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Eyckmans, J.

Publications and source records attributed to Eyckmans, J..

2 recordsLinked to original sources

Intrinsic Repair Capacity of Resident Tendon Cells is Dependent on Hole Size in an Ex Vivo Model of Laser-Induced Microdamage

While it is generally accepted that tendon healing following widespread extracellular matrix trauma is limited, tenocytes are thought to have the capacity to repair small amounts of microdamage generated through activities of daily living. Despite this, few studies have directly studied the mechanisms governing this process. To address this, we developed a tunable in vitro model of extracellular matrix microdamage in live tendon explants that enables us to track both clearance of denatured collagen microdamage and closure of a micro-sized defect in the tendon matrix. The purpose of this study was to controllably induce varying levels of localized microdamage to the tendon explants and identify (1) if thresholds for healing exist and (2) whether repair mechanisms are dependent on initial damage size. We found that within three weeks, all tendon explants were able to clear damaged matrix to some extent regardless of the damage size. Interestingly, larger 5 mJ and 10 mJ injuries resulted in a more robust rate of damaged matrix clearance in the later weeks, while smaller injuries exhibited a more consistent rate that led to full clearance in two explants. Greater than 50% clearance of denatured collagen microdamage was typically associated with an accompanying closure of the ECM defect, suggesting a strong relationship between clearance and closure. Overall, our work demonstrates the power of our laser-induced microdamage model, which enables the direct visualization of microdamage responses. This model will be a powerful asset for investigating mechanisms of damage accumulation and/or healing, as well as identifying local tendon-specific factors that can be leveraged for therapeutics.

bioengineering↗

Three-dimensional flow assessment of microvascular beds with interstitial space

The health and function of microvascular beds are dramatically impacted by the mechanical forces that they experience due to fluid flow. These fluid flow-generated forces are challenging to measure directly and are typically calculated from experimental flow data. However, current computational fluid dynamics (CFD) models either employ truncated 2D models or overlook the presence of extraluminal flows within the interstitial space between vessels that result from the permeability of the endothelium lining the vessels, which are crucial components affecting flow dynamics. To address this, we present a bottom-up modeling approach that assesses fluid flow in 3D-engineered vessel networks featuring an endothelial lining and interstitial space. Using image processing algorithms to segment 3D confocal image stacks from engineered capillary networks, we reconstructed a 3D computational model of the networks. We incorporated vascular permeability and matrix porosity values to model the contributions of the endothelial lining and interstitial spaces to the flow dynamics in the networks. Simulations suggest that including the endothelial monolayer and the interstitium significantly affects the predicted flow magnitude in the vessels and flow profiles in the interstitium. To demonstrate the importance of these factors, we showed experimentally and computationally that while cytokine (IL-1{beta}) treatment did not affect the network architecture, it significantly increased vessel permeability and resulted in a dramatic decrease in wall shear stresses and flow velocities intraluminally within the networks. In conclusion, this framework offers a robust methodology for studying flow dynamics in 3D in vitro vessel networks, enhancing our understanding of vascular physiology and pathology. TRANSLATIONAL IMPACT STATEMENTThis study introduces a new approach to modeling and flow assessment in 3D microvascular beds and surrounding interstitial spaces. Modeling interstitial space and endothelial monolayer thickness is essential for capturing fluid leakage from the microvascular network into the interstitial space and vice versa when the endothelial monolayer permeability is significantly affected in pathological conditions. Our approach to modeling 3D vascular networks can be used in vivo and in clinical settings to understand flow in tissue microvasculature and its surroundings under disease and healthy conditions.

bioengineering↗