In Silico Analysis of Stem Cells Mechanical Stimulations for Mechnoregulation Toward Cardiomyocytes

Ebad, Mahtab; Vahidi, Behrooz

doi:10.5829/ije.2022.35.11b.18

Cited by 5 publications

(3 citation statements)

References 37 publications

(49 reference statements)

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“…Equation 25 is the mathematical model of the blood pressure in the human body. The required boundary condition and the values of the other parameters to solve these equations are; the pressure gradient, ∂ P /∂z = 40-100 mmHg, the Initial blood flow rate value of Q = 1 to 5.4 liter/minute, the Kinematic viscosity of blood, v = 0.035 cm 2 /s and the density of blood ρ = 1.043 to 1.057 g/cm 3 , the radius of a normal artery R0 = 0.1 cm, the constant dynamic viscosity (μ) of 3.71×10-3 Pa s, the blood density, initial value of S0 = 2.0 to 3.0 cm 3 , and Q0 = 16.7 cm 3 /s. For simplicity, the length of the artery model L = 14 cm, L0 = 3-8 cm, The mean Reynold number = 300, the artery systole duration for 0.3 seconds and diastole 0.5 seconds, and the period is 0.2 seconds (40,(44)(45)(46).…”

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confidence: 99%

A Novel Design and Simulation of a Nano Prosthetic Artificial Heart Valves

Mahmood Ali

2024

IJE

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Heart valve replacement is a major health burden and is required by millions of people worldwide, which invites the continuous need to discover and manufacture more effective and permanent artificial replacements. In the present work, unique models of eight artificial heart valves were designed and examined using seven synthetic and nanocomposite materials. The designed valves were examined to determine the best designs and materials in terms of durability, flexibility, and energy consumption, and to improve the biomechanical performance by using the Response Surface Methodology (RSM) and the Design Expert System 13. The highest values of the equivalent stress due to the applied blood pressure on the moving parts on each type of manufactured heart valve occur in valves with three dimensions moving parts, reached in the mitral tri-leaflet valve 14.13 MPa, followed by the tricuspid aortic valve. The equivalent stresses for other types of valves produced with simple surface action were lower than 2 MPa. The strain energy that is expended during the process of diastole and systole was found to be directly proportional to the strength and flexibility of the materials used. The energy consumption rates decrease when using highly elastic materials such as TPE and PSN4. The values of this energy also increase with an increase in the area of the moving parts of the valve, especially when faced with the process of closing blood flow, as with the use of the tricuspid aortic valve (TAV). The highest total deformation resulted in the valve body when using TPU, followed by TPE, nylon, PETG, and PLA, while the lowest deformation rates were observed when using PSN4, which ranged from 5x10 5 to 0.1 mm, followed by SIBSTAR103 nanostructured rubber. The obtained values of stress safety factors were decreased with the complexity of the movement for the moving parts of the valve. The highest rates were recorded when using the tricuspid mitral valve, reaching 2.45 when using the high-strength and flexible PSN4 nanomaterial. It can be concluded that the best materials for manufacturing these four types of valves are the PSN4, followed by SIBSTAR103T, TPU, and TPE. The use of PETG, PLA, and nylon materials is not recommended for the manufacture of any prosthetic heart valves, due to their lack of strength, flexibility, and high brittleness, especially for PETG and PLA materials. It was also noted here that PSN4 is the only material suitable for the manufacture of mitral tri-leaflet and tricuspid mitral valve artificial valves. For other types of valves manufactured with a single leaflet, high safety stress factors were obtained because their movement is simple, flat, and in one direction, where the highest values were observed when testing a single hemispherical leaflet type valve, then the conical caged ball and the caged ball type, respectively.

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confidence: 99%

A Novel Design and Simulation of a Nano Prosthetic Artificial Heart Valves

Mahmood Ali

2024

IJE

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“…This monitoring process is crucial to ensuring the safety of the animals and gathering accurate data for toxicity studies. Considering animal ethics, minimizing the need for animal testing, and reducing the costs and time of toxicity tests, computational assessments are an essential way to bypass in vitro experiments. ,− …”

Section: Introductionmentioning

confidence: 99%

Multi-Endpoint Acute Toxicity Assessment of Organic Compounds Using Large-Scale Machine Learning Modeling

Daghighi,

Casanola-Martin,

Iduoku

et al. 2024

Environ. Sci. Technol.

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In recent years, alternative animal testing methods such as computational and machine learning approaches have become increasingly crucial for toxicity testing. However, the complexity and scarcity of available biomedical data challenge the development of predictive models. Combining nonlinear machine learning together with multicondition descriptors offers a solution for using data from various assays to create a robust model. This work applies multicondition descriptors (MCDs) to develop a QSTR (Quantitative Structure–Toxicity Relationship) model based on a large toxicity data set comprising more than 80,000 compounds and 59 different end points (122,572 data points). The prediction capabilities of developed single-task multi-end point machine learning models as well as a novel data analysis approach with the use of Convolutional Neural Networks (CNN) are discussed. The results show that using MCDs significantly improves the model and using them with CNN-1D yields the best result (R 2 train = 0.93, R 2 ext = 0.70). Several structural features showed a high level of contribution to the toxicity, including van der Waals surface area (VSA), number of nitrogen-containing fragments (nN+), presence of S–P fragments, ionization potential, and presence of C–N fragments. The developed models can be very useful tools to predict the toxicity of various compounds under different conditions, enabling quick toxicity assessment of new compounds.

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“…Given the considerable time and financial investments involved in laboratory methods, along with the challenges of measuring specific parameters, numerical simulations provide an effective way to overcome these obstacles and explore the desired variables [ [11] , [12] , [13] , [14] , [15] , [16] , [17] ]. Computational simulation of blood vessels proves to be a powerful tool for investigating the environmental behavior of the circulatory system relevant to this disease, all in a completely non-invasive manner.…”

Section: Introductionmentioning

confidence: 99%

In silico analysis of embolism in cerebral arteries using fluid-structure interaction method

Talebibarmi,

Vahidi,

Ebad

2024

Heliyon

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In Silico Analysis of Stem Cells Mechanical Stimulations for Mechnoregulation Toward Cardiomyocytes

Cited by 5 publications

References 37 publications

A Novel Design and Simulation of a Nano Prosthetic Artificial Heart Valves

A Novel Design and Simulation of a Nano Prosthetic Artificial Heart Valves

Multi-Endpoint Acute Toxicity Assessment of Organic Compounds Using Large-Scale Machine Learning Modeling

In silico analysis of embolism in cerebral arteries using fluid-structure interaction method

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