Determination of Aroma Composition of Santalum album Linn by Solid-phase Microextraction-Gas Chromatography-Mass Spectrometry

[Objectives]This study aimed to determine the volatile components in Santalum album Linn and gradually clarify the aroma composition of S.album Linn.[Methods]Solid-phase microextraction method was used to obtain the volatile components of S.album Linn.The aroma components were analyzed by gas chromatography-mass spectrometry and their relative contents were calculated using the area normalization method.[Results]In a dry state at room temperature,39 chemical components were identified from S.album Linn,mainly olefins(91.15%),alkanes(3.00%),alcohols(2.56%),esters(2.19%),ketones(0.55%),aldehydes(0.41%)and heterocyclics(0.14%).[Conclusions]This method has the advantages of low sample consumption,easy operation,rapid identification of aroma components and high sensitivity,and can effectively separate and determine volatile components in S.album Linn,realizing the rapid identification of different S.album Linn varieties and providing technical support for further research on Chinese medicinal materials.

环糊精超交联聚合物纤维顶空固相微萃取-气相色谱-质谱法分析植物油中的邻苯二甲酸酯

邻苯二甲酸酯(PAEs)因具有改善塑料柔软性和柔韧性的特性而被作为增塑剂广泛应用于各种食品包装材料,然而,其对人类健康的重大危害使得建立准确的分析方法显得至关重要。为了解决油性基质样品前处理费时费力的问题,我们开发了一种基于顶空固相微萃取(HS-SPME)结合气相色谱-质谱(GC-MS)检测的分析方法,用于快速检测植物油基质中的12种PAEs。将苄基化环糊精超交联聚合物(BnCD-HCP)涂敷在不锈钢纤维上制备了一种具有较大比表面积、良好稳定性好和较高重复性的固相微萃取探针,并对其结构、形貌进行了表征。将油脂样品以甲醇改性后以该探针顶空萃取PAEs,优化得到如下最佳萃取参数:萃取时间20 min,萃取温度50℃,解吸时间4 min,解吸温度275℃。在优化的分析条件下,12种目标PAEs在线性范围内具有良好的线性关系(相关系数(R^(2))均大于099),检出限和定量限分别为021~374μg/kg和069~1234μg/kg,单针的相对标准偏差(RSD)≤114%,针间RSD≤139%。将此方法应用于大豆油、花生油和葵花油样品中PAEs的检测,加标试验结果表明该方法具有良好的精密度(RSD为117%~1173)和回收率(7249%~12443%)。该研究建立的基于BnCD-HCP的HS-SPME方法不需要溶剂萃取和净化等繁琐操作,具有快速、灵敏、准确、环保等优点,为植物油中PAEs的灵敏筛检提供了新的方法和技术。

Mapping the metabolic responses to oxaliplatin-based chemotherapy with in vivo spatiotemporal metabolomics

Adjuvant chemotherapy improves the survival outlook for patients undergoing operations for lung metastases caused by colorectal cancer (CRC). However, a multidisciplinary approach that evaluates several factors related to patient and tumor characteristics is necessary for managing chemotherapy treatment in metastatic CRC patients with lung disease, as such factors dictate the timing and drug regimen, which may affect treatment response and prognosis. In this study, we explore the potential of spatial metabolomics for evaluating metabolic phenotypes and therapy outcomes during the local delivery of the anticancer drug, oxaliplatin, to the lung. 12 male Yorkshire pigs underwent a 3 h left lung in vivo lung perfusion (IVLP) with various doses of oxaliplatin (7.5, 10, 20, 40, and 80 mg/L), which were administered to the perfusion circuit reservoir as a bolus. Biocompatible solid-phase microextraction (SPME) microprobes were combined with global metabolite profiling to obtain spatiotemporal information about the activity of the drug, determine toxic doses that exceed therapeutic efficacy, and conduct a mechanistic exploration of associated lung injury. Mild and subclinical lung injury was observed at 40 mg/L of oxaliplatin, and significant compromise of the hemodynamic lung function was found at 80 mg/L. This result was associated with massive alterations in metabolic patterns of lung tissue and perfusate, resulting in a total of 139 discriminant compounds. Uncontrolled inflammatory response, abnormalities in energy metabolism, and mitochondrial dysfunction next to accelerated kynurenine and aldosterone production were recognized as distinct features of dysregulated metabolipidome. Spatial pharmacometabolomics may be a promising tool for identifying pathological responses to chemotherapy.

Determining organic compounds in coking wastewater by SPME-GC /MS

The solid-phase microextraction （SPME） combined with gas chromatography/mass spectrometry （GC/MS） was used to determine and analyze organic pollutants in coking wastewater. Based on the fact that the main compounds in the wastewater were organics, some key parameters of the SPME were optimized. The method has good linearity （ its correlation coefficients 〉 0.99） in the range determined,its relative standard deviations （RSD） are less than 15%, and its recovery is from 87.9% to 128.1% with the lowest quantification limit of 5 ~g/L. This method has been used to measure 15 organic pollutants in wastewater from a certain coking plant. The results show that compared with the conventional method,it can save an hour in pretreatment time. It is a fast, low-cost, accurate, simple and efficient analytical method indeed.

