Computational Modeling to Quantify the Contributions of VEGFR1, VEGFR2, and Lateral Inhibition in Sprouting Angiogenesis

Sprouting angiogenesis is a necessary process in regeneration and development as well as in tumorigenesis. VEGF-A is the main pro-angiogenic chemoattractant and it can bind to the decoy receptor VEGFR1 or to VEGFR2 to induce sprouting. Active sprout cells express Dll4, which binds to Notch1 on neighboring cells, in turn inhibiting VEGFR2 expression. It is known that the balance between VEGFR2 and VEGFR1 determines tip selection and network architecture, however the quantitative interrelationship of the receptors and their interrelated balances, also with relation to Dll4-Notch1 signaling, remains yet largely unknown. Here, we present an agent-based computer model of sprouting angiogenesis, integrating VEGFR1 and VEGFR2 in a detailed model of cellular signaling. Our model reproduces experimental data on VEGFR1 knockout. We show that soluble VEGFR1 improves the efficiency of angiogenesis by directing sprouts away from existing cells over a wide range of parameters. Our analysis unravels the relevance of the stability of the active notch intracellular domain as a dominating hub in this regulatory network. Our analysis quantitatively dissects the regulatory interactions in sprouting angiogenesis. Because we use a detailed model of intracellular signaling, the results of our analysis are directly linked to biological entities. We provide our computational model and simulation engine for integration in complementary modeling approaches

Computational Modeling to Quantify the Contributions of VEGFR1, VEGFR2, and Lateral Inhibition in Sprouting Angiogenesis

Sprouting angiogenesis is a necessary process in regeneration and development as well as in tumorigenesis. VEGF-A is the main pro-angiogenic chemoattractant and it can bind to the decoy receptor VEGFR1 or to VEGFR2 to induce sprouting. Active sprout cells express Dll4, which binds to Notch1 on neighboring cells, in turn inhibiting VEGFR2 expression. It is known that the balance between VEGFR2 and VEGFR1 determines tip selection and network architecture, however the quantitative interrelationship of the receptors and their interrelated balances, also with relation to Dll4-Notch1 signaling, remains yet largely unknown. Here, we present an agent-based computer model of sprouting angiogenesis, integrating VEGFR1 and VEGFR2 in a detailed model of cellular signaling. Our model reproduces experimental data on VEGFR1 knockout. We show that soluble VEGFR1 improves the efficiency of angiogenesis by directing sprouts away from existing cells over a wide range of parameters. Our analysis unravels the relevance of the stability of the active notch intracellular domain as a dominating hub in this regulatory network. Our analysis quantitatively dissects the regulatory interactions in sprouting angiogenesis. Because we use a detailed model of intracellular signaling, the results of our analysis are directly linked to biological entities. We provide our computational model and simulation engine for integration in complementary modeling approaches

Multiscale Modeling of Bone Healing

Bone is a living part of the body that can, in most situations, heal itself after fracture. However, in some situations, healing may fail. Compromised conditions, such as large bone defects, aging, immuno-deficiency, or genetic disorders, might lead to delayed or non-unions. Treatment strategies for those conditions remain a clinical challenge, emphasizing the need to better understand the mechanisms behind endogenous bone regeneration. Bone healing is a complex process that involves the coordination of multiple events at different length and time scales. Computer models have been able to provide great insights into the interactions occurring within and across the different scales (organ, tissue, cellular, intracellular) using different modeling approaches [partial differential equations (PDEs), agent-based models, and finite element techniques]. In this review, we summarize the latest advances in computer models of bone healing with a focus on multiscale approaches and how they have contributed to understand the emergence of tissue formation patterns as a result of processes taking place at the lower length scales

El olor como símbolo de identidad: El Perfume. Historia de un asesino, de Patrick Süskind

En este trabajo tengo por objeto analizar el sentido del olfato, y más concretamente, el olor como símbolo de identidad en la obra del autor alemán Patrick Süskind El perfume. Historia de un asesino. Su protagonista, Jean Baptiste Grenouille, es un hombre deforme que tiene un olfato privilegiado y conoce todo su entorno a través de este sentido, lo que no puede reconocer por el olor, no existe. Pero, paradojas de la vida, él mismo no posee olor propio y eso le lleva a obsesionarse con la creación de un perfume que contenga el alma, la esencia de las cosas y de las personas, con crear un perfume que haga que los demás lo reconozcan. Y así es como se convierte en un asesino

Initial mechanical conditions within an optimized bone scaffold do not ensure bone regeneration – an in silico analysis

Large bone defects remain a clinical challenge because they do not heal spontaneously. 3-D printed scaffolds are a promising treatment option for such critical defects. Recent scaffold design strategies have made use of computer modelling techniques to optimize scaffold design. In particular, scaffold geometries have been optimized to avoid mechanical failure and recently also to provide a distinct mechanical stimulation to cells within the scaffold pores. This way, mechanical strain levels are optimized to favour the bone tissue formation. However, bone regeneration is a highly dynamic process where the mechanical conditions immediately after surgery might not ensure optimal regeneration throughout healing. Here, we investigated in silico whether scaffolds presenting optimal mechanical conditions for bone regeneration immediately after surgery also present an optimal design for the full regeneration process. A computer framework, combining an automatic parametric scaffold design generation with a mechano-biological bone regeneration model, was developed to predict the level of regenerated bone volume for a large range of scaffold designs and to compare it with the scaffold pore volume fraction under favourable mechanical stimuli immediately after surgery. We found that many scaffold designs could be considered as highly beneficial for bone healing immediately after surgery; however, most of them did not show optimal bone formation in later regenerative phases. This study allowed to gain a more thorough understanding of the effect of scaffold geometry changes on bone regeneration and how to maximize regenerated bone volume in the long term

