The objective of the current research was to develop the posaconazole (PCZ) loaded NS into the carbopol 934 polymeric gel for prolonged drug release and improved topical delivery; seven different nanosponge formulations of PCZ were formulated using the emulsion solvent diffusion method using various amounts of polymer (ethylcellulose, EC). The aqueous and dispersed phases were prepared using polyvinyl alcohol (PVA) and dichloromethane. The prepared nanosponges (NS) were studied for particle size, structural appearance, and in vitro drug release. Furthermore, the selected formula was formulated as hydrogel and was evaluated for physical characteristics, drug content, and in-vitro drug release. Morphological studies revealed irregular shapes, rough and porous surfaces of nanosponges. The particle sizes were in the range of 201.6 ± 29.9 to 4904.7 ± 540.4 nm. In-vitro release studies revealed the sustained release pattern of the drug-loaded nanosponges. The lyophilized PCZ-NS formula had a 12-fold increase in saturation solubility over PCZ pure powder. Fourier transform infrared spectroscopy (FTIR) of the selected formula showed no significant shifts in the positions of wavenumbers compared to that of pure drug. This indicates there is no interaction between drug and excipients used. PCZ NS loaded hydrogel significantly improved the dissolution rate, which was significantly higher (p is less than 0.05) than that of pure PCZ hydrogel.
Titanium dioxide nanorods have been prepared by sol-gel template
method. The structural and surface morphology of the TiO2 nanorods was
investigated by X-ray diffraction (XRD) and atomic force microscopy
(AFM), it was found that the nanorods produced were anatase TiO2 phase.
The photocatalytic activity of the TiO2 nanorods was evaluated by the
photo degradation of methyl orange (MO). The relatively higher
degradation efficiency for MO (D%=78.2) was obtained after 6h of exposed
to UV irradiation.
Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate
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