气相色谱-质谱联用分析花椒挥发油的成分

 采用气相色谱 质谱联用技术对陕西富平产花椒挥发油的成分进行了分析 ,分离出了 17个峰 ,鉴定出了相对峰面积大于 1 0 %的组分共 16个 ,用峰面积归一化法定量测定了已确定组分的相对含量 ,其占挥发油总质量的95 %以上。     

单叶蔓荆子挥发油成分的GC/MS分析

采用气相色谱／质谱（ＧＣ／ＭＳ）联用技术对山东泰山产单叶蔓荆子挥发油的化学成分进行了分析,分离出３０多个峰,确认了其中２８种成分,占总离子流的９５％以上,并对挥发油的主要化学成分Δ３－蒈烯,用气相色谱／傅里叶红外光谱（ＧＣ／ＦＴＩＲ）法进行了验证。     

吹扫/捕集-热脱附气质联用法对荷叶挥发油成分的对比分析

采用同时蒸馏萃取提取得到荷叶挥发油, 通过吹扫/捕集-热脱附法(P&T-TD)对上述提取物中挥发性成分进行富集, 以气质联用(GC/MS)进行定性检测, 同时与直接进样GC/MS法分析的成分进行比较. 两种方法成功分离分析出有机酸、酯、醛、醇、酚、烷烃、芳香烃、烯烃以及含氮、硫、氧杂原子的化合物等共计84种成分, 其中P&T-TD GC/MS鉴定出63种有机化合物, GC/MS鉴定出41种有机化合物, 有20种成分共同检出. 对比分析表明: P&T-TD GC/MS的吹扫/捕集-热脱附过程能富集各种组分, 相比GC/MS分析, 可以鉴定出微量成分及更多挥发性和半挥发性成分, 在精油等挥发性成分的分析检测中使用优势明显.     

水蔓菁挥发油成分的气相色谱/质谱分析

采用常规水蒸气蒸馏法提取出水蔓菁精油，经气相色谱-质谱联机分析，分离出40多个峰，鉴定出41种化合物，主要是4-亚甲基-1-（1-甲基乙基）-环己烯、β-蒎烯、1S-α蒎烯、β-月桂烯、大根香叶烯-D等，占总峰面积的97%。     

松潘乌头和展毛多根乌头挥发油的GC／MS分析

松潘乌头(Aconitum sungpanense Hand.-Mazz.)为毛茛科乌头属植物,根有剧毒,供药用,可治疗跌打损伤、风湿性关节痛等症.主产于甘肃南部、四川北部、青海东部等地.我们曾对其进行了二萜生物碱的分离鉴定.展毛多根乌头(A.Karakolicum var.patentipilumW.T.Wang)是新疆民间常用草药之一,民间称为草乌,主治神经痛、牙痛等症.我们曾对     

山腊梅中挥发油成分分析

山腊梅(Chimonanthus nitensO liv.)除了具有较大的观赏价值,还具有较高的药用价值,如中国药典记载山腊梅叶可用于防治感冒和流行性感冒[1],中药腊梅解毒汤能治疗单纯疱疹性角膜炎,目前临床上已开发出了腊梅止咳露、山腊梅滴丸等产品。山腊梅具有浓郁的香味,据报道山腊梅叶的精     

GC/MS法研究苦黄注射液中挥发油成分

利用气相色谱-质谱联用装置分析了苦黄注射液中挥发油的化学成分及相对含量。共鉴定了55个化合物，其中以单萜和倍半萜为主，占已鉴定的挥发油种类的56．36％和3．63％，为挥发油的主要成分。     

苦丁茶冬青挥发油成分的GC-MS分析

采用乙醚超声萃取-水蒸气蒸馏方法提取苦丁茶冬青的挥发油，用气相色谱-质谱联用分析，鉴定了挥发油中的57个成分，其中主要成分是醇、醛、酮、醚、脂肪酸、脂肪酸酯及含氧萜类等化合物。     

