References of "Geris, Liesbet"
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See detailA mathematical model of the role of oxygen during normal and delayed fracture repair
Carlier, Aurélie ULg; Van Gastel, Nick; Carmeliet, Geert et al

Conference (2013, October 24)

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See detailAssessing local Ca2+ concentrations in calcium phosphate scaffolds by computational modelling
Manhas, Varun ULg; Guyot, Yann ULg; Chai, Yoke Chin et al

Poster (2013, October 24)

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See detailModeling cell/matrix growth in three dimensional scaffolds under dynamic culture conditions
Guyot, Yann ULg; Papantoniou, Ioannis; Chai, Yoke Chin et al

Conference (2013, October)

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See detailCongenital pseudarthrosis of the tibia: a mathematical approach
Van Schepdael, An; Carlier, Aurélie ULg; Ashbourn, Joanna et al

Conference (2013, September 13)

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See detailA MODEL FOR CELL/MATRIX GROWTH ON 3D SURFACES: A COUPLING OF LEVEL SET METHOD AND BRINKMAN EQUATION
Guyot, Yann ULg; Papantoniou, Ioannis; Chai, Yoke Chin et al

Conference (2013, September 11)

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See detailA gene regulatory network model evaluating the impact of individual factors in the hypertrophic switch
Kerkhofs, Johan ULg; Van Oosterwyck, Hans; Geris, Liesbet ULg

Conference (2013, September 11)

Chondrocytes undergoing hypertrophy show a major switch in phenotype underlied by a change in expression from the chondrocyte master gene, Sox9, to the osteoblastic one, Runx2. Strategies to stimulate or ... [more ▼]

Chondrocytes undergoing hypertrophy show a major switch in phenotype underlied by a change in expression from the chondrocyte master gene, Sox9, to the osteoblastic one, Runx2. Strategies to stimulate or inhibit this switch are of use in bone and cartilage tissue engineering respectively, as well as in the prevention of ectopic hypertrophy in osteoarthritis. We have constructed a literature based network comprised of 46 nodes and 161 interactions shown to play a part in chondrocyte hypertrophy. Network dynamics are simulated in discrete time through random updating by the use of additive functions to determine each node’s value. Furthermore, each species is represented by a fast variable (activity level, as determined by post translation modifications) which is assumed to be in equilibrium with a slow variable (mRNA) at all times. Through a Monte Carlo approach the importance of each node in the stability of chondrocytic phenotypes (proliferating, hypertrophic) is assessed in random initial conditions. A perturbation analysis of the stable states is used to determine the transition likelihood between states and the influence of individual nodes in this transition as a second measure of stability. Our results show that the hypertrophic state, marked by Runx2 expression, has a larger attractor basin and is more stable to perturbation than the proliferative state characterized by Sox9. The added time resolution seems to favour the Runx2 phenotype. The results for single nodes in overexpression or knockout simulations show a certain asymmetry, indicating that factors that are necessary for maintaining a certain phenotype are not necessarily useful in inducing it. [less ▲]

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See detailTo heal or not to heal: modeling the influence of oxygen during fracture healing.
Carlier, Aurélie ULg; Geris, Liesbet ULg; Van Oosterwyck, Hans

Conference (2013, September 11)

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See detailA Gene Regulatory Network Model to Assess the Stability of the Cartilage Phenotype
Kerkhofs, Johan ULg; Van Oosterwyck, Hans; Geris, Liesbet ULg

Poster (2013, August 29)

Introduction Chondrocyte hypertrophy entails the switching of a genetic program driven by Sox9 to one under control of the osteoblast master regulator Runx2. The switch is a prerequisite step in the bone ... [more ▼]

