Elastomeric Trilayer Substrates with Native-like Mechanical Properties for Heart Valve Leaflet Tissue Engineering

Heart valve leaflets have a complex trilayered structure with layer-specific orientations, anisotropic tensile properties, and elastomeric characteristics that are difficult to mimic collectively. Previously, trilayer leaflet substrates intended for heart valve tissue engineering were developed with nonelastomeric biomaterials that cannot deliver native-like mechanical properties. In this study, by electrospinning polycaprolactone (PCL) polymer and poly(l-lactide-co-ε-caprolactone) (PLCL) copolymer, we created elastomeric trilayer PCL/PLCL leaflet substrates with native-like tensile, flexural, and anisotropic properties and compared them with trilayer PCL leaflet substrates (as control) to find their effectiveness in heart valve leaflet tissue engineering. These substrates were seeded with porcine valvular interstitial cells (PVICs) and cultured for 1 month in static conditions to produce cell-cultured constructs. The PCL/PLCL substrates had lower crystallinity and hydrophobicity but higher anisotropy and flexibility than PCL leaflet substrates. These attributes contributed to more significant cell proliferation, infiltration, extracellular matrix production, and superior gene expression in the PCL/PLCL cell-cultured constructs than in the PCL cell-cultured constructs. Further, the PCL/PLCL constructs showed better resistance to calcification than PCL constructs. Trilayer PCL/PLCL leaflet substrates with native-like mechanical and flexural properties could significantly improve heart valve tissue engineering.

A Physics-Guided Neural Operator Learning Approach to Model Biological Tissues From Digital Image Correlation Measurements

We present a data-driven workflow to biological tissue modeling, which aims to predict the displacement field based on digital image correlation (DIC) measurements under unseen loading scenarios, without postulating a specific constitutive model form nor possessing knowledge of the material microstructure. To this end, a material database is constructed from the DIC displacement tracking measurements of multiple biaxial stretching protocols on a porcine tricuspid valve anterior leaflet, with which we build a neural operator learning model. The material response is modeled as a solution operator from the loading to the resultant displacement field, with the material microstructure properties learned implicitly from the data and naturally embedded in the network parameters. Using various combinations of loading protocols, we compare the predictivity of this framework with finite element analysis based on three conventional constitutive models. From in-distribution tests, the predictivity of our approach presents good generalizability to different loading conditions and outperforms the conventional constitutive modeling at approximately one order of magnitude. When tested on out-of-distribution loading ratios, the neural operator learning approach becomes less effective. To improve the generalizability of our framework, we propose a physics-guided neural operator learning model via imposing partial physics knowledge. This method is shown to improve the model's extrapolative performance in the small-deformation regime. Our results demonstrate that with sufficient data coverage and/or guidance from partial physics constraints, the data-driven approach can be a more effective method for modeling biological materials than the traditional constitutive modeling.

Leaflet Tissue Generation from Microfibrous Heart Valve Leaflet Scaffolds with Native Characteristics

Mechanical and bioprosthetic valves that are currently applied for replacing diseased heart valves are not fully efficient. Heart valve tissue engineering may solve the issues faced by the prosthetic valves in heart valve replacement. The leaflets of native heart valves have a trilayered structure with layer-specific orientations; thus, it is imperative to develop functional leaflet tissue constructs with a native trilayered, oriented structure. Its key solution is to develop leaflet scaffolds with a native morphology and structure. In this study, microfibrous leaflet scaffolds with a native trilayered and oriented structure were developed in an electrospinning system. The scaffolds were implanted for 3 months in rats subcutaneously to study the scaffold efficiencies in generating functional tissue-engineered leaflet constructs. These in vivo tissue-engineered leaflet constructs had a trilayered, oriented structure similar to native leaflets. The tensile properties of constructs indicated that they were able to endure the hydrodynamic load of the native heart valve. Collagen, glycosaminoglycans, and elastin─the predominant extracellular matrix components of native leaflets─were found sufficiently in the leaflet tissue constructs. The residing cells in the leaflet tissue constructs showed vimentin and α-smooth muscle actin expression, i.e., the constructs were in a growing state. Thus, the trilayered, oriented fibrous leaflet scaffolds produced in this study could be useful to develop heart valve scaffolds for successful heart valve replacements.

A novel culture device for the evaluation of three-dimensional extracellular matrix materials

Cell-matrix interactions in a three-dimensional (3D) extracellular matrix (ECM) are of fundamental importance in living tissue, and their in vitro reconstruction in bioartificial structures represents a core target of contemporary tissue engineering concepts. For a detailed analysis of cell-matrix interaction under highly controlled conditions, we developed a novel ECM evaluation culture device (EECD) that allows for a precisely defined surface-seeding of 3D ECM scaffolds, irrespective of their natural geometry. The effectiveness of EECD was evaluated in the context of heart valve tissue engineering. Detergent decellularized pulmonary cusps were mounted in EECD and seeded with endothelial cells (ECs) to study EC adhesion, morphology and function on a 3D ECM after 3, 24, 48 and 96 h. Standard EC monolayers served as controls. Exclusive top-surface-seeding of 3D ECM by viable ECs was demonstrated by laser scanning microscopy (LSM), resulting in a confluent re-endothelialization of the ECM after 96 h. Cell viability and protein expression, as demonstrated by MTS assay and western blot analysis (endothelial nitric oxide synthase, von Willebrand factor), were preserved at maintained levels over time. In conclusion, EECD proves as a highly effective system for a controlled repopulation and in vitro analysis of cell-ECM interactions in 3D ECM.