To study immune reactions and the mechanism of anergy induced by recombinant enterotoxin A (rSEA) of Staphylococcus aureus. The gene encoding SEA was cloned from standard strain of S. aureus and high efficiently expre...To study immune reactions and the mechanism of anergy induced by recombinant enterotoxin A (rSEA) of Staphylococcus aureus. The gene encoding SEA was cloned from standard strain of S. aureus and high efficiently expressed in E. coli. After immunization with purified rSEA, mice were examined for production of specific antibody, subtype of IgG, cytokine mRNA levels such as IFN-γ, IL-2 secretion and T-cell surface PD-1 expression. Results showed that high levels of specific antibodies were produced in two weeks of primary immunization shot. During this time, humoral immune reactions prevailed (IgG2a/ IgG1 【1). During the early phase, Th1 type cytokine mRNA is expressed at a higher level than Th2 type, indicating cellular immune reaction prevailed. Splen- ocyte IFN-γ secretion was significantly decreased after boosting immunization. The PD-1 expression was detected by a flow cytometry examination in the surface of T- lymphocytes which were induced by rSEA, and the expression of PD-1 molecules increased along with the number of boosting and the time after immunization.展开更多
Two traditional recommendation techniques, content-based and collaborative filtering （CF）, have been widely used in a broad range of domain areas. Both meth- ods have their advantages and disadvantages, and some of ...Two traditional recommendation techniques, content-based and collaborative filtering （CF）, have been widely used in a broad range of domain areas. Both meth- ods have their advantages and disadvantages, and some of the defects can be resolved by integrating both techniques in a hybrid model to improve the quality of the recommendation. In this article, we will present a problem-oriented approach to design a hybrid immunizing solution for job recommen- dation problem from applicant＇s perspective. The proposed approach aims to recommend the best chances of opening jobs to the applicant who searches for job. It combines the artificial immune system （AIS）, which has a powerful explo- ration capability in polynomial time, with the collaborative filtering, which can exploit the neighbors＇ interests. We will discuss the design issues, as well as the hybridization process that should be applied to the problem. Finally, experimental studies are conducted and the results show the importance of our approach for solving the job recommendation problem.展开更多
文摘To study immune reactions and the mechanism of anergy induced by recombinant enterotoxin A (rSEA) of Staphylococcus aureus. The gene encoding SEA was cloned from standard strain of S. aureus and high efficiently expressed in E. coli. After immunization with purified rSEA, mice were examined for production of specific antibody, subtype of IgG, cytokine mRNA levels such as IFN-γ, IL-2 secretion and T-cell surface PD-1 expression. Results showed that high levels of specific antibodies were produced in two weeks of primary immunization shot. During this time, humoral immune reactions prevailed (IgG2a/ IgG1 【1). During the early phase, Th1 type cytokine mRNA is expressed at a higher level than Th2 type, indicating cellular immune reaction prevailed. Splen- ocyte IFN-γ secretion was significantly decreased after boosting immunization. The PD-1 expression was detected by a flow cytometry examination in the surface of T- lymphocytes which were induced by rSEA, and the expression of PD-1 molecules increased along with the number of boosting and the time after immunization.
文摘Two traditional recommendation techniques, content-based and collaborative filtering （CF）, have been widely used in a broad range of domain areas. Both meth- ods have their advantages and disadvantages, and some of the defects can be resolved by integrating both techniques in a hybrid model to improve the quality of the recommendation. In this article, we will present a problem-oriented approach to design a hybrid immunizing solution for job recommen- dation problem from applicant＇s perspective. The proposed approach aims to recommend the best chances of opening jobs to the applicant who searches for job. It combines the artificial immune system （AIS）, which has a powerful explo- ration capability in polynomial time, with the collaborative filtering, which can exploit the neighbors＇ interests. We will discuss the design issues, as well as the hybridization process that should be applied to the problem. Finally, experimental studies are conducted and the results show the importance of our approach for solving the job recommendation problem.
