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Low-grade inflammation and pathological endochondral ossification are key processes underlying the progression of osteoarthritis, the most prevalent joint disease worldwide. In this study, we employed a multi-faceted approach, integrating publicly available datasets, in silico analyses, in vitro experiments and in vivo models to identify new therapeutic candidates targeting these processes. Data mining of transcriptomic datasets identified EPHA2, a receptor tyrosine kinase associated with cancer, as being linked to both inflammation and endochondral ossification in osteoarthritis. A computational model of cellular signaling networks in chondrocytes predicted that in silico activation of EPHA2 in healthy chondrocytes increases inflammatory mediators and induces hypertrophic differentiation, a hallmark of endochondral ossification. We then evaluated the effect of EPHA2 inhibition using the tyrosine kinase inhibitor ALW-II-41-27 in cultured human chondrocytes from individuals with osteoarthritis, demonstrating significant reductions in both inflammation and hypertrophy. Additionally, systemic subcutaneous administration of ALW-II-41-27 in a mouse osteoarthritic model attenuated joint degeneration by reducing local inflammation and pathological endochondral ossification. Collectively, this study demonstrates a novel drug discovery pipeline that integrates computational, experimental, and animal models, paving the way for the development of disease-modifying treatments for osteoarthritis., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Gerjo van Osch reports financial support was provided by European Union Horizon 2020. Gerjo van Osch reports financial support was provided by Reumafonds ReumaNederland. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Digital twins represent a key technology for precision health. Medical digital twins consist of computational models that represent the health state of individual patients over time, enabling optimal therapeutics and forecasting patient prognosis. Many health conditions involve the immune system, so it is crucial to include its key features when designing medical digital twins. The immune response is complex and varies across diseases and patients, and its modelling requires the collective expertise of the clinical, immunology, and computational modelling communities. This review outlines the initial progress on immune digital twins and the various initiatives to facilitate communication between interdisciplinary communities. We also outline the crucial aspects of an immune digital twin design and the prerequisites for its implementation in the clinic. We propose some initial use cases that could serve as "proof of concept" regarding the utility of immune digital technology, focusing on diseases with a very different immune response across spatial and temporal scales (minutes, days, months, years). Lastly, we discuss the use of digital twins in drug discovery and point out emerging challenges that the scientific community needs to collectively overcome to make immune digital twins a reality., Competing Interests: Competing interests: The authors declare no competing interests., (© 2024. The Author(s).)

The evolution of information and communication technologies has affected all fields of science, including health sciences. However, the rate of technological innovation adoption by the healthcare sector has been historically slow, compared to other industrial sectors. Innovation in computer modeling and simulation approaches has changed the landscape in biomedical applications and biomedicine, paving the way for their potential contribution in reducing, refining, and partially replacing animal and human clinical trials. In Silico Clinical Trials (ISCT) allow the development of virtual populations used in the safety and efficacy testing of new drugs and medical devices. This White Paper presents the current framework for ISCT, the role of in silico medicine research communities, the different perspectives (research, scientific, clinical, regulatory, standardization, data quality, legal and ethical), the barriers, challenges, and opportunities for ISCT adoption. In addition, an overview of successful ISCT projects, market-available platforms, and FDA- approved paradigms, along with their vision, mission and outcomes are presented.

The kinetics of the protein elongation cycle by the ribosome depends on intertwined factors. One of these factors is the electrostatic interaction of the nascent protein with the ribosome exit tunnel. In this computational biology theoretical study, we focus on the rate of the peptide bond formation and its dependence on the ribosome exit tunnel electrostatic potential profile. We quantitatively predict how oligopeptides of variable lengths can affect the peptide bond formation rate. We applied the Michaelis-Menten model as previously extended to incorporate the mechano-biochemical effects of forces on the rate of reaction at the catalytic site of the ribosome. For a given pair of carboxy-terminal amino acid substrate at the P- and an aminoacyl-tRNA at the A-sites, the relative time courses of the peptide bond formation reaction can be reversed depending on the oligopeptide sequence embedded in the tunnel and their variable lengths from the P-site. The reversal is predicted to occur from a shift in positions of charged amino acids upstream in the oligopeptidyl-tRNA at the P-site. The position shift must be adjusted by clever design of the oligopeptide probes using the electrostatic potential profile along the exit tunnel axial path. These predicted quantitative results bring strong evidence of the importance and relative contribution of the electrostatic interaction of the ribosome exit tunnel with the nascent peptide chain during elongation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 The Author(s).)

Objectives: Calcium phosphate-based biomaterials (CaP) are the most widely used biomaterials to enhance bone regeneration in the treatment of alveolar bone deficiencies, cranio-maxillofacial and periodontal infrabony defects, with positive preclinical and clinical results reported. This systematic review aimed to assess the influence of the physicochemical properties of CaP biomaterials on the performance of bone regeneration in preclinical animal models., Methods: The PubMed, EMBASE and Web of Science databases were searched to retrieve the preclinical studies investigating physicochemical characteristics of CaP biomaterials. The studies were screened for inclusion based on intervention (physicochemical characterization and in vivo evaluation) and reported measurable outcomes., Results: A total of 1532 articles were retrieved and 58 studies were ultimately included in the systematic review. A wide range of physicochemical characteristics of CaP biomaterials was found to be assessed in the included studies. Despite a high degree of heterogeneity, the meta-analysis was performed on 39 studies and evidenced significant effects of biomaterial characteristics on their bone regeneration outcomes. The study specifically showed that macropore size, Ca/P ratio, and compressive strength exerted significant influence on the formation of newly regenerated bone. Moreover, factors such as particle size, Ca/P ratio, and surface area were found to impact bone-to-material contact during the regeneration process. In terms of biodegradability, the amount of residual graft was determined by macropore size, particle size, and compressive strength., Conclusion: The systematic review showed that the physicochemical characteristics of CaP biomaterials are highly determining for scaffold's performance, emphasizing its usefulness in designing the next generation of bone scaffolds to target higher rates of regeneration., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Liesbet Geris reports financial support was provided by 10.13039/501100000781European Research Council under the European Union's Horizon Europe programme/ERC Consolidator Grant No. 101088919. Liesbet Geris and France Lambert report financial support was provided by Walloon Region via the BIOWIN-BIOPTOS and Win2Wal-B2Bone projects. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 Published by Elsevier Ltd.)

Automated technologies are attractive for enhancing the robust manufacturing of tissue-engineered products for clinical translation. In this work, we present an automation strategy using a robotics platform for media changes, and imaging of cartilaginous microtissues cultured in static microwell platforms. We use an automated image analysis pipeline to extract microtissue displacements and morphological features as noninvasive quality attributes. As a result, empty microwells were identified with a 96% accuracy, and dice coefficient of 0.84 for segmentation. Design of experiment are used for the optimization of liquid handling parameters to minimize empty microwells during long-term differentiation protocols. We found no significant effect of aspiration or dispension speeds at and beyond manual speed. Instead, repeated media changes and time in culture were the driving force or microtissue displacements. As the ovine model is the preclinical model of choice for large skeletal defects, we used ovine periosteum-derived cells to form cartilage-intermediate microtissues. Increased expression of COL2A1 confirms chondrogenic differentiation and RUNX2 shows no osteogenic specification. Histological analysis shows an increased secretion of cartilaginous extracellular matrix and glycosaminoglycans in larger microtissues. Furthermore, microtissue-based implants are capable of forming mineralized tissues and bone after 4 weeks of ectopic implantation in nude mice. We demonstrate the development of an integrated bioprocess for culturing and manipulation of cartilaginous microtissues and anticipate the progressive substitution of manual operations with automated solutions for the manufacturing of microtissue-based living implants., (© The Author(s) 2024. Published by Oxford University Press.)

