Determination of bromazepam in human plasma by high-performance liquid chromatography with electrospray ionization tandem mass spectrometric detection: application to a bioequivalence study

A simple method using a one-step liquid-liquid extraction (LLE) followed by high-performance liquid chromatography (HPLC) with positive ion electrospray ionization tandem mass spectrometric (ESI-MS/MS) detection was developed for the determination of bromazepam in human plasma, using lorazepam as internal standard. The acquisition was performed in the multiple reaction monitoring mode, monitoring the transitions: m/z 316 > 182 for bromazepam and m/z 321 > 275 for lorazepam. The method was linear over the studied range (1-100 ng ml(-1)), with r(2) > 0.98, and the run time was 2.5 min. The intra- and inter-assay precisions were 2.7-14.6 and 4.1-17.3%, respectively and the intra- and inter-assay accuracies were 87-111 and 75.8-109.5%, respectively. The mean recovery was 73.7%, ranging from 64.5 to 79.7%. The limit of quantification was 1 ng ml(-1). At this concentration the mean intra- and inter-assay precisions were 14.6 and 7.1%, respectively, and the mean intra- and inter-assay accuracies were 102.5 and 104%, respectively. Bromazepam stability was evaluated and the results showed that the drug is stable in standard solution and in plasma samples under typical storage and processing conditions. The method was applied to a bioequivalence study in which 27 healthy adult volunteers (14 men) received single oral doses (6 mg) of reference and test bromazepam formulations, in an open, two-period, randomized, crossover protocol. The 90% confidence interval of the individual ratios (test formulation/reference formulation) for C(max) (peak plasma concentration), AUC(0-96) and AUC(0-inf) (area under the plasma concentration versus time curve from time zero to 96 h and to infinity, respectively) were within the range 80-125%, which supports the conclusion that the test formulation is bioequivalent to the reference formulation regarding the rate and extent of bromazepam absorption.     

基于泊松分布模型的蛋白质串联质谱鉴定算法研究

数据库搜索方法被广泛应用于蛋白质串联质谱的鉴定之中,该方法主要包括4部分:去同位素峰、选取有效峰、产生理论图谱、对理论图谱与实验图谱进行相似度打分.其中打分函数是数据库搜索方法的核心,在此基础上探究了一种基于泊松分布模型下的蛋白质串联质谱鉴定算法,并合理的融入了峰强度信息.为了验证该算法的有效性及可靠性,将该算法搜索结果与主流鉴定商业软件Mascot和Sequest在FDR为1%的条件下进行比较,基于泊松分布模型的蛋白质串联质谱鉴定算法具有更高的鉴定量和鲁棒性.     

Facile access to α-acyloxyamides via epoxide rearrangement/three-component domino reaction catalyzed by indium(III) chloride

A simple and efficient Passerini reaction of epoxides involving highly regioselective rearrangement of epoxide to aldehyde/three-component Passerini reaction catalyzed by indium(III) chloride is described. In the present protocol, epoxides served as wonderful substrates to furnish a library of α-acyloxyamides under mild reaction conditions in shorter reaction times and in good yields.     

Analysis of 29 per- and polyfluorinated compounds in water,sediment, soil and sludge by liquid chromatography–tandem mass spectrometry

Several analytical methods were optimised for the analysis of 29 per- and polyfluoroalkyl substances (PFASs), including perfluorocarboxylic acids, perfluoroalkyl sulphonic acids and fluorotelomers (FTs), such as sulphonate, saturated carboxylic acid, unsaturated carboxylic acid, sulphonamide and sulphonamide betaine (FTAB), in environmental samples in order to assess pollution by PFASs around heavily contaminated sites. Non-filtered water samples were extracted, purified and pre-concentrated by a solid-phase extraction (SPE) procedure. Solid samples (sediments, soils and sludges) were extracted through solvent extraction under acidic conditions and thereafter purified and pre-concentrated using the same SPE procedure as for the water samples. An ultra-high performance liquid chromatography coupled to tandem mass spectrometry in negative electrospray ionisation mode was employed to separate and detect targeted compounds. Twelve labelled internal standards were used to provide an adequate correction compensating for matrix effects. The limits of quantification (LOQs) were between 4 and 10 ng/L in water depending on the analytes. For solid samples, the LOQs were 2 ng/g dry weight (dw) in sediments and soils, and 20 ng/g dw in sludges for all analytes. A surrogate parameter method based on the carboxylation of perfluoroalkyl acid precursors under basic pH conditions was furthermore implemented to estimate the occurrence of non-targeted PFAS compounds. In order to evaluate the reliability of these analytical methods, environmental samples collected around a training area in France, where aqueous fire-fighting foam is used, were analysed. Of all the compounds detected in these environmental samples, 6:2 FTAB was found in the highest concentrations.     

Direct glycan structure determination of intact N-linked glycopeptides by low-energy collision-induced dissociation tandem mass spectrometry and predicted spectral library searching

Intact glycopeptide MS analysis to reveal site-specific protein glycosylation is an important frontier of proteomics. However, computational tools for analyzing MS/MS spectra of intact glycopeptides are still limited and not well-integrated into existing workflows. In this work, a new computational tool which combines the spectral library building/searching tool, SpectraST (Lam et al. Nat. Methods2008, 5, 873–875), and the glycopeptide fragmentation prediction tool, MassAnalyzer (Zhang et al. Anal. Chem.2010, 82, 10194–10202) for intact glycopeptide analysis has been developed. Specifically, this tool enables the determination of the glycan structure directly from low-energy collision-induced dissociation (CID) spectra of intact glycopeptides. Given a list of possible glycopeptide sequences as input, a sample-specific spectral library of MassAnalyzer-predicted spectra is built using SpectraST. Glycan identification from CID spectra is achieved by spectral library searching against this library, in which both m/z and intensity information of the possible fragmentation ions are taken into consideration for improved accuracy. We validated our method using a standard glycoprotein, human transferrin, and evaluated its potential to be used in site-specific glycosylation profiling of glycoprotein datasets from LC-MS/MS. In addition, we further applied our method to reveal, for the first time, the site-specific N-glycosylation profile of recombinant human acetylcholinesterase expressed in HEK293 cells. For maximum usability, SpectraST is developed as part of the Trans-Proteomic Pipeline (TPP), a freely available and open-source software suite for MS data analysis.     

