种植体表面处理研究概述

种植体表面处理是种植体能否形成骨结合的一个重要因素,对提高种植成功率起了关键作用,究其共性是形成一个粗糙的表面,提高种植体的骨结合及生物相容性。该文就种植体表面各种处理技术如机械处理法、化学处理法、生物处理法等对骨结合的影响做一综述。     

Factors Associated with Hepatitis B Surface Antigen Kinetics and Responses in Pegylated Interferon Alpha-2a Monotherapy for Patients with Chronic Hepatitis B

Objective Pegylated-interferon monotherapy is the standard treatment for patients with chronic hepatitis B; however, the factors associated with its therapeutic effects remain unclear. Methods Patients with chronic hepatitis B were treated with pegylated interferon α-2a for 48 weeks. We evaluated the kinetics of hepatitis B surface antigen (HBsAg) during treatment and follow-up periods and the factors associated with an HBsAg response (defined as a change in HBsAg of ≥-1 log IU/mL from baseline). Results The study population comprised 50 patients. The median baseline levels of hepatitis B virus DNA and HBsAg were 5.00 and 3.40 log IU/mL. The median values of HBsAg reduction from baseline were -0.44 (n=48), -0.41 (n=40), and -0.68 (n=11) log IU/mL at the end of treatment and at 48 and 144 weeks post-treatment, respectively. The rates of HBsAg response were 24.0% and 22.5% at the end of treatment and at 48 weeks post-treatment, respectively. A multivariate analysis identified HBsAg <3.00 log IU/mL as an independent baseline factor contributing to the HBsAg response at the end of treatment and 48 weeks post-treatment (p=1.07×10^-2 and 4.42×10^-2, respectively). There were significant differences in the reduction of the HBsAg levels at 12 weeks of treatment and in the incidence of serum ALT increase during treatment between patients with and without an HBsAg response. Conclusion These findings suggest that the baseline HBsAg level, HBsAg kinetics at 12 weeks of treatment, and ALT increase during treatment are important factors contributing to the HBsAg response in pegylated interferon α-2a monotherapy for patients with chronic hepatitis B.     

Adaptive dynamic surface control using neural networks for hypersonic flight vehicle with input nonlinearities

This study proposes an effective adaptive dynamic surface control (DSC) method based on the radial basis function neural networks and the auxiliary system for hypersonic flight vehicle (HFV) systems in the presence of system uncertainties, external disturbances, and state variable and control input constraints. Firstly, to enhance the robustness of the system, the neural network is combined with the robust term to deal with the uncertainties and external disturbances of the system. Secondly, to prevent the deterioration of the dynamic performance of the system due to the over-adaptation of the neural networks and the robust terms caused by the state and control input constraints, the auxiliary system is added at each step in the DSC design to adjust the dynamic process of the reference signal and virtual control. Furthermore, the variable structure control is used to solve the problem of dead zone in the control input. Using the Lyapunov analysis method, all signals of the closed-loop system are semi-globally uniformly ultimate bounded. The simulation results illustrate the effectiveness of the proposed control scheme for the HFVs.