Application of intelligent neural network method for prediction of mechanical behavior of wire-rope scaffold in tissue engineering

Abstract

In tissue engineering, proper mechanical property is one of the key subjects for modeling tendon and ligament scaffolds. In this research, attempts were made to determine the factors of structural parameters of wire-rope silk scaffolds by using the intelligent neural network method to find optimum mechanical behavior for tendon and ligament regeneration. Experimental design of wire-rope scaffolds was made according to Taguchi orthogonal method. The input structural parameters were the number of filament and twist in each layer in four levels wire-rope and output was determined by an index that was defined according to mechanical properties of anterior cruciate ligament for young age group. Finally, a back-propagation neural network with a high accuracy was designed to predict the mechanical properties of wire-rope tendon and ligament scaffold and according to sensitivity analysis, the number of filaments and twist in outer layers is less important than other input parameters. Finally, a multiple linear regression, a most widely used statistical method, developed from the data.

Evaluation of structural and mechanical properties of electrospun nano-micro hybrid of poly hydroxybutyrate-chitosan/silk scaffold for cartilage tissue engineering

“…First of all to degumming and removing sericin due to prevent the negative effects on chondrocytes, silk was treated at 25% weight sodium carbonate solutions for 30 min at a temperature of 90°C. [17] Knitted structure was fabricated in Passap Duomatic machine by 5 and 10 gauge needles. Rib 1 × 1 structure with low density was selected as the basic knitted substrate.…”

“…The results demonstrated an increasing in mechanical properties and no cytotoxic effects and a good level of cytocompatibility. [17] Based on these studies, silk could be an appropriate option to fabricate microscale part of a nano-micro hybrid structure.…”

Nano/Micro Hybrid Scaffold of PCL or P3HB Nanofibers Combined with Silk Fibroin for Tendon and Ligament Tissue Engineering

“…Finally, by changing the number of twisted SF yarns in the hybrid structure and selecting the appropriate one relative to individual native tissues, the mechanical properties of the final structure can be adapted to different natural tendon and ligament tissues properties. Therefore, by coating the SF yarns with electrospun nanofibers, the mechanical properties can be made more similar to those of native tissues (29).…”

“…Because of the mechanical properties similar to textile structures, such as the viscoelastic and nonlinear behavior, many fabrication textile techniques have been developed to design different scaffolds (26). In particular, textile-based scaffolds like braided (27), woven (28), wire-rope (29) or knitted (30) structures have been widely used in the last decade.…”

Developing a hybrid artificial neural network-genetic algorithm model to predict resilient modulus of polypropylene/polyester fiber-reinforced asphalt concrete

“…Over the last few decades, a new approach for modeling was presented known as artificial neural network (ANN) and used widely for prediction. There are many published works about using ANN in different areas of textile engineering (Alibi, Fayala, Bhouri, Jemni, & Zeng, 2013;Almetwally, Idrees, & Hebeish, 2014;Çelik, Dülger, & Topalbekiroğlu, 2013;Minapoor, Ajeli, Hasani, & Shanbeh, 2012;Naghashzargar, Semnani, Karbasi, & Nekoee, 2013;Semnani & Vadood, 2010;Shabaridharan & Das, 2013a, 2013bVadood, Semnani, & Morshed, 2011). However, the ANN model contains various parameters directly affect the prediction accuracy and should be optimized to obtain the highest prediction accuracy.…”