Optimization of in situ derivatization SPME by experimental design for GC-MS multi-residue analysis of pharmaceutical drugs in wastewater

This paper presents the development of a procedure, which enables the analysis of nine pharmaceutical drugs in wastewater using gas chromatography-mass spectrometry (GC-MS) associated with solid-phase microextraction (SPME) for the sample preparation. Experimental design was applied to optimize the in situ derivatization and the SPME extraction conditions. Ethyl chloroformate (ECF) was employed as derivatizing agent and polydimethylsiloxane-divinylbenzene (PDMS-DVB) as the SPME fiber coating. A fractional factorial design was used to evaluate the main factors for the in situ derivatization and SPME extraction. Thereafter, a Doehlert matrix design was applied to find out the best experimental conditions. The method presented a linear range from 0.5 to 10 mu g/L, and the intraday and interday precision were lower than 16%. Applicability of the method was verified from real influent and effluent samples of a wastewater treatment plant, as well as from samples of an industry wastewater and a river.

A general framework for multi-compartmental analysis of drug chemotherapy dynamics in human immunodeficiency virus type-1 infected individuals

An optimal control strategy for the highly active antiretroviral therapy associated to the acquired immunodeficiency syndrome should be designed regarding a comprehensive analysis of the drug chemotherapy behavior in the host tissues, from major viral replication sites to viral sanctuary compartments. Such approach is critical in order to efficiently explore synergistic, competitive and prohibitive relationships among drugs and, hence, therapy costs and side-effect minimization. In this paper, a novel mathematical model for HIV-1 drug chemotherapy dynamics in distinct host anatomic compartments is proposed and theoretically evaluated on fifteen conventional anti-retroviral drugs. Rather than interdependence between drug type and its concentration profile in a host tissue, simulated results suggest that such profile is importantly correlated with the host tissue under consideration. Furthermore, the drug accumulative dynamics are drastically affected by low patient compliance with pharmacotherapy, even when a single dose lacks. (C) 2012 Elsevier Inc. All rights reserved.

Numerical simulation of anisotropic polymeric foams

This paper shows in detail the modelling of anisotropic polymeric foam under compression and tension loadings, including discussions on isotropic material models and the entire procedure to calibrate the parameters involved. First, specimens of poly(vinyl chloride) (PVC) foam were investigated through experimental analyses in order to understand the mechanical behavior of this anisotropic material. Then, isotropic material models available in the commercial software Abaqus (TM) were investigated in order to verify their ability to model anisotropic foams and how the parameters involved can influence the results. Due to anisotropy, it is possible to obtain different values for the same parameter in the calibration process. The obtained set of parameters are used to calibrate the model according to the application of the structure. The models investigated showed minor and major limitations to simulate the mechanical behavior of anisotropic PVC foams under compression, tension and multi-axial loadings. Results show that the calibration process and the choice of the material model applied to the polymeric foam can provide good quantitative results and save project time. Results also indicate what kind and order of error one will get if certain choices are made throughout the modelling process. Finally, even though the developed calibration procedure is applied to specific PVC foam, it still outlines a very broad drill to analyze other anisotropic cellular materials.

Exploration of the parameter space in an agent-based model of tuberculosis spread: emergence of drug resistance in developing vs developed countries

In this work we present an agent-based model for the spread of tuberculosis where the individuals can be infected with either drug-susceptible or drug-resistant strains and can also receive a treatment. The dynamics of the model and the role of each one of the parameters are explained. The whole set of parameters is explored to check their importance in the numerical simulation results. The model captures the beneficial impact of the adequate treatment on the prevalence of tuberculosis. Nevertheless, depending on the treatment parameters range, it also captures the emergence of drug resistance. Drug resistance emergence is particularly likely to occur for parameter values corresponding to less efficacious treatment, as usually found in developing countries.