While available treatments have addressed a variety of complications in the dentoalveolar region, associated challenges have resulted in exploration of tissue engineering techniques. Often, scaffold biomaterials with specific properties are required for such strategies to be successful, development of which is an active area of research. This study focuses on the development of a copolymer of poly (N-isopropylacrylamide) (pNIPAM) and chitosan, used for 3D printing of scaffolds for dentoalveolar regeneration. The synthesized material was characterized by Fourier transform infrared spectroscopy, and the possibility of printing was evaluated through various printability tests. The rate of degradation and swelling was analyzed through gravimetry, and surface morphology was characterized by scanning electron microscopy. Viability of dental pulp stem cells seeded on the scaffolds was evaluated by live/dead analysis and DNA quantification. The results demonstrated successful copolymerization, and three formulations among various synthesized formulations were successfully 3D printed. Up to 35% degradability was confirmed within 7 days, and a maximum swelling of approximately 1200% was achieved. Furthermore, initial assessment of cell viability demonstrated biocompatibility of the developed scaffolds. While further studies are required to achieve the tissue engineering goals, the present results tend to indicate that the proposed hydrogel might be a valid candidate for scaffold fabrication serving dentoalveolar tissue engineering through 3D printing.

In biomaterial-based bone tissue engineering, optimizing scaffold structure and composition remains an active field of research. Additive manufacturing has enabled the production of custom designs in a variety of materials. This study aims to improve the design of calcium-phosphate-based additively manufactured scaffolds, the material of choice in oral bone regeneration, by using a combination of in silico and in vitro tools. Computer models are increasingly used to assist in design optimization by providing a rational way of merging different requirements into a single design. The starting point for this study was an in-house developed in silico model describing the in vitro formation of neotissue, i.e., cells and the extracellular matrix they produced. The level set method was applied to simulate the interface between the neotissue and the void space inside the scaffold pores. In order to calibrate the model, a custom disk-shaped scaffold was produced with prismatic canals of different geometries (circle, hexagon, square, triangle) and inner diameters (0.5 mm, 0.7 mm, 1 mm, 2 mm). The disks were produced with three biomaterials (hydroxyapatite, tricalcium phosphate, and a blend of both). After seeding with skeletal progenitor cells and a cell culture for up to 21 days, the extent of neotissue growth in the disks' canals was analyzed using fluorescence microscopy. The results clearly demonstrated that in the presence of calcium-phosphate-based materials, the curvature-based growth principle was maintained. Bayesian optimization was used to determine the model parameters for the different biomaterials used. Subsequently, the calibrated model was used to predict neotissue growth in a 3D gyroid structure. The predicted results were in line with the experimentally obtained ones, demonstrating the potential of the calibrated model to be used as a tool in the design and optimization of 3D-printed calcium-phosphate-based biomaterials for bone regeneration.

Bone fracture healing is a well-orchestrated but complex process that involves numerous regulations at different scales. This complexity becomes particularly evident during the inflammatory stage, as immune cells invade the healing region and trigger a cascade of signals to promote a favorable regenerative environment. Thus, the emergence of criticalities during this stage might hinder the rest of the process. Therefore, the investigation of the many interactions that regulate the inflammation has a primary importance on the exploration of the overall healing progression. In this context, an in silico model named COMMBINI (COmputational Model of Macrophage dynamics in the Bone INjury Immunoresponse) has been developed to investigate the mechano-biological interactions during the early inflammatory stage at the tissue, cellular and molecular levels. An agent-based model is employed to simulate the behavior of immune cells, inflammatory cytokines and fracture debris as well as their reciprocal multiscale biological interactions during the development of the early inflammation (up to 5 days post-injury). The strength of the computational approach is the capacity of the in silico model to simulate the overall healing process by taking into account the numerous hidden events that contribute to its success. To calibrate the model, we present an in silico immunofluorescence method that enables a direct comparison at the cellular level between the model output and experimental immunofluorescent images. The combination of sensitivity analysis and a Genetic Algorithm allows dynamic cooperation between these techniques, enabling faster identification of the most accurate parameter values, reducing the disparity between computer simulation and histological data. The sensitivity analysis showed a higher sensibility of the computer model to the macrophage recruitment ratio during the early inflammation and to proliferation in the late stage. Furthermore, the Genetic Algorithm highlighted an underestimation of macrophage proliferation by in vitro experiments. Further experiments were conducted using another externally fixated murine model, providing an independent validation dataset. The validated COMMBINI platform serves as a novel tool to deepen the understanding of the intricacies of the early bone regeneration phases. COMMBINI aims to contribute to designing novel treatment strategies in both the biological and mechanical domains., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Borgiani, Nasello, Ory, Herpelinck, Groeneveldt, Bucher, Schmidt-Bleek and Geris.)

In fracture fixation, biodegradable implant materials are an interesting alternative to conventional non-biodegradable materials as the latter often require a second implant removal surgery to avoid long-term complications. In this study, we present an in silico strategy to design/study biodegradable metal implants focusing on mandibular fracture fixation plates of WE43 (Mg alloy). The in silico strategy is composed of an orchestrated interaction between three separate computational models. The first model simulates the mass loss of the degradable implant based on the chemistry of Mg biodegradation. A second model estimates the loading on the jaw plate in the physiological environment, incorporating a phenomenological dynamic bone regeneration process. The third model characterizes the mechanical behavior of the jaw plate and the influence of material degradation on the mechanical behavior. A sensitivity analysis was performed on parameters related to choices regarding numerical implementation and parameter dependencies were implemented to guarantee robust and correct results. Different clinical scenarios were tested, related to the amount of screws used to fix the plate. The results showed a lower initial strength when more screw holes were left open, as well as a faster decrease over time in strength due to the increased area available for surface degradation. The obtained degradation results were found to be in accordance with previously reported data of in vivo studies with biodegradable plates. The combination of these three models allows for the design of patient-specific biodegradable fixation implants able to deliver the desired mechanical behavior tuned to the bone regeneration process., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The cartilaginous endplates (CEP) are key components of the intervertebral disc (IVD) necessary for sustaining the nutrition of the disc while distributing mechanical loads and preventing the disc from bulging into the adjacent vertebral body. The size, shape, and composition of the CEP are essential in maintaining its function, and degeneration of the CEP is considered a contributor to early IVD degeneration. In addition, the CEP is implicated in Modic changes, which are often associated with low back pain. This review aims to tackle the current knowledge of the CEP regarding its structure, composition, permeability, and mechanical role in a healthy disc, how they change with degeneration, and how they connect to IVD degeneration and low back pain. Additionally, the authors suggest a standardized naming convention regarding the CEP and bony endplate and suggest avoiding the term vertebral endplate. Currently, there is limited data on the CEP itself as reported data is often a combination of CEP and bony endplate, or the CEP is considered as articular cartilage. However, it is clear the CEP is a unique tissue type that differs from articular cartilage, bony endplate, and other IVD tissues. Thus, future research should investigate the CEP separately to fully understand its role in healthy and degenerated IVDs. Further, most IVD regeneration therapies in development failed to address, or even considered the CEP, despite its key role in nutrition and mechanical stability within the IVD. Thus, the CEP should be considered and potentially targeted for future sustainable treatments., Competing Interests: Benjamin Gantenbein and Christine Le Maitre are editorial board members of JOR Spine and co‐author of this article. They were excluded from editorial decision‐making related to the acceptance of this article for publication in the journal. All other authors have no conflicts of interest to declare in relation to this article., (© 2023 The Authors. JOR Spine published by Wiley Periodicals LLC on behalf of Orthopaedic Research Society.)

The idea of a systematic digital representation of the entire known human pathophysiology, which we could call the Virtual Human Twin, has been around for decades. To date, most research groups focused instead on developing highly specialised, highly focused patient-specific models able to predict specific quantities of clinical relevance. While it has facilitated harvesting the low-hanging fruits, this narrow focus is, in the long run, leaving some significant challenges that slow the adoption of digital twins in healthcare. This position paper lays the conceptual foundations for developing the Virtual Human Twin (VHT). The VHT is intended as a distributed and collaborative infrastructure, a collection of technologies and resources (data, models) that enable it, and a collection of Standard Operating Procedures (SOP) that regulate its use. The VHT infrastructure aims to facilitate academic researchers, public organisations, and the biomedical industry in developing and validating new digital twins in healthcare solutions with the possibility of integrating multiple resources if required by the specific context of use. Healthcare professionals and patients can also use the VHT infrastructure for clinical decision support or personalised health forecasting. As the European Commission launched the EDITH coordination and support action to develop a roadmap for the development of the Virtual Human Twin, this position paper is intended as a starting point for the consensus process and a call to arms for all stakeholders.

