Zinc oxide nanoparticle-reinforced sodium alginate/hydroxyapatite scaffolds for osteoporosis treatment in fragility fracture patients: Development and characterization using artificial neural networks (ANNs) modeling

Articles in Press

Document Type : Original Article

Authors

Department of Orthopedics, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, Jiangsu, China

10.22038/ijbms.2024.78958.17077

Abstract

Objective(s): Osteoporosis is a significant public health concern due to its association with fragility fractures. Despite experiencing such fractures, many patients remain at high risk of future fractures due to inadequate management and treatment of their underlying osteoporosis. This research presents a comprehensive intervention to enhance osteoporosis management in patients with fragility fractures. The intervention involves a thorough personalized assessment of fracture risk using clinical factors and bone density testing, followed by customized treatment based on the individual’s fracture risk level. It also addresses non-compliance through patient education, counseling, reminders, and improved care coordination among acute, primary, and specialty providers. 
Materials and Methods: The aim is to create and characterize sodium alginate/hydroxyapatite (HA) scaffolds reinforced with zinc oxide nanoparticles (ZnO-NP) for bone tissue engineering. Freeze-drying was used to produce scaffolds with 0–15% ZnO-NP. Analyses confirmed the composite structure, uniform ZnO-NP distribution, and decreasing pore size with higher ZnO-NP content. Mechanical testing showed increased compressive strength with greater ZnO-NP. 
Results: The scaffolds exhibited over 70% porosity, neutral pH, and increased apatite deposition and bioactivity with higher ZnO-NP. They also demonstrated decreased swelling and strong antibacterial activity against Escherichia coli and Staphylococcus aureus, making them a promising candidate for bone regeneration. 
Conclusion: Additionally, the researchers used an artificial neural network (ANN) to better understand the relationships between various scaffold properties, and the ANN-based predictions showed that changes in pore size and porosity affect the other properties, with acceptable error compared to experimental results.

Keywords

Main Subjects

References

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Iranian Journal of Basic Medical Sciences

Articles in Press, Accepted Manuscript
Available Online from 27 August 2024

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