纳米材料在用于癌症诊断的呼出气挥发性有机物检测中的应用

细胞新陈代谢的变化会导致挥发性有机化合物（VOCs）类型及含量发生变化,因此可通过分析某些标志性VOCs简立起多种疾病早期诊断的模型. 人体呼出物中特征VOCs的检测作为一种非侵入性、无损的检测手段,近些年在疾病检测领域已成为世界范围内的研究热点. 其中,纳米材料可用于增强传感器性能,并使传感器便携式小型化,推进检测传感器进入临床. 在这篇综述中,作者将种类繁多的传感器中用到的纳米材料归纳总结为金属、金属氧化物、碳基、复合物和MOFs基纳米材料等几类,并讨论了不同类纳米材料在VOCs检测中的优劣势. 本文所建立起的分析方法及讨论有助于进一步了解检测技术的优越性与局限性. 最后,作者对利用VOCs的检测实现癌症早期筛选的研究及发展提出了个人观点.     

Comparison of Targeted and Untargeted Approaches in Breath Analysis for the Discrimination of Lung Cancer from Benign Pulmonary Diseases and Healthy Persons

The aim of the present study was to compare the efficiency of targeted and untargeted breath analysis in the discrimination of lung cancer (Ca+) patients from healthy people (HC) and patients with benign pulmonary diseases (Ca−). Exhaled breath samples from 49 Ca+ patients, 36 Ca− patients and 52 healthy controls (HC) were analyzed by an SPME–GC–MS method. Untargeted treatment of the acquired data was performed with the use of the web-based platform XCMS Online combined with manual reprocessing of raw chromatographic data. Machine learning methods were applied to estimate the efficiency of breath analysis in the classification of the participants. Results: Untargeted analysis revealed 29 informative VOCs, from which 17 were identified by mass spectra and retention time/retention index evaluation. The untargeted analysis yielded slightly better results in discriminating Ca+ patients from HC (accuracy: 91.0%, AUC: 0.96 and accuracy 89.1%, AUC: 0.97 for untargeted and targeted analysis, respectively) but significantly improved the efficiency of discrimination between Ca+ and Ca− patients, increasing the accuracy of the classification from 52.9 to 75.3% and the AUC from 0.55 to 0.82. Conclusions: The untargeted breath analysis through the inclusion and utilization of newly identified compounds that were not considered in targeted analysis allowed the discrimination of the Ca+ from Ca− patients, which was not achieved by the targeted approach.     

人体呼出气分析的技术进展及其在非侵入式医学诊断方面的临床应用前景

人体呼出气被视为血液顶空气体,通过肺泡交换排出体外,可在一定程度上反映人体的内源代谢情况。近些年,随着医学诊断无损化的不断发展,呼出气分析由于其无创性,无痛性,便捷性,具有临床疾病早期诊断与大规模筛查的潜力,受到越来越多的关注。研究表明,呼出气中包含的挥发性有机化合物和人体的疾病代谢状态密切相关,如丙酮与糖尿病,醛类物质与乳腺癌,烷烃类与氧化应激水平等。现代分析方法(如气相色谱、质谱、光谱、传感器等)对呼出气中上千种痕量组分的定性定量分析,使得呼出气分析成为可能。此文总结了呼出气分析的技术发展:样品采集手段,预富集技术和定性定量分析技术。评价了呼出气生物标识物在糖尿病,乳腺癌,以及肺癌等疾病中的临床诊断前景。最后讨论了呼出气分析的技术在国内的发展现状及其面临的主要问题。     

Comprehensive Two-Dimensional Gas Chromatography–Mass Spectrometry Analysis of Exhaled Breath Compounds after Whole Grain Diets

Exhaled breath is a potential noninvasive matrix to give new information about metabolic effects of diets. In this pilot study, non-targeted analysis of exhaled breath volatile organic compounds (VOCs) was made by comprehensive two-dimensional gas chromatography–mass spectrometry (GCxGC-MS) to explore compounds relating to whole grain (WG) diets. Nine healthy subjects participated in the dietary intervention with parallel crossover design, consisting of two high-fiber diets containing whole grain rye bread (WGR) or whole grain wheat bread (WGW) and 1-week control diets with refined wheat bread (WW) before both diet periods. Large interindividual differences were detected in the VOC composition. About 260 VOCs were detected from exhaled breath samples, in which 40 of the compounds were present in more than half of the samples. Various derivatives of benzoic acid and phenolic compounds, as well as some furanones existed in exhaled breath samples only after the WG diets, making them interesting compounds to study further.     

