An electrochemical sensing platform was fabricated based on composition of poly(sodium 4-styrenesulfonate) (PSS), graphene (GN) and WO nanorods on glassy carbon electrode (GCE). The PSS-GN/WO nanocomposite significantly increased the oxidative activity of puerarin due to the individual merit and mutual effect of PSS-GN and WO nanorods which improved the performance of the electrochemical sensor with high sensitivity. Cyclic voltammetry (CV) and linear sweep voltammetry (LSV) measurements were used for the detection of puerarin.
View Article and Find Full Text PDFMultidrug resistance (MDR) has been a major obstacle to tumor chemotherapy. Pluronic unimers have been reported to be promising copolymers to reverse MDR, and the intracellular delivery of Pluronic unimers is a problem worth thinking. To exert the excellent reversal effect of Pluronic unimers, DOX-loaded G4.
View Article and Find Full Text PDFThis research focused on optimizing the preparations of pDNA-loaded calcium phosphate (CaP) nanoparticles by employing a 3-factor, 3-level Box-Behnken design. Results indicated that a Ca/P ratio of 189.56, pH of 7.
View Article and Find Full Text PDFIn this study, the CaP/pDNA nanoparticles were prepared using Triton X-100/Butanol/Cyclohexane/Water reverse microemulsion system. Optimization of preparation conditions was based on evaluation of particle size by Box-Behnken design method. The particle sizes of the optimized CaP/pDNA nanoparticles were found to be 60.
View Article and Find Full Text PDFOrganic metal complexes as a type of hybrid materials have been used for gene delivery. In the present study, a metal organic complex of zoledronate-calcium (CaZol) was prepared for transporting pDNA. Then, the effects of different molar ratios of Ca to Zol (Ca/Zol) on the formulation characteristics were investigated.
View Article and Find Full Text PDFComput Math Methods Med
March 2017
Segmentation of infarcts at hyperacute stage is challenging as they exhibit substantial variability which may even be hard for experts to delineate manually. In this paper, a sparse representation based classification method is explored. For each patient, four volumetric data items including three volumes of diffusion weighted imaging and a computed asymmetry map are employed to extract patch features which are then fed to dictionary learning and classification based on sparse representation.
View Article and Find Full Text PDF