Objective To construct AWP1 (associated with protein kinase C related kinase 1) recombinant adenovirus as the tool of transferring the gene and investigate its expression and localization in human vascular endothelial cell ECV304. Methods Cloned AWP1 cDNA was inserted into the multiply clone sites (MCS) of plasmid pcDNA3 for adding flag tag, and the flag-AWP1 gene was subcloned into shuttle vector pAdTrack-CMV. After identified with restrictional enzymes, plasmid pAdTrack-flag-AWP1 was linearized by digestion with restriction endonuclease PmeⅠ, and subsequently cotransformed into E.coli BJ5183 cells with adenoviral backbone plasmid pAdEasy-1 to make homologous recombination. After linearized by PacⅠ, the homologous recombinant adenovirus plasmid transfected into 293 cells with Lipofectamine to pack recombinant adenovirus. After PCR assay of recombinant adenovirus granules, recombinant adenoviruses infected 293 cells repeatedly for obtaining the high-level adenoviruses solution. And then, the recombinant adenoviruses infected human ECV304 cells for observing the expression and localization of AWP1 under laser scanning confocal microscope (LSCM). Results PCR assay showed that recombinant adenovirus Ad-flag-AWP1 was obtained successfully; and ECV304 cells were infected high-efficiently by the homologous recombinant virus. Then, it was observed that flag-AWP1 protein expressed in ECV304 cells and distributed in the leading edges of the cell membrane. Conclusion The vectors of flag-AWP1 recombinant adenovirus are constructed, and the localization of AWP1 protein in ECV304 cells might show that AWP1 may be a potential role on the cell signal transduction.
ObjectiveTo combine specific examples and R Studio language code, to apply the Bayesian quantile regression method in the analysis of clinical medicine data, and show the advantages of Bayesian quantile regression method, so as to provide references for improving the accuracy of medical research. Methods The clinical data of 250 patients with knee osteoarthritis from the capital special research on the application of clinical characteristics project were used. A Bayesian quantile regression model based on data set was constructed to explore the relationship between the level of serum IgG and the age of the patients. Results The Monte Carlo algorithm converge can judge the efficiency of parameter estimation based on Gibbs sampling which was used to draw samples from the posterior distribution of parameters in Bayesian quantile regression. By generating the parameter into the regression formula, we can obtain the regression under different quantiles: Y1=−6.022 063 47+2.026 913 73X−0.015 077 69X2……Y5=24.610 542 414−0.395 059 497X+0.004 205 064X2. It can be found that the serum level of IgG was obviously increased with age. Conclusion Bayesian quantile regression parameter estimation results are accurate and highly credible, and reliable parameter information can be obtained even under small sample conditions. It has great advantages in the research of clinical medicine data and has certain promotional value.