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Recent advances in nanomedicine have led to the introduction and subsequent establishment of nanoparticles in cancer treatment and diagnosis. Nonetheless, their application is still hindered by a series of challenges related to their biocompatibility and biodistribution. In this paper, we take inspiration from the recently produced and widely spread COVID vaccines, based on the combinational use of ionizable solid lipid nanoparticles, cholesterol, PEGylated lipids, and neutral lipids able to incorporate mRNA fragments. Here, we focus on the implementation of a lipidic formulation meant to be used as a smart coating of solid-state nanoparticles. The composition of this formulation is finely tuned to ensure efficient and stable shielding of the cargo. The resulting shell is a highly customized tool that enables the possibility of further functionalizations with targeting agents, peptides, antibodies, and fluorescent moieties for future in vitro and in vivo tests and validations. Finally, as a proof of concept, zinc oxide nanoparticles doped with iron and successively coated with this lipidic formulation are tested in a pancreatic cancer cell line, BxPC-3. The results show an astonishing increase in cell viability with respect to the same uncoated nanoparticles. The preliminary results presented here pave the way towards many different therapeutic approaches based on the massive presence of highly biostable and well-tolerated nanoparticles in tumor tissues, such as sonodynamic therapy, photodynamic therapy, hyperthermia, and diagnosis by means of magnetic resonance imaging. [ABSTRACT FROM AUTHOR]

The purpose of this paper was to detect and separate the cluster intensity provided by Iron oxide nanoparticles (IO-NPs), in the MRI images, to investigate the drug delivery effectiveness. IO-NPs were attached to the macrophages and inserted into the eye of the inflamed mouse's calf. The low resolution of MRI and the tiny dimension of the IO-NPs made the situation challenging. IO-NPs serve as a marker, due to their strong intensity in the MRI, enabling us to follow the track of the macrophages. An image processing procedure was developed to estimate the position and the amount of IO-NPs spreading inside the inflamed mouse leg. A fuzzy Clustering algorithm was adopted to select the region of interest (ROI). A 3D model of the femoral region was used for the detection and then the extraction IO-NPs in the MRI images. The results achieved prove the effectiveness of the proposed method to improve the control process of targeted drug delivered. It helps in optimizing the treatment and opens a promising novel research axis for nanomedicine applications. [ABSTRACT FROM AUTHOR]

In recent years, many promising nanotechnological approaches to biomedical research have been developed in order to increase implementation of regenerative medicine and tissue engineering in clinical practice. In the meantime, the use of nanomaterials for the regeneration of diseased or injured tissues is considered advantageous in most areas of medicine. In particular, for the treatment of cardiovascular, osteochondral and neurological defects, but also for the recovery of functions of other organs such as kidney, liver, pancreas, bladder, urethra and for wound healing, nanomaterials are increasingly being developed that serve as scaffolds, mimic the extracellular matrix and promote adhesion or differentiation of cells. This review focuses on the latest developments in regenerative medicine, in which iron oxide nanoparticles (IONPs) play a crucial role for tissue engineering and cell therapy. IONPs are not only enabling the use of non-invasive observation methods to monitor the therapy, but can also accelerate and enhance regeneration, either thanks to their inherent magnetic properties or by functionalization with bioactive or therapeutic compounds, such as drugs, enzymes and growth factors. In addition, the presence of magnetic fields can direct IONP-labeled cells specifically to the site of action or induce cell differentiation into a specific cell type through mechanotransduction. [ABSTRACT FROM AUTHOR]