18.0 for windows

The correlation between patients’ clinicopathological features and EGFR mutation status was assessed using chi-square test or independent sample t-test. For multivariate analysis, logistic regression model was used. All analyses were performed using the Statistical Product and Service Solutions program 18.0 for windows (SPSS, Chicago, IL). p value below 0.05 was considered to indicate statistical significance.

All data are expressed as the mean±SD. Student’s t-test was used for comparisons between groups. Fisher’s exact test was applied for gender. Pearson’s correlation test was performed to examine the relationships between continuous variables and the SYNTAX and Jeopardy scores. The non-parametric Mann-Whitney test was used to analyze glutamic pyruvic transaminase (GPT) and hs-CRP since they are not normally distributed. In addition, multiple linear regression analyses were performed to determine associations between severity scores and OGTT, with SYNTAX or Jeopardy scores as the dependent variable and components of metabolic syndrome as the independent variables. The results were considered statistically significant at P<0.05. All data were analyzed using SPSS (Statistical Package for the Social Sciences) 18.0 for Windows (SPSS, Inc., Chicago, IL, USA).

One-way analysis of variance (ANOVA) including post-hoc correction for multiple comparisons using the Bonferroni method was used to determine the statistical significance of differences in MBC and the Chao1 index for each sampling event among the four experimental treatments in the two plantation management schemes. Two-way ANOVA was performed to assess the combined effect of N deposition and management practices on microbial biomass and diversity. The Pearson correlation coefficient between soil properties and α-diversity was also calculated. Analyses were conducted using SPSS (Statistical Package for the Social Sciences) 18.0 for Windows (SPSS Inc., Chicago, Illinois, USA).
QIIME was used to calculate the weighted UniFrac. PCoA and UPGMA (unweighted pair group method with arithmetic mean) clustering were conducted on the weighted UniFrac based on a protocol published previously73 (link). In addition, a CCA was performed to identify the abiotic factors with the most impact on bacterial community composition, and these results were used to construct a soil property matrix for variation partitioning analysis in R v.2.8.1 with the vegan package.