Introduction Chondrocyte hypertrophy entails the switching of a genetic program driven by Sox9 to one under control of the osteoblast master regulator Runx2. The switch is a prerequisite step in the bone forming process (endochondral ossification) during development and in postnatal fracture repair of larger bone defects. However, this switch can also be detrimental in tissue engineered cartilage constructs and in osteoarthritis development [Saito, 2010]. Therefore, a detailed model of the pathways that can facilitate, or inhibit, this phenotypic switch will lead to a more profound understanding of these processes and provide hints as to how to manipulate them. Methods The model formalism accommodates the qualitative information that is typically available in developmental studies. The literature based network comprises 46 nodes and 161 interactions, shown to be important in endochondral ossification. To simulate network dynamics in discrete time the normalized value of each gene is determined by additive functions where all interactions are assumed to be equally powerful. Furthermore, each species is represented by a fast variable (activity level, as determined by post translation modifications) which is assumed to be in equilibrium with a slow variable (mRNA) at all times. Through a Monte Carlo approach the importance of each node in the stability of chondrocytic phenotypes (proliferating, hypertrophic) is assessed in random initial conditions. A perturbation analysis of the stable states is used to determine the transition likelihood between them as a second measure of stability. Results Both measures of stability indicate that the hypertrophic (Runx2 driven) state is more stable than the proliferating one driven by Sox9. The results for the second measure are given in Fig.1. This higher stability seems to be partly conferred by faster reactions that favour the hypertrophic phenotype. In addition, the results point out that some transcription factors are necessary for the induction of a certain phenotype, whereas other transcription factors are required to maintain the phenotype, but are not necessary capable of inducing it. Discussion These results may relate to the difficulty experienced by researchers in maintaining a stable cartilage phenotype in culture and the occurrence of ectopic hypertrophy in osteoarthritis. By analysing the effect of changes to individual nodes, strategies to stabilise the proliferating phenotype can be developed. Overall, the model allows the importance of several important factors in the fate decision of mesenchymal cells to be quantitatively assessed based mainly on topological information. [less ▲]

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See detailMULTIPHYSICS MODELING OF CELL/MATRIX GROWTH ON 3D STRUCTURES.
Guyot, Yann ULg; Papantoniou, Ioannis; Chai, Yoke Chin et al

Conference (2013, August 26)

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See detailModeling the influence of oxygen in delayed bone fracture healing.
Carlier, Aurélie ULg; Geris, Liesbet ULg; Van Oosterwyck, Hans

Conference (2013, August 25)

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See detailContrast-enhanced nanofocus X-ray computed tomography allows virtual 3D histopathology and morphometric analysis of osteoarthritis in small animal models
Kerckhofs, Greet ULg; Sainz, J.; Maréchal, M. et al

in Cartilage (2013)

Objective: One of the early hallmarks of osteoarthritis (OA) is a progressive degeneration of the articular cartilage. Early diagnosis of OA-associated cartilage alterations would be beneficial for ... [more ▼]

Objective: One of the early hallmarks of osteoarthritis (OA) is a progressive degeneration of the articular cartilage. Early diagnosis of OA-associated cartilage alterations would be beneficial for disease prevention and control, and for the development of disease-modifying treatments. However, early diagnosis is still hampered by a lack of quantifiable readouts in preclinical models. Design: In this study, we have shown the potency of contrast-enhanced nanofocus x-ray computed tomography (CE-nanoCT) to be used for virtual 3-dimensional (3D) histopathology in established mouse models for OA, and we compared with standard histopathology. Results: We showed the equivalence of CE-nanoCT images to histopathology for the modified Mankin scoring of the cartilage structure and quality. Additionally, a limited set of 3D cartilage characteristics measured by CE-nanoCT image analysis in a user-independent and semiautomatic manner, that is, average and maximum of the noncalcified cartilage thickness distribution and loss in glycosaminoglycans, was shown to be predictive for the cartilage quality and structure as can be evaluated by histopathological scoring through the use of an empirical model. Conclusions: We have shown that CE-nanoCT is a tool that allows virtual histopathology and 3D morphological quantification of multitissue systems, such as the chondro-osseous junction. It provides faster and more quantitative data on cartilage structure and quality compared with standard histopathology while eliminating user bias. CE-nanoCT thus should allow capturing subtle differences in cartilage characteristics, carefully mapping OA progression and, ultimately, asses the beneficial changes when testing a candidate disease-modifying treatment. [less ▲]

