spp. Causatives of Infections and Carrier of , , and Genes Associated with Resistance.

spp. have been associated with cases of healthcare associated infections due to their high incidence in isolates from the hospital environment and their ability to cause infections in immunocompromised patients; synthesize biofilms on medical instruments, in the case of negative coagulase species; and change in genetic material, thus making it possible to disseminate genes that code for the acquisition of resistance mechanisms against the action of antibiotics. This study evaluated the presence of , , and chromosomal and plasmid genes of spp.

Detection of Oxacillin/Cefoxitin Resistance in Present in Recurrent Tonsillitis.

Background: Recurrent tonsillitis is one of the most common diseases in childhood, caused many times by ß-lactam-resistant . The objective of this study was to investigate an alternative method to identify resistance to oxacillin/cefoxitin in from hospitalized children with recurrent tonsillitis.

Methods: The samples of came from patients with recurrent tonsillitis and were used in 16S rRNA sequencing and an antibiogram test for identification and verifying resistance, after which HSI methodology were applied for separation of resistances.

Computer-aided diagnosis in chest radiography for detection of childhood pneumonia.

Objectives: This article presents a novel approach based on computer-aided diagnostic (CAD) scheme and wavelet transforms to aid pneumonia diagnosis in children, using chest radiograph images. The prototype system, named Pneumo-CAD, was designed to classify images into presence (PP) or absence of pneumonia (PA).

Materials And Methods: The knowledge database for the Pneumo-CAD comprised chest images confirmed as PP or PA by two radiologists trained to interpret chest radiographs according to the WHO guidelines for the diagnosis of pneumonia in children.

A linear semi-infinite programming strategy for constructing optimal wavelet transforms in multivariate calibration problems.

A novel strategy for the optimization of wavelet transforms with respect to the statistics of the data set in multivariate calibration problems is proposed. The optimization follows a linear semi-infinite programming formulation, which does not display local maxima problems and can be reproducibly solved with modest computational effort. After the optimization, a variable selection algorithm is employed to choose a subset of wavelet coefficients with minimal collinearity.