Xuan Pei

Preparation and characterization of bone marrow mesenchymal stem cell-derived extracellular matrix scaffolds

The aim of this study was to assess the feasibility of creating extracellular matrix (ECM) scaffolds from mesenchymal stem cells. Bone marrow mesenchymal stem cell (BMSC)-derived ECM (BMSC-dECM) scaffolds were fabricated by lyophilization after crosslinking, without using a decellularization process. Acellular porcine chondrocyte-derived ECM (AC-dECM) scaffolds were used as a control. The surface morphology, internal structure, water uptake ratio, mechanical properties, and biocompatibility of the scaffolds, as well as the in vitro behavior of cells grown on the scaffolds were examined and compared between the two scaffold types. For the BMSC-dECM scaffolds, the average pore size was 304.4 ± 108.2 μm, average porosity was 93.3% ± 4.5%, average compressive modulus was 6.8 ± 1.5 kPa, and average water uptake ratio exceeded 20. The BMSC-dECM scaffolds supported the in vitro attachment and proliferation of cells, with these aspects likely being comparable to those of the AC-dECM scaffolds. The findings of this preliminary study highlight the potential utility of BMSC-derived ECM scaffolds for future cartilage tissue-engineering applications.

Feasibility of Autologous Bone Marrow Mesenchymal Stem Cell–Derived Extracellular Matrix Scaffold for Cartilage Tissue Engineering

Extracellular matrix (ECM) materials are widely used in cartilage tissue engineering. However, the current ECM materials are unsatisfactory for clinical practice as most of them are derived from allogenous or xenogenous tissue. This study was designed to develop a novel autologous ECM scaffold for cartilage tissue engineering. The autologous bone marrow mesenchymal stem cell-derived ECM (aBMSC-dECM) membrane was collected and fabricated into a three-dimensional porous scaffold via cross-linking and freeze-drying techniques. Articular chondrocytes were seeded into the aBMSC-dECM scaffold and atelocollagen scaffold, respectively. An in vitro culture and an in vivo implantation in nude mice model were performed to evaluate the influence on engineered cartilage. The current results showed that the aBMSC-dECM scaffold had a good microstructure and biocompatibility. After 4 weeks in vitro culture, the engineered cartilage in the aBMSC-dECM scaffold group formed thicker cartilage tissue with more homogeneous structure and higher expressions of cartilaginous gene and protein compared with the atelocollagen scaffold group. Furthermore, the engineered cartilage based on the aBMSC-dECM scaffold showed better cartilage formation in terms of volume and homogeneity, cartilage matrix content, and compressive modulus after 3 weeks in vivo implantation. These results indicated that the aBMSC-dECM scaffold could be a successful novel candidate scaffold for cartilage tissue engineering.

How does calcification influence plaque vulnerability? Insights from fatigue analysis.

Background. Calcification is commonly believed to be associated with cardiovascular disease burden. But whether or not the calcifications have a negative effect on plaque vulnerability is still under debate. Methods and Results. Fatigue rupture analysis and the fatigue life were used to evaluate the rupture risk. An idealized baseline model containing no calcification was first built. Based on the baseline model, we investigated the influence of calcification on rupture path and fatigue life by adding a circular calcification and changing its location within the fibrous cap area. Results show that 84.0% of calcified cases increase the fatigue life up to 11.4%. For rupture paths 10D far from the calcification, the life change is negligible. Calcifications close to lumen increase more fatigue life than those close to the lipid pool. Also, calcifications in the middle area of fibrous cap increase more fatigue life than those in the shoulder area. Conclusion. Calcifications may play a positive role in the plaque stability. The influence of the calcification only exists in a local area. Calcifications close to lumen may be influenced more than those close to lipid pool. And calcifications in the middle area of fibrous cap are seemly influenced more than those in the shoulder area.

