Online trapping and enrichment ultra performance liquid chromatography–tandem mass spectrometry method for sensitive measurement of “arginine-asymmetric dimethylarginine cycle” biomarkers in human exhaled breath condensate

Background

Exhaled breath condensate (EBC) is a biofluid collected non invasively that, enabling the measurement of several biomarkers, has proven useful in the study of airway inflammatory diseases, including asthma, COPD and cystic fibrosis. To the best of our knowledge, there is no previous report of any analytical method to detect ADMA in EBC.

Objectives

Aim of this work was to develop an online sample trapping and enrichment system, coupled with an UPLC–MS/MS method, for simultaneous quantification of seven metabolites related to “Arginine-ADMA cycle”, using the isotopic dilution.

Methods

Butylated EBC samples were trapped in an online cartridge, washed before and after each injection with cleanup solution to remove matrix components and switched inline into the high pressure analytical column. Multiple reaction monitoring in positive mode was used for analyte quantification by tandem mass spectrometry.

Results

Validation studies were performed in EBC to examine accuracy, precision and robustness of the method. For each compound, the calibration curves showed a coefficient of correlation (r²) greater than 0.992. Accuracy (%Bias) was <3% except for NMMA and H-Arg (<20%), intra- and inter-assay precision (expressed as CV%) were within ±20% and recovery ranged from 97.1 to 102.8% for all analytes.Inter-day variability analysis on 20 EBC of adult subjects did not demonstrate any significant variation of quantitative data for each metabolite. ADMA and SDMA mean concentrations (μmol L⁻¹), measured in EBC samples of asthmatic adolescents are significantly increased (p < 0.0001) than in normal controls (0.0040 ± 0.0021 vs. 0.0012 ± 0.0005 and 0.0020 ± 0.0015 vs. 0.0002 ± 0.0001, respectively), as well the ADMA/Tyr (0.34 ± 0.09 vs. 0.12 ± 0.02, p < 0.0001) and the SDMA/Tyr ratio (0.10 ± 0.04 vs. 0.015 ± 0.004, p < 0.0001).

Conclusions

The proposed method features simple specimen preparation, maintenance of an excellent peak shape of all metabolites and reduced matrix effects as well mass spectrometer noise. Moreover, the possibility to perform different cycles of enrichment, using large injection volumes, compensated for the low concentration of analytes contained in EBC, leading to a good analytical sensitivity. Preliminary data obtained from asthmatic and healthy adolescents, demonstrated that the analytical method applied to EBC seems suitable not only for research purposes, but also for clinical routinely analysis.     

13C-aminopyrine demethylation is decreased in cirrhotic patients with normal biochemical markers

This study determined the rates of ¹³C-aminopyrine metabolism in patients with varying degrees of liver cirrhosis as defined by clinical scores. Twenty-five cirrhotic patients and 18 healthy subjects underwent a ¹³C-aminopyrine breath test. The cumulative per cent dose recovery (cPDR) of ¹³C on breath expressed as a percentage of the administered dose at 2 h was significantly lower in cirrhotic patients than in healthy subjects (median: 1.7% versus 9.0%; p<.0001). Significant inverse associations between cPDR at 2 h and the model for end-stage liver disease score, Child–Pugh score, international normalised ratio and bilirubin (all p<.05), but not alanine aminotransferase or alkaline phosphatase were observed in the cirrhotic patients. Taking each biochemical marker independently, cirrhotic patients with normal biochemistry had a significantly lower cPDR at 2 h than healthy subjects (all p<.05). Differences in ¹³C-aminopyrine metabolism were evident in cirrhotic patients with less severe disease and may mark hepatic dysfunction when conventional biochemical markers appear unchanged.     

