Statistical analysis
Statistical analysis was made using the repeated measures ANOVA procedure, while the weights data fitted all the required assumptions, arthritis score data did not meet the linear and sphericity assumption. Thus, increasing type 1 error for the model furthermore, violation for this assumptions is not known to bias the post hoc analysis (36). Therefore, we aggressively adjusted for multiple comparisons using the Bonferroni adjustment. For both models, time was set as the within subject effect while, the treatment group as the between subjects effect. The significance level was set at 5%. Statistical analysis and graph plotting were made with IBM Corp. Released 2015. IBM SPSS Statistics for Windows, Version 23.0. Armonk, NY: IBM Corp. Cytokine and anti-collagen concentration were first assessed for distribution. Since, normal distribution was not met, non-parametric tests were chosen throughout the statistical analysis. Comparisons of the mean concentrations began with the Kruskal-Wallis H test and followed with the Dunnett’s test for pair-wise comparisons. Post-hoc comparisons, including plotted comparisons, were adjusted for multiple comparisons following the Bonferroni procedure. Both plots and statistical analysis were conducted using R Core Team (2013). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/