Cryopreservation of 3D Bioprinted Scaffolds with Temperature-Controlled-Cryoprinting.

Temperature-Controlled-Cryoprinting (TCC) is a new 3D bioprinting technology that allows for the fabrication and cryopreservation of complex and large cell-laden scaffolds. During TCC, bioink is deposited on a freezing plate that descends further into a cooling bath, keeping the temperature at the nozzle constant. To demonstrate the effectiveness of TCC, we used it to fabricate and cryopreserve cell-laden 3D alginate-based scaffolds with high cell viability and no size limitations.

Computational Fontan Analysis: Preserving Accuracy While Expediting Workflow.

Postoperative outcomes of the Fontan operation have been linked to geometry of the cavopulmonary pathway, including graft shape after implantation. Computational fluid dynamics (CFD) simulations are used to explore different surgical options. The objective of this study is to perform a systematic validation for investigating the accuracy and efficiency of CFD simulation to predict Fontan hemodynamics.

Non-invasive Prediction of Peak Systolic Pressure Drop across Coarctation of Aorta using Computational Fluid Dynamics.

This paper proposes a novel method to noninvasively measure the peak systolic pressure difference (PSPD) across coarctation of the aorta for diagnosing the severity of coarctation. Traditional non-invasive estimates of pressure drop from the ultrasound can underestimate the severity and invasive measurements by cardiac catheterization can carry risks for patients. To address the issues, we employ computational fluid dynamics (CFD) computation to accurately predict the PSPD across a coarctation based on cardiac magnetic resonance (CMR) imaging data and cuff pressure measurements from one arm.

Setting Up All-Atom Molecular Dynamics Simulations to Study the Interactions of Peripheral Membrane Proteins with Model Lipid Bilayers.

All-atom molecular dynamics (MD) simulations enable the study of biological systems at atomic detail, complement the understanding gained from experiment, and can also motivate experimental techniques to further examine a given biological process. This method is based on statistical mechanics; it predicts the trajectory of atoms over time by solving Newton's Laws of motion taking into account all forces. Here, we describe the use of this methodology to study the interaction between peripheral membrane proteins and a lipid bilayer.

Effect of Membrane Lipid Packing on Stable Binding of the ALPS Peptide.

The amphipathic lipid packing sensor (ALPS) motif, originally discovered on the ArfGAP1 membrane-binding protein, binds to pre-existing large packing defects in a membrane (spontaneous or due to membrane curvature), though a more precise relationship between the ALPS peptide and packing defect characteristics of a membrane remains unclear. We developed an image processing technique for identifying packing defects to quantify the relationship between the ALPS peptide of the Osh4 protein in yeast and packing defects on a membrane model using molecular dynamics simulations. We used the highly mobile membrane mimetic (HMMM) model to create very large packing defects and expedite the binding time scale.