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Analysis of sublingual microvasculature. (A) Workflow of sublingual video acquisition and analysis of <t>microvascular</t> parameters. (B) Sidestream Dark Field (SDF) image showing software-identified valid (green) and invalid (yellow) capillaries (vascular segments). (C) Schematic of red blood cell (RBC) flow through a capillary under healthy conditions (left). The perfused boundary region (PBR, in µm) estimates this dynamic lateral movement of RBCs into the permeable part of the endothelial glycocalyx layer. Impaired glycocalyx allows RBCs to penetrate deeper into the endothelium, resulting in higher PBR values (right). RBCW, Red Blood Cell Column Width.
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Analysis of sublingual microvasculature. (A) Workflow of sublingual video acquisition and analysis of <t>microvascular</t> parameters. (B) Sidestream Dark Field (SDF) image showing software-identified valid (green) and invalid (yellow) capillaries (vascular segments). (C) Schematic of red blood cell (RBC) flow through a capillary under healthy conditions (left). The perfused boundary region (PBR, in µm) estimates this dynamic lateral movement of RBCs into the permeable part of the endothelial glycocalyx layer. Impaired glycocalyx allows RBCs to penetrate deeper into the endothelium, resulting in higher PBR values (right). RBCW, Red Blood Cell Column Width.
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Analysis of sublingual microvasculature. (A) Workflow of sublingual video acquisition and analysis of microvascular parameters. (B) Sidestream Dark Field (SDF) image showing software-identified valid (green) and invalid (yellow) capillaries (vascular segments). (C) Schematic of red blood cell (RBC) flow through a capillary under healthy conditions (left). The perfused boundary region (PBR, in µm) estimates this dynamic lateral movement of RBCs into the permeable part of the endothelial glycocalyx layer. Impaired glycocalyx allows RBCs to penetrate deeper into the endothelium, resulting in higher PBR values (right). RBCW, Red Blood Cell Column Width.

Journal: Frontiers in Immunology

Article Title: Changes in immune cell signatures during early infection reflect decoupling of capillary perfusion and glycocalyx dimensions

doi: 10.3389/fimmu.2025.1589959

Figure Lengend Snippet: Analysis of sublingual microvasculature. (A) Workflow of sublingual video acquisition and analysis of microvascular parameters. (B) Sidestream Dark Field (SDF) image showing software-identified valid (green) and invalid (yellow) capillaries (vascular segments). (C) Schematic of red blood cell (RBC) flow through a capillary under healthy conditions (left). The perfused boundary region (PBR, in µm) estimates this dynamic lateral movement of RBCs into the permeable part of the endothelial glycocalyx layer. Impaired glycocalyx allows RBCs to penetrate deeper into the endothelium, resulting in higher PBR values (right). RBCW, Red Blood Cell Column Width.

Article Snippet: The Microvascular Health Score (MVHS; in points) is a composite metric, which has been previously presented in detail ( ).

Techniques: Software

Analysis of microvascular parameters. Visualization of (A) PBR, (B) capillary density and (C) MVHS in Healthy volunteers and patients, respectively. (D) Scatter dot plots and simple linear regression (slope) with 95% confidence intervals of capillary density plotted against PBR (D4 to 25µm) in patients. The dotted lines represent the median values of capillary density and PBR, respectively. (E, F) show the ranked Spearman's correlation coefficients (ρ) of 125 mononuclear blood cell parameters with the perfused boundary region (PBR) and capillary density, respectively. Positive and negative correlations are shown in both panels. The colored bars represent significant correlations: orange for parameters significantly correlated with PBR, blue for those significantly correlated with capillary density, green for parameters significantly correlated with both PBR and capillary density, and grey for those with no significant correlation. (G – J) Insets below each panel highlight specific cell types or parameters with the most significant correlations. (K) Venn diagram illustrating associations of mononuclear blood cell parameters with PBR and/or capillary density.

Journal: Frontiers in Immunology

Article Title: Changes in immune cell signatures during early infection reflect decoupling of capillary perfusion and glycocalyx dimensions

doi: 10.3389/fimmu.2025.1589959

Figure Lengend Snippet: Analysis of microvascular parameters. Visualization of (A) PBR, (B) capillary density and (C) MVHS in Healthy volunteers and patients, respectively. (D) Scatter dot plots and simple linear regression (slope) with 95% confidence intervals of capillary density plotted against PBR (D4 to 25µm) in patients. The dotted lines represent the median values of capillary density and PBR, respectively. (E, F) show the ranked Spearman's correlation coefficients (ρ) of 125 mononuclear blood cell parameters with the perfused boundary region (PBR) and capillary density, respectively. Positive and negative correlations are shown in both panels. The colored bars represent significant correlations: orange for parameters significantly correlated with PBR, blue for those significantly correlated with capillary density, green for parameters significantly correlated with both PBR and capillary density, and grey for those with no significant correlation. (G – J) Insets below each panel highlight specific cell types or parameters with the most significant correlations. (K) Venn diagram illustrating associations of mononuclear blood cell parameters with PBR and/or capillary density.

Article Snippet: The Microvascular Health Score (MVHS; in points) is a composite metric, which has been previously presented in detail ( ).

Techniques:

Correlation of PBMC with microvascular flow parameters (A) Family Tree of correlation coefficients (Spearman's ρ) of flow cytometry markers with PBR (B) Family Tree of correlation coefficients (Spearman's ρ) of flow cytometry markers with capillary density. Color filling represents correlation coefficients, solid node borders indicating statistical significance with p < 0.05.

Journal: Frontiers in Immunology

Article Title: Changes in immune cell signatures during early infection reflect decoupling of capillary perfusion and glycocalyx dimensions

doi: 10.3389/fimmu.2025.1589959

Figure Lengend Snippet: Correlation of PBMC with microvascular flow parameters (A) Family Tree of correlation coefficients (Spearman's ρ) of flow cytometry markers with PBR (B) Family Tree of correlation coefficients (Spearman's ρ) of flow cytometry markers with capillary density. Color filling represents correlation coefficients, solid node borders indicating statistical significance with p < 0.05.

Article Snippet: The Microvascular Health Score (MVHS; in points) is a composite metric, which has been previously presented in detail ( ).

Techniques: Flow Cytometry