RESUMO
Molecular methods have emerged as the most reliable techniques to detect and characterize pathogenic Escherichia coli. These molecular techniques include conventional single analyte and multiplex PCR, PCR followed by microarray detection, pulsed-field gel electrophoresis (PFGE), and whole genome sequencing. The choice of methods used depends upon the specific needs of the particular study. One versatile method involves detecting serogroup-specific markers by hybridization or binding to encoded microbeads in a suspension array. This molecular serotyping method has been developed and adopted for investigating E. coli outbreaks. The major advantages of this technique are the ability to simultaneously serotype E. coli and detect the presence of virulence and pathogenicity markers. Here, we describe the development of a family of multiplex molecular serotyping methods for Shiga toxin-producing E. coli, compare their performance to traditional serotyping methods, and discuss the cost-benefit balance of these methods in the context of various food safety objectives.
RESUMO
OBJECTIVE: This study investigated whether glucose readings from a sensor sampling in interstitial fluid differ substantially from blood glucose (BG) values measured at the same time. RESEARCH DESIGN AND METHODS: We have evaluated the relationship between BG and glucose extracted from interstitial fluid using the GlucoWatch (Cygnus, Redwood City, CA) biographer, a device that collects glucose from subcutaneous interstitial space through intact skin by application of a low electric current. We evaluated the relative change in the interstitial glucose (IG) signal (IGS) as measured by the biographer versus BG using a normalized two-point sensitivity index (NSI). RESULTS: The results show that biographer measures of IG differ in time and magnitude from the corresponding BG values. In particular, the biographer values were shifted in time due to instrumental and physiological lag. Results show an average total lag of 17.2 +/- 7.2 min for all subjects evaluated. The instrumental lag was 13.5 min, suggesting that physiological lag is approximately 5 min. In addition, when glucose was increasing, the change in IGS was less than that in BG, while when BG was decreasing, the change in IGS was greater than that in BG. CONCLUSIONS: Similar results have been reported for other measures of IG, suggesting that differences reflect physiological variation in glucose uptake, utilization, and elimination in blood and interstitial space. This further evidence of the difference between IG and BG should be considered when interpreting glucose measurements from devices that sample interstitial fluid.