直接获取生物组织内部磷脂类物质的质谱分析方法

选择肺癌组织等多种生物组织为代表性样品,在正离子检测模式下,以磷脂类物质丰度、信号强度高为目标,考察了21种不同组成的CH3OH/H2O溶剂体系,获得了最佳溶剂(CH3OH-H2O,30∶70, V/V),建立了一种无需破坏、研磨即可获取组织内部样品中磷脂类物质信号的内部萃取电喷雾电离质谱( iEESI-MS)方法,并成功应用于肺癌、食管癌、猪肉、牛肉、猪肺、猪心等不同生物组织样品中磷脂类物质的直接质谱分析。本方法无需样品预处理,可通过选择合适的萃取溶剂来提高方法的分析灵敏度和选择性,单个样品的平均分析时间少于1 min,样品耗量少,有望为生物组织样品中磷脂类物质的研究提供一种质谱学新方法。     

牛油果中化学成分的内部萃取电喷雾电离质谱检测

采用内部萃取电喷雾电离质谱(iEESI-MS)技术,以甲醇作为萃取溶剂,无需样品预处理,在优化条件下分别对牛油果果肉和果皮中化学成分进行快速直接鉴定,并考察了不同成熟度牛油果果肉中化学成分的差异.实验结果表明,在负离子检测模式下,从果肉中鉴定出棕榈酸、硬脂酸、棕榈油酸、油酸和亚麻酸等12种有效营养成分,从果皮中鉴定出儿茶素、绿原酸等11种营养成分.利用正交偏最小二乘判别分析法(OPLS-DA)对不同成熟度的牛油果果肉的iEESI-MS指纹谱图数据进行分析发现,此方法能够有效判别不同成熟程度的牛油果且5种化学成分差异显著.本方法无需样品预处理、样品耗量少、分析速度快(单个样品检测时间小于1 min)且操作简便,为植物有效营养成分和医用价值的开发提供了一种快速质谱分析新方法.     

电喷雾内部萃取电离质谱直接分析蒜瓣组织的研究

固态复杂基体样品的直接电离一般仅发生在样品浅层表面,对固体内部深层物质的质谱分析往往需将样品破碎后才能进行。本研究以蒜瓣样品为例,无需样品预处理,带电的甲醇溶液以2μL/min持续流经蒜瓣深层组织,内部组织中的化学物质选择性地溶解到流动液中,并在蒜瓣组织的尖端形成电喷雾,产生相应气态离子供后续质谱分析。在正离子检测模式下,实验记录了两种蒜瓣样品(共24个)、经不同方式贮存加工后的同种蒜瓣样品(共36个)在m/z 50~2000范围内的化学指纹谱图,并将指纹谱图数据进行主成分分析( PCA),获得了令人满意的分组结果。研究表明,电喷雾内部萃取电离质谱( iEESI-MS)可以直接获取蒜瓣内部组织生物化学信息,鉴定蒜瓣组织中重要的化学成分(如蒜氨酸、蒜素、精氨酸、多糖等),快速识别蒜瓣组织中代谢组分的变化。本方法无需样品预处理、操作简单、分析速度快(单个样品分析时间小于2 min),最大程度避免了生物组织分析过程中活性物质受环境作用(如酸解、空气氧化等)的降解,有望为生物组织样品的代谢组学研究提供一种直接、快速的质谱分析方法。     

样品预处理与实时直接分析质谱的联用技术及应用

近年来,与实时直接分析质谱(DART-MS)相结合的样品预处理技术发展迅速,使得对复杂生物、环境、法医学、食品、个体小生物以及单细胞样品中的分析物进行直接分析成为可能。然而固体基质内部分析物检测困难、痕量分析物检测性能不佳已成为限制DART-MS进一步发展的关键问题。针对这些问题,多年来,研究人员在不同领域对样品预处理与质谱联用进行了多种尝试。该文以固相萃取(SPE)、分散固相萃取(DSPE)、搅拌棒吸附萃取(SBSE)、固相微萃取(SPME)、机械化学提取(MCE)和微波提取(MAE)等样品预处理技术为例,对不同研究领域中样品预处理技术与DART-MS联用的研究成果进行了综述,并对未来的发展趋势进行了展望。希望该综述能为开发与DART-MS联用的新型样品处理技术提供参考和帮助。     