南天竹花挥发油化学成分的GC-MS分析及体外抗氧化活性

采用水蒸气蒸馏法提取南天竹花挥发油,利用气相色谱-质谱联用技术分析挥发油化学成分;以ABTS自由基清除作用、金属离子螯合作用为指标评价20%挥发油的体外抗氧化活性。从南天竹花挥发油中共鉴定出60种化合物,占挥发油总量的76.98%,主要成分为棕榈酸、棕榈醛、十八烷醛、3,7-二甲基-1,5,7-辛三烯-3-醇、1-十六烯等;挥发油对ABTS自由基和金属离子具有较好地清除作用和螯合作用,且样品量与活性呈量效关系。     

Comparison of Origanum Essential Oil Chemical Compounds and Their Antibacterial Activity against Cronobacter sakazakii

Origanum vulgare L. (oregano) is an aromatic plant with wide applications in the food and pharmaceutical industries. Cronobacter sakazakii, which has a high detection rate in powdered infant formula, adversely impacts susceptible individuals. Oregano essential oil (OEO) is a natural antibacterial agent that can be used to fight bacterial contamination. Here, OEO chemical compounds from eight oregano varieties were analyzed by gas chromatography–mass spectrometry and their antibacterial properties were assessed. The eight OEOs were clustered into two groups and were more diverse in group 2 than in group 1. Six compounds, including p-cymene, 3-thujene, γ-terpinene, thymol, carvacrol, and caryophyllene, were shared by eight OEOs. Among the eight oregano varieties, OEOs from O. vulgare sc2 had the strongest antibacterial activity against C. sakazaki, with the inhibition zone of 18.22mm. OEOs from O. vulgare jx, O. ‘Nvying’, O. vulgare ‘Ehuang’, and O. vulgare ssp. virens were also potent. Moreover, the antibacterial activity of OEOs was positively correlated with the relative content of thymol. As the main OEO antibacterial compound, thymol affected the normal growth and metabolism of C. sakazakii cells by destroying the bacterial membrane and decreasing the intracellular ATP concentration. Thus, in light of the antibacterial activity detected in the OEOs from the eight oregano varieties, this study provides a theoretical foundation for oregano cultivar management and development.     

七里香蔷薇精油化学成分的研究

用毛细管气相色谱法分离七里香蔷薇花精油中的各种组份，用GC/MS和Kvoats指数对各种组份进行鉴定，共定性出31种化合物，其中以正十一烷、正十九烷、十九烷-1、正二十三烷为主要成分。     

云南玉龙雪山一种苔类植物精油化学成分研究

苔藓植物分苔纲(Liverworts)、角苔纲(Hornworts)和藓纲(Mosses),分布广泛,多见于阴暗潮湿处,且多呈附生形式。在民间,苔藓被广泛用于治疗外伤、烧伤、感染、肺结核、神经衰弱、惊厥、烫伤和肺炎等,几乎所有苔藓植物都不被各种动物所食用,也不被细菌、真菌或病毒所感染。所有这     

Statistics of the Popularity of Chemical Compounds in Relation to the Non-Target Analysis

The idea of popularity/abundance of chemical compounds is widely used in non-target chemical analysis involving environmental studies. To have a clear quantitative basis for this idea, frequency distributions of chemical compounds over indicators of their popularity/abundance are obtained and discussed. Popularity indicators are the number of information sources, the number of chemical vendors, counts of data records, and other variables assessed from two large databases, namely ChemSpider and PubChem. Distributions are approximated by power functions, special cases of Zipf distributions, which are characteristic of the results of human/social activity. Relatively small group of the most popular compounds has been denoted, conventionally accounting for a few percent (several million) of compounds. These compounds are most often explored in scientific research and are practically used. Accordingly, popular compounds have been taken into account as first analyte candidates for identification in non-target analysis.     

