Implementing computational modeling in tissue engineering: where disciplines meet

Computational methods for biofabrication in tissue engineering and regenerative medicine - a literature review

This literature review rigorously examines the growing scientific interest in computational methods for Tissue Engineering and Regenerative Medicine biofabrication, a leading-edge area in biomedical innovation, emphasizing the need for accurate, multi-stage, and multi-component biofabrication process models. The paper presents a comprehensive bibliometric and contextual analysis, followed by a literature review, to shed light on the vast potential of computational methods in this domain. It reveals that most existing methods focus on single biofabrication process stages and components, and there is a significant gap in approaches that utilize accurate models encompassing both biological and technological aspects. This analysis underscores the indispensable role of these methods in understanding and effectively manipulating complex biological systems and the necessity for developing computational methods that span multiple stages and components. The review concludes that such comprehensive computational methods are essential for developing innovative and efficient Tissue Engineering and Regenerative Medicine biofabrication solutions, driving forward advancements in this dynamic and evolving field.

Nanofibrous Microspheres: A Biomimetic Platform for Bone Tissue Regeneration

Bone, a fundamental constituent of the human body, is a vital scaffold for support, protection, and locomotion, underscoring its pivotal role in maintaining skeletal integrity and overall functionality. However, factors such as trauma, disease, or aging can compromise bone structure, necessitating effective strategies for regeneration. Traditional approaches often lack biomimetic environments conducive to efficient tissue repair. Nanofibrous microspheres (NFMS) present a promising biomimetic platform for bone regeneration by mimicking the native extracellular matrix architecture. Through optimized fabrication techniques and the incorporation of active biomolecular components, NFMS can precisely replicate the nanostructure and biochemical cues essential for osteogenesis promotion. Furthermore, NFMS exhibit versatile properties, including tunable morphology, mechanical strength, and controlled release kinetics, augmenting their suitability for tailored bone tissue engineering applications. NFMS enhance cell recruitment, attachment, and proliferation, while promoting osteogenic differentiation and mineralization, thereby accelerating bone healing. This review highlights the pivotal role of NFMS in bone tissue engineering, elucidating their design principles and key attributes. By examining recent preclinical applications, we assess their current clinical status and discuss critical considerations for potential clinical translation. This review offers crucial insights for researchers at the intersection of biomaterials and tissue engineering, highlighting developments in this expanding field.

Mini-bones: miniaturized bone in vitro models

In bone tissue engineering (TE) and regeneration, miniaturized, (sub)millimeter-sized bone models have become a popular trend since they bring about physiological biomimicry, precise orchestration of concurrent stimuli, and compatibility with high-throughput setups and high-content imaging. They also allow efficient use of cells, reagents, materials, and energy. In this review, we describe the state of the art of miniaturized in vitro bone models, or 'mini-bones', describing these models based on their characteristics of (multi)cellularity and engineered extracellular matrix (ECM), and elaborating on miniaturization approaches and fabrication techniques. We analyze the performance of 'mini-bone' models according to their applications for studying basic bone biology or as regeneration models, disease models, and screening platforms, and provide an outlook on future trends, challenges, and opportunities.

Mechanotransduction in stem cells

Nowadays, it is an established concept that the capability to reach a specialised cell identity via differentiation, as in the case of multi- and pluripotent stem cells, is not only determined by biochemical factors, but that also physical aspects of the microenvironment play a key role; interpreted by the cell through a force-based signalling pathway called mechanotransduction. However, the intricate ties between the elements involved in mechanotransduction, such as the extracellular matrix, the glycocalyx, the cell membrane, Integrin adhesion complexes, Cadherin-mediated cell/cell adhesion, the cytoskeleton, and the nucleus, are still far from being understood in detail. Here we report what is currently known about these elements in general and their specific interplay in the context of multi- and pluripotent stem cells. We furthermore merge this overview to a more comprehensive picture, that aims to cover the whole mechanotransductive pathway from the cell/microenvironment interface to the regulation of the chromatin structure in the nucleus. Ultimately, with this review we outline the current picture of the interplay between mechanotransductive cues and epigenetic regulation and how these processes might contribute to stem cell dynamics and fate.

Bridging systems biology and tissue engineering: Unleashing the full potential of complex 3D in vitro tissue models of disease

Rapid advances in tissue engineering have resulted in more complex and physiologically relevant 3D in vitro tissue models with applications in fundamental biology and therapeutic development. However, the complexity provided by these models is often not leveraged fully due to the reductionist methods used to analyze them. Computational and mathematical models developed in the field of systems biology can address this issue. Yet, traditional systems biology has been mostly applied to simpler in vitro models with little physiological relevance and limited cellular complexity. Therefore, integrating these two inherently interdisciplinary fields can result in new insights and move both disciplines forward. In this review, we provide a systematic overview of how systems biology has been integrated with 3D in vitro tissue models and discuss key application areas where the synergies between both fields have led to important advances with potential translational impact. We then outline key directions for future research and discuss a framework for further integration between fields.