纳升液相色谱-高分辨串联质谱研究冻存条件对唾液多肽组的影响

唾液多肽组学为疾病相关的生物标记物研究提供了新方法,但冻存条件对分析结果的影响并不清楚。本研究采用氧化石墨烯-磷酸镧纳米复合材料分离富集唾液多肽,利用纳升液相色谱-高分辨串联质谱技术,考察唾液样品分别置于-80℃与-20℃冻存6个月后对唾液多肽组的影响。结果表明,在-80℃冻存条件下的唾液样品中,共鉴定出归属于33种蛋白的429条肽段;在-20℃冻存条件下的唾液样品中,鉴定出595条肽段,对应31种蛋白。实验结果表明,相比于-80℃,唾液置于-20℃条件下的新增加肽段主要来源于已有肽段的降解,并且唾液中的蛋白质也发生了一定降解。本研究在肽段序列水平上考察了冻存条件对多肽的影响,结果表明,-20℃冻存条件不适合长期保存用于多肽组分析的唾液样品。本研究结果可为相关医学研究提供借鉴。     

超高效液相色谱-三重四级杆串联质谱法同时测定植物组织中多种激素

建立了同时测定植物组织中玉米素(ZT)、吲哚乙酸(IAA)、赤霉素类(GA1、GA3、GA4)、脱落酸(ABA)、茉莉酸(JA)7种植物激素的超高效液相色谱-三重四级杆串联质谱法(UHPLC-QqQ-MS/MS)。采用C18色谱柱(50×2.1mm,1.8μm)分离,以甲醇-0.1%甲酸水溶液为流动相,梯度洗脱,在多反应监测(MRM)模式下进行定性定量分析,外标法定量。7种植物激素的检出限为0.01~8.77ng·mL~(-1),定量限为0.02~29.23ng·mL~(-1),在实验所采用的浓度范围内线性相关系数(R2)在0.9870~0.9990之间。植物样本前处理采用C18-SPE小柱进行富集和纯化,极大地减少了基质干扰。在辣椒叶片基质中,7种植物激素在低、中、高3个加标水平下的平均回收率为65.8%~90.9%,相对标准偏差(RSDs,n=5)为2.1%~5.5%。该方法简单、快速,灵敏,准确,适用于对植物组织中多种激素的同时测定。     

Insertion of Isolated Alkynes into Carbon–Carbon σ‐Bonds of Unstrained Cyclic β‐Ketoesters via Transition‐Metal‐Free Tandem Reactions: Synthesis of Medium‐Sized Ring Compounds

The transition‐metal‐free insertion of isolated alkynes into carbon–carbon σ‐bonds of unstrained cyclic β‐dicarbonyl compounds has been reported. These tandem reactions offer an efficient synthesis of medium‐sized ring or fused‐ring compounds through ring expansion. The methodology has the potential to be widely used throughout organic synthesis due to the easily accessible starting materials and mild reaction conditions.     

Bovine serum albumin as a universal suppressor of non-specific peptide binding in vials prior to nano-chromatography coupled mass-spectrometry analysis

Non-specific binding (NSB) is a well-known problem for any application that deals with ultralow analyte quantities. The modern nano-flow chromatography coupled tandem mass-spectrometry (nanoLC-MS/MS) works with the lowest conceivable analyte concentrations. However, while the NSB problem is widely accepted and investigated for metabolomics and single-peptide medicine-related assays, its impact is not studied for complex peptide mixtures in proteomic applications. In this work peptide NSB to a common plastic autosampler vial was studied for a model mixture of 46 synthetic peptides. A significant NSB level was demonstrated for total peptide concentrations of up to 1 mg mL⁻¹. Different agents were tried for NSB suppression and compatibility with nanoLC-MS/MS analysis: a chaotropic agent, an amino acid mixture, a peptide mixture and a protein solution. The first two were inefficacious. The peptide matrix blocked NSB, however, it also led to analyte ionization suppression in nanoLC-MS/MS. The protein solution (0.1% BSA) efficiently eliminated NSB, while a trap-elute nanoHPLC configuration together with a small-pore reverse-phased sorbent effectively and quantitatively extracted the model peptides and depleted protein material from the sample. Higher protein concentration partially impeded peptide extraction. Thus, the 0.1% BSA solution might be regarded as an effective non-interfering blockader of NSB for sample resuspension and storage in an autosampler prior to LC-MS/MS analysis.     

Mono-isotope Prediction for Mass Spectra Using Bayes Network

Mass spectrometry is one of the widely utilized important methods to study protein functions and components. The challenge of mono-isotope pattern recognition from large scale protein mass spectral data needs computational algorithms and tools to speed up the analysis and improve the analytic results. We utilized na¨?ve Bayes network as the classifier with the assumption that the selected features are independent to predict monoisotope pattern from mass spectrometry. Mono-isotopes detected from validated theoretical spectra were used as prior information in the Bayes method. Three main features extracted from the dataset were employed as independent variables in our model. The application of the proposed algorithm to public Mo dataset demonstrates that our na¨?ve Bayes classifier is advantageous over existing methods in both accuracy and sensitivity.