Design of a Mechanobioreactor to Apply Anisotropic, Biaxial Strain to Large Thin Biomaterials for Tissue Engineered Heart Valve Applications

Strategies for Development of Synthetic Heart Valve Tissue Engineering Scaffolds

The current clinical solutions, including mechanical and bioprosthetic valves for valvular heart diseases, are plagued by coagulation, calcification, nondurability, and the inability to grow with patients. The tissue engineering approach attempts to resolve these shortcomings by producing heart valve scaffolds that may deliver patients a life-long solution. Heart valve scaffolds serve as a three-dimensional support structure made of biocompatible materials that provide adequate porosity for cell infiltration, and nutrient and waste transport, sponsor cell adhesion, proliferation, and differentiation, and allow for extracellular matrix production that together contributes to the generation of functional neotissue. The foundation of successful heart valve tissue engineering is replicating native heart valve architecture, mechanics, and cellular attributes through appropriate biomaterials and scaffold designs. This article reviews biomaterials, the fabrication of heart valve scaffolds, and their in-vitro and in-vivo evaluations applied for heart valve tissue engineering.

Serum- and xeno-free culture of human umbilical cord perivascular cells for pediatric heart valve tissue engineering

BACKGROUND

Constructs currently used to repair or replace congenitally diseased pediatric heart valves lack a viable cell population capable of functional adaptation in situ, necessitating repeated surgical intervention. Heart valve tissue engineering (HVTE) can address these limitations by producing functional living tissue in vitro that holds the potential for somatic growth and remodelling upon implantation. However, clinical translation of HVTE strategies requires an appropriate source of autologous cells that can be non-invasively harvested from mesenchymal stem cell (MSC)-rich tissues and cultured under serum- and xeno-free conditions. To this end, we evaluated human umbilical cord perivascular cells (hUCPVCs) as a promising cell source for in vitro production of engineered heart valve tissue.

METHODS

The proliferative, clonogenic, multilineage differentiation, and extracellular matrix (ECM) synthesis capacities of hUCPVCs were evaluated in a commercial serum- and xeno-free culture medium (StemMACS™) on tissue culture polystyrene and benchmarked to adult bone marrow-derived MSCs (BMMSCs). Additionally, the ECM synthesis potential of hUCPVCs was evaluated when cultured on polycarbonate polyurethane anisotropic electrospun scaffolds, a representative biomaterial for in vitro HVTE.

RESULTS

hUCPVCs had greater proliferative and clonogenic potential than BMMSCs in StemMACS™ (p < 0.05), without differentiation to osteogenic and adipogenic phenotypes associated with valve pathology. Furthermore, hUCPVCs cultured with StemMACS™ on tissue culture plastic for 14 days synthesized significantly more total collagen, elastin, and sulphated glycosaminoglycans (p < 0.05), the ECM constituents of the native valve, than BMMSCs. Finally, hUCPVCs retained their ECM synthesizing capacity after 14 and 21 days in culture on anisotropic electrospun scaffolds.

CONCLUSION

Overall, our findings establish an in vitro culture platform that uses hUCPVCs as a readily-available and non-invasively sourced autologous cell population and a commercial serum- and xeno-free culture medium to increase the translational potential of future pediatric HVTE strategies. This study evaluated the proliferative, differentiation and extracellular matrix (ECM) synthesis capacities of human umbilical cord perivascular cells (hUCPVCs) when cultured in serum- and xeno-free media (SFM) against conventionally used bone marrow-derived MSCs (BMMSCs) and serum-containing media (SCM). Our findings support the use of hUCPVCs and SFM for in vitro heart valve tissue engineering (HVTE) of autologous pediatric valve tissue. Figure created with BioRender.com.

Control of hydrostatic pressure and osmotic stress in 3D cell culture for mechanobiological studies

Hydrostatic pressure (HP) and osmotic stress (OS) play an important role in various biological processes, such as cell proliferation and differentiation. In contrast to canonical mechanical signals transmitted through the anchoring points of the cells with the extracellular matrix, the physical and molecular mechanisms that transduce HP and OS into cellular functions remain elusive. Three-dimensional cell cultures show great promise to replicate physiologically relevant signals in well-defined host bioreactors with the goal of shedding light on hidden aspects of the mechanobiology of HP and OS. This review starts by introducing prevalent mechanisms for the generation of HP and OS signals in biological tissues that are subject to pathophysiological mechanical loading. We then revisit various mechanisms in the mechanotransduction of HP and OS, and describe the current state of the art in bioreactors and biomaterials for the control of the corresponding physical signals.

3D Localization of Hand Acupoints Using Hand Geometry and Landmark Points Based on RGB-D CNN Fusion

Acupoint stimulation has proven to be of significant importance for rehabilitation and preventive therapy. Moxibustion, a kind of acupoint therapy, has mainly been performed by practitioners relying on manual localization and positioning of acupoints, leading to variance in the accuracy owing to human error. Developments in the automatic detection of acupoints using deep learning techniques have proven to somewhat tackle the problem. But the current methods lack depth-based localization and are thus confined to two-dimensional (2D) localization. In this research, a new approach towards 3D acupoint localization is introduced, based on a fusion of RGB and depth convolutional neural networks (CNN) to guide the manipulator. This research aims to tackle the challenge of real-time 3D acupoint localization in order to provide guidance for robot-controlled moxibustion. In the first step, the 3D sensor (Kinect v1) is calibrated and transformation matrix is computed to project the depth data into the RGB domain. Secondly, a fusion of RGB-CNN and depth-CNN is employed, in order to obtain 3D localization. Lastly, 3D coordinates are fed to the manipulator to perform artificially controlled moxibustion therapy. Furthermore, a 3D acupoint dataset consisting of RGB and depth images of hands, is constructed to train, validate and test the network. The network was able to localize 5 sets of acupoints with an average localization error of less than 0.09. Further experiments prove the efficacy of the approach and lay grounds for development of automatic moxibustion robots.