Prism v8

For ELISA assay, the EC₅₀ values for plasmas and monoclonal antibodies were determined using four-parameter nonlinear regression (GraphPad Prism v8.3). For pseudotyped virus neutralizing assay, the inhibition percent was calculated by comparing the relative luminescence units to the blank control (cells without pseudotyped virus or antibody) and virus control (cells with pseudotyped virus but without antibody). IC₅₀ was calculated using a three-parameter nonlinear regression (GraphPad Prism v8.3). For authentic virus neutralizing assay, percent neutralization was calculated as (Sample signals − Virus control signals)/(Blank control signals − Virus control signals) × 100%. Data were fitted using a three-parameter nonlinear regression (GraphPad Prism v8.3). For SPR assay, affinity values, including association rates (K_on), dissociation rates (K_off), and affinity constants (K_D), were calculated using Biacore T200 Evaluation Software with 1:1 binding model. For BLI competition assay, the competition value was defined as the percentage of the shift of tested group during the second antibody contact compared to the shift of control group, where buffer was used as the first antibody.

Comparisons of baseline preintervention albumin levels between lymphatic disease presentations were done using the Kruskal-Wallis test with Dunn’s multiple comparisons test in Prism v8.1.2 (Graphpad). From the imaging data, differences between imaging findings and lymphatic disease were analyzed using a Pearson chi-squared test (4 × 2 tables) (or 5 × 2 tables for supplemental graph) in Prism v8.1.2 (Graphpad). Differences in clinical outcomes based on lymphatic imaging category (normal vs. abnormal) were statistically analyzed using STATA v14: for the length of stay and time to symptom resolution the Wilcoxon rank-sum test was used and for failure to resolve and death the Fisher’s exact test was performed. The number of interventions was analyzed using the Mann-Whitney test in Prism v8.1.2 (Graphpad).

Data processing was performed using MS‐DIAL v3.90 (Tsugawa et al., 2015). Raw data are available on the Metabolomics Workbench. Compounds were identified by matching retention times and experimental spectra downloaded from the HILIC‐MS/MS database in MassBank of North America in addition to NIST17 MS/MS spectra. For statistical analysis, samples were normalized to the sum of all identified metabolites. Heat maps were generated using GraphPad Prism v8.4.0. Heat map values are Z‐scores of each metabolite. Z‐scores were calculated by subtracting the mean of the group values and then dividing by the standard deviation in order to scale the data for relative expression for each region. Line graphs and violin plots were generated using GraphPad Prism v8.4.0. All p‐values listed for metabolites are normalized raw p‐values. PCA, Wilcoxon rank‐sum test, and volcano plots were generated used MetaboAnalyst v4.0. False discovery rate (FDR) adjustment was used to correct for multiple comparisons in the volcano plot. For animal experiments and immunohistochemistry data, statistical analysis was carried out using GraphPad Prism v8.4.0. All values are expressed as mean ± SEM. Groups were compared using the one‐way ANOVA test with the multiple comparison post hoc tests. p ≤ .05 were considered statistically significant.

Statistical analyses for zebrafish experiments were performed with GraphPad Prism v8.2. All data were based on at least two independent experiments with independent biological replicates. The Shapiro-Wilk normality test was used to confirm the normality of the data. If data passed the normality test (alpha = 0.05), then a parametric test, such as an unpaired t test or ordinary one-way ANOVA (in case of multiple comparisons), was used. If data did not pass the normality test, a non-parametric test was used (Mann-Whitney test or Kruskal-Wallis test for multiple comparisons). To correct for multiple comparisons, either Tukey’s multiple comparisons test (for ordinary one-way ANOVA) or Dunnet’s multiple comparisons test (for Kruskal-Wallis test) was used. The value of sample size (n) is given in figure legends, and for in-vivo experiments it indicates the number of animals/samples. Data are presented as mean and single points, with standard error of the mean (SEM), as indicated in figure legends. Statistical analyses for in vitro experiments were performed with GraphPad Prism v8.2. Results were expressed as the mean ± SEM. A p value <0.05 was considered significant.

Statistical analysis was conducted on the previously defined groups 1–5 using GraphPad Prism V8.3.1 (San Diego, CA, USA). Statistical differences in infiltrating CD3⁺ T cells, Mac3+ macrophages and TBEV antigen-positive cells were analyzed for groups 1–3 by using the Kruskal–Wallis test (p < 0.05) and individual groups were compared by using a Mann–Whitney-U-test with Bonferroni-corrected p values (p < 0.02). To evaluate the dependency of the occurrence of ganglioneuritis with detection of viral antigen, a McNemar analysis was conducted using GraphPad Prism V8.3.1 (San Diego, CA, USA).