• Journal of Food Hygiene and Safety
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• v.29 no.4
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• pp.327-333
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• 2014

A method for analysis of five artificial sweetners (sodium saccharin, aspartame, acesulfame-K, sucralose, cyclamate) in beverage samples was developed using high-performance liquid chromatography/triple quadrupole mass spectrometry (HPLC/MS/MS). The method uses a single-step dilution for sample preperation. Seperation was achieved on a $C_{18}$ column ($2.1{\times}150mm$, $3.5{\mu}m$) with A- 2% methanol (1 mM ammonium acetate), B-95% methanol (1 mM ammonium acetate) as mobile phase with gradient mode. The quantitation of target compounds was performed by external calibration in selected reaction monitorning (SRM) mode. The coefficient of determination of calibration curve for sodium saccharin, aspartame, acesulfame-K, sucralose and cyclamate were 0.9957, 0.9991, 0.9943, 0.9982 and 0.9948, respectively. The limits of detection (LODs) and limits of quantitation (LOQs) were in the range of 0.001~0.022 mg/L and 0.004~0.073 mg/L, repectively. Recoveries for beverage samples were in the range of 92.76~113.50% with RSD < 10.91%. The method has applied to the determination of the five sweetners in 102 beverage samples. Three artificial sweetners-aspartame, acesulfame-K, sucralose were detected from 42 samples. Sodium saccharin and cyclamate were not detected in all samples.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.755-762
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• 2018

The purpose of this study was to compare the FA(faractional anisotropy) and ADC(apparent diffusion coefficient) values, which were derived from diffusion tensor imaging in breast cancer patients. The diffusion gradient used in this study was derived from quantitative diffusion indices using 20 directions(b-value, 0 and $1,000s/mm^2$). Quantitative analysis was analyzed using Pearson's correction and qualitative analysis using for correction coefficients. As a result, $FA_{min}$, $FA_{mean}$ and $FA_{max}$ were $0.098{\pm}0.065$, $0.302{\pm}0.142$ and $0.634{\pm}0.236$, respectively(p > 0.05). The $ADC_{min}$, $ADC_{mean}$ and $ADC_{max}$ were $0.741{\pm}0.403$, $1.095{\pm}0.394$ and $1.530{\pm}0.447$, respectively(p > 0.05). The $FA_{min}$, $FA_{mean}$, and $FA_{max}$ mean values were $0.132{\pm}0.050$, $0.418{\pm}0.094$, and $0.770{\pm}0.164$ for Category 6 and Kinetic Curve Pattern III, respectively. $ADC_{min}$, $ADC_{mean}$, and $ADC_{max}$ were $0.753{\pm}0.189$, $1.120{\pm}0.236$, and $1.615{\pm}0.372$, respectively. Quantitative analysis showed negative correlation between $ADC_{mean}-FA_{mean}$ and $ADC_{max}-FA_{max}$(p = 0.001, 0.003). The qalitative analysis showed ADC 0.628(p = 0.001), FA 0.620(p = 0.001) in the internal evaluations, ADC 0.677(p = 0.001), FA 0.695(p = 0.001) in external evaluations. In conclusion, based on the morphological examination, time to signal intensity graph is the form of wash-out(pattern III) in the dynamic contrast enhance examination, As a result, the $ADC_{mean}$ $1.120{\pm}0.236$ and $FA_{mean}$ values were $0.032{\pm}0.142$ with a negative correlation (Y=1.44-1.12X). Therefore, If we understand the shape of time to signal intensity graph and the relationship between ADC and FA, It will be a criterion for distinguishing malignant diseases in breast cancer.