References of "Kerkhofs, Johan"
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See detailThe search for a core functionality network in chondrocyte differentiation using heuristic and genetic algorithms
Kerkhofs, Johan ULg

Conference (2014, June 18)

Introduction: In the growth plate a continuing process where cartilage is replaced by bone provides the fuel for bone growth until its closure towards the end of puberty. At the cellular level the growth ... [more ▼]

Introduction: In the growth plate a continuing process where cartilage is replaced by bone provides the fuel for bone growth until its closure towards the end of puberty. At the cellular level the growth rate is maintained by proliferation and enlargement of maturing cells (hypertrophy). Mature cartilage cells (hypertrophic chondrocytes) secrete Ihh, a growth factor that induces expression of PTHrP, another growth factor, in immature proliferating chondrocytes. Since PTHrP in turn inhibits chondrocyte maturation, Ihh secretion limits the number of maturing chondrocytes through a negative feedback loop, striking a balance between proliferation and hypertrophy [Kronenberg, 2003]. Materials and methods: A gene network centering on the control of Ihh, PTHrP and transcription factors Sox9 and Runx2, which are the master regulators of early and late chondrocyte differentiation respectively, was manually constructed from literature. The dynamics of this network are simulated in a discrete framework that divides reactions into two speed classes. In this framework all interactions are considered additive, and each interaction is associated with a weight. Starting from the observation that the gene network must activate Runx2 in the presence of Ihh and Sox9 in the presence of Ihh and PTHrP, we investigate which edges are vital in achieving this. To this end, we employ both a heuristic and a genetic algorithm where the weights attached to the edges function as variables. In the heuristic algorithm weights are uniformly distributed in [0,1] and the means (based on 450 samples) of the weights that satisfy the above mentioned observations are contrasted with those that do not. If the difference of the means passes a certain threshold, the weight of the corresponding edge is fixed at 1. Results and discussion: Preliminary results from the heuristic algorithm show that fixing 14 weights (out of 147) is sufficient to match the biological observations in about 22% of cases, all other weights being selected randomly. The selected edges show that the BMP pathway is crucial in effecting a switch between hypertrophy in the absence of PTHrP and proliferation in its presence. This observation can be substantiated by earlier findings that BMP signalling plays a crucial role in prehypertrophic cells that are on the verge of hypertrophy [Yoon, 2006]. References: Kronenberg, 2003, Nature, 423:332-336; Yoon et al., 2006, Development, 133:4667-4678. [less ▲]

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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 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 detailA Gene Regulatory Network Model to Assess the Stability of the Cartilage Phenotype
Kerkhofs, Johan 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 detailA computational Model to Assess the Contribution of Growth Factors to Phenotype Stability in Chondrocytes
Kerkhofs, Johan ULg; Van Oosterwyck, Hans

Conference (2013, June 17)

Cell-based tissue engineering constructs are an interesting expansion of the surgeon’s toolkit in treating long bone defects. However, the outcome of interventions with these constructs suffers from high ... [more ▼]

Cell-based tissue engineering constructs are an interesting expansion of the surgeon’s toolkit in treating long bone defects. However, the outcome of interventions with these constructs suffers from high variability barring their regular appearance in the clinic, in no small part due to the inter-patient variability in cell behaviour. In the paradigm of ‘developmental engineering’ a solution to this problem is envisioned by mimicking robust developmental processes in combination with a rigorous analysis thereof through the construction of computational models. From our knowledge of developmental biology we can form a computational model to facilitate understanding of how growth factors and transcription factors influence cell fate decisions in the growth plate and consequently answer the question whether – and how – they can boost bone healing. The model presented in this study includes 46 factors and 146 interactions between them. The dynamics of the system were simulated in a simplified manner that differentiates between slow and fast interactions. Through a Monte Carlo approach the importance of each factor in the stability of chondrocytic phenotypes (proliferating, hypertrophic) is assessed. The hypertrophic state was found to be more stable than that of the proliferating chondrocyte. This higher stability in random initial conditions seems to be conferred by faster reactions that favor the hypertrophic phenotype. Overall, the model allows the importance of several important factors in the fate decision of chondrocytes to be quantitatively assessed and can make suggestions as to how an in vitro bone forming process could be steered. [less ▲]

