Spss statistic 25

Statistical analysis was performed with unpaired Student’s t-test for pairwise comparisons in SigmaPlot version 12.5 software (Systat Software Inc. Washington, USA) or one-way analysis of variance (ANOVA) with a Bonferroni post-test for multiple comparisons and using Kaplan-Meier method and a log-rank test (survival) and Mann-Whitney U test (body weight) in IBM SPSS Statistic 25 software (IBM. NY, USA). A P-values less than 0.05 were considered to be statistically significant. The data were presented as the means ± SD or SEM of three independent experiments.

Statistical tests were performed using the IBM SPSS Statistic 25 software (IBM Corp., Armok, NY, USA). Normal distribution of variables included in this study was checked prior statistical analyses and logarithmically transformed to achieve approximate normal distribution. Differences in mRNA expression between vis and sc AT were assessed using the paired Student’s t-test. Unpaired t-Test was used to analyze differences in adipose tissue mRNA expression among the groups. Logistic regression analyses have been conducted for the association of the SNP and the obesity/diabetes status. Linear regression analyses were used to assess the relationship between genetic variants/mRNA expression levels and quantitative metabolic traits. Pearson’s correlation analyses were conducted using two-way bivariate correlations. The additive model (with genotypes coded to 0, 1, and 2) was used, and if not stated otherwise, all p-values are adjusted for age, sex, and BMI. Two-sided p-values ≤ 0.05 were considered to provide evidence for nominal association and are presented without correction for multiple hypothesis testing.

For all experiments with the exception of RT-qPCR, linear raw data were first log transformed and then analyzed by a blocked (“experiment” and “treatment”) Student’s t-Test or one-way ANOVA with Dunnett’s post hoc test with “Experiment” being the blocking factor. For qRT-PCR analysis, 2^−ΔΔCt values were used in the same test. Data were obtained from at least three independent experiments and graphically represented as mean ± standard error of the mean (SEM). All statistical analyses were performed using SPSS statistic 25 (IBM, SPSS Inc., Chicago, IL, USA) and p-values < 0.05 were considered significant. Prism 8 (GraphPad Software, San Diego, CA, USA) was used to plot all data with control condition normalized to 100%. Graphical abstract was created with BioRender (Toronto, ON, Canada, agreement number; HX24FPAASI).

The normal data distribution was tested using the one-sample Kolmogorov–Smirnov test. All continuous variables were expressed as mean ± standard deviation, while categorical variables as frequency and percentage. T test and Mann–Whitney test were performed as appropriate. Contingency tables (chi-square test) were used to investigate the relationship between pre- and post-recurrence DME pattern and between baseline DME pattern and pre- and post-recurrence morphological parameters (ELM and IS/OS). A one-way repeated measures analysis of variance (ANOVA) for each group was conducted to evaluate the null hypothesis that there is no change in functional and morphological parameter values when measured at baseline, maximal answer, and after recurrence in study groups. Post hoc tests were performed using the Bonferroni correction. Statistical evaluation was performed using SPSS (IBM SPSS Statistic 25). A p value < 0.05 was considered statistically significant.

All data were tested for their normality distribution by Kolmogorov-Smirnov and Shapiro-Wisk test and for their homogeneity of variance with the Levene test. Female development, seed set, reproduction pathway of seed formation, and pollen viability were determined per flower as a percentage and subsequently averaged per plants. The percentage of data were arcsine transformed before statistical analysis. We tested the influence of treatment on mean sexual ovules and seed set among ploidies with General Linear Model (GLM) univariate (Two-way ANOVA) for completely randomized factorial design model, and means were compared according to the least significant difference (LSD) test at 0.05 probability level (p-value < 0.05). Tukey HSD was performed to the means of sexual ovules to determine the main factors. Nonparametric Kruskal-Wallis and Mann-Whitney U-test were applied to test the influence of treatment on sexual seed formation per ploidy. Boxplots were plotted with untransformed percentage values and show the 25^th, and 75^th percentile ranges as a box, and the median as a black line: circles are outliers; asterisks are extreme values. All statistical analyses were performed with IBM SPSS Statistic 25 (IBM Deutschland GmbH).

Statistical analyses were carried out with IBM SPSS statistic 25 software. In human study Mann-Whitney U test was used to compare the variables in different groups and Wilcoxon signed-rank test to compare the variables within the same groups. T-test was used in mouse study. P-values less than 0.05 were considered significant (* p < 0.05, ** p < 0.01, *** p < 0.001).

All values were expressed as Mean ± S.E.M. (standard error of means). The data were analyzed and plotted using IBM SPSS Statistic 25 and GraphPad Prism 9. The normality test was conducted in IBM SPSS Statistic 25; all data were normally distributed. Multiple comparisons of data were performed with GraphPad Prism 9. Multiple groups were compared by one-way ANOVA followed by the Bonferroni post-hoc test. The statistical significance was defined as follows: *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001; ****p ≤ 0.0001; *p ≤ 0.05 was considered statistically significant.