Response surface methodology to determine optimal measles-specific cytokine responses in human peripheral blood mononuclear cells

Optimization of multiplex quantitative polymerase chain reaction based on response surface methodology and an artificial neural network-genetic algorithm approach

Multiplex quantitative polymerase chain reaction (qPCR) has found an increasing range of applications. The construction of a reliable and dynamic mathematical model for multiplex qPCR that analyzes the effects of interactions between variables is therefore especially important. This work aimed to analyze the effects of interactions between variables through response surface method (RSM) for uni- and multiplex qPCR, and further optimize the parameters by constructing two mathematical models via RSM and back-propagation neural network-genetic algorithm (BPNN-GA) respectively. The statistical analysis showed that Mg2+ was the most important factor for both uni- and multiplex qPCR. Dynamic models of uni- and multiplex qPCR could be constructed using both RSM and BPNN-GA methods. But RSM was better than BPNN-GA on prediction performance in terms of the mean absolute error (MAE), the mean square error (MSE) and the Coefficient of Determination (R2). Ultimately, optimal parameters of uni- and multiplex qPCR were determined by RSM.

Profiling of measles-specific humoral immunity in individuals following two doses of MMR vaccine using proteome microarrays

INTRODUCTION

Comprehensive evaluation of measles-specific humoral immunity after vaccination is important for determining new and/or additional correlates of vaccine immunogenicity and efficacy.

METHODS

We used a novel proteome microarray technology and statistical modeling to identify factors and models associated with measles-specific functional protective immunity in 150 measles vaccine recipients representing the extremes of neutralizing antibody response after two vaccine doses.

RESULTS

Our findings demonstrate a high seroprevalence of antibodies directed to the measles virus (MV) phosphoprotein (P), nucleoprotein (N), as well as antibodies to the large polymerase (L) protein (fragment 1234 to 1900 AA). Antibodies to these proteins, in addition to anti-F antibodies (and, to a lesser extent, anti-H antibodies), were correlated with neutralizing antibody titer and/or were associated with and predictive of neutralizing antibody response.

CONCLUSION

Our results identify antibodies to specific measles virus proteins and statistical models for monitoring and assessment of measles-specific functional protective immunity in vaccinated individuals.