Mechano-Biological Computer Model of Scaffold-Supported Bone Regeneration: Effect of Bone Graft and Scaffold Structure on Large Bone Defect Tissue Patterning

Large segmental bone defects represent a clinical challenge for which current treatment procedures have many drawbacks. 3D-printed scaffolds may help to support healing, but their design process relies mainly on trial and error due to a lack of understanding of which scaffold features support bone regeneration. The aim of this study was to investigate whether existing mechano-biological rules of bone regeneration can also explain scaffold-supported bone defect healing. In addition, we examined the distinct roles of bone grafting and scaffold structure on the regeneration process. To that end, scaffold-surface guided migration and tissue deposition as well as bone graft stimulatory effects were included in an in silico model and predictions were compared to in vivo data. We found graft osteoconductive properties and scaffold-surface guided extracellular matrix deposition to be essential features driving bone defect filling in a 3D-printed honeycomb titanium structure. This knowledge paves the way for the design of more effective 3D scaffold structures and their pre-clinical optimization, prior to their application in scaffold-based bone defect regeneration

The Degradation of Synthetic Polymeric Scaffolds With Strut-like Architecture Influences the Mechanics-dependent Repair Process of an Osteochondral Defect in Silico

Current clinical treatments of osteochondral defects in articulating joints are frequently not successful in restoring articular surfaces. Novel scaffold-based tissue engineering strategies may help to improve current treatment options and foster a true regeneration of articulating structures. A frequently desired property of scaffolds is their ability to degrade over time and allow a full restoration of tissue and function. However, it remains largely unknown how scaffold degradation influences the mechanical stability of the tissue in a defect region and, in turn, the regenerative process. Such differing goals-supporting regeneration by degrading its own structure-can hardly be analyzed for tissue engineered constructs in clinical trials and in vivo preclinical experiments. Using an in silico analysis, we investigated the degradation-induced modifications in material and architectural properties of a scaffold with strut-like architecture over the healing course and their influence on the mechanics-dependent tissue formation in osteochondral defects. The repair outcome greatly varied depending on the degradation modality, i.e. surface erosion or bulk degradation with and without autocatalysis, and of the degradation speed, i.e. faster, equal or slower than the expected repair time. Bulk degradation with autocatalysis, independently of degradation speed, caused the mechanical failure of the scaffold prior to osteochondral defect repair and was thereby deemed inappropriate for further application. On the other hand, scaffolds with strut-like architecture degrading by both surface erosion and bulk degradation with slow degradation speed resulted in comparably good repair outcomes, thereby indicating such degradation modalities as favorable for the application in osteochondral defects

A 3D in Silico Multi-Tissue Evolution Model Highlights the Relevance of Local Strain Accumulation in Bone Fracture Remodeling

Since 5–10% of all bone fractures result in non-healing situations, a thorough understanding of the various bone fracture healing phases is necessary to propose adequate therapeutic strategies. In silico models have greatly contributed to the understanding of the influence of mechanics on tissue formation and resorption during the soft and hard callus phases. However, the late-stage remodeling phase has not been investigated from a mechanobiological viewpoint so far. Here, we propose an in silico multi-tissue evolution model based on mechanical strain accumulation to investigate the mechanobiological regulation of bone remodeling during the late phase of healing. Computer model predictions are compared to histological data of two different pre-clinical studies of bone healing. The model predicted the bone marrow cavity re-opening and the resorption of the external callus. Our results suggest that the local strain accumulation can explain the fracture remodeling process and that this mechanobiological response is conserved among different mammal species. Our study paves the way for further understanding of non-healing situations that could help adapting therapeutic strategies to foster bone healing

Application to a short-stem hip implant

Today, different implant designs exist in the market; however, there is not a clear understanding of which are the best implant design parameters to achieve mechanical optimal conditions. Therefore, the aim of this project was to investigate if the geometry of a commercial short stem hip prosthesis can be further optimized to reduce stress shielding effects and achieve better short- stemmed implant performance. To reach this aim, the potential of machine learning techniques combined with parametric Finite Element analysis was used. The selected implant geometrical parameters were: total stem length (L), thickness in the lateral (R1) and medial (R2) and the distance between the implant neck and the central stem surface (D). The results show that the total stem length was not the only parameter playing a role in stress shielding. An optimized implant should aim for a decreased stem length and a reduced length of the surface in contact with the bone. The two radiuses that characterize the stem width at the distal cross-section in contact with the bone were less influential in the reduction of stress shielding compared with the other two parameters; but they also play a role where thinner stems present better results

Multiscale Modeling of Bone Healing: Toward a Systems Biology Approach

Bone is a living part of the body that can, in most situations, heal itself after fracture. However, in some situations, healing may fail. Compromised conditions, such as large bone defects, aging, immuno-deficiency, or genetic disorders, might lead to delayed or non-unions. Treatment strategies for those conditions remain a clinical challenge, emphasizing the need to better understand the mechanisms behind endogenous bone regeneration. Bone healing is a complex process that involves the coordination of multiple events at different length and time scales. Computer models have been able to provide great insights into the interactions occurring within and across the different scales (organ, tissue, cellular, intracellular) using different modeling approaches [partial differential equations (PDEs), agent-based models, and finite element techniques]. In this review, we summarize the latest advances in computer models of bone healing with a focus on multiscale approaches and how they have contributed to understand the emergence of tissue formation patterns as a result of processes taking place at the lower length scales