Spss version 25

Studies 1 and 2 were analyzed separately. The primary outcome measures were the three conversation rating questionnaires completed at the end of each session. Each question was analyzed separately because individual questions addressed different aspects of the interaction, and it was not known how drugs would affect each question. Mixed model analysis of variance (ANOVA) was conducted using drug condition as a within-subject variable, and sex and condition order (drug-placebo, placebo-drug) as between subject factors (SPSS Version 25), for each item. Sex and drug order were included as factors because the influence of sex and test–retest reliability on this task were not known. For subjective and cardiovascular measures taken repeatedly throughout each session, we calculated the peak change from baseline (pre-drug) on each session and compared drug vs. placebo scores using two-tailed paired t-tests (SPSS Version 25) within each study. Pearson correlations (SPSS Version 25) were conducted to determine the relationship between oxytocin levels and closeness ratings. The criterion for significance was p < 0.05.

Statistical analyses were performed by using the SPSS version 25.0 software. Continuous variables are presented as mean ± standard deviation (SD) or median (IQR) and compared between patients with and without CAD. Categorical variables are presented as percentages. For the univariate analysis between CAD and non-CAD, continuous variables were compared using unpaired t test or Mann-Whitney test as appropriate, and categorical variables were compared using the chi-square test or Fisher's exact test. Binary logistic regression analysis was performed to identify independent factors associated with CAD, and ordinal regression analysis was used to examine the association between fibrosis markers and severity of CAD. Variables with a p value less than 0.05 in the univariate logistic regression analyses were included in the multivariate logistic regression analysis. Receiver operating characteristic (ROC) curves were constructed to assess the predictive value of fibrosis markers and inflammation markers for CAD. Mediation analysis was accomplished by SPSS version 25.0 software, using the PROCESS macro (Process V3.2) developed by Hayes and Preacher [12 (link)]. Figure S1 is a mediation analysis path diagram. A p value less than 0.05 was considered statistically significant.

The correlation analyses between expression levels of nine miRNAs and 83 genes were performed by Pearson correlation test using SPSS version 25.0 separately for TT and NNT samples. All correlation values were plotted in R statistical software v. 4.0.2 using the corrplot, ggplot2, ggrepel, and ggpubr packages. All miRNA-mRNA expression levels combinations were plotted in a scatter plot to select pairs showing inverse correlation values between the two evaluated groups, which was determined by outliers of a linear distribution from the most negatively correlated R values (−1, −1) to the most positively correlated R values (1, 1) with a confidence interval equal to 99%.
The Receiver Operating Characteristic (ROC) curves were constructed using SPSS version 25.0, and the area under the curve (AUC) was calculated to analyze the accuracy of each DEmiR and DEG for distinguishing TT from NNT with specificity and sensitivity. For the eight miRNA-mRNA pairs identified in the correlation analyses, ROC curves analysis was performed to evaluate the diagnostic test ability of these pairs (using the ratio values of -delta CT miRNA and-delta CT mRNA).