Fatigue Crack Growth Under Pulsatile Pressure and Plaque Rupture

Identification of vulnerable plaque pre-rupture is extremely important for patient risk stratification. The mechanism of plaque rupture is still not entirely clear, but it is thought to be a process involving multiple factors. From a biomechanical viewpoint, plaque rupture is usually seen as a structural failure when the plaque cannot resist the hemodynamic blood pressure and shear stress exerted on it. However, the cardiovascular system is naturally a cyclical hemodynamic environment, and myocardial infarction can be a symptomatically quiescent but potentially progressive process when plaque ruptures at stresses much lower than its strength. Therefore, fatigue accumulation is a possible mechanism for plaque rupture. In this study, a crack growth model was developed, and the previously-mentioned hypothesis was tested by conducting a comparative study between 18 symptomatic and 16 asymptomatic patients with carotid stenosis.

Combining IVUS and Optical Coherence Tomography for More Accurate Coronary Cap Thickness Quantification and Stress/Strain Calculations: A Patient-Specific Three-Dimensional Fluid-Structure Interaction Modeling Approach

Accurate cap thickness and stress/strain quantifications are of fundamental importance for vulnerable plaque research. Virtual histology intravascular ultrasound (VH-IVUS) sets cap thickness to zero when cap is under resolution limit and IVUS does not see it. An innovative modeling approach combining IVUS and optical coherence tomography (OCT) is introduced for cap thickness quantification and more accurate cap stress/strain calculations. In vivo IVUS and OCT coronary plaque data were acquired with informed consent obtained. IVUS and OCT images were merged to form the IVUS + OCT data set, with biplane angiography providing three-dimensional (3D) vessel curvature. For components where VH-IVUS set zero cap thickness (i.e., no cap), a cap was added with minimum cap thickness set as 50 and 180 μm to generate IVUS50 and IVUS180 data sets for model construction, respectively. 3D fluid-structure interaction (FSI) models based on IVUS + OCT, IVUS50, and IVUS180 data sets were constructed to investigate cap thickness impact on stress/strain calculations. Compared to IVUS + OCT, IVUS50 underestimated mean cap thickness (27 slices) by 34.5%, overestimated mean cap stress by 45.8%, (96.4 versus 66.1 kPa). IVUS50 maximum cap stress was 59.2% higher than that from IVUS + OCT model (564.2 versus 354.5 kPa). Differences between IVUS and IVUS + OCT models for cap strain and flow shear stress (FSS) were modest (cap strain <12%; FSS <6%). IVUS + OCT data and models could provide more accurate cap thickness and stress/strain calculations which will serve as basis for further plaque investigations.

A parametric study of inflammatory effects on plaque mechanical stress

Acute myocardial infarction (AMI), caused by the rupture of vulnerable coronary plaque is the leading cause of death and disability worldwide. Inflammation as a risk factor is commonly found in atherosclerosis and strong evidence reported in the literature suggests that plaques with high macrophage accumulation are often unstable and susceptible to rupture [4] and [5]. Although a series of non-invasive imaging techniques has been developed to identify inflammation in the fibrous cap and inflammation has been proved to be a prominent imaging target due to its useful application in each stage of plaque evolution [2] and [3], the studies are inadequate in addressing whether inflammation directly impacts the mechanical stability of the plaque by altering the maximum tensile stress in the fibrous cap. In this work, we investigated the influence of focal inflammation on the mechanical stress in plaque by varying three key parameters of the inflammation region — its Youngs modulus, size and location...

A Machine Learning-Based Method for Intracoronary OCT Segmentation and Vulnerable Coronary Plaque Cap Thickness Quantification

Accurate cap thickness quantification is of fundamental importance for vulnerable plaque detection in cardiovascular research. A segmentation method for intracoronary optical coherence tomography (OCT) image based on least squares support vector machine (LS-SVM) was performed to characterize plaque component borders and quantify fibrous cap thickness. Manual segmentation of OCT images were performed by experts based on combination of virtual-histology intravascular ultrasound (VH-IVUS) and OCT images and used as gold standard. The segmentation methods based on LS-SVM provided accurate plaque cap thickness (an 8.6% error by LS-SVM vs. 71% error by IVUS50) serving as solid basis for plaque modeling and assessment.