From this perspective, we discuss the different stages of development the tissue engineering (TE) field has gone through in its relatively young history. We discuss how TE is evolving from a ...technology-driven, science-focused field toward a patient-driven, manufacturing-focused one where patients' needs are translated into production process requirements, and subsequently into technological and biological innovations needed to meet the regulatory and clinical demands.
A combination of reaction–diffusion models with moving-boundary problems yields a system in which the diffusion (spreading and penetration) and reaction (transformation) evolve the system’s state and ...geometry over time. These systems can be used in a wide range of engineering applications. In this study, as an example of such a system, the degradation of metallic materials is investigated. A mathematical model is constructed of the diffusion-reaction processes and the movement of corrosion front of a magnesium block floating in a chemical solution. The corresponding parallelized computational model is implemented using the finite element method, and the weak and strong-scaling behaviors of the model are evaluated to analyze the performance and efficiency of the employed high-performance computing techniques.
•Mathematical modeling of corrosion of degradable magnesium.•Bayesian optimization for model calibration using experimental data.•Dedicated corrosion tests in saline and SBF solutions for ...validation.•A good agreement of model predictions with experimentally obtained values.•Mathematical presentation of local and global pH changes.
Despite the advantages of using biodegradable metals in implant design, their uncontrolled degradation and release remain a challenge in practical applications. A validated computational model of the degradation process can facilitate tuning implant biodegradation properties. In this study, a mathematical model of the chemistry of magnesium biodegradation was developed and implemented in a 3D computational model. The parameters were calibrated by Bayesian optimization using dedicated experimental data. The model was validated by comparing the predicted and experimentally obtained pH change in saline and buffered solutions, showing maximum 5% of difference, demonstrating the model's validity to be used for practical cases.
In the field of regenerative medicine, microcarriers are used as support matrix for the growth of adherent cells. They are increasingly recognised as promising biomaterials for large scale, ...cost-effective cell expansion bioreactor processes. However, their individual morphologies can be highly heterogeneous which increases bioprocesses' variability. Additionally, only limited information is available on the microcarriers' 3D morphology and how it affects cell proliferation. Most imaging modalities do not provide sufficient 3D information or have a too limited field of view to appropriately study the 3D morphology. While microfocus X-ray computed tomography (microCT) could be appropriate, many microcarriers are hydrated before in-vitro use. This wet state makes them swell, changing considerably their morphology and making them indistinguishable from the culture solution in regular microCT images due to their physical density close to water. The use of contrast-enhanced microCT (CE-CT) has been recently reported for 3D imaging of soft materials. In this study, we selected a range of commercially available microcarrier types and used a combination of microCT and CE-CT for full 3D morphological characterization of large numbers of microcarriers, both in their dry and wet state. With in-house developed image processing and analysis tools, morphometrics of individual microcarriers were collected. Also, the morphology in wet state was assessed and related to accessible attachment surface area as a function of cell size. The morphological information on all microcarriers was collected in a publicly available database. This work provides a quantitative basis for optimization and modelling of microcarrier based cell expansion processes.
Clinical translation of cell‐based products is hampered by their limited predictive in vivo performance. To overcome this hurdle, engineering strategies advocate to fabricate tissue products through ...processes that mimic development and regeneration, a strategy applicable for the healing of large bone defects, an unmet medical need. Natural fracture healing occurs through the formation of a cartilage intermediate, termed “soft callus,” which is transformed into bone following a process that recapitulates developmental events. The main contributors to the soft callus are cells derived from the periosteum, containing potent skeletal stem cells. Herein, cells derived from human periosteum are used for the scalable production of microspheroids that are differentiated into callus organoids. The organoids attain autonomy and exhibit the capacity to form ectopic bone microorgans in vivo. This potency is linked to specific gene signatures mimicking those found in developing and healing long bones. Furthermore, callus organoids spontaneously bioassemble in vitro into large engineered tissues able to heal murine critical‐sized long bone defects. The regenerated bone exhibits similar morphological properties to those of native tibia. These callus organoids can be viewed as a living “bio‐ink” allowing bottom‐up manufacturing of multimodular tissues with complex geometric features and inbuilt quality attributes.
