Folate-Targeted Curcumin-Loaded Niosomes for Site-Specific Delivery in Breast Cancer Treatment: In Silico and In Vitro Study

As the most common cancer in women, efforts have been made to develop novel nanomedicine-based therapeutics for breast cancer. In the present study, the in silico curcumin (Cur) properties were investigated, and we found some important drawbacks of Cur. To enhance cancer therapeutics of Cur, three different nonionic surfactants (span 20, 60, and 80) were used to prepare various Cur-loaded niosomes (Nio-Cur). Then, fabricated Nio-Cur were decorated with folic acid (FA) and polyethylene glycol (PEG) for breast cancer suppression. For PEG-FA@Nio-Cur, the gene expression levels of Bax and p53 were higher compared to free drug and Nio-Cur. With PEG-FA-decorated Nio-Cur, levels of Bcl2 were lower than the free drug and Nio-Cur. When MCF7 and 4T1 cell uptake tests of PEG-FA@Nio-Cur and Nio-Cur were investigated, the results showed that the PEG-FA-modified niosomes exhibited the most preponderant endocytosis. In vitro experiments demonstrate that PEG-FA@Nio-Cur is a promising strategy for the delivery of Cur in breast cancer therapy. Breast cancer cells absorbed the prepared nanoformulations and exhibited sustained drug release characteristics.     

Investigation and Modeling of Temperature Dependence Recovery Behavior of Shape‐Memory Crosslinked Polyethylene

Shape memory was induced in crosslinked low‐density polyethylene by a heating‐stretching‐cooling cycle. The effect of crosslink content on thermal properties and temperature dependence recovery behavior was studied experimentally. The importance of stretching temperature and crosslink content on recovery behavior could be reasonably explained by the observed changes in the thermal properties which were attributed to the differences in crystalline structures and mechanism of crystal formation during the heating‐stretching‐cooling process. A mechanical model was developed to describe qualitatively and quantitatively the temperature dependence recovery behavior of the prepared shape memory crosslinked polyethylene at nonisothermal state under various conditions by driving constitutive equations using a set of model constants. These model constants were determined with the help of a set of optimization codes using a genetic algorithm method. By choosing a suitable set of model constants one can describe with high accuracy the temperature dependence recovery behavior of any shape memory polymer.