Spss statistics version 19

Statistical analyses were performed using the statistical software package IBM SPSS Statistics version 19.0 (IBM Corp., Somers, NY, USA). MANOVA was used to compare the IOP values of groups A, B, C and D. The correlation of IOP values before removal of needle and the scores of reflux in all intravitreal infusion eyes were calculated using the Spearman’s rank correlation coefficient. Statistical significance was considered when p < 0.05.

Data are expressed as mean ± SEM from at least three independent experiments. Student’s t-test was used to determine significant differences. Statistical analyses were performed using IBM-SPSS Statistics version 19.0 software (IBM Corp., Armonk, NY). A value of P < 0.05 was considered statistically significant.

Baseline characteristics were compared among patients categorized by age groups and admission eGFR levels. We expressed continuous variables as means ± standard deviation or medians (interquartile range, IQR), as appropriate, and reported categorical variables as counts and percentages. The correlation of eGFR with age was tested by Pearson correlation test. Hazard ratios (HRs) were presented with their 95% confidence intervals (CIs) based on the results of Cox proportional hazards regression models, which we used to investigate the risk effect of RRF on the outcome events in different age groups. The univariate and multivariate models were generated sequentially to determine the successive influence of potential confounders on the relative risk for outcomes by RRF after stratification by age group. We also employed a single Cox regression model including age group (1 reference variable and 2 indicator variables), RRF, the interaction terms for RRF and age group, and other covariates, to further confirm whether the age-related changes in the association of RRF with clinical outcomes existed. Two-sided P values of less than 0.05 were considered to indicate statistical significance. We performed all the statistical analyses with the use of SPSS Statistics (version 19.0).

The StatLight–2000(C) program (Yukms corp., Yokohama, Kanagawa, Japan) was used for the statistical analysis of the results of in vivo and in vitro experiments. ProteinPilot™ 2.0 Software was employed for the statistical analysis of the quantitative changes of protein expression in mice HCCs and CNPY2kn Huh7 and HepG2 human liver cancer cells. First, the F test was used for the evaluation of the significance of differences between mean values. If non-homogeneous, the results were then analyzed with the Welch test, and if homogenous, with the Student’s t-test (two-sided) using SPSS statistics version 19.0. (SPSS Inc., Chicago, IL, USA). Statistical significance of associations between CNPY2 staining and various clinicopathological variables was evaluated using chi-square and Fisher’s tests. Survival curves were calculated from the day of surgery to relapse or death or to the last follow-up using the Kaplan–Meier method, and differences in overall survival curves were assessed with the Log rank test. In all applied analyses, p-values <0.05 were considered statistically significant. Univariate Cox proportional hazard model analysis was performed to calculate hazard ratios (HRs) and to determine associations between CNPY2 overexpression and disease-specific mortality.

All statistical analyses were performed by SPSS Statistics, version 19.0 software (SPSS, Inc, Armonk, NY). All graphs were generated by GraphPad Prism version 5.00 (GraphPad Software, San Diego,CA USA). All data were expressed as mean ± standard deviation (SD). Differences in characteristics between the AIS patients and controls were evaluated using the Student’s t-test for continuous variables or Chi square test for dischotomous variables. The Mann–Whitney U Test was used to compare the autophagy biomarkers between the AIS patients and controls. Differences in good outcome group and poor outcome group assessed by the improvement in NIHSS were evualted by the Student’s t-test. Pearson’s correlation test was used to assess the linear dependence between autophagy biomarkers and infarct volume, NIHSS and mRS. P <0.05 were considered to be statistically significant.