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https://www.selleckchem.com/products/tak-243-mln243.html For decades, mathematical models have been used to predict the behavior of physical and biological systems, as well as to define strategies aiming at the minimization of the effects regarding different types of diseases. In the present days, the development of mathematical models to simulate the dynamic behavior of the novel coronavirus disease (COVID-19) is considered an important theme due to the quantity of infected people worldwide. In this work, the objective is to determine an optimal control strategy for vaccine administration in COVID-19 pandemic treatment considering real data from China. Two optimal control problems (mono- and multi-objective) to determine a strategy for vaccine administration in COVID-19 pandemic treatment are proposed. The first consists of minimizing the quantity of infected individuals during the treatment. The second considers minimizing together the quantity of infected individuals and the prescribed vaccine concentration during the treatment. An inverse problem is formulaic, as well as essential elements for decision making in the economic and governmental spheres.Ceftriaxone is a third-generation cephalosporin, worldwide use as a first-line treatment for several infections, including life-threatening infections as meningitis or endocarditis. Nowadays, ceftriaxone use is changing, embracing high-dose schemes, new populations treated and requirement of dose individualization and optimization. These reasons warranted the development of new sensitive assays. This study aimed to develop and validate a fast and handy bioanalytical method for the quantification of ceftriaxone in human plasma covering a broad range of concentrations. The analysis was performed using high-performance liquid chromatography coupled to tandem mass spectrometry. Sample preparation was based on protein precipitation with acetonitrile followed by centrifugation. Chromatography separation was performed on Ph
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