组织样品的直接质谱分析及其应用

质谱技术具有灵敏度高、分析速度快、能提供分子结构信息等特点,在生命科学研究领域扮演着重要角色,常用于组织样品分析。传统地,组织样品分析一般需经过研磨、萃取、分离等繁杂的预处理过程,导致耗时低效,无法满足大量样品高通量分析的实际需求,且不可避免地使组织样品中的一些活性成分损失。近年来,随着新型常压质谱技术的发展,使得组织样品可在无需样品预处理的条件下进行实时、非破坏、在线直接质谱分析,大大提高了分析效率。该文着重介绍了新型直接质谱技术在组织样品分析中的应用,并简要展望了该技术在生命科学、临床医学、食品科学、活体分析等领域的发展趋势。     

质谱快速分析猪肉中痕量沙丁胺醇及克伦特罗

采用内部萃取电喷雾电离质谱( iEESI-MS)技术,在无需样品预处理的前提下,采用标准加入法直接对猪肉组织中沙丁胺醇与克伦特罗进行定性和定量分析。结果表明,本实验对猪肉组织中沙丁胺醇与克伦特罗具有较高的灵敏度,单个样品单一指标的检测时间少于30 s。在0.01~1000μg/kg浓度范围内,信号强度对数(Y)与浓度对数(X)具有较好的线性关系,定量限分别为6.2和9.8 ng/kg。本方法分析速度快、样本耗量少、灵敏度高,适用于猪肉中痕量沙丁胺醇与克伦特罗等“瘦肉精”的快速检测。     

电喷雾萃取电离质谱法分析莲子中的生物碱

在无需样品预处理的前提下,直接对莲子醇提液进行电喷雾萃取电离质谱(EESI-MS)检测,并对其中可能存在的生物碱母离子进行串联质谱分析确认,通过主成分分析(PCA)对不同贮藏时间莲子的醇提液进行区分.研究结果表明,电离电压、离子传输管温度和样品进样流速的最佳条件分别为3.5 kV,250℃和5μL/min;串联质谱结果表明莲子醇提液中存在莲心碱、甲基莲心碱、莲心季铵碱、荷叶碱及O-去甲基荷叶碱等生物碱.PCA可将不同贮藏时间的莲子明显区分在二维平面的不同区域.本方法无需样品预处理,可用于复杂基体样品中生物碱的快速鉴定,与化学计量学结合可对不同新陈度的莲子样品进行有效区分.     

基于中性解吸-电喷雾萃取电离质谱直接检测蜂蜜中的四环素

基于中性解吸-电喷雾萃取电离质谱(ND-EESI-MS)建立了无需样品预处理即可直接检测蜂蜜中四环素的方法. 测定结果表明, 加标蜂蜜四环素样品在20~1000 ng/mL浓度范围内线性关系良好(R²>0.997), 检出限为1.08 ng/mL; 加标浓度为50, 500和1000 ng/mL蜂蜜样品的回收率分别为94.26%, 98.38%和103.00%, 精密度(RSD)分别为3.28%, 1.39%和1.12%. 应用此方法对8种市售蜂蜜进行检测, 发现2种蜂蜜中含有痕量的四环素, 其余蜂蜜均未检出, 而应用高效液相色法在这8种市售蜂蜜中均未检出四环素. 本方法无需经过复杂的样品预处理, 灵敏度高、 精密度好、 分析速度快且特异性强, 能够承受蜂蜜中复杂基体的影响, 是一种快速检测蜂蜜中四环素的方法.     

复杂样品质谱分析技术的原理与应用

原位、实时、在线、非破坏、高通量、低耗损的质谱学方法是质谱分析技术发展的重要趋势.在无需样品预处理的条件下对复杂基体样品中痕量待测物直接离子化技术的出现,极大地提高了质谱分析的效率,使实际样品的快速质谱分析成为可能.本文着重综述了能够在无需样品预处理情况下对复杂基体样品离子化的新兴质谱技术及其应用研究,系统阐述了直接离子化技术的基本原理和方法,介绍了几种典型的常压直接离子化技术和装置,对直接离子化质谱分析技术在食品、药品、环境、活体分析、代谢组学、蛋白质组学以及生物组织质谱成像等领域的典型应用进行了述评,讨论了提高复杂样品快速质谱分析选择性的可能方法,并展望了常压直接离子化技术未来发展的可能趋势.     

