External Quality Assessment for Rubella Virus RNA Detection Using Armored RNA in China.

BACKGROUND: Although tremendous efforts have been made to reduce rubella incidence, there are still 300 new cases of congenital rubella syndrome daily; thus, rubella infections remain one of the leading causes of preventable congenital birth defects. An effective surveillance system, which could be achieved and maintained by using an external quality assessment program, is critical for prevention and control of this disease. METHODS: Armored RNAs, which are noninfectious and RNase-resistant, were used for encapsulation of the E1 gene of rubella virus and for preparation of a 10-specimen panel for external quality assessment. Thirty-two laboratories across mainland China that used nucleic acid tests for rubella virus RNA detection were included in the external quality assessment program organized by the National Center for Clinical Laboratories of China. RESULTS: Different kinds of commercial kits were used by the laboratories for nucleic acid extraction and TaqMan real-time reverse-transcription PCR for rubella virus RNA detection; 99.2% sensitivity and 100% specificity were achieved in this external quality assessment program. CONCLUSIONS: Most of the participating laboratories obtained accurate results for rubella nucleic acid tests, thereby achieving the quality required for regional rubella and congenital rubella syndrome elimination.

How optimization of potential functions affects protein folding.

The relationship between the optimization of the potential function and the foldability of theoretical protein models is studied based on investigations of a 27-mer cubic-lattice protein model and a more realistic lattice model for the protein crambin. In both the simple and the more complicated systems, optimization of the energy parameters achieves significant improvements in the statistical-mechanical characteristics of the systems and leads to foldable protein models in simulation experiments. The foldability of the protein models is characterized by their statistical-mechanical properties--e.g., by the density of states and by Monte Carlo folding simulations of the models. With optimized energy parameters, a high level of consistency exists among different interactions in the native structures of the protein models, as revealed by a correlation function between the optimized energy parameters and the native structure of the model proteins. The results of this work are relevant to the design of a general potential function for folding proteins by theoretical simulations.