Overview: In Silico Approaches to Understand Bone Adaptation

2018 ◽  
pp. 1-11
Author(s):  
Yoshitaka Kameo ◽  
Ken-ichi Tsubota ◽  
Taiji Adachi
Keyword(s):  
In Silico ◽  
Bone Adaptation

In silico reproduction of bone adaptation to cyclic loading in mouse caudal vertebrae

2019 ◽  
Vol 2019.30 (0) ◽  
pp. 2B21
Author(s):  
Yoshitaka KAMEO ◽  
Denis J. CENER ◽  
Ariane C. SCHEUREN ◽  
Ralph MÜLLER ◽  
Taiji ADACHI
Keyword(s):  
Cyclic Loading ◽  
In Silico ◽  
Bone Adaptation ◽  
Caudal Vertebrae

In silico biology of bone modelling and remodelling: adaptation

2009 ◽  
Vol 367 (1895) ◽  
pp. 2011-2030 ◽  
Author(s):  
Friederike A. Gerhard ◽  
Duncan J. Webster ◽  
G. Harry van Lenthe ◽  
Ralph Müller
Keyword(s):  
In Silico ◽  
Simulation Models ◽  
Local Strain ◽  
Cell Types ◽  
Cellular Level ◽  
Bone Adaptation ◽  
Cellular Mechanisms ◽  
Structural Reorganization ◽  
Trabecular Thickness ◽  
In Silico Biology

Modelling and remodelling are the processes by which bone adapts its shape and internal structure to external influences. However, the cellular mechanisms triggering osteoclastic resorption and osteoblastic formation are still unknown. In order to investigate current biological theories, in silico models can be applied. In the past, most of these models were based on the continuum assumption, but some questions related to bone adaptation can be addressed better by models incorporating the trabecular microstructure. In this paper, existing simulation models are reviewed and one of the microstructural models is extended to test the hypothesis that bone adaptation can be simulated without particular knowledge of the local strain distribution in the bone. Validation using an experimental murine loading model showed that this is possible. Furthermore, the experimental model revealed that bone formation cannot be attributed only to an increase in trabecular thickness but also to structural reorganization including the growth of new trabeculae. How these new trabeculae arise is still an unresolved issue and might be better addressed by incorporating other levels of hierarchy, especially the cellular level. The cellular level sheds light on the activity and interplay between the different cell types, leading to the effective change in the whole bone. For this reason, hierarchical multi-scale simulations might help in the future to better understand the biomathematical laws behind bone adaptation.

scholarly journals In silico experiments of bone remodeling explore metabolic diseases and their drug treatment

2020 ◽  
Vol 6 (10) ◽  
pp. eaax0938 ◽  
Author(s):  
Y. Kameo ◽  
Y. Miya ◽  
M. Hayashi ◽  
T. Nakashima ◽  
T. Adachi
Keyword(s):  
Bone Metabolism ◽  
Bone Remodeling ◽  
In Silico ◽  
Bone Structure ◽  
Bone Adaptation ◽  
Bone Diseases ◽  
Therapeutic Effects ◽  
Cellular Interactions ◽  
Metabolic Bone Diseases ◽  
Metabolic Bone

Bone structure and function are maintained by well-regulated bone metabolism and remodeling. Although the underlying molecular and cellular mechanisms are now being understood, physiological and pathological states of bone are still difficult to predict due to the complexity of intercellular signaling. We have now developed a novel in silico experimental platform, V-Bone, to integratively explore bone remodeling by linking complex microscopic molecular/cellular interactions to macroscopic tissue/organ adaptations. Mechano-biochemical couplings modeled in V-Bone relate bone adaptation to mechanical loading and reproduce metabolic bone diseases such as osteoporosis and osteopetrosis. V-Bone also enables in silico perturbation on a specific signaling molecule to observe bone metabolic dynamics over time. We also demonstrate that this platform provides a powerful way to predict in silico therapeutic effects of drugs against metabolic bone diseases. We anticipate that these in silico experiments will substantially accelerate research into bone metabolism and remodeling.

