Objective To compare clinical outcome and adverse reactions between the regimens SOX and XELOX for chemotherapy of advanced gastric carcinoma in Chinese population.Methods The original articles on randomized controlled trials ( RCTs) comparing the chemotherapy of SOX and XELOX in Chinese patients with advanced gastric carcinoma were recruited from the PUBMED, WANFANG, VIP and CNKI databases.The quality of the selected trials were assessed by JADAD method.Meta-analysis about the efficacy and safety of the two chemotherapy methods was performed by Rev Man 5.2.0 software ( Cochrane-information Management System) .Results Eight RCT studies were recruited in our work, including 293 patients in the SOX treatment group and 310 in the XELOX treatment group.The analysis results showed that there was no significant difference in the effect of the two chemotherapy methods (OR=1.19, 95%CI:0.86-1.64,P=0.29), and referred to the safety evaluation, the stomatitis (OR=2.29, 95%CI:1.74-4.89, P<0.0001) incidence in SOX treatment group was higher than XELOX treatment group, and in total, there was no significant difference in adverse reaction incidence of the two chemotherapy methods(OR =0.88, 95%CI: 0.66-1.19, P =0.41).Conclusion In the chemotherapy of advanced gastric carcinoma in Chinese population, there is no significant difference in clinical response rate between SOX and XELOX, and the stomatitis incidence of SOX is significantly higher than that of XELOX.

With thousands of sequenced 16 S rRNA genes available,and advancements in oligonucleotide microarray technology,the detection of microorganisms in microbial communities consisting of hundreds of species may be possible.The existing algorithms developed for sequence-specific probe design are not suitable for applications in large-scale bacteria detection due to the lack of coverage,flexibility and efficiency.Many other strategies developed for group-specific probe design focus on how to find a unique group-specific probe that can specifically detect all target sequences of a group.Unique group-specific probe for each group can not always be found.Hence,it is necessary to design non-unique probes.Each probe can specifically detect target sequences of a different subgroup.Combination of multiple probes can achieve higher coverage.However,it is a time-consuming task to evaluate all possible combinations.A feasible algorithm using relative entropy and genetic algorithm (GA) to design group-specific non-unique probes was presented.