[Systematic analysis of oral hypoglycemic agents in health foods].

A systematic analysis for 11 ingredients of oral hypoglycemic agent in health foods was established using three different analytical methods; i.e. thin-layer chromatography (TLC), high-performance liquid chromatography (HPLC) and comparison of MS/MS spectra analyzed by liquid chromatography/tandem mass spectrometry (LC/MS/MS). In Normal-phase and reversed-phase TLC, each condition to separate and detect 10 ingredients except nateglinide was developed. On the other hand, 11 ingredients were detected qualitatively and quantitatively by HPLC. The recovery rates were 92-101% and each coefficient of variation was less than 5.4%. Then UV spectra were monitored using this HPLC method and furthermore MS/MS spectra of 11 ingredients were obtained by LC/MS/MS. Identification of each ingredient became precise and rapid by comparing UV and MS/MS spectra of standard solutions with that of extract solutions from health foods. Using this systematic analysis, glibenclamide was accurately determined and identified from health foods.

[Rapid determination of medical components found in the health food for weight loss by liquid chromatography/tandem mass spectrometry (LC/MS/MS)].

A method for the rapid determination of 11 medical components found in health foods for weight loss using liquid chromatography/tandem mass spectrometry (LC/MS/MS) has been developed. HPLC separation is performed on an ODS column with the gradient elution method. The mobile phase consists of two solvents. Solvent A is water and solvent B is methanol/acetonitrile (1:1), and both contain 0.1% formic acid and 5 mmol/l of ammonium acetate. Each medical component is analyzed with multiple-reaction monitoring (MRM) in both negative and positive modes through electrospray ionization (ESI). The recovery rates of the 11 medical components added to commercially available health foods were 46.3-114% and each coefficient of variation was 13.7% or less. It was confirmed that this method is applicable to the urgent analysis of health foods that have caused damage to health.

Rapid quantification methods for genetically modified maize contents using genomic DNAs pretreated by sonication and restriction endonuclease digestion for a capillary-type real-time PCR system with a plasmid reference standard.

For rough quantitative analysis of genetically modified maize contents, rapid methods for measurement of the copy numbers of the cauliflower mosaic virus 35S promoter region (P35S) and MON810 construct-specific gene (MON810) using a combination of a capillary-type real-time PCR system with a plasmid DNA were established. To reduce the characteristic differences between the plasmid DNA and genomic DNA, we showed that pretreatment of the extracted genomic DNA by a combination of sonication and restriction endonuclease digestion before measurement is effective. The accuracy and reproducibility of this method for MON810 content (%) at a level of 5.0% MON810 mixed samples were within a range from 4.26 to 5.11% in the P35S copy number quantification. These methods should prove to be a useful tool to roughly quantify GM maize content.

Quantification of genetically modified soybeans using a combination of a capillary-type real-time PCR system and a plasmid reference standard.

Because the labeling of grains and feed- and foodstuffs is mandatory if the genetically modified organism (GMO) content exceeds a certain level of approved genetically modified varieties in many countries, there is a need for a rapid and useful method of GMO quantification in food samples. In this study, a rapid detection system was developed for Roundup Ready Soybean (RRS) quantification using a combination of a capillary-type real-time PCR system, a LightCycler real-time PCR system, and plasmid DNA as the reference standard. In addition, we showed for the first time that the plasmid and genomic DNA should be similar in the established detection system because the PCR efficiencies of using plasmid DNA and using genomic DNA were not significantly different. The conversion factor (Cf) to calculate RRS content (%) was further determined from the average value analyzed in three laboratories. The accuracy and reproducibility of this system for RRS quantification at a level of 5.0% were within a range from 4.46 to 5.07% for RRS content and within a range from 2.0% to 7.0% for the relative standard deviation (RSD) value, respectively. This system rapidly monitored the labeling system and had allowable levels of accuracy and precision.