Superparamagnetic iron oxide nanoparticles (SPIONs) are commonly used in magnetic resonance imaging (MRI), but their fast phagocytosis makes them less than ideal for this application. To circumvent the lymphocyte-macrophage system, we encapsulated SPIONs into red blood cells (RBCs). For loading, the RBC's membrane was opened by swelling under hypoosmotic conditions and subsequently resealed. In this work, we demonstrate that SPIONs can be loaded into RBCs in a concentration sufficient to obtain strong contrast enhancement in MRI.
Magnetic resonance was used to investigate the kinetic disposition of magnetite nanoparticles (9.4 nm core diameter) from the blood circulation after intravenous injection of magnetite-based dextran-coated magnetic fluid in female Swiss mice. In the first 60 min the time-decay of the nanoparticle concentration in the blood circulation follows the one-exponential (one-compartment) model with a half-life of (6.9 +/- 0.7) min. The X-band spectra show a broad single line at g approximately 2, typical of nanomagnetic particles suspended in a nonmagnetic matrix. The resonance field shifts toward higher values as the particle concentration reduces, following two distinct regimes. At the higher concentration regime (above 10(14) cm(-3)) the particle-particle interaction responds for the nonlinear behavior, while at the lower concentration regime (below 10(14) cm(-3)) the particle-particle interaction is ruled out and the system recovers the linearity due to the demagnetizing field effect alone.
We present a new method for the determination of the magnetic moment distribution ρ(µ) of ferrofluid particles from the magnetization curve measured on diluted ferrofluid samples in the liquid state. The method employs the solution of the standard integral equation describing the magnetization of a non-interacting particle system in the given external field as a convolution of the Langevin function with the distribution of particle moments. No a priori assumptions concerning the shape of the corresponding distribution are required. We present the reconstruction results obtained both for the computer simulated magnetization curves and for real experimental data. In the latter case we compare the distributions found using our algorithm with those calculated from the particle size distributions obtained via the electron microscopy images of the ferrofluid particles.
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