[Genotypes of Staphylococcus aureus strains with methicillin resistant phenotype]. / Genotipos de Staphylococcus aureus con fenotipo meticilino resistente, aislados de pacientes del Hospital Base de Valdivia.

BACKGROUND: Methicillin resistant strains of Staphylococcus aureus (MRSA) are an important cause of nosocomial infections. AIM: To determine the genotypes of MRSA strains. MATERIAL AND METHODS: Fifty five strains of MRSA, isolated from patients hospitalized in Hospital Base Valdivia, were studied. The phenotype was determined through MicroScan in all strains and by minimum inhibitory concentration (MIC) in 41. The genotype of the strains was analyzed by a duplex polymerase chain reaction (PCR) of the mecA gene, amplifying eight hypervariable DNA regions associated to such gene. RESULTS: According to MIC, 88% of strains had a pattern of resistance against multiple antimicrobial (penicillin, ampicillin, cephradine, gentamycin, ciprofloxacin, lincomycin and erythromycin). Vancomicin resistan strains were not detected. Only 53 strains (96%) had at least one of the eight hypervariable regions and were classified as MRSA. Genotypic patterns types 15 were the most commonly detected in 38% and 34% of strains, respectively. MicroScan erroneously classified five strains in an incorrect phenotype, according to results obtained with duplex PCR. MIC results did not differ from those of duplex PCR. CONCLUSIONS: Duplex- PCR is a useful tool to detect hyper variable regions associated to mecA gene.

The balance between initial training and lifelong adaptation in evolving robot controllers.

A central aim of robotics research is to design robots that can perform in the real world; a real world that is often highly changeable in nature. An important challenge for researchers is therefore to produce robots that can improve their performance when the environment is stable, and adapt when the environment changes. This paper reports on experiments which show how evolutionary methods can provide lifelong adaptation for robots, and how this evolutionary process was embodied on the robot itself. A unique combination of training and lifelong adaptation are used, and this paper highlights the importance of training to this approach.