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See detailA MATHEMATICAL MODEL FOR CELL/MATRIX GROWTH ON 3D SURFACES USING THE LEVEL SET METHOD.
Guyot, Yann ULg; Papantoniou, Ioannis; Chai, Yoke Chin et al

Conference (2013, April 03)

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See detailA multiscale model of the influence of oxygen during bone fracture healing.
Carlier, Aurélie ULg; Geris, Liesbet ULg; Van Oosterwyck, Hans

Poster (2013, April 03)

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See detailComputational modeling in tissue engineering
Geris, Liesbet ULg

Book published by Springer - 1 (2013)

One of the major challenges in tissue engineering is the translation of biological knowledge on complex cell and tissue behavior into a predictive and robust engineering process. Mastering this complexity ... [more ▼]

One of the major challenges in tissue engineering is the translation of biological knowledge on complex cell and tissue behavior into a predictive and robust engineering process. Mastering this complexity is an essential step towards clinical applications of tissue engineering. This volume discusses computational modeling tools that allow studying the biological complexity in a more quantitative way. More specifically, computational tools can help in: (i) quantifying and optimizing the tissue engineering product, e.g. by adapting scaffold design to optimize micro-environmental signals or by adapting selection criteria to improve homogeneity of the selected cell population; (ii) quantifying and optimizing the tissue engineering process, e.g. by adapting bioreactor design to improve quality and quantity of the final product; and (iii) assessing the influence of the in vivo environment on the behavior of the tissue engineering product, e.g. by investigating vascular ingrowth. The book presents examples of each of the above mentioned areas of computational modeling. The underlying tissue engineering applications will vary from blood vessels over trachea to cartilage and bone. For the chapters describing examples of the first two areas, the main focus is on (the optimization of) mechanical signals, mass transport and fluid flow encountered by the cells in scaffolds and bioreactors as well as on the optimization of the cell population itself. In the chapters describing modeling contributions in the third area, the focus will shift towards the biology, the complex interactions between biology and the micro-environmental signals and the ways in which modeling might be able to assist in investigating and mastering this complexity. The chapters cover issues related to (multiscale/multiphysics) model building, training and validation, but also discuss recent advances in scientific computing techniques that are needed to implement these models as well as new tools that can be used to experimentally validate the computational results. [less ▲]

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See detailMechanobiological modeling can explain orthodontic tooth movement: three case studies.
Van Schepdael, An ULg; Vander Sloten, J.; Geris, Liesbet ULg

in Journal of Biomechanics (2013), 46(3), 470-7

Progress in medicine and higher expectation of quality of life has led to a higher demand for several dental and medical treatments. This increases the occurrence of situations in which orthodontic ... [more ▼]

Progress in medicine and higher expectation of quality of life has led to a higher demand for several dental and medical treatments. This increases the occurrence of situations in which orthodontic treatment is complicated by pathological conditions, medical therapies and drugs. Together with experiments, computer models might lead to a better understanding of the effect of pathologies and medical treatment on tooth movement. This study uses a previously presented mechanobiological model of orthodontic tooth displacement to investigate the effect of pathologies and (medical) therapies on the result of orthodontic treatment by means of three clinically relevant case studies looking at the effect of estrogen deficiency, the effect of OPG injections and the influence of fluoride intake. When less estrogen was available, the model predicted bone loss and a rise in the number of osteoclasts present at the compression side, and a faster bone resorption. These effects were also observed experimentally. Experiments disagreed on the effect of estrogen deficiency on bone formation, while the mechanobiological model predicted very little difference between the pathological and the non-pathological case at formation sites. The model predicted a decrease in tooth movement after OPG injections or fluoride intake, which was also observed in experiments. Although more experiments and model analysis is needed to quantitatively validate the mechanobiological model used in this study, its ability to conceptually describe several pathological conditions is an important measure for its validity. [less ▲]

