Fluconazole-loaded PLGA microspheres were prepared by the spray-drying process. The influence of some process parameters on the physical characteristics of the microspheres was evaluated. Neither type nor polymer concentration influenced significantly the mean diameter of the microspheres, their size distribution and encapsulation efficiency of the drug. However, the drug loading greatly affected their size and the physical state in which fluconazole can exist in the matrix of the carriers, and, thus, affected the release rate of the drug. Results obtained by differential thermal analysis and X-ray powder diffraction revealed that at low nominal drug loading, fluconazole was incorporated in an amorphous state or in a molecular dispersion in the matrix of the microspheres and at high nominal drug loading part of the drug was in a crystalline form. Release profiles of fluconazole from the microspheres displayed a biphasic shape. The duration and extent of each phase were affected mainly by polymer nature, drug loading and physical state in which fluconazole existed in the polymeric matrix.
Utilizing chemiresistive gas sensors for volatile organic compound (VOC) detection has been a growing area of investigation in the last decade. VOCs have been extensively studied as potential biomarkers for biomedical applications as they are byproducts of metabolic pathways which are dysregulated by disease. Therefore, sensor arrays have been fabricated in previous studies to detect VOC biomarkers. In the process of testing these sensors, it is highly advantageous to quantify the concentration of the VOC biomarkers with high accuracy to diagnose the disease with high sensitivity and specificity. To investigate, analyze, and understand the relation between the concentrations of the VOC to the sensor resistance response, Gaussian Process (GP) models were implemented to predict the behavior of the data with respect to the resistance when the sensor is exposed to a range of concentrations of VOCs. Additionally, the relation between the concentration and resistance of the sensor was studied to predict the concentration of the VOC when a resistance is obtained. Monte Carlo Simulation Sampling from the GP model was utilized to generate data to further understand the trend. The results demonstrated that the relation between the concentration and resistance is linear. The model was tested with sampling data and its accuracy was evaluated.
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