色谱-氨化学电离质谱法分析催化裂化柴油中非碱性氮化物

利用色谱-氨化学电离质谱法直接分析催化裂化柴油中的非碱性含氮化合物;实验考察了离子源压力、温度及电子能量等因素对仪器灵敏度及选择性的影响,结果表明离子源压力是影响分析结果的主要因素,在合适的离子源压力下,氮化物的选择性提高103以上;通过质量色谱图对催化裂化柴油中的氮化物进行了定性定量分析,大港催化裂化柴油中的非碱性氮化合物主要由C0-C4吲哚和C0-C4咔唑组成,确定了26个非碱性氮化物结构;用N＿苯基咔唑作为内标物,测得C0-C4吲哚含量为1811.94μg·g-1,C0-C4咔唑含量为5399.97μg·g-1。     

Chemical composition and cytotoxicity of the essential oil from different parts of Datura metel L.

The essential oil from different parts of Datura metel L. were extracted using hydrodistillation and GC–MS was used to analyse the essential oil. The main components of flowers were ketone (23.61%) and ethyl palmitate (15.84%). The main components of leaves were ketone (18.84%) and phytol (18.71%). Ketone (39.45%) and phytol (31.32%) were the major components of petioles. Palmitic acid (30.60%) and ethyl linoleate (21.56%) were the major components of seeds. The major ingredient of roots was palmitic acid (52.61%). The main ingredients of the stems were palmitic acid (38.38%) and ethyl linoleate (17.38%). All the different parts of essential oil were screened for cytotoxicity. The roots and stems showed the inhibitory effects against HepG-2 with IC₅₀ levels of 613.88 and 341.12 mg/L. The leaves and roots showed the inhibitory effects against HeLa with IC₅₀ levels of 267.76 and 348.35 mg/L. All the six parts have inhibitory effects against SGC-7901 cell lines.     

Variability of the Chemical Composition of the Essential Oil from the Amazonian Ishpingo Species (Ocotea quixos)

Ocotea quixos (Lam.) Kosterm. is an aromatic tree native to Ecuador, whose leaves are used to prepare aromatic beverages to which different health benefits are attributed. In this study, Ocotea quixos leaves were collected in the Amazon region in different environmental conditions and subjected to hydrodistillation to isolate the essential oil. The collection variables used were type of soil, amount of shade, and height; in addition, the presence of twig and leaf age and moisture were used as variables. Chemical composition was analyzed by means of gas chromatography equipped with a flame ionization detector and gas chromatography coupled to mass spectrometry. A wide variety of chemical compositions were detected in the samples. In total, forty-seven compounds were identified, which represented between 97.17% and 99.89% of the total composition. The constituents were mainly grouped into aliphatic sesquiterpene hydrocarbons (33.03–55.89%), other compounds (8.94–47.83%), and oxygenated monoterpenes (1.97–39.66%). The main constituents were found to be (E)-cinnamyl acetate (5.96–41.65%), (E)-methyl cinnamate (0.38–37.91%), and trans-caryophyllene (8.77–37.02%). The statistical analysis suggested the existence of two essential oil chemotypes and a direct correlation between environmental conditions and chemical composition of the essential oils.     

A Novel Approach to Evaluate the Quality and Identify the Active Compounds of the Essential Oil from Curcuma longa L.

Composition-Activity Relationship (CAR) modeling is a novel approach to evaluate the quality and identify active components of herbal medicine. In this study, Grid Search Method (GSM) and Heuristics algorithms, particularly Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), were adopted to determine the optimal parameters automatically. Then, support vector regression (SVR) combined with a linear kernel function or a radial basis kernel function (RBF) and back propagation artificial neural networks (BPANN) were employed to construct the model that correlated the main chemical components with the cytotoxicity of the essential oil from Curcuma longa L., respectively. Considering the robustness and predictive ability, the ν-SVR-RBF-PSO model had the best performance in various tests performed in this paper. Nine components were then identified to have significant cytotoxicity based on the superior model and Mean Impact Value (MIV) analysis. An optimal model can therefore be a useful tool to predict the bioactivity for quality evaluation and active components identification of herbal medicine.