996 resultados para Chorionic Villus Sampling


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Prepared in cooperation with South Carolina Agricultural Experiment Station.

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Performing organization: Dept. of Statistics, University of Michigan.

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"AEDC-TR-67-65."

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"DOT HS 808 538"--P. [4] of cover.

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An epidemiologic survey among four administrative villages around Poyang Lake, in Jiangxi Province, China (two experimental and two controls) is being conducted to determine if bovine infections are responsible for the persistence of human schistosomiasis transmission on Yangtze River marshlands. A previously published paper presented the experimental design and baseline data for humans and bovines. This paper presents basic data for the four villages using remote sensing, and baseline data for snails that includes geographic information systems and remote sensing technology to classify the areas of bovine grazing ranges and habitats suitable for snails. A new method for sampling Oncomelania snails in China is used to determine the distribution, density, and infection rates of snails throughout the grazing ranges from season to season over a four-year period. Hypothetically, treating bovines should reduce infection rates in snails to below the critical number necessary to maintain infections in man and bovines.

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Blood sampling is an essential technique in many herpetological studies. This paper describes a quick and humane technique to collect blood samples from three species of Australian chelid turtles ( Order Pleurodira): Chelodina expansa, Elseya latisternum, and Emydura macquarii signata.

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Radar target identification based on complex natural resonances is sometimes achieved by convolving a linear time-domain filter with a received target signature. The filter is constructed from measured or pre-calculated target resonances. The performance of the target identification procedure is degraded if the difference between the sampling rates of the target signature and the filter is ignored. The problem is investigated for the natural extinction pulse technique (E-pulse) for the case of identifying stick models of aircraft.

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The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R-2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).