两种微波等离子体炬质谱测定水中铅的对比研究

建立了一种新型的能够灵敏分析水中痕量铅的质谱方法,以微波等离子体炬(MPT)为离子源,可无需样品预处理而直接分析水样。样品经雾化和去溶后由MPT的中心管道引入等离子体,离子由国产的四极杆质谱仪(Q-MS)检测,得到铅的MPT特征质谱。定量结果表明,该方法的检出限为20 ng/L,线性范围为200~1 000 ng/L,相对标准偏差(RSD)为5.3%;所得定量指标优于相同条件下商用的线性离子阱质谱(LTQ-MS)测试结果,且四极杆质谱仪上所得的铅离子特征质谱信号更简单、易归属,无需复杂的多级串联质谱加以确认。这种MPT可与国产质谱仪器相结合发展成为一种低成本的现场检测铅的质谱仪器,在环境监控、饮用水检验等方面具有一定的应用价值。     

内部萃取电喷雾电离质谱直接分析脐橙

在正离子模式下, 分别对不同品质脐橙的内果皮和果肉进行了内部萃取电喷雾电离质谱(iEESI-MS)分析, 在未经过预处理的前提下直接获得了72个脐橙内果皮样品和72个脐橙果肉样品在m/z 50~2000范围内的化学指纹谱图, 鉴定了脐橙组织中氨基酸、 糖类和生物碱等重要化学成分. iEESI-MS化学指纹谱图表明, 脐橙的果肉与内果皮组织中脯氨酸和糖类等成分的组成具有一定的相似性, 而其它化学组分(如水苏碱、 辛弗林等)在2类组织中的含量差异明显. 主成分分析(PCA)结果表明, 样品的iEESI-MS指纹谱图与该脐橙的品质相关, 与样品的实际品质差异一致. 因此, iEESI-MS可直接获得不同品质脐橙差异性化学成分的信息, 从分子水平上判断脐橙品质的优劣.     

Relation Between Thermal Decomposition of Medicinal Herbs and their Non-Metals Concentration

The studies on the concentration of total nitrogen, phosphorus, sulphur, chlorine, iodine and boron as well as on the thermal decomposition of commercial raw plant materials used in medicine were performed. The 50 independent samples of herbs originating from 25 medicinal plant species collected in 1986–92 were analysed. The content of non-metallic elements was determined spectrophotometrically after previous mineralization of plant sample. The thermal decomposition was performed using the derivatograph with the application of 100 mg samples and heating rate of 5°C min⁻¹. In order to obtain more clear classification of the analysed plant materials principal component analysis (PCA) was applied. Interpretation of PCA results for two databases (non-metals and thermoanalytical data sets) allows to state, that samples of herbs from the same plant species in majority of cases are characterized by similar elemental composition and similar course of their thermal decomposition. In this way the differences in general chemical composition of medicinal plants raw materials can be determined. This revised version was published online in August 2006 with corrections to the Cover Date.     

Influence of The Elemental Composition of Medicinal Fruits on The Results of Their Thermal Analysis

Studies on the thermal decomposition and on the elemental composition of commercial raw plant materials used in medicine were performed. 16independent samples of fruits originating from 12 medicinal plant species collected in1988–92 were analysed. The thermal decomposition was performed using the derivatograph. The content of non-metallic (N, P, S, Cl, I and B) and metallic (Ca, Mg, Fe, Mn, Cu and Zn)elements was determined by spectrophotometric techniques after previous mineralization of sample. In order to obtain more clear classification of the analysed plant materials principal component analysis was applied. The interpretation of PCA results for three databases (thermoanalytical, non-metals and metals data sets) allows to state, that samples of fruits from the same plant species in the majority of cases are characterized by similar elemental composition and similar course of their thermal decomposition. In this way the differences in general chemical composition of medicinal plants raw materials can be determined. This revised version was published online in August 2006 with corrections to the Cover Date.     

The application of artificial neural networks for the selection of key thermoanalytical parameters in medicinal plants analysis

In the present study three thermoanalytical methods: differential thermal analysis (DTA), thermogravimetric analysis (TGA), and derivative thermogravimetric analysis (DTG) were used to investigate the thermal behavior of medicinal plant raw materials. In order to describe DTA curve, designation of the onset T(i), and peak T(p), temperatures was required. In TGA the mass losses Delta(m), and in DTG the temperature range of peak DeltaT, peak temperature T(p), and peak height h, were recorded. All parameters were read for three stages of the thermal decomposition of plant samples which resulted in obtaining eighteen thermal variables for each sample. Some similarities in the course of thermal decomposition of the same plant organs were recognized, but complexity of the obtained data made it very difficult to determine if they could differentiate between medicinal plant materials and which of them encode the most valuable information about the studied herbals. In order to confirm the existence of any relations between the chemical composition of medicinal plants and their thermal decomposition and to find out which thermoanalytical variables or decomposition stages can be considered as the most significant in terms of their evaluation, it was decided to apply fully connected feed-forward artificial neural networks (ANN). Two different training algorithms were used to address the problem: back-propagation of error and conjugate gradient descent. To verify the results two-dimensional (2-D) Kohonen self-organizing feature maps (SOFMs) were employed. Two alternative datasets of thirteen key variables discriminating plant samples have been proposed.     