Developmentally engineered callus organoids allow implementation of bone by design strategies. Callus organoids exhibit a remarkable capacity to form bone microorgans upon implantation. This capacity is linked to specific gene profiles that correspond to developmental and fracture healing processes. When assembled in vitro, the callus organoids fuse resulting in large multimodular implants able to rapidly heal critical‐sized long bone defects.
Regulation of mRNA translation elongation impacts nascent protein synthesis and integrity and plays a critical role in disease establishment. Here, we investigate features linking regulation of ...codon-dependent translation elongation to protein expression and homeostasis. Using knockdown models of enzymes that catalyze the mcm
s
wobble uridine tRNA modification (U
-enzymes), we show that gene codon content is necessary but not sufficient to predict protein fate. While translation defects upon perturbation of U
-enzymes are strictly dependent on codon content, the consequences on protein output are determined by other features. Specific hydrophilic motifs cause protein aggregation and degradation upon codon-dependent translation elongation defects. Accordingly, the combination of codon content and the presence of hydrophilic motifs define the proteome whose maintenance relies on U
-tRNA modification. Together, these results uncover the mechanism linking wobble tRNA modification to mRNA translation and aggregation to maintain proteome homeostasis.
Advances in additive manufacturing technologies are leading to an increased interest in the design of intricate 3D geometries for applications ranging from aerospace to biomedical engineering. In ...this paper, we present ASLI (A Simple Lattice Infiller), a cross-platform tool for the generation of cellular solid structures that allows users to provide implicitly defined lattice infills to 3D objects by specifying the desired local unit cell type, size and feature. It is written in C++ and relies on the open-source libraries Mmg and CGAL to handle the implicit domain discretisation. Although developed to design lattice infills for skeletal tissue engineering applications, ASLI can be used for any application that requires the user to provide lattice infills to 3D objects. Its capabilities are shown through a series of examples that demonstrate complex designs can easily be accomplished. The code is published under an open-source license and is available for download at
github.com/tpms-lattice/ASLI
.
Boolean models have been instrumental in predicting general features of gene networks and more recently also as explorative tools in specific biological applications. In this study we introduce a ...basic quantitative and a limited time resolution to a discrete (Boolean) framework. Quantitative resolution is improved through the employ of normalized variables in unison with an additive approach. Increased time resolution stems from the introduction of two distinct priority classes. Through the implementation of a previously published chondrocyte network and T helper cell network, we show that this addition of quantitative and time resolution broadens the scope of biological behaviour that can be captured by the models. Specifically, the quantitative resolution readily allows models to discern qualitative differences in dosage response to growth factors. The limited time resolution, in turn, can influence the reachability of attractors, delineating the likely long term system behaviour. Importantly, the information required for implementation of these features, such as the nature of an interaction, is typically obtainable from the literature. Nonetheless, a trade-off is always present between additional computational cost of this approach and the likelihood of extending the model's scope. Indeed, in some cases the inclusion of these features does not yield additional insight. This framework, incorporating increased and readily available time and semi-quantitative resolution, can help in substantiating the litmus test of dynamics for gene networks, firstly by excluding unlikely dynamics and secondly by refining falsifiable predictions on qualitative behaviour.
Osteoarthritis (OA), a degenerative joint disease, is the most common chronic condition of the joints, which cannot be prevented effectively. Computational modeling of joint degradation allows to ...estimate the patient-specific progression of OA, which can aid clinicians to estimate the most suitable time window for surgical intervention in osteoarthritic patients. This paper gives an overview of the different approaches used to model different aspects of joint degeneration, thereby focusing mostly on the knee joint. The paper starts by discussing how OA affects the different components of the joint and how these are accounted for in the models. Subsequently, it discusses the different modeling approaches that can be used to answer questions related to OA etiology, progression and treatment. These models are ordered based on their underlying assumptions and technologies: musculoskeletal models, Finite Element models, (gene) regulatory models, multiscale models and data-driven models (artificial intelligence/machine learning). Finally, it is concluded that in the future, efforts should be made to integrate the different modeling techniques into a more robust computational framework that should not only be efficient to predict OA progression but also easily allow a patient's individualized risk assessment as screening tool for use in clinical practice.
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