EBSCO Logo
Connecting you to content on EBSCOhost
Results
Title

Gamma radiation preparation of chitosan nanoparticles for controlled delivery of memantine.

Authors

Radwan, Rasha R; Abdel Ghaffar, Ashraf M; Ali, Hussein E

Abstract

The purpose of the current study is to prepare chitosan nanoparticles by gamma radiation as a new brain delivery system for memantine to improve its therapeutic efficiency. Fourier-transform infrared analysis of chitosan nanoparticles showed the characteristic peaks of chitosan and the reduction of particle size induced by irradiation at doses 10, 20 and 30 kGy. The solubility of chitosan nanoparticles was tested using different solvents and exhibited good solubility in both water and 1% acetic acid than other tested solvents at 80°C. Different formulations containing memantine - loaded chitosan nanoparticles were evaluated for brain targeting on aluminum-induced Alzheimer's disease in rats. Memory deficit was evaluated using the Morris water maze test. The levels of amyloid-β peptide, tumour necrosis factor alpha, interleukin-1β and interleukin-6 in brain tissues as well as the serum level of brain-derived neurotrophic factor were assayed. Data demonstrated that memantine - loaded chitosan nanoparticles 1:1 transported memantine effectively into the brain compared to free memantine as evidenced by better behaviour performance and biochemical amelioration and confirmed by histopathological examination in Alzheimer's disease rats. Interestingly, the therapeutic effect of memantine - loaded chitosan nanoparticles 1:1 was superior to memantine - loaded chitosan nanoparticles 1:2 and memantine - loaded chitosan nanoparticles 2:1. Based on these findings, it is reasonable to suggest that memantine - loaded chitosan nanoparticles 1:1 could be a promising approach for Alzheimer's disease.

Subjects

BRAIN-derived neurotrophic factor; CHITOSAN; SIZE reduction of materials; AMYLOID beta-protein; NANOPARTICLES; MAZE tests; ALZHEIMER'S disease; GAMMA rays

Publication

Journal of Biomaterials Applications, 2020, Vol 34, Issue 8, p1150

ISSN

0885-3282

Publication type

Academic Journal

DOI

10.1177/0885328219890071

EBSCO Connect | Privacy policy | Terms of use | Copyright | Manage my cookies
Journals | Subjects | Sitemap
© 2025 EBSCO Industries, Inc. All rights reserved