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18. A Review on Advances and Challenges in Core‐Shell Scaffolds for Bone Tissue Engineering: Design, Fabrication, and Clinical Translation.

Author

Ang, Bee Chin, Nam, Hui Yin, Abdullah, Muhammad Faiq, Muhammad, Farina, and Truong, Yen Bach

Subjects
*TISSUE scaffolds, *TISSUE engineering, *BONE growth, *ENGINEERING design, *ELECTROSPINNING
Abstract

This review explores core‐shell scaffolds in bone tissue engineering, highlighting their osteoconductive and osteoinductive properties critical for bone growth and regeneration. Key design factors include material selection, porosity, mechanical strength, biodegradation kinetics, and bioactivity. Electrospun core‐shell nanofibrous scaffolds demonstrate potential in delivering therapeutic agents and enhancing bone regeneration. Critical characterization techniques include structural, surface, chemical composition, mechanical, and degradation analyses. Scaling up production poses challenges, addressed by innovative electrospinning techniques. Future research focuses on regulatory and commercial considerations, while exploring advanced materials and fabrication methods to optimize scaffold performance for improved clinical outcomes. [ABSTRACT FROM AUTHOR]

Published
2024
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20. Bioresorbable and degradable behaviors of PGA: Current state and future prospects

Author

Low, Yan Jie, Andriyana, Andri, Ang, Bee Chin, and Abidin, Nor Ishida Zainal

Subjects
Tissue engineering -- Research, Materials research, Solubility -- Analysis, Biodegradation -- Analysis, Polymers -- Composition -- Structure -- Properties, Engineering and manufacturing industries, Science and technology
Abstract

Polyglycolic acid (PGA) is a class of semicrystalline, bioresorbable polymers that have been widely used in a number of applications. No other bioresorbable materials can fully replace PGA in tissue engineering. Understanding degradation mechanisms in PGA is important for improving the efficiency and effectiveness in various fields including implantation. This review begins with a discussion on terminology of polymer degradation and hydrolytic degradation mechanism with a delineative model. This review also focus on previous degradation studies taking advantage of its fast-degrading behavior and the mechanism behind hexafluoroisopropanol (HFIP) being the sole solvent for PGA. Finally, the merits of PGA are discussed with many potential future applications along with their associated challenges. KEYWORDS bioresorbable polymer, degradation mechanism, hydrolytic degradation, polyglycolic acid, solubility in HFIP, tissue engineering, 1 | INTRODUCTION In this era of advancement of technology and research, engineers and scientists have been looking for a way to push the development of technology and people's health [...]

Published
2020
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40. Prediction, modeling and characterization of surface texturing by sulfuric etchant on non-toxic titanium bio-material using artificial neural networks and fuzzy logic systems

Author

Khanlou Hossein Mohammad, Ang Bee Chin, and Barzani Mohsen Marani

Subjects
acid etching, artificial neural networks, characterization, fuzzy logic, prediction, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

Multilayer feed forward network, radial biased function network, generalized regression neural network and adaptive network-based fuzzy inference system (ANFIS) were used to predict the surface roughness of Ti-13Zr-13Nb alloy in etching sulfuric acid. Subsequent processes – polishing, sandblasting and acid etching or SLA – were employed to modify the surface. Alumina particles for surface blasting and concentrated sulfuric acid for acid etching were utilized in this experiment. This was performed for three different periods of time (10, 20 and 30 s) and temperature (25, 45 and 60°C). Correspondingly, the Ti-13Zr-13Nb surfaces were evaluated using a field emission scanning electron microscope for roughening and a contact mode profilometer for the average surface roughness (Ra) (nm). Different configurations of neural networks and ANFIS approaches are examined in order to minimize the root mean square error. Consequently, the ANFIS model is selected by dividing the time and temperature into one and three spaces, respectively, using the Gaussian-shaped membership function. A mathematical model is attained from the best approach in terms of root mean square error to realize the relation of the surface roughness of Ti-13Zr-13Nb alloy in etching sulfuric acid and time and temperature as the effective parameters.

Published
2016
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