Major achievements in bone research have always relied on animal models and in vitro systems derived from patient and animal material. However, the use of animals in research has drawn intense ethical debate and the complete abolition of animal experimentation is demanded by fractions of the population. This phenomenon is enhanced by the reproducibility crisis in science and the advance of in vitro and in silico techniques. 3D culture, organ-on-a-chip, and computer models have improved enormously over the last few years. Nevertheless, the overall complexity of bone tissue cross-talk and the systemic and local regulation of bone physiology can often only be addressed in entire vertebrates. Powerful genetic methods such as conditional mutagenesis, lineage tracing, and modeling of the diseases enhanced the understanding of the entire skeletal system. In this review endorsed by the European Calcified Tissue Society (ECTS), a working group of investigators from Europe and the US provides an overview of the strengths and limitations of experimental animal models, including rodents, fish, and large animals, as well the potential and shortcomings of in vitro and in silico technologies in skeletal research. We propose that the proper combination of the right animal model for a specific hypothesis and state-of-the-art in vitro and/or in silico technology is essential to solving remaining important questions in bone research. This is crucial for executing most efficiently the 3R principles to reduce, refine, and replace animal experimentation, for enhancing our knowledge of skeletal biology, and for the treatment of bone diseases that affect a large part of society. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR)., (© 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).)

The central function of the large subunit of the ribosome is to catalyze peptide bond formation. This biochemical reaction is conducted at the peptidyl transferase center (PTC). Experimental evidence shows that the catalytic activity is affected by the electrostatic environment around the peptidyl transferase center. Here, we set up a minimal geometrical model fitting the available x-ray solved structures of the ribonucleic cavity around the catalytic center of the large subunit of the ribosome. The purpose of this phenomenological model is to estimate quantitatively the electrostatic potential and electric field that are experienced during the peptidyl transfer reaction. At least two reasons motivate the need for developing this quantification. First, we inquire whether the electric field in this particular catalytic environment, made only of nucleic acids, is of the same order of magnitude as the one prevailing in catalytic centers of the proteic enzymes counterparts. Second, the protein synthesis rate is dependent on the nature of the amino acid sequentially incorporated in the nascent chain. The activation energy of the catalytic reaction and its detailed kinetics are shown to be dependent on the mechanical work exerted on the amino acids by the electric field, especially when one of the four charged amino acid residues (R, K, E, D) has previously been incorporated at the carboxy-terminal end of the peptidyl-tRNA. Physical values of the electric field provide quantitative knowledge of mechanical work, activation energy and rate of the peptide bond formation catalyzed by the ribosome. We show that our theoretical calculations are consistent with two independent sets of previously published experimental results. Experimental results for E.coli in the minimal case of the dipeptide bond formation when puromycin is used as the final amino acid acceptor strongly support our theoretically derived reaction time courses. Experimental Ribo-Seq results on E. coli and S. cerevisiae comparing the residence time distribution of ribosomes upon specific codons are also well accounted for by our theoretical calculations. The statistical queueing time theory was used to model the ribosome residence time per codon during nascent protein elongation and applied for the interpretation of the Ribo-Seq data. The hypo-exponential distribution fits the residence time observed distribution of the ribosome on a codon. An educated deconvolution of this distribution is used to estimate the rates of each elongation step in a codon specific manner. Our interpretation of all these results sheds light on the functional role of the electrostatic profile around the PTC and its impact on the ribosome elongation cycle., Competing Interests: All authors declare the absence of any conflict of interest., (© 2023 The Author(s).)

Facial trauma, bone resection due to cancer, periodontal diseases, and bone atrophy following tooth extraction often leads to alveolar bone defects that require bone regeneration in order to restore dental function. Guided bone regeneration using synthetic biomaterials has been suggested as an alternative approach to autologous bone grafts. The efficiency of bone substitute materials seems to be influenced by their physico-chemical characteristics; however, the debate is still ongoing on what constitutes optimal biomaterial characteristics. The purpose of this study was to develop an empirical model allowing the assessment of the bone regeneration potential of new biomaterials on the basis of their physico-chemical characteristics, potentially giving directions for the design of a new generation of dental biomaterials. A quantitative data set was built composed of physico-chemical characteristics of seven commercially available intra-oral bone biomaterials and their in vivo response. This empirical model allowed the identification of the construct parameters driving optimized bone formation. The presented model provides a better understanding of the influence of driving biomaterial properties in the bone healing process and can be used as a tool to design bone biomaterials with a more controlled and custom-made composition and structure, thereby facilitating and improving the clinical translation.

Bone fractures are one of the most common traumatic large-organ injuries and although many fractures can heal on their own, 2-12% of fractures are slow healing or do not heal (non-unions). Autologous grafts are currently used for treatment of non-unions but are associated with limited healthy bone tissue. Tissue engineered cell-based products have promise for an alternative treatment method. It was previously demonstrated that cartilaginous microspheroids of periosteum-derived cells could be assembled into scaffold-free constructs and heal murine critically-sized long bone defects (non-unions). However, the handleability of such scaffold-free implants can be compromised when scaling-up. In this work, cartilaginous spheroids were combined with melt electrowritten (MEW) meshes to create an engineered cell-based implant, able to induce in vivo bone formation. MEW polycaprolactone meshes were tailored to contain pores (116 ± 28 µm) of a size that captured microspheroids (180 ± 15 µm). Periosteum-derived microspheroids pre-cultured for 4 days, were seeded on MEW meshes and gene expression analysis demonstrated up-regulation of chondrogenic (SOX9, COL2) and prehypertrophic (VEGF) gene markers after 14 days, creating a biohybrid sheet. When implanted subcutaneously (4 weeks), the biohybrid sheets mineralized (23 ± 3% MV/TV) and formed bone and bone marrow. Bone formation was also observed when implanted in a murine critically-sized long bone defect, though a high variation between samples was detected. The high versatility of this biofabrication approach lies in the possibility to tailor the scaffolds to shape and dimensions corresponding to the large bone defects and the individual patient using robust bone forming building blocks. These strategies are instrumental in the development of personalized regenerative therapies with predictive clinical outcomes. STATEMENT OF SIGNIFICANCE: Successful treatments for healing of large long bone defects are still limited and 2-12% of fractures do not heal properly. We combined a novel biofabrication technique: melt electrowriting (MEW), with robust biology: bone forming cartilaginous spheroids to create biohybrid sheets able to form bone upon implantation. MEW enabled the fabrication of scaffolds with micrometer-sized fibers in defined patterns which allowed the capturing of and merging with cartilaginous spheroids which had the potency to mature into bone via the developmental process of endochondral ossification. The present study contributes to the rapidly growing field of "Biofabrication with Spheroid and Organoid Materials'' and demonstrates design considerations that are of great importance for biofabrication of functional tissues through the assembly of cellular spheroids., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: The authors Katrina Mosley and Matei Cirstea are employed at the Electrospinning Company Ltd, England., (Copyright © 2022. Published by Elsevier Ltd.)

Cold plasmas have found their application in a wide range of biomedical fields by virtue of their high chemical reactivity. In the past decades, many attempts have been made to use cold plasmas in wound healing, and within this field, many studies have focused on plasma-induced cell proliferation mechanisms. In this work, one step further has been taken to demonstrate the advanced role of plasma in wound healing. To this end, the simultaneous ability of plasma to induce cell proliferation and permeabilize treated cells has been examined in the current study. The driving force was to advance the wound healing effect of plasma with drug delivery. On this subject, we demonstrate in vitro the healing effect of Ar, Ar+N 2 plasma, and their aerosol counterparts. A systematic study has been carried out to study the role of reactive oxygen species (ROS) and reactive nitrogen species (RNS) in cell adhesion, signaling, differentiation, and proliferation. An additional investigation was also performed to study the permeabilization of cells and the delivery of the modeled drug carrier fluorescein isothiocyanate (FITC) labeled dextran into cells upon plasma treatment. Short 35 s plasma treatments were found to promote fibroblast adhesion, migration, signaling, proliferation, and differentiation by means of reactive oxygen and nitrogen species (RONS) created by plasma and deposited into the cell environment. The impact of the plasma downstream products NO 2 - and NO 3 - on the expressions of the focal adhesion's genes, syndecans, and collagens was observed to be prominent. On the other hand, the differentiation of fibroblasts to myofibroblasts was mainly initiated by ROS produced by the plasma. In addition, the ability of plasma to locally permeabilize fibroblast cells was demonstrated. During proliferative cell treatment, plasma can simultaneously induce cell membrane permeabilization ( d ∼ 7.3 nm) by the species OH and H 2 O 2 . The choice for a plasma or a plasma-aerosol configuration thus allows the possibility to change the spatial chemistry of drug delivery molecules and thus to locally deliver drugs. Accordingly, this study offers a pivotal step toward plasma-assisted wound healing advanced by drug delivery.

