PEGylation of superparamagnetic iron oxide nanoparticle for drug delivery applications with decreased toxicity: an in vivo study
Source abstract
Abstract
Superparamagnetic iron oxide nanoparticles (SPIONs) are evolving as a mainstay across various applications in the field of Science and Technology. SPIONs have enticed attention on the grounds of their unique physicochemical properties as well as potential applications in magnetic hyperthermia, immunoassays, as a contrast agent in magnetic resonance imaging and targeted drug delivery among others. Toward this goal, we synthesized SPIONs by chemical co-precipitation and PEGylated it. PEGylated SPIONs (PS) were studied for its detailed in vivo toxicity profile, in view of further surface engineering for its clinical applications. The intravenous LD50(14) of the PS was ascertained as 508.16 ± 41.52 mg/kg b wt. Histopathology of the vital organs of the animals injected with acute toxic doses showed pathological changes in spleen, lung, liver, and kidney. Accumulation of SPION was found in the aforementioned organs as confirmed by Prussian blue staining. Further, 1/10th dose of LD50(14) of PS and the Bare SPION (BS) was used to analyze a detailed toxicity profile, including genotoxicity (micronuclei formation and chromosomal aberration assays), organ-specific toxicity (a detailed serum biochemical analysis), and also determination of oxidative stress. The results of toxicity profile indicated no significant toxicity due to systemic exposure of PS. Atomic absorption spectroscopy (AAS) analysis confirmed the accumulation of SPION majorly in lungs, liver spleen, and kidneys. The present study thus indicated an optimal dose of PS which could be used for surface modification for targeted drug delivery applications with least toxicity.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Nanoparticle-Based Drug Delivery · Iron oxide chemistry and applications · Nanoparticles: synthesis and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (80)
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