In silico modeling of bone adaptation to rest-inserted loading: Strain energy density versus fluid flow as stimulus

2018 ◽  
Vol 446 ◽  
pp. 110-127 ◽  
Author(s):  
Abhishek Kumar Tiwari ◽  
Rakesh Kumar ◽  
Dharmendra Tripathi ◽  
Subham Badhyal
Keyword(s):  
Fluid Flow ◽  
Energy Density ◽  
In Silico ◽  
Strain Energy Density ◽  
Strain Energy ◽  
Bone Adaptation ◽  
In Silico Modeling

scholarly journals Upscaling of In Vivo HR-pQCT Images Enables Accurate Simulations of Human Microstructural Bone Adaptation

2020 ◽  
Author(s):  
Nicholas Ohs ◽  
Duncan C. Tourolle né Betts ◽  
Penny R. Atkins ◽  
Stephanie Sebastian ◽  
Bert van Rietbergen ◽  
...  
Keyword(s):  
High Resolution ◽  
In Silico ◽  
Ex Vivo ◽  
Quantitative Computed Tomography ◽  
Ground Truth ◽  
Peripheral Quantitative Computed Tomography ◽  
Bone Adaptation ◽  
Bone Diseases ◽  
Clinical Models

AbstractIn silico trials of treatments in a virtual physiological human (VPH) would revolutionize research in the biomedical field. Hallmarks of bone disease and treatments can already be simulated in pre-clinical models and in ex vivo data of humans using microstructural bone adaptation simulations. The increasing availability of in vivo high resolution peripheral quantitative computed tomography (HR-pQCT) images provides novel opportunities to validate and ultimately utilize microstructural bone adaptation simulations to improve our understanding of bone diseases and move towards in silico VPH decision support systems for clinicians.In the present study, we investigated if microstructural bone adaptation simulations of in vivo human HR-pQCT images yielded accurate results. Since high-resolution ground truth images cannot be obtained in vivo, we applied an ex vivo approach to study resolution dependence and the effect of upscaling on morphometric accuracy. To address simulation initialisation issues, we developed an input regularisation approach to reduce initialisation shocks observed in microstructural bone adaptation simulations and evaluated upscaling as a way to improve the accuracy of model inputs. Finally, we compared our ex vivo results to simulations run on in vivo images to investigate whether in vivo image artefacts further affect simulation outcomes.

Strain-adaptive in silico modeling of bone adaptation — A computer simulation validated by in vivo micro-computed tomography data

Bone ◽  
2013 ◽  
Vol 52 (1) ◽  
pp. 485-492 ◽  
Author(s):  
Friederike A. Schulte ◽  
Alexander Zwahlen ◽  
Floor M. Lambers ◽  
Gisela Kuhn ◽  
Davide Ruffoni ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Computer Simulation ◽  
In Silico ◽  
Bone Adaptation ◽  
Micro Computed Tomography ◽  
In Silico Modeling ◽  
Tomography Data

A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gallbladder Carcinoma ◽  
In Silico ◽  
In Silico Analysis ◽  
Transcriptomic Profile ◽  
Silico Analysis

Common and well-documented Allele List: unverzichtbares Hilfsmittel für die moderne HLA-Typisierung

2019 ◽  
Vol 9 (04) ◽  
pp. 241-245
Author(s):  
Nils Lachmann ◽  
Diana Stauch ◽  
Axel Pruß
Keyword(s):  
In Silico ◽  
Regionale Unterschiede

ZusammenfassungDie Typisierung der humanen Leukozytenantigene (HLA) vor Organ- und hämatopoetischer Stammzelltransplantation zur Beurteilung der Kompatibilität von Spender und Empfänger wird heutzutage in der Regel molekulargenetisch mittels Amplifikation, Hybridisierung oder Sequenzierung durchgeführt. Durch die exponentiell steigende Anzahl an neu entdeckten HLA-Allelen treten vermehrt Mehrdeutigkeiten, sogenannte Ambiguitäten, in der HLA-Typisierung auf, die aufgelöst werden müssen, um zu einem eindeutigen Ergebnis zu gelangen. Mithilfe kategorisierter Allelfrequenzen (häufig, gut dokumentiert und selten) in Form von CWD-Allellisten (CWD: common and well-documented) ist die In-silico-Auflösung von Ambiguitäten durch den Ausschluss seltener Allele als mögliches Ergebnis realisierbar. Ausgehend von einer amerikanischen CWD-Liste existieren derzeit auch eine europäische, deutsche und chinesische CWD-Liste, die jeweils regionale Unterschiede in den Allelfrequenzen erkennbar werden lassen. Durch die Anwendung von CWD-Allelfiltern in der klinischen HLA-Typisierung können Zeit, Kosten und Arbeitskraft eingespart werden.

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