Optimization of the linear quantification range of an online trypsin digestion coupled liquid chromatography–tandem mass spectrometry (LC–MS/MS) platform

Tandem mass spectrometry (MS/MS)-based proteomic workflows with a bottom-up approach require enzymatic digestion of proteins to peptide analytes, usually by trypsin. Online coupling of trypsin digestion of proteins, using an immobilized enzyme reactor (IMER), with liquid chromatography (LC) and MS/MS is becoming a frequently used approach. However, finding IMER digestion conditions that allow quantitative analysis of multiple proteins with wide range of endogenous concentration requires optimization of multiple interactive parameters: digestion buffer flow rate, injection volume, sample dilution, and surfactant type/concentration. In this report, we present a design of experiment approach for the optimization of an integrated IMER-LC–MS/MS platform. With bovine serum albumin as a model protein, the digestion efficacy and digestion rate were monitored based on LC–MS/MS peak area count versus protein concentration regression. The optimal parameters were determined through multivariate surface response modeling and consideration of diffusion controlled immobilized enzyme kinetics. The results may provide guidance to other users for the development of quantitative IMER-LC–MS/MS methods for other proteins.     

Velocity measurement of the liquid–solid flow in a vertical pipeline using gamma-ray absorption and weighted cross-correlation

Developing technology for the deep-sea mining of polymetallic nodules requires, theoretical analyses, simulation and numerous experimental studies. In this paper authors focused on nuclear methods adoption to velocity of solid phase measurement in an extremely hard and varying environment. Selected results of the experimental studies of two-phase liquid–solid particles flow in a vertical pipeline obtained by probing with photon beams are presented. With the use of the sealed ²⁴¹Am isotopes emitting gamma radiation of 59.5 keV, and the scintillation probes with NaI(TI) detectors, the average transport velocity for ceramic models representing natural polymetallic nodules were determined. In the paper for analysis of the signals coming from the probes, the cross correlation function (CCF) and its modifications consisting in the combination of the CCF with such procedures as the average square difference function (ASDF) and the average magnitude difference function (AMDF) were used. An example of measurement is presented and its resulting uncertainties determined. In described experiment the relative values of the combined uncertainty of solid particles average velocity estimation are equal to: 3.2% for the CCF, 3.0% for the CCF/AMDF and 2.8% for the CCF/ASDF.     

Geographic analysis of the cultivation region of Ai pian derived from Blumea balsamifera through the determination of volatiles in the medicinal product and blood of treated mice by gas chromatography – mass spectrometry (GC-MS)

Abstract

Ai pian, derived from Blumea balsamifera (L.) DC. has various medicinal effects and a complex composition. The goal of this study was to analyze the chemical composition of Ai pian by using samples from different regions to explore differences between the chemical composition and its blood composition from treated mice to clarify whether its efficacy is related to synergism of multiple components to provide references for rational quality control. Gas chromatography – mass spectrometry (GC-MS) was used to determine and compare chemical compositions of blank and Ai pian containing serum of mice after 30?min of oral administration of Ai pian of seven batches from Zhenfeng, Wangmo and Luodian Counties; Guizhou Province; and Tian’e County; and Guangxi Province. Sixteen to twenty-two compounds of Ai pian were identified, with fourteen common compounds including L-borneol, L-camphor, borneol acetate, L-linalool, α-gurjunene, and 3-t-butyl-1, 2-dimethoxybenzene. Four to seven compounds were identified as blood components of Ai pian, and L-borneol, L-camphor, and borneol acetate were common prototypes with relative compositions from 13.720 to 36.509%, 2.336 to 5.219%, and 0.401 to 1.188%, respectively. Methyl oleate was a common metabolic component with a relative concentration of 0.021 to 0.446%. The chemical composition and blood components of Ai pian were complex, and its efficacy was related to synergism between several components including L-borneol, L-camphor, and borneol acetate. Therefore, detecting multiple index components of Ai pian is essential for quality control.     

Automated ultratrace determination of musty odiferous compounds from environmental waters by online purge and trap (P&T) gas chromatography–mass spectrometry (GC–MS)

Abstract

Odoriferous compounds are troublesome in natural waters in many parts of the world. The simultaneous determination of these complex compounds due to their low sample concentration and odor thresholds has been difficult. A simple, sensitive and automated technique for the determination of eight odoriferous compounds from aqueous samples was developed using online purge and trap (P&T) coupled to gas chromatography with mass spectrometry. P&T was selected to extract and purify the water samples. Several parameters that affect the extraction and concentration performance were investigated, including the trap sorbent, ionic strength, purge time, sample temperature and desorption time. Under the optimal conditions, the adsorption capacity for the Tenax TA sorbent to 2-isopropyl-3-methoxypyrazine, 4-chloroanisole, 2-isobutyl-3-methoxypyrazine, 2-methylisoborneol, 2-tert-butylphenol, 2,4-dichloroanisole, 2,4,6-trichloroanisole and geosmin reached an equilibration when sample volume was 25?ml at a concentration of 150.0?μg/l. The method provided good linearity in the range from 1.0 to1000?ng/l and the limits of detection were from 0.1 to 0.3?ng/l, which are below the odor thresholds for most of these compounds. The proposed method was applied to the determination of eight odoriferous compounds in surface and tap waters with recoveries from 74.7% to 112.8% and relative standard deviations from 2.6% to 10.8%. This method may be widely employed for monitoring odoriferous compounds in water samples.