Determination of Multiple Pesticide Residues in Okra by QuEChERS Combined with PTV-GC-MS/MS and UPLC-MS/MS

[Objectives] To establish Qu ECh ERS based extraction method for determining multiple pesticide residues in okra combined with programmed temperature vaporizer-gas chromatography-triple quadrupole mass spectrometry( PTV-GC-MS/MS) and ultra high performance liquid chromatography-mass spectrometry( UPLC-MS/MS). [Methods] In this experiment,124 pesticide residues in okra were determined by an optimized Qu ECh ERS method combined with PTV-GC-MS/MS and UPLC-MS/MS. The pesticides in okra were extracted and purified by the optimized Qu ECh ERS pretreatment method and determined by PTV-GC-MS/MS and UPLC-MS/MS. [Results] In this experiment,124 kinds of pesticides had a good linearity with a limit of detection( LOD) of 0. 000 5-0. 008 0 mg/kg; the average recovery rate at three levels was 65. 5%-128. 1% with relative standard deviation of 2. 2%-9. 7%. [Conclusions] This method is simple,rapid,accurate and sensitive,and can provide reliable and valid data support for the determination of multiple pesticide residues in okra by GC-MS/MS and UPLC-MS/MS.

Determination of Veterinary Drug Residues in Animal-derived Foods by Liquid Chromatography-Mass Spectrometry

[Objectives]This study was conducted to establish a rapid and effective method for simultaneous extraction of 54 kinds of veterinary drug residues in animal-derived food, including sulfonamides, quinolones, tetracyclines, malachite greens, penicillins, nitroimidazoles, tranquilizers and macrolides, by HPLC-MS. [Methods] The samples were extracted with 80% acetonitrile water(containing 0.1% formic acid), combined with QuEChERS extraction technology and C18 and PSA purification, analyzed by high performance liquid chromatography-mass spectrometry, and quantified by external standard method. The target substances were analyzed on ZORBAX Eclipse C18 chromatographic column using 0.2% formic acid water and 0.2% methanol as mobile phases. The gradient elution mode was used for chromatographic separation and multiple reaction detection. [Results] In the linear range of 0.5-50.0 ng/ml, the linear relationship of the 54 kinds of veterinary drug residues was good, with correlation coefficients(r~2) greater than 0.995, and the detection limits ranged from 0.30 to 1.00 μg/kg. The results showed that the recovery ranged from 75.4% to 118.2% when different matrixes were added for recovery. [Conclusions] This method is simple, efficient, accurate, stable, and highly operable. It is applicable to simultaneous batch screening of veterinary drug residues in animal-derived food, and has high practical application value.

Rapid Determination of Pesticide Residues in Fresh Sweet Corn

Objective] This study aimed to detect al organophosphate, organochlorine and pyrethroid pesticide residues in fresh sweet corn in one determination using a gas chromatograph. [Method] The pesticide residues in fresh sweet corn were ex-tracted and loaded to simultaneously the gas chromatograph Agilent 6890N which was equipped with two autosamplers, two columns and two detectors. [Result] Al the 26 pesticides were completely separated and eluted out within 25 min. The re-coveries of standard addition of the 26 pesticides ranged from 76% to 106%, with relative standard deviations （RSD） ranging from 0.5% to 8.9%. The linear regression equation fit wel from 0.050 to 1.500 mg/L corn extract （r2＆gt;0.996）. [Conclusion] The method is accuracy, which meets the requirements of pesticide residue analysis and can be used for the rapid detection, qualitative and quantitative analysis of pesticide residues in fresh sweet corn.

A computational model of the human glucose-insulin regulatory system

Objective：A computational model of insulin secretion and glucose metabolism for assisting the diagnosis of diabetes mellitus in clinical research is introduced.The proposed method for the estimation of parameters for a system of ordinary differential equations（ODEs）that represent the time course of plasma glucose and insulin concentrations during glucose tolerance test（GTT）in physiological studies is presented.The aim of this study was to explore how to interpret those laboratory glucose and insulin data as well as enhance the Ackerman mathematical model.Methods：Parameters estimation for a system of ODEs was performed by minimizing the sum of squared residuals（SSR）function,which quantifies the difference between theoretical model predictions and GTT＇s experimental observations.Our proposed perturbation search and multiple-shooting methods were applied during the estimating process.Results：Based on the Ackerman＇s published data,we estimated the key parameters by applying R-based iterative computer programs.As a result,the theoretically simulated curves perfectly matched the experimental data points.Our model showed that the estimated parameters,computed frequency and period values,were proven a good indicator of diabetes.Conclusion：The present paper introduces a computational algorithm to biomedical problems,particularly to endocrinology and metabolism fields,which involves two coupled differential equations with four parameters describing the glucose-insulin regulatory system that Ackerman proposed earlier.The enhanced approach may provide clinicians in endocrinology and metabolism field insight into the transition nature of human metabolic mechanism from normal to impaired glucose tolerance.