Analysis on Volatile Components of Flowers and Leaves of Thymus mongolicus by SPME-GC/MS

[Objectives] To analyze volatile components of flowers and leaves of Thymus mongolicus. [Methods]Volatile components of collected T. mongolicus flower and leaves were separated by headspace solid-phase microextraction( SPME) and identified by gas chromatography/mass spectrometry( GC/MS) and normallized by peak area. [Results] A total of 24 and 14 compounds were identified from flowers and leaves of T. mongolicus in the total ion chromatogram,accounting for 99. 573% and 97. 187% of the total peak area,respectively. Main components of flowers and leaves of T. mongolicus include phenols and terpenes,and thymol accounts for 35. 38% and 49. 13% of flowers and leaves of T. mongolicus,respectively. [Conclusions] SPME-GC/MS can be applied in analyzing volatile components of flowers and leaves of T. mongolicus,to provide basis for further development and utilization of T. mongolicus.

烤制时间对中式烤五花肉挥发性风味物质的影响

以猪五花肉为研究对象,利用万能蒸烤箱,研究恒定温度160℃条件下,不同烤制时间(5,10,15,20,25 min)对中式烤五花肉挥发性物质的影响。运用顶空固相微萃取(solid-phase microextraction,SPME)和气相色谱-质谱(gas chromatography-mass spectrometry,GC-MS)联用仪进行分析和鉴定,研究结果表明,中式烤五花肉在烤制时间下共鉴定出40种挥发性风味物质,其中醛类化合物7种、酯类化合物4种、醇类化合物8种、烃类化合物14种、其他化合物7种。从不同时间段来看,中式烤五花肉在烤制过程中,随着烤制时间的变化,在烤制25 min的条件下产生的挥发性物质数量最多。

固相微萃取-气相色谱-质谱法分析云烟浸膏和烟末浸膏的挥发性化学成分

用固相微萃取-气相色谱-质谱法(SPME-GC/MS)测定了云烟浸膏和烟末浸膏的挥发性化学成分,采用总离子流色谱峰面积归一化方法进行定量,对它们的化学成分进行了比较。结果表明:云烟浸膏和烟末浸膏分别鉴定出47种和50种化合物,占挥发性成分的86.04％和81.37％;云烟浸膏中的尼古丁含量大大低于烟末浸膏中的含量,新植二烯的含量则较高;两种浸膏在制备过程中都有少量其他醇类引入。这些特征为充分利用天然资源、开发烟用香精提供科学依据。

Processing impact on volatile compounds profile in higholeic and normal peanut oil

With the improvement of living quality, high-oleic peanuts have drawn people’s attention. Increasing oleic acid content of peanut oil should be desired for improving shelf life and potential health benefits. The flavor is among the most important quality attributes for commercial acceptance of peanuts products. The volatile components of high-oleic pea-nuts oil and normal-oleic lines were compared in this research. First, volatile components of peanut oils were analyzed and identified by solid-phase microextraction/gas chroma- tography/mass spectrometry （SPME/GC/MS）. Then principal components analysis （PCA） was used to identify principal volatile components in peanut oils of different cultivars fo卜 lowing three different processing methods, including roasting, boiling and roasting, and roasting by microwave-assisted. The results showed that there were obvious differences of the volatile components between high-oleic and normal peanut oils. Among different pro-cessing method of peanuts, there was no clear separation on volatile components observed between roasting and boiling and roasting by microwave-assisted. Moreover, the same genotype had the similar flavor characteristic. Different processing methods had no signifi-cant effect on volatile components in peanut oils.

A study revealing the key aroma compounds of steamed bread made by Chinese traditional sourdough

Aroma of Chinese steamed bread（CSB） is one of the important parameters that determines the overall quality attributes and consumer acceptance. However, the aroma profile of CSB still remains poorly understood, mainly because of relying on only a single method for aroma extraction in previous studies. Therefore, the objective of this study was to determine the volatile aroma compounds of five different samples of CSB using three different aroma extraction methods, namely solid-phase microextraction（SPME）, simultaneous distillation–extraction（SDE）, and purge and trap（PT）. All samples showed a unique aroma profile, which could be attributed to their unique microbial consortia.（E）-2-Nonenal and（E,E）-2,4-decadienal were the most prevalent aromatic compounds revealed by SDE, which have not been reported previously, while ethanol and acetic acid proved to be the most dominant compounds by both SPME and PT. Our approach of combining three different aroma extraction methods provided better insights into the aroma profile of CSB, which had remained largely unknown in previous studies.

QSRR Study of GC Retention Indices of Volatile Compounds Emitted from Mosla chinensis Maxim by Multiple Linear Regression

The volatile compounds emitted from Mosla chinensis Maxim were analyzed by headspace solid-phase micro- extraction （HS-SPME） and headspace liquid-phase microextraction （HS-LPME） combined with gas chromatography-mass spectrometry （GC-MS）. The main volatiles from Mosla chinensis Maxim were studied in this paper. It can be seen that 61 compounds were separated and identified. Forty-nine volatile compounds were identified by SPME method, mainly including myrcene, a-terpinene, p-cymene, （E）-ocimene, thymol, thymol acetate and （E）-fl-farnesene. Forty-five major volatile compounds were identified by LPME method, including a-thujene, a-pinene, camphene, butanoic acid, 2-methylpropyl ester, myrcene, butanoic acid, butyl ester, a-terpinene, p-cymene, （E）-ocimene, butane, 1,1-dibutoxy-, thymol, thymol acetate and （E）-fl-farnesene. After analyzing the volatile compounds, multiple linear regression （MLR） method was used for building the regression model. Then the quantitative structure-retention relationship （QSRR） model was validated by predictive-ability test. The prediction results were in good agreement with the experimental values. The results demonstrated that headspace SPME-GC-MS and LPME-GC-MS are the simple, rapid and easy sample enrichment technique suitable for analysis of volatile compounds. This investigation provided an effective method for predicting the retention indices of new compounds even in the absence of the standard candidates.