Figure 1.
Figure 1. Metabolomics of RBCs in a rat model of HS. (A) A well-established rodent model of HS in Sprague-Dawley rats was used to investigate the effect of severe HS (MAP, <30 mm Hg; no trauma) on RBC metabolism at baseline (BASE), 15, or 60 minutes through shock (Post-Shock and END, respectively). Results were compared against sham controls (no trauma; MAP, >80 mm Hg). (B) Heat-map and hierarchical-clustering analysis of metabolites was performed (B; an extended and vectorial version is provided in supplemental Figure 1). (C) PLS-DA was performed, revealing that metabolic phenotypes could discriminate samples on the basis of grouping (sham vs shock, PC1; explaining 20.9% of the variance) and time-course progression (PC3, 26.9%), whereas PC2 mostly explained biological variability across rats (14.4%). (D) Metabolites informing hierarchical clustering analysis and PLS-DA discrimination (ie, metabolites with the highest loading weights from the analysis in panel C) were used to elaborate pathway analyses of HS RBCs. (E) The top 5 metabolites are ranked on the basis of VIP scores from the PLS-DA analysis. 2,3-BPG, 2,3-bisphosphoglyceric acid; ADP, adenosine 5′-diphosphate; BisPh, bisphosphoglycerate; Max, maximum; Min, minimum; TCA, tricarboxylic acid.

Metabolomics of RBCs in a rat model of HS. (A) A well-established rodent model of HS in Sprague-Dawley rats was used to investigate the effect of severe HS (MAP, <30 mm Hg; no trauma) on RBC metabolism at baseline (BASE), 15, or 60 minutes through shock (Post-Shock and END, respectively). Results were compared against sham controls (no trauma; MAP, >80 mm Hg). (B) Heat-map and hierarchical-clustering analysis of metabolites was performed (B; an extended and vectorial version is provided in supplemental Figure 1). (C) PLS-DA was performed, revealing that metabolic phenotypes could discriminate samples on the basis of grouping (sham vs shock, PC1; explaining 20.9% of the variance) and time-course progression (PC3, 26.9%), whereas PC2 mostly explained biological variability across rats (14.4%). (D) Metabolites informing hierarchical clustering analysis and PLS-DA discrimination (ie, metabolites with the highest loading weights from the analysis in panel C) were used to elaborate pathway analyses of HS RBCs. (E) The top 5 metabolites are ranked on the basis of VIP scores from the PLS-DA analysis. 2,3-BPG, 2,3-bisphosphoglyceric acid; ADP, adenosine 5′-diphosphate; BisPh, bisphosphoglycerate; Max, maximum; Min, minimum; TCA, tricarboxylic acid.

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