Spss statistics 25 for windows software

The mean fungal frequencies and the mean aflatoxin concentrations were subjected to a three-way ANOVA (multivariate) test, followed by Tukey’s HSD test (p < 0.05) using the GraphPad Prism 8.0.0. software for Windows, San Diego, CA, USA, www.graphpad.com. A cluster analysis was performed and a dendrogram of phenotypic relatedness was constructed using the IBM^® SPSS^® Statistics software for Windows 25.0.
To evaluate the association between aflatoxin production and the sclerotia morphotype, a logistic regression analysis was performed using the IBM^® SPSS^® Statistics software for Windows 25.0. A principal coordinate analysis (PCoA) was performed using GenAlEx^® 6.5 software [47 (link)]. Aspergillus flavus isolates were selected by a random sampling method based on morphologically and physiologically characterized isolates representing the phenotypes of Aspergillus flavus (section Flavi), Aspergillus tamarii (section Flavi), A. awamorii (section Nigri), and Aspergillus section Aspergillus.

For statistical analysis, we used IBM SPSS Statistics 25 Software for Windows (Version 25.0; IBM Corporation, Armonk, NY, USA). After testing for normal distribution by Shapiro‐Wilk test, data were analyzed by Generalized Linear Mixed Models (GLMM) with Bonferroni correction. If data exhibited a right‐skewed distribution pattern gamma distribution was used. The percentual changes of immune cell subsets in the course of treatment were calculated from absolute numbers in comparison to baseline. P‐values were considered significant as follows: *P ≤ 0.05, **P ≤ 0.01, ***P ≤ 0.001 and ****P ≤ 0.0001. Graphs were created with GraphPad PRISM 8 (Graphpad Software, San Diego, CA, USA).

Statistical analysis was performed by IBM SPSS Statistics 25 Software for Windows (Version 25.0; IBM Corporation, Armonk, NY, USA). The Mann–Whitney U-test for independent samples was used to detect differences between the baseline values of pwMS and healthy blood donors. To evaluate changes in CAMs and CoSs over time, we used generalized linear mixed models (GLMM) with Bonferroni’s correction. GLMM was also used to test for intra-individual significant differences within HCs to determine stability of CAM and CoS expression. Data were tested for a normal distribution with the Shapiro–Wilk test. If the data exhibited a right-skewed distribution pattern, a gamma distribution was used. Significant differences for the CLAD-associated effects on the expression pattern of CAMs and CoSs on lymphocytes were calculated every 3 months throughout the 2-year observational period and compared with pre-treatment values (BL). The evaluation of CD154 expression was made after cell stimulation in a separate experiment, which allowed the possibility to calculate absolute cell numbers. In this regard, CD4+ cell counts were extracted from complete blood cells. p-values were considered significant as follows: * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001 and **** p ≤ 0.0001. Graphs were created with GraphPad PRISM8 (GraphPad Software, San Diego, CA, USA).