In silico medicine describes the application of computational modelling and simulation (CM&S) to the study, diagnosis, treatment or prevention of a disease. Tremendous research advances have been achieved to facilitate the use of CM&S in clinical applications. Nevertheless, the uptake of CM&S in clinical practice is not always timely and accurately reflected in the literature. A clear view on the current awareness, actual usage and opinions from the clinicians is needed to identify barriers and opportunities for the future of in silico medicine. The aim of this study was capturing the state of CM&S in clinics by means of a survey toward the clinical community. Responses were collected online using the Virtual Physiological Human institute communication channels, engagement with clinical societies, hospitals and individual contacts, between 2020 and 2021. Statistical analyses were done with R. Participants ( n  = 163) responded from all over the world. Clinicians were mostly aged between 35 and 64 years-old, with heterogeneous levels of experience and areas of expertise ( i.e., 48% cardiology, 13% musculoskeletal, 8% general surgery, 5% paediatrics). The CM&S terms "Personalised medicine" and "Patient-specific modelling" were the most well-known within the respondents. "In silico clinical trials" and "Digital Twin" were the least known. The familiarity with different methods depended on the medical specialty. CM&S was used in clinics mostly to plan interventions. To date, the usage frequency is still scarce. A well-recognized benefit associated to CM&S is the increased trust in planning procedures. Overall, the recorded level of trust for CM&S is high and not proportional to awareness level. The main barriers appear to be access to computing resources, perception that CM&S is slow. Importantly, clinicians see a role for CM&S expertise in their team in the future. This survey offers a snapshot of the current situation of CM&S in clinics. Although the sample size and representativity could be increased, the results provide the community with actionable data to build a responsible strategy for accelerating a positive uptake of in silico medicine. New iterations and follow-up activities will track the evolution of responses over time and contribute to strengthen the engagement with the medical community., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Lesage, Van Oudheusden, Schievano, Van Hoyweghen, Geris and Capelli.)

The genetic code is textbook scientific knowledge that was soundly established without resorting to Artificial Intelligence (AI). The goal of our study was to check whether a neural network could re-discover, on its own, the mapping links between codons and amino acids and build the complete deciphering dictionary upon presentation of transcripts proteins data training pairs. We compared different Deep Learning neural network architectures and estimated quantitatively the size of the required human transcriptomic training set to achieve the best possible accuracy in the codon-to-amino-acid mapping. We also investigated the effect of a codon embedding layer assessing the semantic similarity between codons on the rate of increase of the training accuracy. We further investigated the benefit of quantifying and using the unbalanced representations of amino acids within real human proteins for a faster deciphering of rare amino acids codons. Deep neural networks require huge amount of data to train them. Deciphering the genetic code by a neural network is no exception. A test accuracy of 100% and the unequivocal deciphering of rare codons such as the tryptophan codon or the stop codons require a training dataset of the order of 4-22 millions cumulated pairs of codons with their associated amino acids presented to the neural network over around 7-40 training epochs, depending on the architecture and settings. We confirm that the wide generic capacities and modularity of deep neural networks allow them to be customized easily to learn the deciphering task of the genetic code efficiently., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Joiret, Leclercq, Lambrechts, Rapino, Close, Louppe and Geris.)

Surface curvature both emerges from, and influences the behavior of, living objects at length scales ranging from cell membranes to single cells to tissues and organs. The relevance of surface curvature in biology is supported by numerous experimental and theoretical investigations in recent years. In this review, first, a brief introduction to the key ideas of surface curvature in the context of biological systems is given and the challenges that arise when measuring surface curvature are discussed. Giving an overview of the emergence of curvature in biological systems, its significance at different length scales becomes apparent. On the other hand, summarizing current findings also shows that both single cells and entire cell sheets, tissues or organisms respond to curvature by modulating their shape and their migration behavior. Finally, the interplay between the distribution of morphogens or micro-organisms and the emergence of curvature across length scales is addressed with examples demonstrating these key mechanistic principles of morphogenesis. Overall, this review highlights that curved interfaces are not merely a passive by-product of the chemical, biological, and mechanical processes but that curvature acts also as a signal that co-determines these processes., (© 2023 The Authors. Advanced Materials published by Wiley-VCH GmbH.)

Cartilage microtissues are promising tissue modules for bottom up biofabrication of implants leading to bone defect regeneration. Hitherto, most of the protocols for the development of these cartilaginous microtissues have been carried out in static setups, however, for achieving higher scales, dynamic process needs to be investigated. In the present study, we explored the impact of suspension culture on the cartilage microtissues in a novel stirred microbioreactor system. To study the effect of the process shear stress, experiments with three different impeller velocities were carried out. Moreover, we used mathematical modeling to estimate the magnitude of shear stress on the individual microtissues during dynamic culture. Identification of appropriate mixing intensity allowed dynamic bioreactor culture of the microtissues for up to 14 days maintaining microtissue suspension. Dynamic culture did not affect microtissue viability, although lower proliferation was observed as opposed to the statically cultured ones. However, when assessing cell differentiation, gene expression values showed significant upregulation of both Indian Hedgehog ( IHH ) and collagen type X ( COLX ), well known markers of chondrogenic hypertrophy, for the dynamically cultured microtissues. Exometabolomics analysis revealed similarly distinct metabolic profiles between static and dynamic conditions. Dynamic cultured microtissues showed a higher glycolytic profile compared with the statically cultured ones while several amino acids such as proline and aspartate exhibited significant differences. Furthermore, in vivo implantations proved that microtissues cultured in dynamic conditions are functional and able to undergo endochondral ossification. Our work demonstrated a suspension differentiation process for the production of cartilaginous microtissues, revealing that shear stress resulted to an acceleration of differentiation towards hypertrophic cartilage., Competing Interests: Gabriella Nilsson Hall is now an employee in Astra Zeneca., (© 2022 The Authors. Bioengineering & Translational Medicine published by Wiley Periodicals LLC on behalf of American Institute of Chemical Engineers.)

Background: Without the availability of disease-modifying drugs, there is an unmet therapeutic need for osteoarthritic patients. During osteoarthritis, the homeostasis of articular chondrocytes is dysregulated and a phenotypical transition called hypertrophy occurs, leading to cartilage degeneration. Targeting this phenotypic transition has emerged as a potential therapeutic strategy. Chondrocyte phenotype maintenance and switch are controlled by an intricate network of intracellular factors, each influenced by a myriad of feedback mechanisms, making it challenging to intuitively predict treatment outcomes, while in silico modeling can help unravel that complexity. In this study, we aim to develop a virtual articular chondrocyte to guide experiments in order to rationalize the identification of potential drug targets via screening of combination therapies through computational modeling and simulations., Results: We developed a signal transduction network model using knowledge-based and data-driven (machine learning) modeling technologies. The in silico high-throughput screening of (pairwise) perturbations operated with that network model highlighted conditions potentially affecting the hypertrophic switch. A selection of promising combinations was further tested in a murine cell line and primary human chondrocytes, which notably highlighted a previously unreported synergistic effect between the protein kinase A and the fibroblast growth factor receptor 1., Conclusions: Here, we provide a virtual articular chondrocyte in the form of a signal transduction interactive knowledge base and of an executable computational model. Our in silico-in vitro strategy opens new routes for developing osteoarthritis targeting therapies by refining the early stages of drug target discovery., (© 2022. The Author(s).)

