with and without L-glutathione reduced (GSH) and dithiothreitol (DTT) are also shown. Size distribution curves of RRNPs and nRR-NPs nanoparticles incubated at 37☌ (30 min) in PBS and under different in vitro reducing conditions i.e. Both RRNPs and nRR-NPs had D H around 120 nm, low size PI and high negative zeta potential values thus both nps had similar colloidal properties. Bar graphs show particle size analysis (hydrodynamic diameter (D H) and polydispersity index (PI)) and zeta potential measurements of unloaded nanoparticles in water. Characterisation was carried out using a Zetasizer Nano ZS (Malvern Panalytical) instrument.
For comparison, non redox-responsive nanoparticles PLGA-PEG nanoparticles (nRR-NPs) were also prepared. The RR-NPs were designed to change surface properties when entering tumour microenvironments, which would in turn enhance their cell internalisation and delivery of drug cargo. Redox-responsive PLGA (poly(lactic-co-glycolic acid)) - PEG (polyethylene glycol) nanoparticles (RR-NPs) were synthesised in a study aimed at developing programmable carrier nanoparticles for drug delivery into lung cancer tumour cells. Image 2: Size and zeta potential characterisation of nanoparticles designed for drug deliveryĪn important step in the design of drug carrier nanoparticles is characterisation of particles size and surface change in appropriate environments. Limo, ISAC, Nanoscale and Microscale Research Centre, University of Nottingham The two population sizes were identified with the 22 nm nps being the major/main population by number (%) distribution in the mixture.įigure courtesy of Marion J.
The particle size characterisation was carried out using a DynaPro Plate Reader II (Wyatt) instrument. Large particles scatter much more light than smaller particles, thus the intensity (%) through to number (%) distributions may vary as shown in the exemplar data collected from a mixture of 22 and 200 nm polystyrene nanoparticles. This is especially important where mixed population sizes are present. The figure above illustrates how a comparison of the different distributions gives a better understanding of the sample population.
The distribution of particle sizes obtained from DLS measurements is fundamentally an intensity (%) distribution which can also be converted theoretically into volume (%) and number (%) distribution. Image 1: Size analysis of a mixture of polystyrene nanoparticles
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