A new biological bone remodeling in silico model combined with advanced discretization methods

2019 ◽  
pp. e3196 ◽  
Author(s):  
Madalena M. A. Peyroteo ◽  
Jorge Belinha ◽  
Lucia M.J.S. Dinis ◽  
Renato M. Natal Jorge
Keyword(s):  
Bone Remodeling ◽  
In Silico ◽  
Discretization Methods ◽  
In Silico Model

An In Silico Model for the Prediction of Changes in Mineral Density in Cortical Bone Remodeling

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
Rafael R. Mattazio ◽  
Pedro Y. Noritomi ◽  
Zilda C. Silveira
Keyword(s):  
Parathyroid Hormone ◽  
Cortical Bone ◽  
Bone Remodeling ◽  
In Silico ◽  
Vigorous Physical Activity ◽  
Bone Matrix ◽  
Numerical Error ◽  
Mineral Density ◽  
In Silico Model ◽  
Proposed Model

Abstract An in silico model for the estimation of volumetric bone mineral density (vBMD) changes at a cortical bone site subjected to mechanobiological bone remodeling is proposed in this manuscript. Mechanisms of cell differentiation, receptor–ligand binding, mechanical signaling, and resorption or deposition of bone matrix were considered, therefore providing a comprehensive description of mechanobiological bone remodeling in the bone microenvironment and enabling the analysis of temporal evolution of disease or therapy scenarios. The proposed model is composed by five modules, namely, bone cells populations, mechanobiology, volume fractions and porosity, mineral density, and structural stiffness. The model is an extension of other models found in the literature because equations for the obtaining of cortical vBMD and the binding of parathyroid hormone (PTH) to parathyroid hormone 1 receptor are included. The proposed model showed a satisfactory agreement with the solutions of other in silico models found in the literature. Simulations of walking and running exercise routines were performed for the evaluation of model capability regarding the control of the numerical error and prediction of vBMD. The computational method used to solve the case study controlled the relative numerical error by less than 1 × 10−7 for approximately 1.7 × 106 time steps. The predicted values correlate with the concept of increasing BMD by vigorous physical activity; however, they contrast with the specific effect of physical activities on cortical vBMD.

Usefulness of collaboration between mathematical models and cell engineering for elucidating complex disease mechanisms and discover effective drugs

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
H Kohjitani ◽  
A Kashiwa ◽  
T Makiyama ◽  
F Toyoda ◽  
Y Yamamoto ◽  
...  
Keyword(s):  
Mathematical Model ◽  
In Silico ◽  
Complex Disease ◽  
Ion Selectivity ◽  
Public Institution ◽  
Cell Engineering ◽  
Funding Source ◽  
Patch Clamp Technique ◽  
In Silico Model

Abstract Background A missense mutation, CACNA1C-E1115K, located in the cardiac L-type calcium channel (LTCC), was recently reported to be associated with diverse arrhythmias. Several studies reported in-vivo and in-vitro modeling of this mutation, but actual mechanism and target drug of this disease has not been clarified due to its complex ion-mechanisms. Objective To reveal the mechanism of this diverse arrhythmogenic phenotype using combination of in-vitro and in-silico model. Methods and results Cell-Engineering Phase: We generated human induced pluripotent stem cell (hiPSC) from a patient carrying heterozygous CACNA1C-E1115K and differentiated into cardiomyocytes. Spontaneous APs were recorded from spontaneously beating single cardiomyocytes by using the perforated patch-clamp technique. Mathematical-Modeling Phase: We newly developed ICaL-mutation mathematical model, fitted into experimental data, including its impaired ion selectivity. Furthermore, we installed this mathematical model into hiPSC-CM simulation model. Collaboration Phase: Mutant in-silico model showed APD prolongation and frequent early afterdepolarization (EAD), which are same as in-vitro model. In-silico model revealed this EAD was mostly related to robust late-mode of sodium current occurred by Na+ overload and suggested that mexiletine is capable of reducing arrhythmia. Afterward, we applicated mexiletine onto hiPSC-CMs mutant model and found mexiletine suppress EADs. Conclusions Precise in-silico disease model can elucidate complicated ion currents and contribute predicting result of drug-testing. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): Japan Society for the Promotion of Science, Grant-in-Aid for Young Scientists

scholarly journals A corneal-PAMPA-based in silico model for predicting corneal permeability

2021 ◽  
pp. 114218
Author(s):  
Anna Vincze ◽  
Gergö Dargó ◽  
Anita Rácz ◽  
György T. Balogh
Keyword(s):  
In Silico ◽  
Corneal Permeability ◽  
In Silico Model

Development of a predictive in silico model for mixtures of azole fungicides acting on the skeletal craniofacial AOP

2017 ◽  
Vol 280 ◽  
pp. S287
Author(s):  
Maria Battistoni ◽  
Luca Palazzolo ◽  
Frederic Yves Bois ◽  
Francesca Di Renzo ◽  
Ivano Eberini ◽  
...  
Keyword(s):  
In Silico ◽  
In Silico Model ◽  
Azole Fungicides

An in silico model to predict renal clearance of xenobiotics in humans

2015 ◽  
Vol 238 (2) ◽  
pp. S165-S166
Author(s):  
M. Atari ◽  
S. Thomas
Keyword(s):  
Renal Clearance ◽  
In Silico ◽  
In Silico Model

scholarly journals Automatic Optimization of an in Silico Model of Human iPSC Derived Cardiomyocytes Recapitulating Calcium Handling Abnormalities

2018 ◽  
Vol 9 ◽  
Author(s):  
Michelangelo Paci ◽  
Risto-Pekka Pölönen ◽  
Dario Cori ◽  
Kirsi Penttinen ◽  
Katriina Aalto-Setälä ◽  
...  
Keyword(s):  
In Silico ◽  
Calcium Handling ◽  
In Silico Model ◽  
Automatic Optimization ◽  
Human Ipsc

Development of an in silico model to evaluate in vivo chromosome damaging potential of chemicals

2018 ◽  
Vol 295 ◽  
pp. S98
Author(s):  
M. Van Bossuyt ◽  
G. Raitano ◽  
E. Van Hoeck ◽  
V. Rogiers ◽  
E. Benfenati ◽  
...  
Keyword(s):  
In Silico ◽  
In Silico Model
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