The COVID-19 pandemic created an unprecedented global healthcare emergency prompting the exploration of new therapeutic avenues, including drug repurposing. A large number of ongoing studies revealed pervasive issues in clinical research, such as the lack of accessible and organised data. Moreover, current shortcomings in clinical studies highlighted the need for a multi-faceted approach to tackle this health crisis. Thus, we set out to explore and develop new strategies for drug repositioning by employing computational pharmacology, data mining, systems biology, and computational chemistry to advance shared efforts in identifying key targets, affected networks, and potential pharmaceutical intervention options. Our study revealed that formulating pharmacological strategies should rely on both therapeutic targets and their networks. We showed how data mining can reveal regulatory patterns, capture novel targets, alert about side-effects, and help identify new therapeutic avenues. We also highlighted the importance of the miRNA regulatory layer and how this information could be used to monitor disease progression or devise treatment strategies. Importantly, our work bridged the interactome with the chemical compound space to better understand the complex landscape of COVID-19 drugs. Machine and deep learning allowed us to showcase limitations in current chemical libraries for COVID-19 suggesting that both in silico and experimental analyses should be combined to retrieve therapeutically valuable compounds. Based on the gathered data, we strongly advocate for taking this opportunity to establish robust practices for treating today's and future infectious diseases by preparing solid analytical frameworks., Competing Interests: Declaration of Competing Interest Authors declare no conflict of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

In Silico Trials methodologies will play a growing and fundamental role in the development and de-risking of new medical devices in the future. While the regulatory pathway for Digital Patient and Personal Health Forecasting solutions is clear, it is more complex for In Silico Trials solutions, and therefore deserves a deeper analysis. In this position paper, we investigate the current state of the art towards the regulatory system for in silico trials applied to medical devices while exploring the European regulatory system toward this topic. We suggest that the European regulatory system should start a process of innovation: in principle to limit distorted quality by different internal processes within notified bodies, hence avoiding that the more innovative and competitive companies focus their attention on the needs of other large markets, like the USA, where the use of such radical innovations is already rapidly developing.

Dentoalveolar tissue engineering is an emerging yet challenging field, considering the lack of suitable materials and difficulty to produce patient-specific hydrogel scaffolds. The present paper aims to produce a 3D printable and tuneable biomaterial by copolymerizing a synthesized water-soluble chitosan derivative called maleic anhydride grafted chitosan (MA-C) with gelatin using genipin, a natural crosslinking agent. Development and testing of this material for 3D printing, degradation, and swelling demonstrated the ability to fabricate scaffolds with controlled physical properties based on pre-determined designs. The MA-C-gelatin copolymer demonstrated excellent biocompatibility, which was verified by analyzing the viability, growth and proliferation of human dental pulp stem cells seeded on MA-C-gelatin constructs through live/dead, alamar blue and DNA quantification assays. Based on the present findings, the proposed material might be a suitable candidate for dentoalveolar tissue engineering, while further research is required to achieve this goal., (Copyright © 2022. Published by Elsevier Ltd.)

Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiating event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological mechanistic information. As such, AOPs inform on key events underlying toxicity, thus supporting the development of New Approach Methodologies (NAMs), which aim to reduce the use of animal testing for toxicology purposes. However, the establishment of a novel AOP relies on the gathering of multiple streams of evidence and information, from available literature to knowledge databases. Often, this information is in the form of free text, also called unstructured text, which is not immediately digestible by a computer. This information is thus both tedious and increasingly time-consuming to process manually with the growing volume of data available. The advancement of machine learning provides alternative solutions to this challenge. To extract and organize information from relevant sources, it seems valuable to employ deep learning Natural Language Processing techniques. We review here some of the recent progress in the NLP field, and show how these techniques have already demonstrated value in the biomedical and toxicology areas. We also propose an approach to efficiently and reliably extract and combine relevant toxicological information from text. This data can be used to map underlying mechanisms that lead to toxicological effects and start building quantitative models, in particular AOPs, ultimately allowing animal-free human-based hazard and risk assessment., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

Low back pain is a highly prevalent, chronic, and costly medical condition predominantly triggered by intervertebral disc degeneration (IDD). IDD is often caused by structural and biochemical changes in intervertebral discs (IVD) that prompt a pathologic shift from an anabolic to catabolic state, affecting extracellular matrix (ECM) production, enzyme generation, cytokine and chemokine production, neurotrophic and angiogenic factor production. The IVD is an immune-privileged organ. However, during degeneration immune cells and inflammatory factors can infiltrate through defects in the cartilage endplate and annulus fibrosus fissures, further accelerating the catabolic environment. Remarkably, though, catabolic ECM disruption also occurs in the absence of immune cell infiltration, largely due to native disc cell production of catabolic enzymes and cytokines. An unbalanced metabolism could be induced by many different factors, including a harsh microenvironment, biomechanical cues, genetics, and infection. The complex, multifactorial nature of IDD brings the challenge of identifying key factors which initiate the degenerative cascade, eventually leading to back pain. These factors are often investigated through methods including animal models, 3D cell culture, bioreactors, and computational models. However, the crosstalk between the IVD, immune system, and shifted metabolism is frequently misconstrued, often with the assumption that the presence of cytokines and chemokines is synonymous to inflammation or an immune response, which is not true for the intact disc. Therefore, this review will tackle immunomodulatory and IVD cell roles in IDD, clarifying the differences between cellular involvements and implications for therapeutic development and assessing models used to explore inflammatory or catabolic IVD environments., Competing Interests: EK and LK were employed by ProtATonce Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Bermudez-Lekerika, Crump, Tseranidou, Nüesch, Kanelis, Alminnawi, Baumgartner, Muñoz-Moya, Compte, Gualdi, Alexopoulos, Geris, Wuertz-Kozak, Le Maitre, Noailly and Gantenbein.)

Methacryloyl gelatin (GelMA) is a versatile material for bioprinting because of its tunable physical properties and inherent bioactivity. Bioprinting of GelMA is often met with challenges such as lower viscosity of GelMA inks due to higher methacryloyl substitution and longer physical gelation time at room temperature. In this study, a tunable interpenetrating polymer network (IPN) hydrogel was prepared from gelatin-hyaluronan dialdehyde (Gel-HDA) Schiff's polymer, and 100% methacrylamide substituted GelMA for biofabrication through extrusion based bioprinting. Temperature sweep rheology measurements show a higher sol-gel transition temperature for IPN (30 °C) compared to gold standard GelMA (27 °C). Furthermore, to determine the tunability of the IPN hydrogel, several IPN samples were prepared by combining different ratios of Gel-HDA and GelMA achieving a compressive modulus ranging from 20.6 ± 2.48 KPa to 116.7 ± 14.80 KPa. Our results showed that the mechanical properties and printability at room temperature could be tuned by adjusting the ratios of GelMA and Gel-HDA. To evaluate cell response to the material, MC3T3-E1 mouse pre-osteoblast cells were embedded in hydrogels and 3D-printed, demonstrating excellent cell viability and proliferation after 10 d of 3D in vitro culture, making the IPN an interesting bioink for the fabrication of 3D constructs for tissue engineering applications., (© 2022 IOP Publishing Ltd.)

Lymphangiogenesis (LA) is the formation of new lymphatic vessels by lymphatic endothelial cells (LECs) sprouting from pre-existing lymphatic vessels. It is increasingly recognized as being involved in many diseases, such as in cancer and secondary lymphedema, which most often results from cancer treatments. For some cancers, excessive LA is associated with cancer progression and metastatic dissemination to the lymph nodes (LNs) through lymphatic vessels. The study of LA through in vitro, in vivo, and, more recently, in silico models is of paramount importance in providing novel insights and identifying the key molecular actors in the biological dysregulation of this process under pathological conditions. In this review, the different biological (in vitro and in vivo) models of LA, especially in a cancer context, are explained and discussed, highlighting their principal modeled features as well as their advantages and drawbacks. Imaging techniques of the lymphatics, complementary or even essential to in vivo models, are also clarified and allow the establishment of the link with computational approaches. In silico models are introduced, theoretically described, and illustrated with examples specific to the lymphatic system and the LA. Together, these models constitute a toolbox allowing the LA research to be brought to the next level.

