135 Systemic Immune Response in Burn Patients Gating Strategy for Supervised Flow Cytometry The gating strategy is shown in Supplementary Figure 1. Viable CD45+ cellswere gated on FSC and SSC to characterize granulocytes, monocytes and lymphocytes. Subsequently, cells were determined as follows: immature neutrophils (CD10dimCD15+CD16+ granulocytes), mature neutrophils (CD10brightCD15+CD16+ granulocytes), eosinophils (CD9+CD15+CD16¯ granulocytes), classical monocytes (CD14brightCD16¯ monocytes), intermediate monocytes (CD14brightCD16+ monocytes), non-classical monocytes (CD14dimCD16+ monocytes), T cells (CD3+ lymphocytes), and Tregs (CD3+CD25+CD127¯). Unsupervised Analysis of Flow Cytometry Data The innate and lymphocyte panel were used for unsupervised analysis in Cytobank [74]. Viable monocytes, granulocytes or lymphocytes were gated using 7-AAD and CD45 staining and FSC/SSC in MACSQuantify 2.13 software (Miltenyi). The data was uploaded to Cytobank to create Flow Self-Organizing Map (FlowSOM) cluster plots. Plasma Cytokine Analysis Plasma samples were thawed, and debris was removed using a filter plate (Multiscreen, Merck KGaA, Darmstadt, Germany). Luminex assay was performed according to the manufacturer’s instructions (Merck KGaA). The following assay kits were used: HCYTA60K, TGFBMAG-64K, HCYTA-60K, HCYP2MAG-62K and HTH17MAG-14K. In short, 25 μL of plasma was used to determine the concentrations of 33 cytokines and chemokines, namely MCP-1 (CCL2), MIP-1α (CCL3), MIP-1β (CCL4), MIP-3α (CCL20), GRO-α (CXCL1), IP-10 (CXCL10), IFN-α2, IFN-γ, TNF-α, TGF-β1, TGF-β2, TGF-β3, CTACK (CCL27), RANTES (CCL5; in a 1:100 dilution), IL-1α, IL-1β, IL-2, IL-4, IL-5, IL-6, IL-8 (CXCL8), IL-9, IL-10, IL-12p40, IL- 12p70, IL-13, IL-17A (CTLA-8), IL-17F, IL-18, IL-21, IL-22, IL-23, and IL-33 (NF-HEV). Mean fluorescence intensity of samples was measured with a Flexmap 3D System (Luminex Corp, Austin, USA) and concentrations were calculated using Bio-Plex Manager Software (Bio-Rad Laboratories, Veenendaal, The Netherlands). When cytokine levels were out of range of the standard, either the lowest level of quantification or the highest level of quantification was used. To combine results of multiple assays, we transformed the data to fold changes of healthy controls. Statistical Analyses Distribution of the data was checked for normality. For the flow cytometry data, differences between the levels of outcomes of patients on PBD 0–3 and healthy controls were explored using the Mann Whitney U test. Results per time interval (e.g., PBD 0–3) were averaged per patient. Differences in outcomes within patients between time intervals PBD 4–6 through PBD 37–39 vs. PBD 0–3 were analyzed in SPSS version 25 (IBM, Armonk, USA) using linear mixed model to correct for the dependent data structure. 4
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