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See detailAnalytical determination of stress patterns in the periodontal ligament during orthodontic tooth movement.
Van Schepdael, An ULg; Geris, Liesbet ULg; Vander Sloten, Jos

in Medical Engineering & Physics (2013), 35(3), 403-10

A dedicated software package that allows simulation of tooth movement can lead to shortening of the treatment program in orthodontics. A first step in the development of this software is the modelling of ... [more ▼]

A dedicated software package that allows simulation of tooth movement can lead to shortening of the treatment program in orthodontics. A first step in the development of this software is the modelling of the movement of a single tooth. Forces applied to the crown of the tooth are transmitted to the alveolar bone through the periodontal ligament, stretching, and compressing the ligament, eventually resulting in tooth movement. This paper presents an analytical model that predicts stresses and strains inside this ligament by approximating the shape of the root as an elliptic paraboloid. The model input consists of 2 material parameters and 4 geometrical parameters. To assess the accuracy of the model a finite element model (FEM) was constructed to compare the results and the influence of the eccentricity of the root was studied. The results show that the model is able to successfully describe the global behavior of the PDL and, except at a region near the alveolar crest, the differences between analytical and FEM results are small. In contrast to FEM, the analytical model does not require setting up a 3D-model and creating a mesh, allowing for significantly lower computational times and reducing cost when implementing in clinical practice. [less ▲]

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See detailMechanisms of cell migration in the adult brain: modelling subventricular neurogenesis.
Van Schepdael, An ULg; Ashbourn, J. M. A.; Beard, R. et al

in Computer Methods in Biomechanics & Biomedical Engineering (2013)

Neurogenesis has been the subject of active research in recent years. Although the majority of neurons form during the embryonic period, neurogenesis continues in restricted regions of the mammalian brain ... [more ▼]

Neurogenesis has been the subject of active research in recent years. Although the majority of neurons form during the embryonic period, neurogenesis continues in restricted regions of the mammalian brain well into adulthood. In rodent brains, neuronal migration is present in the rostral migratory stream (RMS), connecting the subventricular zone to the olfactory bulb (OB). The migration in the RMS is characterised by a lack of dispersion of neuroblasts into the surrounding tissues and a highly directed motion towards the OB. This study uses a simple mathematical model to investigate several theories of migration of neuroblasts through the RMS proposed in the literature, including chemo-attraction, chemorepulsion, general inhibition and the presence of a migration-inducing protein. Apart from the general inhibition model, all the models were able to provide results in good qualitative correspondence with the experimental observations. [less ▲]

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See detailA mechanobiological model of orthodontic tooth movement.
Van Schepdael, A; Vander Sloten, J; Geris, Liesbet ULg

in Biomechanics & Modeling in Mechanobiology (2013)

Orthodontic tooth movement is achieved by the process of repeated alveolar bone resorption on the pressure side and new bone formation on the tension side. In order to optimize orthodontic treatment, it ... [more ▼]

Orthodontic tooth movement is achieved by the process of repeated alveolar bone resorption on the pressure side and new bone formation on the tension side. In order to optimize orthodontic treatment, it is important to identify and study the biological processes involved. This article presents a mechanobiological model using partial differential equations to describe cell densities, growth factor concentrations, and matrix densities occurring during orthodontic tooth movement. We hypothesize that such a model can predict tooth movement based on the mechanobiological activity of cells in the PDL. The developed model consists of nine coupled non-linear partial differential equations, and two distinct signaling pathways were modeled: the RANKL-RANK-OPG pathway regulating the communication between osteoblasts and osteoclasts and the TGF-beta pathway mediating the differentiation of mesenchymal stem cells into osteoblasts. The predicted concentrations and densities were qualitatively validated by comparing the results to experiments reported in the literature. In the current form, the model supports our hypothesis, as it is capable of conceptually simulating important features of the biological interactions in the alveolar bone-PDL complex during orthodontic tooth movement. [less ▲]

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