Early limb bud development has been of considerable interest for the study of embryological development and especially morphogenesis. The focus has long been on biochemical signalling and less on cell biomechanics and mechanobiology. However, their importance cannot be understated since tissue shape changes are ultimately controlled by active forces and bulk tissue rheological properties that in turn depend on cell-cell interactions as well as extracellular matrix composition. Moreover, the feedback between gene regulation and the biomechanical environment is still poorly understood. In recent years, novel experimental techniques and computational models have reinvigorated research on this biomechanical and mechanobiological side of embryological development. In this review, we consider three stages of early limb development, namely: outgrowth, elongation, and condensation. For each of these stages, we summarize basic biological regulation and examine the role of cellular and tissue mechanics in the morphogenetic process.

The impact of ribosome exit tunnel electrostatics on the protein elongation rate or on forces acting upon the nascent polypeptide chain are currently not fully elucidated. In the past, researchers have measured the electrostatic potential inside the ribosome polypeptide exit tunnel at a limited number of spatial points, at least in rabbit reticulocytes. Here we present a basic electrostatic model of the exit tunnel of the ribosome, providing a quantitative physical description of the tunnel interaction with the nascent proteins at all centro-axial points inside the tunnel. We show that a strong electrostatic screening is due to water molecules (not mobile ions) attracted to the ribosomal nucleic acid phosphate moieties buried in the immediate vicinity of the tunnel wall. We also show how the tunnel wall components and local ribosomal protein protrusions impact on the electrostatic potential profile and impede charged amino acid residues from progressing through the tunnel, affecting the elongation rate in a range of -40% to +85% when compared to the average elongation rate. The time spent by the ribosome to decode the genetic encrypted message is constrained accordingly. We quantitatively derive, at single-residue resolution, the axial forces acting on the nascent peptide from its particular sequence embedded in the tunnel. The model sheds light on how the experimental data point measurements of the potential are linked to the local structural chemistry of the inner wall, shape, and size of the tunnel. The model consistently connects experimental observations coming from different fields in molecular biology, x-ray crystallography, physical chemistry, biomechanics, and synthetic and multiomics biology. Our model should be a valuable tool to gain insight into protein synthesis dynamics, translational control, and the role of the ribosome's mechanochemistry in the cotranslational protein folding.

Osteoarthritis is a whole joint disease with cartilage degeneration being an important manifestation. Tissue engineering treatment is a solution for repairing cartilage defects by implantation of chondrocyte-laden hydrogel constructs within the defect. In silico models have recently been introduced to simulate and optimize the design of these constructs. These models require accurate knowledge on the mechanical properties of the hydrogel constructs and cartilage explants, which are challenging to obtain due to their anisotropic structure and time-dependent behaviour. We performed a systematic in silico parameter sensitivity analysis to find the most efficient unconfined compression testing protocols for mechanical characterization of hydrogel constructs and cartilage explants, with a minimum number of tests but maximum identifiability of the material parameters. The construct and explant were thereby modelled as porohyperelastic and fibril-reinforced poroelastic materials, respectively. Three commonly used loading regimes were simulated in Abaqus (ramp, relaxation and dynamic loading) with varying compressive strain magnitudes and rates. From these virtual experiments, the resulting material parameters were obtained for each combination using a numerical inverse identification scheme. For hydrogels, maximum sensitivity to the different material parameters was found when using a single step ramp loading (20% compression with 10%/s rate) followed by 15 min relaxation. For cartilage explants, a two-stepped ramp loading (10% compression with 10%/s rate and 10% compression with 1%/s rate), each step followed by 15 min relaxation, yielded the maximum sensitivity to the different material parameters. With these protocols, the material parameters could be retrieved with the lowest amount of uncertainty (hydrogel: < 2% and cartilage: < 6%). These specific results and the overall methodology can be used to optimize mechanical testing protocols to yield reliable material parameters for in silico models of cartilage and hydrogel constructs., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

A fundamental question in cartilage biology is: what determines the switch between permanent cartilage found in the articular joints and transient hypertrophic cartilage that functions as a template for bone? This switch is observed both in a subset of OA patients that develop osteophytes, as well as in cell-based tissue engineering strategies for joint repair. A thorough understanding of the mechanisms regulating cell fate provides opportunities for treatment of cartilage disease and tissue engineering strategies. The objective of this study was to understand the mechanisms that regulate the switch between permanent and transient cartilage using a computational model of chondrocytes, ECHO. To investigate large signaling networks that regulate cell fate decisions, we developed the software tool ANIMO, Analysis of Networks with interactive Modeling. In ANIMO, we generated an activity network integrating 7 signal transduction pathways resulting in a network containing over 50 proteins with 200 interactions. We called this model ECHO, for executable chondrocyte. Previously, we showed that ECHO could be used to characterize mechanisms of cell fate decisions. ECHO was first developed based on a Boolean model of growth plate. Here, we show how the growth plate Boolean model was translated to ANIMO and how we adapted the topology and parameters to generate an articular cartilage model. In ANIMO, many combinations of overactivation/knockout were tested that result in a switch between permanent cartilage (SOX9+) and transient, hypertrophic cartilage (RUNX2+). We used model checking to prioritize combination treatments for wet-lab validation. Three combinatorial treatments were chosen and tested on metatarsals from 1-day old rat pups that were treated for 6 days. We found that a combination of IGF1 with inhibition of ERK1/2 had a positive effect on cartilage formation and growth, whereas activation of DLX5 combined with inhibition of PKA had a negative effect on cartilage formation and growth and resulted in increased cartilage hypertrophy. We show that our model describes cartilage formation, and that model checking can aid in choosing and prioritizing combinatorial treatments that interfere with normal cartilage development. Here we show that combinatorial treatments induce changes in the zonal distribution of cartilage, indication possible switches in cell fate. This indicates that simulations in ECHO aid in describing pathologies in which switches between cell fates are observed, such as OA., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Khurana, Schivo, Plass, Mersinis, Scholma, Kerkhofs, Zhong, van de Pol, Langerak, Geris, Karperien and Post.)

Bioengineering of tissues and organs has the potential to generate functional replacement organs. However, achieving the full-thickness vascularization that is required for long-term survival of living implants has remained a grand challenge, especially for clinically sized implants. During the pre-vascular phase, implanted engineered tissues are forced to metabolically rely on the diffusion of nutrients from adjacent host-tissue, which for larger living implants results in anoxia, cell death, and ultimately implant failure. Here it is reported that this challenge can be addressed by engineering self-oxygenating tissues, which is achieved via the incorporation of hydrophobic oxygen-generating micromaterials into engineered tissues. Self-oxygenation of tissues transforms anoxic stresses into hypoxic stimulation in a homogenous and tissue size-independent manner. The in situ elevation of oxygen tension enables the sustained production of high quantities of angiogenic factors by implanted cells, which are offered a metabolically protected pro-angiogenic microenvironment. Numerical simulations predict that self-oxygenation of living tissues will effectively orchestrate rapid full-thickness vascularization of implanted tissues, which is empirically confirmed via in vivo experimentation. Self-oxygenation of tissues thus represents a novel, effective, and widely applicable strategy to enable the vascularization living implants, which is expected to advance organ transplantation and regenerative medicine applications., Competing Interests: Conflict of Interest The authors declare no conflict of interest.

The term "In Silico Trial" indicates the use of computer modelling and simulation to evaluate the safety and efficacy of a medical product, whether a drug, a medical device, a diagnostic product or an advanced therapy medicinal product. Predictive models are positioned as new methodologies for the development and the regulatory evaluation of medical products. New methodologies are qualified by regulators such as FDA and EMA through formal processes, where a first step is the definition of the Context of Use (CoU), which is a concise description of how the new methodology is intended to be used in the development and regulatory assessment process. As In Silico Trials are a disruptively innovative class of new methodologies, it is important to have a list of possible CoUs highlighting potential applications for the development of the relative regulatory science. This review paper presents the result of a consensus process that took place in the InSilicoWorld Community of Practice, an online forum for experts in in silico medicine. The experts involved identified 46 descriptions of possible CoUs which were organised into a candidate taxonomy of nine CoU categories. Examples of 31 CoUs were identified in the available literature; the remaining 15 should, for now, be considered speculative.

