]]SCI[[booktype]]紙

Intertemporal asset allocation when the underlying factors are unobservable

The aim of this paper is to develop an optimal long-term bond investment strategy which can be applied to real market situations. This paper employs Merton’s intertemporal framework to accommodate the features of a stochastic interest rate and the time-varying dynamics of bond returns. The long-term investors encounter a partial information problem where they can only observe the market bond prices but not the driving factors of the variability of the interest rate and the bond return dynamics. With the assumption of Gaussian factor dynamics, we are able to develop an analytical solution for the optimal long-term investment strategies under the case of full information. To apply the best theoretical investment strategy to the real market we need to be aware of the existence of measurement errors representing the gap between theoretical and empirical models. We estimate the model based on data for the German securities market and then the estimation results are employed to develop long-term bond investment strategies. Because of the presence of measurement errors, we provide a simulation study to examine the performance of the best theoretical investment strategy. We find that the measurement errors have a great impact on the optimality of the investment strategies and that under certain circumstance the best theoretical investment strategies may not perform so well in a real market situation. In the simulation study, we also investigate the role of information about the variability of the stochastic interest rate and the bond return dynamics. Our results show that this information can indeed be used to advantage in making sensible long-term investment decisions. Copyright Springer Science+Business Media, LLC 2007Dynamic programming, Feynman-Kac formula, Duffie-Kan model, Kalman filter, Measurement errors,