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The purpose of an experimental design is to improve the productivity of experimentation. It is an efficient procedure for planning experiments, so the data obtained can be analyzed to yield a valid and objective conclusion. This approach has been used as an important tool in the optimization of different analytical approaches. A D-optimal experimental design was used here, for the first time, to optimize the experimental conditions for the detection of reactive oxygen species (ROS) produced by human blood from healthy donors, a biological matrix that better resembles the physiologic environment, following stimulation by a potent inflammatory mediator, phorbol-12-myristate-13-acetate (PMA). For that purpose, different fluorescent probes were used, as 2',7'-dichlorodihydrofluorescein diacetate (DCFH-DA), 2-[6-(4'-amino)-phenoxy-3H-xanthen-3-on-9-yl] benzoic acid (APF), and 10-acetyl-3,7-dihydroxyphenoxazine (amplex red). The variables tested were the human blood dilution, and the fluorescent probe and PMA concentrations. The experiments were evaluated using the Response Surface Methodology and the method was validated using specific compounds. This model allowed the search for optimal conditions for a set of responses simultaneously, enabling, from a small number of experiments, the evaluation of the interaction between the variables under study. Moreover, a cellular model was implemented and optimized to detect the production of ROS using a yet nonexplored matrix, which is human blood.
Pubmed ID: 30733852
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Statistical analysis software that combines scientific graphing, comprehensive curve fitting (nonlinear regression), understandable statistics, and data organization. Designed for biological research applications in pharmacology, physiology, and other biological fields for data analysis, hypothesis testing, and modeling.
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