journal article·2013-05Open access

The novel albumin–chitosan core–shell nanoparticles for gene delivery: preparation, optimization and cell uptake investigation

Mahdi Karimi, Pinar Avci, Rezvan Mobasseri, Michael R. Hamblin, Hossein Naderi-Manesh

Journal of Nanoparticle Research· Volume 15· Issue 5

Abstract

Natural polymers and proteins such as chitosan (CS) and albumin (Alb) have recently attracted much attention both in drug delivery and gene delivery. The underlying rationale is their unique properties such as biodegradability, biocompatibility and controlled release. This study aimed to prepare novel albumin-chitosan-DNA (Alb-CS-DNA) core-shell nanoparticles as a plasmid delivery system and find the best conditions for their preparation. Phase separation method and ionic interaction were used for preparation of Alb nanoparticles and Alb-CS-DNA core-shell nanoparticles, respectively. The effects of three important independent variables (1) CS/Alb mass ratio, (2) the ratios of moles of the amine groups of cationic polymers to those of the phosphate groups of DNA (N/P ratio), and (3) Alb concentration, on the nanoparticle size and loading efficiency of the plasmid were investigated and optimized through Box-Behnken design of response surface methodology (RSM). The optimum conditions were found to be CS/Alb mass ratio = 3, N/P ratio = 8.24 and Alb concentration = 0.1 mg/mL. The most critical factors for the size of nanoparticles and loading efficiency were Alb concentration and N/P ratio. The optimized nanoparticles had an average size of 176 ± 3.4 nm and loading efficiency of 80 ± 3.9 %. Cytotoxicity experiments demonstrated that the prepared nanoparticles were not toxic. The high cellular uptake of nanoparticles (~85 %) was shown by flow cytometry and fluorescent microscopy.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: RNA Interference and Gene Delivery · Advanced biosensing and bioanalysis techniques · Advanced Drug Delivery Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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