Metabolite marker signals contributing to the differentiation and prediction.

<p>a. S-plot analysis showing the correlation and covariation. Metabolites on the upper right corner contribute to the improved group and on the lower left corner contribute to the non-improved group. b. PLS loading plot showing the contribution to the prediction of the HbA1c. Metabolites signals were identified using Chenomx and in-house built metabolite libraries.</p

Prediction of HbA1c using PLS multivariate regression.

<p>PLS regression models were built with the NMR profile at 7-day time point and the 3-month post-operative HbA1c values. The observed (X-axis) values are actually measured values and the predicted (Y-axis) values are from the PLS regression model obtained with two PLS components. The diagonal dashed line represents the theoretical perfect match, and the dotted line represents the least-square fitted line. Comparison between the observed and predicted values obtained from the training dataset (a), leave-one-out analysis (b), and three-fold cross validation (c). The predicted values in (a) do not represent true prediction since all the data were used in the model building. One (b) or seven (c) samples were left out at a time, and the predictions were made using the model built without the test data to be predicted until every sample was left out once.</p

Change of Anthropometric and Metabolic Parameters in improved and non-improved groups.

<p>*Patients who had glycated hemoglobin percentage less than 7.0% without glucose-lowering agent in 3 months after metabolic surgery.</p>1<p>OGTT indicates oral glucose tolerance test at 30, 60, 90, or 120 min after 75 g glucose intake.</p>2<p>paired t-test.</p>3<p>Not available.</p><p>Change of Anthropometric and Metabolic Parameters in improved and non-improved groups.</p

Schematic illustration on relation between glycocalyx accessibility and microvascular perfusion regulation.

<p><b>A</b>) Healthy state: Intact glycocalyx prevents red blood cells (RBC, red dots) from penetrating into its domain, reflected by a low perfused boundary region (PBR), and nicely aligned elongated RBC. The vessels are well perfused (higher tube hematocrit of microvessel and elongated shape of erythrocyte) resulting in a higher percentage of vessel segments with RBC present at any particular time point (high RBC filling percentage). <b>B</b>) Risk State: Altered composition of glycocalyx (lined dots) allows RBCs to penetrate deeper into the glycocalyx, closer to the anatomical border of lumen (endothelium), reflected by the high PBR. Due to the widening of RBC distribution width and volume, there is more space in between each RBC, as shown by decreased RBC filling percentage (less positive contrast per vascular segment per time point). Also, prolonged state of glycocalyx degradation leads to edematous and non-functioning vessels, leading to shorter vessel density per area of tissue (reduced valid microvascular density in risk PBR), depicted by the loss of bottom vessel.</p

Linear regression analysis show association between perfused boundary region and microvascular perfusion parameters.

<p>*Dependent variable: Perfused boundary region (PBR).</p>†<p>95% confidence interval for regression coefficient β.</p>‡<p>Linear regression analysis adjusted for age, sex and BMI.</p>§<p>Valid microvascular density expressed as millimeter of microvessel length per mm² of area of tissue (mm/mm²) for linear regression analysis due to difference in scale from PBR.</p

Sidestream darkfield imaging derived variables characteristics.

<p>Data is presented as mean ± standard deviation.</p

General Clinical Characteristics.

<p>Hb, hemoglobin; Hct, hematocrit; BP, blood pressure. Data is presented as mean ± standard deviation.</p

Glycocheck algorithm on endothelial PBR determination and microvascular perfusion properties.

<p><b>A</b>) Red blood cells (RBC) are detected through reflection of light emitting diodes by hemoglobin. Images captured by the sidestream darkfield camera are sent to the computer for quality checks and assessment. The black contrast is the perfused lumen of the vessels. <b>B</b>) In each recording, the software automatically places the vascular segments (green), every 10 µm along the vascular segments (black contrast). <b>C</b>) After the acquisition, for the analysis, the software undergoes several quality check in the first frame of each recording (see text), to select vascular segments with sufficient quality for further analysis. Invalid vascular segments (yellow) are distinguished from the valid vascular segments (green). During the whole recording session of 40 frames, the percentage of time in which a particular valid vascular segment has RBCs present is used to calculate RBC filling percentage. <b>D</b>) Depiction of the concept of glycocalyx thickness by lateral RBC movement is shown here. <b>E</b>) For each vascular segment, the intensity profile is calculated to derive median RBC column width. <b>F</b>) Then, the distribution of RBC column width is used to calculate the perfused diameter, median RBC column width, and subsequently the perfused boundary region (PBR).</p

Scatterplot between PBR and outcomes of microvascular perfusion.

<p>The perfused boundary region (PBR), a measurement for glycocalyx accessibility to red blood cells (RBC), is associated significantly with spatio-temporal aspects of microvascular perfusion variables: <b>A</b>) RBC filling percentage (percentage of time in which a particular vascular segment is perfused) <b>B</b>) Valid microvascular density. In particular, lower PBR (less accessible glycocalyx, thus a better and thicker glycocalyx) is associated with higher RBC filling percentage (temporal perfusion).</p