In silico modeling is a powerful strategy to investigate the biological events occurring at tissue, cellular and subcellular level during bone fracture healing. However, most current models do not consider the impact of the inflammatory response on the later stages of bone repair. Indeed, as initiator of the healing process, this early phase can alter the regenerative outcome: if the inflammatory response is too strongly down- or upregulated, the fracture can result in a non-union. This review covers the fundamental information on fracture healing, in silico modeling and experimental validation. It starts with a description of the biology of fracture healing, paying particular attention to the inflammatory phase and its cellular and subcellular components. We then discuss the current state-of-the-art regarding in silico models of the immune response in different tissues as well as the bone regeneration process at the later stages of fracture healing. Combining the aforementioned biological and computational state-of-the-art, continuous, discrete and hybrid modeling technologies are discussed in light of their suitability to capture adequately the multiscale course of the inflammatory phase and its overall role in the healing outcome. Both in the establishment of models as in their validation step, experimental data is required. Hence, this review provides an overview of the different in vitro and in vivo set-ups that can be used to quantify cell- and tissue-scale properties and provide necessary input for model credibility assessment. In conclusion, this review aims to provide hands-on guidance for scientists interested in building in silico models as an additional tool to investigate the critical role of the inflammatory phase in bone regeneration., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Lafuente-Gracia, Borgiani, Nasello and Geris.)

Background: Bones have a remarkable capacity to heal upon fracture. Yet, in large defects or compromised conditions healing processes become impaired, resulting in delayed or non-union. Current therapeutic approaches often utilize autologous or allogeneic bone grafts for bone augmentation. However, limited availability of these tissues and lack of predictive biological response result in limitations for clinical demands. Tissue engineering using viable cell-based implants is a strategic approach to address these unmet medical needs., Methods: Herein, the in vitro and in vivo cartilage and bone tissue formation potencies of human pluripotent stem cells were investigated. The induced pluripotent stem cells were specified towards the mesodermal lineage and differentiated towards chondrocytes, which subsequently self-assembled into cartilaginous organoids. The tissue formation capacity of these organoids was then challenged in an ectopic and orthotopic bone formation model., Results: The derived chondrocytes expressed similar levels of collagen type II as primary human articular chondrocytes and produced stable cartilage when implanted ectopically in vivo. Upon targeted promotion towards hypertrophy and priming with a proinflammatory mediator, the organoids mediated successful bridging of critical size long bone defects in immunocompromised mice., Conclusions: These results highlight the promise of induced pluripotent stem cell technology for the creation of functional cartilage tissue intermediates that can be explored for novel bone healing strategies., (© 2021. The Author(s).)

Spheroids have become essential building blocks for biofabrication of functional tissues. Spheroid formats allow high cell-densities to be efficiently engineered into tissue structures closely resembling the native tissues. In this work, we explore the assembly capacity of cartilaginous spheroids ( d ∼ 150 µ m) in the context of endochondral bone formation. The fusion capacity of spheroids at various degrees of differentiation was investigated and showed decreased kinetics as well as remodeling capacity with increased spheroid maturity. Subsequently, design considerations regarding the dimensions of engineered spheroid-based cartilaginous mesotissues were explored for the corresponding time points, defining critical dimensions for these type of tissues as they progressively mature. Next, mesotissue assemblies were implanted subcutaneously in order to investigate the influence of spheroid fusion parameters on endochondral ossification. Moreover, as a step towards industrialization, we demonstrated a novel automated image-guided robotics process, based on targeting and registering single-spheroids, covering the range of spheroid and mesotissue dimensions investigated in this work. This work highlights a robust and automated high-precision biomanufacturing roadmap for producing spheroid-based implants for bone regeneration., (Creative Commons Attribution license.)

Research in bioprinting is booming due to its potential in addressing several manufacturing challenges in regenerative medicine. However, there are still many hurdles to overcome to guarantee cell survival and good printability. For the 3D extrusion-based bioprinting, cell viability is amongst one of the lowest of all the bioprinting techniques and is strongly influenced by various factors including the shear stress in the print nozzle. The goal of this study is to quantify, by means of in silico modeling, the mechanical environment experienced by the bioink during the printing process. Two ubiquitous nozzle shapes, conical and blunted, were considered, as well as three common hydrogels with material properties spanning from almost Newtonian to highly shear-thinning materials following the power-law behavior: Alginate-Gelatin, Alginate and PF127. Comprehensive in silico testing of all combinations of nozzle geometry variations and hydrogels was achieved by combining a design of experiments approach (DoE) with a computational fluid dynamics (CFD) of the printing process, analyzed through a machine learning approach named Gaussian Process. Available experimental results were used to validate the CFD model and justify the use of shear stress as a surrogate for cell survival in this study. The lower and middle nozzle radius, lower nozzle length and the material properties, alone and combined, were identified as the major influencing factors affecting shear stress, and therefore cell viability, during printing. These results were successfully compared with those of reported experiments testing viability for different nozzle geometry parameters under constant flow rate or constant pressure. The in silico 3D bioprinting platform developed in this study offers the potential to assist and accelerate further development of 3D bioprinting., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Reina-Romo, Mandal, Amorim, Bloemen, Ferraris and Geris.)

The value of in silico methods in drug development and evaluation has been demonstrated repeatedly and convincingly. While their benefits are now unanimously recognized, international standards for their evaluation, accepted by all stakeholders involved, are still to be established. In this white paper, we propose a risk-informed evaluation framework for mechanistic model credibility evaluation. To properly frame the proposed verification and validation activities, concepts such as context of use, regulatory impact and risk-based analysis are discussed. To ensure common understanding between all stakeholders, an overview is provided of relevant in silico terminology used throughout this paper. To illustrate the feasibility of the proposed approach, we have applied it to three real case examples in the context of drug development, using a credibility matrix currently being tested as a quick-start tool by regulators. Altogether, this white paper provides a practical approach to model evaluation, applicable in both scientific and regulatory evaluation contexts., (© 2021 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The 3Rs concept, calling for replacement, reduction and refinement of animal experimentation, is receiving increasing attention around the world, and has found its way to legislation, in particular in the European Union. This is aligned by continuing high-level efforts of the European Commission to support development and implementation of 3Rs methods. In this respect, the European project called "ONTOX: ontology-driven and artificial intelligence-based repeated dose toxicity testing of chemicals for next generation risk assessment" was recently initiated with the goal to provide a functional and sustainable solution for advancing human risk assessment of chemicals without the use of animals in line with the principles of 21 st century toxicity testing and next generation risk assessment. ONTOX will deliver a generic strategy to create new approach methodologies (NAMs) in order to predict systemic repeated dose toxicity effects that, upon combination with tailored exposure assessment, will enable human risk assessment. For proof-of-concept purposes, focus is put on NAMs addressing adversities in the liver, kidneys and developing brain induced by a variety of chemicals. The NAMs each consist of a computational system based on artificial intelligence and are fed by biological, toxicological, chemical and kinetic data. Data are consecutively integrated in physiological maps, quantitative adverse outcome pathway networks and ontology frameworks. Supported by artificial intelligence, data gaps are identified and are filled by targeted in vitro and in silico testing. ONTOX is anticipated to have a deep and long-lasting impact at many levels, in particular by consolidating Europe's world-leading position regarding the development, exploitation, regulation and application of animal-free methods for human risk assessment of chemicals., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Tissue engineered constructs have the potential to respond to the unmet medical need of treating deep osteochondral defects. However, current tissue engineering strategies struggle in the attempt to create patterned constructs with biologically distinct functionality. In this work, a developmentally-inspired modular approach is proposed, whereby distinct cartilaginous organoids are used as living building blocks. First, a hierarchical construct was created, composed of three layers of cartilaginous tissue intermediates derived from human periosteum-derived cells: (i) early (SOX9), (ii) mature (COL2) and (iii) (pre)hypertrophic (IHH, COLX) phenotype. Subcutaneous implantation in nude mice generated a hybrid tissue containing one mineralized and one non-mineralized part. However, the non-mineralized part was represented by a collagen type I positive fibrocartilage-like tissue. To engineer a more stable articular cartilage part, iPSC-derived cartilage microtissues (SOX9, COL2; IHH neg) were generated. Subcutaneous implantation of assembled iPSC-derived cartilage microtissues resulted in a homogenous cartilaginous tissue positive for collagen type II but negative for osteocalcin. Finally, iPSC-derived cartilage microtissues in combination with the pre-hypertrophic cartilage organoids (IHH, COLX) could form dual tissues consisting of i) a cartilaginous safranin O positive and ii) a bony osteocalcin positive region upon subcutaneous implantation, corresponding to the pre-engineered zonal pattern. The assembly of functional building blocks, as presented in this work, opens possibilities for the production of complex tissue engineered implants by embedding zone-specific functionality through the use of pre-programmed living building blocks., (Copyright © 2021. Published by Elsevier Ltd.)

