Delivery efficiencies of theranostic nanoparticles (NPs) based on passive tumor targeting strongly depend either on their blood circulation time or on appropriate modulations of the tumor microenvironment. Therefore, predicting the NP delivery efficiency before and after a tumor microenvironment modulation is highly desirable. Here, we present a new erythrocyte membranecamouflaged magnetofluorescent nanocarrier (MMFn) with long blood circulation time (92 h) and high delivery efficiency (10% ID for Ehrlich murine tumor model). MMFns owe their magnetic and fluorescent properties to the incorporation of manganese ferrite nanoparticles (MnFe 2 O 4 NPs) and IR-780 (a lipophilic indocyanine fluorescent dye), respectively, to their erythrocyte membrane-derived camouflage. MMFn composition, morphology, and size, as well as optical absorption, zeta potential, and fluorescent, magnetic, and magnetothermal properties, are thoroughly examined in vitro. We then present an analytical pharmacokinetic (PK) model capable of predicting the delivery efficiency (DE) and the time of peak tumor uptake (t max ), as well as changes in DE and t max due to modulations of the tumor microenvironment, for potentially any nanocarrier. Experimental PK data sets (blood and tumor amounts of MMFns) are simultaneously fit to the model equations using the PK modeling software Monolix. We then validate our model analytical solutions with the numerical solutions provided by Monolix. We also demonstrate how our a priori nonmechanistic model for passive targeting relates to a previously reported mechanistic model for active targeting. All in vivo PK studies, as well as in vivo and ex vivo biodistribution studies, were conducted using two noninvasive techniques, namely, fluorescence molecular tomography (FMT) and alternating current biosusceptometry (ACB). Finally, histopathology corroborates our PK and biodistribution results.

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Aim: This paper aims to investigate a doxorubicin (DOX) chronic kidney disease rat model using magnetic nanoparticles (MNPs) associated with the alternate current biosusceptometry (ACB) to analyze its different perfusion profiles in both healthy and DOX-injured kidneys. Materials & methods: We used the ACB to detect the MNP kidney perfusion in vivo. Furthermore, we performed biochemical and histological analyses, which sustained results obtained from the ACB system. We also studied the MNP biodistribution. Results: We found that DOX kidney injury alters the MNPs' kidney perfusion. These changes became more intense as the disease progressed. Moreover, DOX has an important effect on MNP biodistribution as the disease evolved. Conclusion: This study provides new applications of MNPs in nephrology, instrumentation, pharmacology, physiology and nanomedicine.

Once administered in an organism, the physiological parameters of magnetic nanoparticles (MNPs) must be addressed, as well as their possible interactions and retention and elimination profiles. Alternating current biosusceptometry (ACB) is a biomagnetic detection system used to detect and quantify MNPs. The aims of this study were to evaluate the biodistribution and clearance of MNPs profiles through long-time in vivo analysis and determine the elimination time carried out by the association between the ACB system and MnFe2O4 nanoparticles. The liver, lung, spleen, kidneys, and heart and a blood sample were collected for biodistribution analysis and, for elimination analysis, and over 60 days. During the period analyzed, the animal’s feces were also collectedd. It was possible to notice a higher uptake by the liver and the spleen due to their characteristics of retention and uptake. In 60 days, we observed an absence of MNPs in the spleen and a significant decay in the liver. We also determined the MNPs’ half-life through the liver and the spleen elimination. The data indicated a concentration decay profile over the 60 days, which suggests that, in addition to elimination via feces, there is an endogenous mechanism of metabolization or possible agglomeration of MNPs, resulting in loss of ACB signal intensity.

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