Water-compatible core–shell Ag@SiO2 molecularly imprinted particles for the controlled release of tetracycline
Source abstract
Abstract
Silver nanoparticles coated with molecularly imprinted silica shell (Ag@SiO2-MIP) were synthesized, and their properties for the molecular recognition and the controlled delivery of tetracycline (TC) in aqueous environments were investigated. In this study, a synthesis protocol based in the entrapping of TC into silica particles with a core of silver nanoparticles (AgNPs) was developed. These particles were examined by transmission electron microscopy, scanning electron microscopy, energy dispersion spectroscopy, Fourier transform infrared spectroscopy, zeta potential and UV visible, and fluorescence spectroscopy. The as-prepared Ag@SiO2-MIP particles were evaluated for selective recognition of TC. The imprinted particles have higher TC binding ability as compared with corresponding non-imprinted particles and have high selectivity toward TC over other competitive antibiotics. The studies of release profiles of TC-loaded Ag@SiO2-MIP particles in aqueous solutions demonstrated a strong dependence with pH and temperature. The kinetic delivery of TC showed two types of release which includes initial burst release (low-affinity sites) and slow release (high-affinity sites). The amount of TC release from Ag@SiO2-MIP particles was lower at pH 2 (simulated gastric fluid) to pH 8 (simulated colonic fluid), which makes the proposed system a good candidate for TC oral administration. The excellent biocompatibility of the silica materials, the known bactericidal properties of the AgNPs, and the drug release results render the possibility of designing a new generation of TC delivery systems for controlled release.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Analytical chemistry methods development · Antibiotics Pharmacokinetics and Efficacy · Pharmaceutical and Antibiotic Environmental Impacts
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (46)
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