Given the unequivocal benefits of menopause hormone therapies (MHT) and combined oral contraceptives (COC), there is a clinical need for new formulations devoid of any risk of breast cancer promotion. Accumulating data from preclinical and clinical studies support that estetrol (E4) is a promising natural estrogen for MHT and COC. Nevertheless, we report here that E4 remains active on the endometrium, even under a dose that is neutral on breast cancer growth and lung metastasis dissemination. This implies that a progestogen should be combined with E4 to protect the endometrium of non-hysterectomized women from hyperplasia and cancer. Through in vivo observations and transcriptomic analyses, our work provides evidence that combining a progestogen to E4 is neutral on breast cancer growth and dissemination, with very limited transcriptional impact. The assessment of breast cancer risk in patients during the development of new MHT or COC is not possible given the requirement of long-term studies in large populations. This translational preclinical research provides new evidence that a therapeutic dose of E4 for MHT or COC, combined with progesterone or drospirenone, may provide a better benefit/risk profile towards breast cancer risk compared to hormonal treatments currently available for patients.

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 5 s 2 wobble uridine tRNA modification (U 34 -enzymes), we show that gene codon content is necessary but not sufficient to predict protein fate. While translation defects upon perturbation of U 34 -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 34 -tRNA modification. Together, these results uncover the mechanism linking wobble tRNA modification to mRNA translation and aggregation to maintain proteome homeostasis.

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.

Mesenchymal stromal cells (MSCs) are characterized by a regulatory phenotype and respond promptly to the environmental signals modulating their secretory activity. An appropriate preconditioning may induce MSCs to release secretomes with an enhanced regenerative potential. However, it fails to take into account that secretomes are composed by both soluble factors and extracellular vesicles (EVs), whose functions could be altered differently by the preconditioning approach. Here we demonstrate that the MSC secretome is strongly modulated by the simultaneous stimulation with hypoxia and pro-inflammatory cytokines, used to mimic the harsh environment present at the site of injury. We observed that the environmental variations strongly influenced the angiogenic potential of the different secretome fractions. Upon inflammation, the pro-angiogenic capacity of the soluble component of the MSC secretome was strongly inhibited, regardless of the oxygen level, while the EV-encapsulated component was not significantly affected by the inflammatory stimuli. These effects were accompanied by the modulation of the secreted proteins. On one hand, inflammation-activated MSCs release proteins mainly involved in the interaction with innate immune cells and in tissue remodeling/repair; on the other hand, when MSCs are not exposed to an inflamed environment, they respond to the different oxygen levels modulating the expression of proteins involved in the angiogenic process. The cargo content (in terms of miRNAs) of the corresponding EV fractions was less sensitive to the influence of the external stimuli. Our findings suggest that the therapeutic efficacy of MSC-based therapies could be enhanced by selecting the appropriate preconditioning approach and carefully discriminating its effects on the different secretome components., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

A decade after the term developmental engineering (DE) was coined to indicate the use of developmental processes as blueprints for the design and development of engineered living implants, a myriad of proof-of-concept studies demonstrate the potential of this approach in small animal models. This review provides an overview of DE work, focusing on applications in bone regeneration. Enabling technologies allow to quantify the distance between in vitro processes and their developmental counterpart, as well as to design strategies to reduce that distance. By embedding Nature's robust mechanisms of action in engineered constructs, predictive large animal data and subsequent positive clinical outcomes can be gradually achieved. To this end, the development of next generation biofabrication technologies should provide the necessary scale and precision for robust living bone implant biomanufacturing., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Solid tumors are composed of tumor cells and stromal cells including lymphatic endothelial cells (LEC), which are mainly viewed as cells forming lymphatic vessels involved in the transport of metastatic and immune cells. We here reveal a new mechanism by which tumor exposed-LEC (teLEC) exert mitogenic effects on tumor cells. Our conclusions are supported by morphological and molecular changes induced in teLEC that in turn enhance cancer cell invasion in 3D cultures and tumor cell proliferation in vivo. The characterization of teLEC secretome by RNA-Sequencing and cytokine array revealed that interleukine-6 (IL6) is one of the most modulated molecules in teLEC, whose production was negligible in unexposed LEC. Notably, neutralizing anti-human IL6 antibody abrogated teLEC-mediated mitogenic effects in vivo, when LEC were mixed with tumor cells in the ear sponge assay. We here assign a novel function to teLEC that is beyond their role of lymphatic vessel formation. This work highlights a new paradigm, in which teLEC exert "fibroblast-like properties", contribute in a paracrine manner to the control of tumor cell properties and are worth considering as key stromal determinant in future studies., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Providing therapies tailored to each patient is the vision of precision medicine, enabled by the increasing ability to capture extensive data about individual patients. In this position paper, we argue that the second enabling pillar towards this vision is the increasing power of computers and algorithms to learn, reason, and build the 'digital twin' of a patient. Computational models are boosting the capacity to draw diagnosis and prognosis, and future treatments will be tailored not only to current health status and data, but also to an accurate projection of the pathways to restore health by model predictions. The early steps of the digital twin in the area of cardiovascular medicine are reviewed in this article, together with a discussion of the challenges and opportunities ahead. We emphasize the synergies between mechanistic and statistical models in accelerating cardiovascular research and enabling the vision of precision medicine., (© The Author(s) 2020. Published by Oxford University Press on behalf of the European Society of Cardiology.)

The development of alternatives for autologous bone grafts is a major focus of bone tissue engineering. To produce living bone-forming implants, skeletal stem and progenitor cells (SSPCs) are envisioned as key ingredients. SSPCs can be obtained from different tissues including bone marrow, adipose tissue, dental pulp, and periosteum. Human periosteum-derived cells (hPDCs) exhibit progenitor cell characteristics and have well-documented in vivo bone formation potency. Here, we have characterized and compared hPDCs derived from tibia with craniofacial hPDCs, from maxilla and mandible, respectively, each representing a potential source for cell-based tissue engineered implants for craniofacial applications. Maxilla and mandible-derived hPDCs display similar growth curves as tibial hPDCs, with equal trilineage differentiation potential toward chondrogenic, osteogenic, and adipogenic cells. These craniofacial hPDCs are positive for SSPC-markers CD73, CD164, and Podoplanin (PDPN), and negative for CD146, hematopoietic and endothelial lineage markers. Bulk RNA-sequencing identified genes that are differentially expressed between the three sources of hPDC. In particular, differential expression was found for genes of the HOX and DLX family, for SOX9 and genes involved in skeletal system development. The in vivo bone formation, 8 weeks after ectopic implantation in nude mice, was observed in constructs seeded with tibial and mandibular hPDCs. Taken together, we provide evidence that hPDCs show different profiles and properties according to their anatomical origin, and that craniofacial hPDCs are potential sources for cell-based bone tissue engineering strategies. The mandible-derived hPDCs display - both in vitro and in vivo - chondrogenic and osteogenic differentiation potential, which supports their future testing for use in craniofacial bone regeneration applications., (Copyright © 2020 Groeneveldt, Herpelinck, Maréchal, Politis, van IJcken, Huylebroeck, Geris, Mulugeta and Luyten.)