Sigmastat statistical software

The normality of data was assessed by Kolmogorov-Smirnov test. The statistical differences between experimental groups were carried out by one-way ANOVA. If differences were significant, the post hoc test was applied to compare groups. All statistical analyses were performed with SigmaStat statistical software (Systat Software, Inc) and p-values ≤ 0.05 were considered statistically significant. The values are represented as Mean ± standard error of mean (SEM).

One-way ANOVA with Tukey-Kramer multiple comparison data analysis was used for Mch responses using SigmaStat Statistical Software (Systat software Inc., San Jose, CA). EPO activity analysis was performed using the Student t test. Over the Study period, there were no significant variability in inflammation within each group with weekly measurements for all of the inflammatory parameters being evaluated. Therefore, all the weekly measurements are presented as Cumulative data and are presented as mean ± standard error (SEM). A p<0.05 was considered to be statistically significant for all of the above statistical comparisons.

The statistical analysis was performed using SigmaStat statistical software (Systat Software, San Jose, CA). For immunohistochemistry and cytokine analyses, we logarithmically transformed the data. Data were analyzed using one-way ANOVA followed by Holm-Sidak post hoc analysis for data with a parametric distribution or Kruskal-Wallis test for data with a nonparametric distribution and Dunn’s post hoc analysis. Results are presented as means ± SE and p value < 0.05 was considered statically significant.

All data were analyzed with SigmaStat statistical software (Systat Software Inc., San Jose, CA, United States). Three-way (DEP X LPS X Sex) ANOVAs were performed first, and following an interaction with Sex, two-way (DEP X LPS) ANOVAs within each sex were used to assess differences in regional volume (mm³), average cell volume (μm³), the total number of cells/mm³, and the number of cells (of the 2 different morphologies)/mm³. Following interactions, post hoc comparisons (Fisher’s LSD) were performed to further distinguish between groups. For neuron counts and microglial-neuron overlap, two-way (DEP X Sex) ANOVAs were performed to assess differences in the number of neurons, number of microglia-neuron interactions, microglial volume (μm³), and overlap volume (μm³). Interactions were followed up with Fisher’s LSD post hoc tests. The 3D reconstruction data were log-transformed for analysis due to unequal variance, but are displayed as raw data in the figures. Significance was generally assumed at p < 0.05; however, higher-order interactions at p ≤ 0.1 were used to direct the subdivision of data for further analysis (Snedecor and Cochran, 1967 ). These interactions were only reported if subsequent lower-order ANOVAs and/or post hoc tests achieved significance at p < 0.05 (Slotkin and Seidler, 2015 (link)).

Statistical analysis was performed using SigmaStat statistical software (version 4.0; Systat Software, San Jose, California). Values are presented as median (interquartile range). Data were assumed to be nonparametric due to low number of samples and were analyzed with Kruskal–Wallis one-way ANOVA. If the ANOVA was significant, post-hoc testing was conducted comparing Bioss LIM C, Ultimaster, Biomime and Xience Sierra using Dunn's test. Differences were only considered significant when the calculated p value was < 0.05.