2 resultados para Model-driven design
em Repositório da Produção Científica e Intelectual da Unicamp
Resumo:
The objective of the study was to illustrate the applicability and significance of the novel Lewis urothelial cancer model compared to the classic Fisher 344. Fischer 344 and Lewis females rats, 7 weeks old, were intravesical instilled N-methyl-N-nitrosourea 1.5 mg/kg every other week for a total of four doses. After 15 weeks, animals were sacrificed and bladders analyzed: histopathology (tumor grade and stage), immunohistochemistry (apoptotic and proliferative indices) and blotting (Toll-like receptor 2-TLR2, Uroplakin III-UP III and C-Myc). Control groups received placebo. There were macroscopic neoplastic lesions in 20 % of Lewis strain and 70 % of Fischer 344 strain. Lewis showed hyperplasia in 50 % of animals, normal bladders in 50 %. All Fischer 344 had lesions, 20 % papillary hyperplasia, 30 % dysplasia, 40 % neoplasia and 10 % squamous metaplasia. Proliferative and apoptotic indices were significantly lower in the Lewis strain (p < 0.01). The TLR2 and UP III protein levels were significantly higher in Lewis compared to Fischer 344 strain (70.8 and 46.5 % vs. 49.5 and 16.9 %, respectively). In contrast, C-Myc protein levels were significantly higher in Fischer 344 (22.5 %) compared to Lewis strain (13.7 %). The innovative Lewis carcinogen resistance urothelial model represents a new strategy for translational research. Preservation of TLR2 and UP III defense mechanisms might drive diverse urothelial phenotypes during carcinogenesis in differently susceptible individuals.
Resumo:
Split-plot design (SPD) and near-infrared chemical imaging were used to study the homogeneity of the drug paracetamol loaded in films and prepared from mixtures of the biocompatible polymers hydroxypropyl methylcellulose, polyvinylpyrrolidone, and polyethyleneglycol. The study was split into two parts: a partial least-squares (PLS) model was developed for a pixel-to-pixel quantification of the drug loaded into films. Afterwards, a SPD was developed to study the influence of the polymeric composition of films and the two process conditions related to their preparation (percentage of the drug in the formulations and curing temperature) on the homogeneity of the drug dispersed in the polymeric matrix. Chemical images of each formulation of the SPD were obtained by pixel-to-pixel predictions of the drug using the PLS model of the first part, and macropixel analyses were performed for each image to obtain the y-responses (homogeneity parameter). The design was modeled using PLS regression, allowing only the most relevant factors to remain in the final model. The interpretation of the SPD was enhanced by utilizing the orthogonal PLS algorithm, where the y-orthogonal variations in the design were separated from the y-correlated variation.