An explainable machine learning-based probabilistic framework for the design of scaffolds in bone tissue engineering

Recently, 3D-printed biodegradable scaffolds have shown great potential for bone repair in critical-size fractures. The differentiation of the cells on a scaffold is impacted among other factors by the surface deformation of the scaffold due to mechanical loading and the wall shear stresses imposed by the interstitial fluid flow. These factors are in turn significantly affected by the material properties, the geometry of the scaffold, as well as the loading and flow conditions. In this work, a numerical framework is proposed to study the influence of these factors on the expected osteochondral cell differentiation. The considered scaffold is rectangular with a 0/90 lay-down pattern and a four-layered strut made of polylactic acid with a 5% steel particle content. The distribution of the different types of cells on the scaffold surface is estimated through a scalar stimulus, calculated by using a mechanobioregulatory model. To reduce the simulation time for the computation of the stimulus, a probabilistic machine learning (ML)-based reduced-order model (ROM) is proposed. Then, a sensitivity analysis is performed using the Shapley additive explanations to examine the contribution of the various parameters to the framework stimulus predictions. In a final step, a multiobjective optimization procedure is implemented using genetic algorithms and the ROM, aiming to identify the material parameters and loading conditions that maximize the percentage of surface area populated by bone cells while minimizing the area corresponding to the other types of cells and the resorption condition. The results of the performed analysis highlight the potential of using ROMs for the scaffold design, by dramatically reducing the simulation time while enabling the efficient implementation of sensitivity analysis and optimization procedures.

In silico model development and optimization of in vitro lung cell population growth

Tissue engineering predominantly relies on trial and error in vitro and ex vivo experiments to develop protocols and bioreactors to generate functional tissues. As an alternative, in silico methods have the potential to significantly reduce the timelines and costs of experimental programs for tissue engineering. In this paper, we propose a methodology to formulate, select, calibrate, and test mathematical models to predict cell population growth as a function of the biochemical environment and to design optimal experimental protocols for model inference of in silico model parameters. We systematically combine methods from the experimental design, mathematical statistics, and optimization literature to develop unique and explainable mathematical models for cell population dynamics. The proposed methodology is applied to the development of this first published model for a population of the airway-relevant bronchio-alveolar epithelial (BEAS-2B) cell line as a function of the concentration of metabolic-related biochemical substrates. The resulting model is a system of ordinary differential equations that predict the temporal dynamics of BEAS-2B cell populations as a function of the initial seeded cell population and the glucose, oxygen, and lactate concentrations in the growth media, using seven parameters rigorously inferred from optimally designed in vitro experiments.

Recent Advances in Liver Tissue Engineering as an Alternative and Complementary Approach for Liver Transplantation

Acute and chronic liver diseases cause significant morbidity and mortality worldwide, affecting millions of people. Liver transplantation is the primary intervention method, replacing a non-functional liver with a functional one. However, the field of liver transplantation faces challenges such as donor shortage, postoperative complications, immune rejection, and ethical problems. Consequently, there is an urgent need for alternative therapies that can complement traditional transplantation or serve as an alternative method. In this review, we explore the potential of liver tissue engineering as a supplementary approach to liver transplantation, offering benefits to patients with severe liver dysfunctions.

Lifelike Transformative Materials for Biohybrid Implants: Inspired by Nature, Driven by Technology

Today's living world is enriched with a myriad of natural biological designs, shaped by billions of years of evolution. Unraveling the construction rules of living organisms offers the potential to create new materials and systems for biomedicine. From the close examination of living organisms, several concepts emerge: hierarchy, pattern repetition, adaptation, and irreducible complexity. All these aspects must be tackled to develop transformative materials with lifelike behavior. This perspective article highlights recent progress in the development of transformative biohybrid systems for applications in the fields of tissue regeneration and biomedicine. Advances in computational simulations and data-driven predictions are also discussed. These tools enable the virtual high-throughput screening of implant design and performance before committing to fabrication, thus reducing the development time and cost of biomimetic and biohybrid constructs. The ongoing progress of imaging methods also constitutes an essential part of this matter in order to validate the computation models and enable longitudinal monitoring. Finally, the current challenges of lifelike biohybrid materials, including reproducibility, ethical considerations, and translation, are discussed. Advances in the development of lifelike materials will open new biomedical horizons, where perhaps what is currently envisioned as science fiction will become a science-driven reality in the future.

Automated Quantitative Analysis of Shape Features in Human Epithelial Monolayers and Spheroids Generated from Colorectal Cancer Cells

Advancements in microscopy techniques permit us to acquire endless datasets of images. A major bottleneck in cell imaging is how to analyze petabytes of data in an effective, reliable, objective, and effortless way. Quantitative imaging is becoming crucial to disentangle the complexity of many biological and pathological processes. For instance, cell shape is a summary readout of a myriad of cellular processes. Changes in cell shape use to reflect changes in growth, migration mode (including speed and persistence), differentiation stage, apoptosis, or gene expression, serving to predict health or disease. However, in certain contexts, e.g., tissues or tumors, cells are tightly packed together, and measurement of individual cellular shapes can be challenging and laborious. Bioinformatics solutions like automated computational image methods provide a blind and efficient analysis of large image datasets. Here we describe a detailed and friendly step-by-step protocol to extract various cellular shape parameters quickly and accurately from colorectal cancer cells forming either monolayers or spheroids. We envision those similar settings could be extended to other cell lines, colorectal and beyond, either label/unlabeled or in 2D/3D environments.