Optimization of Experimental Settings for the Assessment of Reactive Oxygen Species Production by Human Blood

• Tipo: Artigo em Revista Científica Internacional
• Data: 2019

Autores

Soares, T (Autor) Outra; Rodrigues, D (Autor) Outra; Sarraguca, M (Autor) Outra; Rocha, S (Autor) Outra; Lima, JLFC (Autor) FFUP; Ribeiro, D (Autor) Outra; Eduarda Fernandes (Autor) FFUP; Freitas, M (Autor) Outra

Revista

Título: Oxidative Medicine and Cellular Longevity

Vol. 2019

Páginas: 1-11

ISSN: 1942-0900

Editora: Hindawi

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 2 Citações

Outras Informações

ID Authenticus: P-00Q-58H

DOI: 10.1155/2019/7198484

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 11