3 resultados para Strain Measurement


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We describe a case of bacteremia due to an as yet unclassified Acinetobacter genomic species 17-like strain. The recognition of this microorganism as non-Acinetobacter baumannii may have important epidemiological implications, as it relieves the hospital of the implementation of barrier precautions for patients infected or colonized as may be necessary with a multiresistant A. baumannii epidemic.

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In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

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The fitness and virulence costs associated with the clinical acquisition of colistin resistance by Acinetobacter baumannii were evaluated. The growth of strain CR17 (colistin resistant) was less than that of strain CS01 (colistin susceptible) when the strains were grown in competition (72-h competition index, 0.008). In a murine sepsis model, CS01 and CR17 reached spleen concentrations when coinfecting of 9.31 and 6.97 log10 CFU/g, respectively, with an in vivo competition index of 0.016. Moreover, CS01 was more virulent than CR17 with respect to mortality and time to death.