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See detailA Dynamic Graph Model of Endochondral Ossification can assess the Importance of Biological Actors in Differentiation
Kerkhofs, Johan ULg; Van Oosterwyck, Hans; Geris, Liesbet ULg

Conference (2012, September 18)

Cell-based tissue engineering constructs are a promising avenue for the treatment of long bone defects since they provide the primordial ingredients for bone regeneration. The construct provides the ... [more ▼]

Cell-based tissue engineering constructs are a promising avenue for the treatment of long bone defects since they provide the primordial ingredients for bone regeneration. The construct provides the appropriate micro-environment through the carrier, cells to form tissue and chemical cues to kick start the natural bone forming process. Clearly this approach will benefit from a more comprehensive appreciation of how cell populations and the microenvironment provided by the carrier can impact on bone formation in all its complexities. A cornucopia of studies of developmental biology have revealed many biological actors that together form a central network that orchestrates cell behaviour during this process and assures its robustness. This knowledge can be brought to bear specifically in the form of a mathematical model of endochondral ossification, the dominant type of ossification. This model can facilitate the understanding of how growth factors and transcription factors influence cell fate decisions and consequently answer the question whether they can boost bone healing. The model formalism accommodates the qualitative information that is typically available in developmental studies. The 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. The hypertrophic state, driven by Runx2, is more stable than the proliferating chondrocyte. This higher stability seems to be conferred by faster reactions that favor 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. 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 detailBridging the Gap: A Theoretical Model of Mechanotransduction Through ERK Signalling
Kerkhofs, Johan ULg; Geris, Liesbet ULg; Bosmans, Bart et al

Conference (2012, July 02)

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See detailRelating the Chondrocyte Gene Network to Growth Plate Morphology: From Genes to Phenotype
Kerkhofs, Johan ULg; Roberts, Scott J; Luyten, Frank P et al

in PLoS ONE (2012)

During endochondral ossification, chondrocyte growth and differentiation is controlled by many local signalling pathways. Due to crosstalks and feedback mechanisms, these interwoven pathways display a ... [more ▼]

During endochondral ossification, chondrocyte growth and differentiation is controlled by many local signalling pathways. Due to crosstalks and feedback mechanisms, these interwoven pathways display a network like structure. In this study, a large-scale literature based logical model of the growth plate network was developed. The network is able to capture the different states (resting, proliferating and hypertrophic) that chondrocytes go through as they progress within the growth plate. In a first corroboration step, the effect of mutations in various signalling pathways of the growth plate network was investigated. [less ▲]

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See detailCoupling Cell Mechanics and Intracellular Signalling: Mechanotransduction through ERK
Kerkhofs, Johan ULg; Geris, Liesbet ULg; Bosmans, Bart et al

in Middleton, John (Ed.) The Proceedings of the 10th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering. Hotel Berlin, Berlin, Germany, April 7th – 11th, 2012 pages:0-0 (2012, April 12)

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See detailA Boolean network approach to developmental engineering
Kerkhofs, Johan ULg; Roberst, Scott J; Luyten, Frank P et al

Conference (2011, June 13)

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See detailA Boolean network model of the growth plate
Kerkhofs, Johan ULg; Roberts, Scott J; Luyten, Frank P et al

Poster (2010, November 26)

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See detailA Boolean network model of the growth plate
Kerkhofs, Johan ULg; Roberts, Scott J; Luyten, Frank P et al

Poster (2010, October 10)

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See detailBMP signalling in growth plate chondrocytes: a Boolean modelling approach
Kerkhofs, Johan ULg; Roberts, Scott J; Van Oosterwyck, Hans et al

Poster (2010, September 15)

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