Percorrer por autor "Silva, A."
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- Staphylococci among Wild European Rabbits from the Azores: A Potential Zoonotic Issue?Publication . Sousa, M.; Silva, V.; Silva, A.; Silva, N.; Ribeiro, J.; Tejedor-Junco, M.T.; Capita, R.; Chenouf, N.S.; Alonso-Calleja, C.; Rodrigues, T.M.; Leitão, M.; Gonçalves, D.; Caniça, M.; Torres, C.; Igrejas, G.; Poeta, P.The prevalence and diversity of Staphylococcus species from wild European rabbits (Oryctolagus cuniculus) in the Azores were investigated, and the antibiotic resistance phenotype and genotype of the isolates were determined. Nasal samples from 77 wild European rabbits from São Jorge and São Miguel islands in Azores were examined. Antibiotic susceptibility of the isolates was determined using the Kirby-Bauer disk diffusion method, and the presence of antimicrobial resistance genes and virulence factors was determined by PCR. The genetic lineages of S. aureus isolates were characterized by spa typing and multilocus sequence typing. A total of 49 staphylococci were obtained from 35 of the 77 wild rabbits. Both coagulase-positive (8.2%) and coagulase-negative (91.8%) staphylococci were detected: 4 S. aureus, 17 S. fleurettii, 13 S. sciuri, 7 S. xylosus, 4 S. epidermidis, and 1 each of S. simulans, S. saprophyticus, S. succinus, and S. equorum. The four S. aureus isolates showed methicillin susceptibility and were characterized as spa type t272/CC121, Panton-Valentine leukocidin negative, and hlB positive. Most of the coagulase-negative staphylococci showed resistance to fusidic acid and beta-lactams, and multidrug resistance was identified especially among S. epidermidis isolates. The mecA gene was detected in 20 isolates of the species S. fleurettii and S. epidermidis, associated with the blaZ gene in one S. epidermidis isolate. Five antimicrobial resistance genes were detected in one S. epidermidis isolate (mecA,dfrA,dfrG,aac6'-aph2'', and ant4). Our results highlight that wild rabbits are reservoirs or "temporary hosts" of Staphylococcus species with zoonotic potential, some of them carrying relevant antimicrobial resistances.
- A study protocol to evaluate the relationship between outdoor air pollution and pregnancy outcomesPublication . Ribeiro, M.C.; Pereira, M.J.; Soares, A.; Branquinho, C.; Augusto, S.; Llop, E.; Fonseca, S.; Nave, J.G.; Tavares, A.B.; Dias, Carlos Matias; Silva, A.; Selemane, I.; De Toro, J.; Santos, M.J.; Santos, F.Background - The present study protocol is designed to assess the relationship between outdoor air pollution and low birth weight and preterm births outcomes performing a semi-ecological analysis. Semi-ecological design studies are widely used to assess effects of air pollution in humans. In this type of analysis, health outcomes and covariates are measured in individuals and exposure assignments are usually based on air quality monitor stations. Therefore, estimating individual exposures are one of the major challenges when investigating these relationships with a semi-ecologic design. Methods/Design Semi-ecologic study consisting of a retrospective cohort study with ecologic assignment of exposure is applied. Health outcomes and covariates are collected at Primary Health Care Center. Data from pregnant registry, clinical record and specific questionnaire administered orally to the mothers of children born in period 2007-2010 in Portuguese Alentejo Litoral region, are collected by the research team. Outdoor air pollution data are collected with a lichen diversity biomonitoring program, and individual pregnancy exposures are assessed with spatial geostatistical simulation, which provides the basis for uncertainty analysis of individual exposures. Awareness of outdoor air pollution uncertainty will improve validity of individual exposures assignments for further statistical analysis with multivariate regression models. Discussion Exposure misclassification is an issue of concern in semi-ecological design. In this study, personal exposures are assigned to each pregnant using geocoded addresses data. A stochastic simulation method is applied to lichen diversity values index measured at biomonitoring survey locations, in order to assess spatial uncertainty of lichen diversity value index at each geocoded address. These methods assume a model for spatial autocorrelation of exposure and provide a distribution of exposures in each study location. We believe that variability of simulated exposure values at geocoded addresses will improve knowledge on variability of exposures, improving therefore validity of individual exposures to input in posterior statistical analysis.