Searching for Potential Markers of Glomerulopathy in Urine by HS-SPME-GC×GC TOFMS

Volatile organic compounds (VOCs) exiting in urine are potential biomarkers of chronic kidney diseases. Headspace solid phase microextraction (HS-SPME) was applied for extraction VOCs over the urine samples. Volatile metabolites were separated and identified by means of two-dimensional gas chromatography and time of flight mass spectrometry (GC × GC TOF MS). Patients with glomerular diseases (n = 27) and healthy controls (n = 20) were recruited in the study. Different VOCs profiles were obtained from patients and control. Developed methodology offers the opportunity to examine the metabolic profile associated with glomerulopathy. Four compounds found in elevated amounts in the patients group, i.e., methyl hexadecanoate; 9-hexadecen-1-ol; 6,10-dimethyl-5,9-undecadien-2-one and 2-pentanone were proposed as markers of glomerular diseases.     

Ultrafast gas chromatography coupled to electronic nose to identify volatile biomarkers in exhaled breath from chronic obstructive pulmonary disease patients: A pilot study

An analytical method to identify volatile organic compounds (VOCs) in the exhaled breath from patients with a diagnosis of chronic obstructive pulmonary disease (COPD) using a ultrafast gas chromatography system equipped with an electronic nose detector (FGC eNose) has been developed. A prospective study was performed in 23 COPD patients and 33 healthy volunteers; exhalation breathing tests were performed with Tedlar bags. Each sample was analyzed by FCG eNose and the identification of VOCs was based on the Kovats index. Raw data were reduced by principal component analysis (PCA) and canonical discriminant analysis [canonical analysis of principal coordinates (CAP)]. The FCG eNose technology was able to identify 17 VOCs that distinguish COPD patients from healthy volunteers. At all stages of PCA and CAP the discrimination between groups was obvious. Chemical prints were correctly classified up to 82.2%, and were matched with 78.9% of the VOCs detected in the exhaled breath samples. Receiver operating characteristic curve analysis indicated the sensitivity and specificity to be 96% and 91%, respectively. This pilot study demonstrates that FGC eNose is a useful tool to identify VOCs as biomarkers in exhaled breath from COPD patients. Further studies should be performed to enhance the clinical relevance of this quick and ease methodology for COPD diagnosis.     

纳米金-卟啉复合传感阵列快速识别肺癌患者呼气中的有机小分子

合成了小粒径纳米金作为卟啉保护剂,以纳米金-卟啉化合物和p H指示剂共同构建6×6传感阵列,将其用于可视化检测12种肺癌患者呼出气体中的有机小分子(OSMs),设置了3个浓度梯度且每个样品重复5次.实验结果显示,纳米金的引入可显著提高阵列的稳定性和灵敏度;聚类分析结果表明,5次平行实验的结果优先聚为一簇,结构相似的目标物随后聚在一起;差谱图显示该方法对不同种类、不同浓度的OSMs具有良好的定性及半定量分析能力.该方法可快速识别OSMs且具有肺癌筛查的潜在应用前景.     

大气有机物热脱附-全二维气相色谱-火焰离子化分析方法

全二维气相色谱（GC×GC）是20世纪90年代发展起来的具有高分辨率、高灵敏度、高峰容量等优势的分离技术,在我国将其用于大气挥发性有机物（VOCs）研究方面才刚刚起步.本文将GC-GC与氢火焰离子化检测器（FID）联用,构建了用于测量大气有机物的热脱附-全二维气相色谱-氢火焰离子化分析系统（TD-GC×GC-FID）.采用HP-5MS和HP-INNOWAX色谱柱,建立了C5-C15大气有机物分析方法,实现了一次分析过程同时分离非甲烷烃（NMHCs）、含氧挥发性有机物（OVOCs）和卤代烃等多种组分.利用标准物质和四级杆质谱（qMS）进行定性,外标法结合FID质量校正因子定量.目标物在GC-GC谱图中第一和第二维保留时间变化分别小于0.6s和0.02s,峰体积平均相对标准偏差为14.3%,其中烷烃和芳香烃为4.5%.标准曲线r2均值大于0.99,平均检出限为6.04ng,平均回收率为111%.利用该方法检测到2010年1月北京市区大气中400多种有机物（信噪比大于50）,鉴定了其中的103种物质,包括烷烃、烯烃、芳香烃、卤代烃、醛、酮、酯、醇和醚等.所测定有机物平均总浓度为51.3×10-9V/V,其中OVOCs约占51%,芳香烃约占30%,烷烃约占15%,卤代烃和烯烃分别占3%和1%.平均浓度最高的前3个组分是乙醇（9.84×10-9V/V）、丙酮（6.72×10-9V/V）和甲苯（3.48×10-9V/V）.     

密闭舱内VOCs现场快速定量检测技术与装置研究

该文发展了可对压强变化的密封舱实现计量采样-富集的采样技术,基于薄壳金属筒式低功耗均温色谱柱组件,结合微池热导检测器/小型氢火焰离子化检测器,建立了一种对密闭舱内挥发性有机物(VOCs)进行现场快速定量检测的方法和装置.根据负压罐和密封舱的压强差值和绝压值以及温度,计算出有效采样体积(折算到标准大气压),进而计算出富集...