Abstract Recently a surface plasmon resonance (SPR) optical sensor, based on the Otto configuration — the Otto chip — has been developed. One essential step in the quality control of the fabrication process is characterization of the active region of several devices in a batch. Characterization is done by measuring the angular spectrum of the optical re ectance on several points across the active region of the device, and determining parameters by regression analysis of the data. Traditional gradient methods used in the regression process are extremely dependent on an initial guess and are not very efficient for batch analysis of curves, when those include poorly defined SPR spectra, where an initial guess may be hard to infer. An alternative approach for the regression problem is to model the analysis as an optimization problem and using an efficient stochastic algorithm. In this paper one discusses the use of Particle Swarm Optimization (PSO) for characterization of Otto chip devices. From comparative studies carried out in an existing Otto chip, it is observed that PSO can be a very efficient approach for batch analysis and yields better results when compared with the traditional gradient-based regression method.

Methasterone is a designer anabolic steroid that is prohibited for athletes and is monitored by anti-doping laboratories. In this work, our objective is to discover new human phase I metabolites, define their excretion kinetics for 30 days and analyze their phase II metabolism (sulfate, cysteine and N-acetylcysteine conjugates). Urine samples from four volunteers were analyzed by chromatographic techniques. Through gas chromatography coupled to mass spectrometry analysis it was possible to detect methasterone and its nine phase I metabolites in the urine samples after glucuronide enzymatic hydrolysis, from which one were previously unreported. These nine compounds were not excreted in free form. The new proposed metabolite is 17β-hydroxy-2α,17α-dimethyl-5β-androstan-3-one, obtained from the epimerization at C5. The 3α-hydroxy metabolite, currently monitored by anti-doping laboratories, was the most abundant and was detected for the longest time. Furthermore, four other long-term metabolites were identified. By ultra-performance liquid chromatography coupled to tandem mass spectrometry, only the drug and a known metabolite were detected after glucuronide hydrolysis, and phase II metabolites were not found. Thus, our results contribute to elucidating methasterone metabolism, including long-term metabolites besides of the 3α-hydroxy in routine doping analysis, which is very important due to variation in human metabolism.

Resumo Objetivo: verificar a associação entre multimorbidade em idosos e variáveis sociodemográficas, autopercepção de saúde e polifarmácia. Método: Estudo de corte transversal, para a coleta de dados utilizou-se o questionário Saúde, Bem-estar e Envelhecimento. A amostra foi constituída de 676 indivíduos com 60 anos de idade ou mais residentes em municípios de pequeno porte do norte do estado do Rio Grande do Sul, Brasil. A variável dependente foi a multimorbidade, isto é, a ocorrência de duas ou mais doenças crônicas não transmissíveis no mesmo indivíduo. As variáveis independentes foram as características demográficas, socioeconômicas e relativas à saúde. O modelo de regressão de Poisson bruta e ajustada foi utilizado para analisar o efeito das variáveis independentes em relação ao desfecho e p foi considerado significativo quando <0,05. Resultados: Dos idosos entrevistados, 45% apresentam multimorbidade, 51,1% relatam autopercepção de saúde ruim/muito ruim e 37,1% faz uso de polifarmácia. Após análise ajustada à ocorrência de multimorbidade, apresentou-se associação às variáveis: percepção de saúde negativa. RP=1,15; (IC95%; 1,09 - 1,22) e uso de polifarmácia RP=1,29; (IC95%; 1,22 - 1,35). Conclusão: A multimorbidade pode interferir negativamente na autopercepção de saúde dos idosos contribuindo para o aumento do consumo de medicamentos.

Abstract Objective: to verify the association between the multimorbidity of the elderly and sociodemographic variables, self-perception of health and polypharmacy. Method: a cross-sectional study was performed. The research data was collected using the Health, Well-Being and Aging questionnaire. The sample was composed of 676 people aged 60 years or more, who were residents of small towns in the north of the state of Rio Grande do Sul, Brazil. The dependent variable was multimorbidity, that is, the occurrence of two or more chronic non-communicable diseases in the same person. The independent variables were demographic, socioeconomic and health-related characteristics. Poisson’s raw and robust regression model was used to analyze the effect of the independent variables in relation to the outcome and p was considered significant when <0.05. Result: among the elderly interviewed, 45% presented multimorbidity, 51.1% reported a self-perception of poor/very poor health and 37.1% used polypharmacy. After the analysis was adjusted to the occurrence of multimorbidity, association with the following variables was found: health perception (regular/poor/very poor) PR=1.15 (CI95%; 1.09 - 1.22) and use of polypharmacy PR=1.29 (CI95%; 1.22 - 1.35). Conclusion: Multimorbidity may interfere negatively in the self-perception of health of the elderly contributing to increased medicine consumption.