Identification of Marchfeld asparagus using Sr isotope ratio measurements by MC-ICP-MS

This work focuses on testing and application of Sr isotope signatures for the fast and reliable authentication and traceability of Asparagus officinalis originating from Marchfeld, Austria, using multicollector inductively coupled plasma mass spectrometry after optimised Rb/Sr separation. The major sample pool comprises freeze-dried and microwave-digested asparagus samples from Hungary and Slovakia which are compared with Austrian asparagus originating from the Marchfeld region, which is a protected geographical indication. Additional samples from Peru, the Netherlands and Germany were limited in number and allowed therefore only restricted statistical evaluation. Asparagus samples from Marchfeld were harvested within two subsequent years in order to investigate the annual variation. The results show that the Sr isotope ratio is consistent within these 2 years of investigation. Moreover, the Sr isotope ratio of total Sr in soil was found to be significantly higher than in an NH₄NO₃ extract, reflecting the mobile (bioavailable) phase. The isotope composition in the latter extract corresponds well to the range found in the asparagus samples in Marchfeld, even though the concentration of Sr in asparagus shows no direct correlation to the concentration of Sr in the mobile phase of the soil. The major question was whether the ‘Marchfelder Spargel’ can be distinguished from samples from the neighbouring countries of Hungary and Slovakia. According to our findings, they can be clearly (100%) singled out from the Hungarian samples and can be distinguished from the Slovakian asparagus samples with a probability of more than 80%.     

Thermal Decomposition of Medicinal Plant Raw Materials Based on Principal Component Analysis

Studies on the thermal decomposition of commercial raw plant materials used in medicine were performed. 144 independent samples of plant materials — herbs, leaves,flowers, inflorescences, fruits, roots, rhizomes and barks, collected by Medicinal Plant Works‘Herbapol’, were analyzed. Thermal decomposition was performed using OD-103 Derivatograph. As a result of analysis, it was established, that thermal decomposition of majority of samples proceeds through three stages. The analysis of fruits revealed, that their thermal decomposition proceeds in four stages. In order to obtain a more clear classification of the analyzed plant materials principal component analysis (PCA) was applied. Interpretation of the PCA results allows to state, that samples of raw materials from the same plant species in majority of cases are characterized by similar course of thermal decomposition due to similar chemical composition. In this way the differences in general chemical composition of medicinal plants raw materials can be determined. This revised version was published online in August 2006 with corrections to the Cover Date.     

激光诱导击穿光谱(LIBS)法微损快速检测党参中Pb

中药材重金属元素快速检测对污染监控及人们健康具有重要意义。激光诱导击穿光谱技术(Laser Induced Breakdown Spectroscopy, LIBS)属于一种快速检测方法,研磨压片等预处理方法相对样品消解已有所简化,但破坏了样品的物理性质,且不能满足中药材大宗品种、大批量检测需求。若进一步简化样品预处理,将更加凸显LIBS快速检测的优势。本文建立了激光诱导击穿光谱技术(LIBS)快速微损检测中药材样品重金属元素定标方法。线性相关系数R2为0.7764,建立的微损定标曲线线性可用于切片党参LIBS快速检测,对待测党参切片样品检测平均相对误差为3.74%,与电感耦合等离子体质谱法(ICP-MS)对比,相关系数R2为0.7957,验证了LIBS技术微损检测的可行性。制备的党参参考定标样品可多次重复用于待测样定标和仪器标定等。实验对待测党参样品仅进行切片处理,避免了研磨、压片等预处理,更加充分地体现LIBS快速检测的优势,为LIBS技术应用于中药材重金属元素快检等领域提供了一种新方法。     

Headspace-solid-phase microextraction in the analysis of the volatile fraction of aromatic and medicinal plants

Headspace (HS)-solid-phase microextraction (SPME) has assumed an ever increasing importance as a technique for HS sampling to study the composition of the HS of medicinal and aromatic plants. HS-SPME has mainly been applied for (a) studying the composition of the volatile fraction, including in addition to or as an alternative to other sampling techniques; (b) monitoring the biological phenomena involved with the volatile fraction of a plant; (c) discriminating between species, subspecies, varieties, cultivars, or chemotypes; and (d) quality control of plant samples. A review of 108 articles published during 2000-2005 is presented covering the use of HS-SPME in the field of aromatic and medicinal plants, selection of the most effective fiber and sampling conditions, comparison of HS-SPME and other volatile fraction sample preparation techniques, and the advantages and limits of HS-SPME when applied to medicinal and aromatic plants.