Chromatographic analysis of VOC patterns in exhaled breath from smokers and nonsmokers

Cigarette smoking harms nearly every organ of the body and causes many diseases. The analysis of exhaled breath for exogenous and endogenous volatile organic compounds (VOCs) can provide fundamental information on active smoking and insight into the health damage that smoke is creating. Various exhaled VOCs have been reported as typical of smoking habit and recent tobacco consumption, but to date, no eligible biomarkers have been identified. Aiming to identify such potential biomarkers, in this pilot study we analyzed the chemical patterns of exhaled breath from 26 volunteers divided into groups of nonsmokers and subgroups of smokers sampled at different periods of withdrawal from smoking. Solid‐phase microextraction technique and gas chromatography/mass spectrometry methods were applied. Many breath VOCs were identified and quantified in very low concentrations (ppbv range), but only a few (toluene, pyridine, pyrrole, benzene, 2‐butanone, 2‐pentanone and 1‐methyldecyclamine) were found to be statistically significant variables by Mann–Whitney test. In our analysis, we did not consider the predictive power of individual VOCs, as well as the criterion of uniqueness for biomarkers suggests, but we used the patterns of the only statistically significant compounds. Probit prediction model based on statistical relevant VOCs‐patterns showed that assessment of smoking status is heavily time dependent. In a two‐class classifier model, it is possible to predict with high specificity and sensitivity if a subject is a smoker who respected 1 hour of abstinence from smoking (short‐term exposure to tobacco) or a smoker (labelled "blank smoker") after a night out of smoking (long‐term exposure to tobacco). On the other side, in our study "blank smokers" are more like non‐smokers so that the two classes cannot be well distinguished and the corresponding prediction results showed a good sensitivity but low selectivity.     

Identification and quantification of VOCs by proton transfer reaction time of flight mass spectrometry: An experimental workflow for the optimization of specificity,sensitivity, and accuracy

Proton transfer reaction time of flight mass spectrometry (PTR‐ToF‐MS) is a direct injection MS technique, allowing for the sensitive and real‐time detection, identification, and quantification of volatile organic compounds. When aiming to employ PTR‐ToF‐MS for targeted volatile organic compound analysis, some methodological questions must be addressed, such as the need to correctly identify product ions, or evaluating the quantitation accuracy. This work proposes a workflow for PTR‐ToF‐MS method development, addressing the main issues affecting the reliable identification and quantification of target compounds. We determined the fragmentation patterns of 13 selected compounds (aldehydes, fatty acids, phenols). Experiments were conducted under breath‐relevant conditions (100% humid air), and within an extended range of reduced electric field values (E/N = 48–144 Td), obtained by changing drift tube voltage. Reactivity was inspected using H₃O⁺, NO⁺, and O₂⁺ as primary ions. The results show that a relatively low (<90 Td) E/N often permits to reduce fragmentation enhancing sensitivity and identification capabilities, particularly in the case of aldehydes using NO⁺, where a 4‐fold increase in sensitivity is obtained by means of drift voltage reduction. We developed a novel calibration methodology, relying on diffusion tubes used as gravimetric standards. For each of the tested compounds, it was possible to define suitable conditions whereby experimental error, defined as difference between gravimetric measurements and calculated concentrations, was 8% or lower.     

ZnO-WO_3纳米材料催化化学发光法测定呼吸气中的丙酮

研究发现丙酮可在Zn O/WO3复合纳米材料表面产生强烈的化学发光现象。在考察波长、温度、流速等因素对该发光反应影响的基础上,设计了一种可测定糖尿病人呼吸气中丙酮的传感器。该传感器测定丙酮浓度的线性范围为0.025 9~5.18 mg/L,检出限为0.013 mg/L。呼吸气中其余气体如二氧化碳、氨气和水蒸气等不干扰测定。经连续60 h通过1.30 mg/L丙酮蒸气,26次测定结果的相对标准偏差(RSD)为3.6%,表明该传感器具有较好的使用寿命。     

甲醇气氛静态呼吸图法制备蜂窝状有序多孔膜

以原子转移自由基聚合方法合成的聚二甲基硅氧烷-b-聚苯乙烯(PDMS-b-PS)为铸膜材料,在静态呼吸图的基础上,首次在甲醇氛围下利用PDMS-b-PS的二硫化碳溶液铸膜得到了高度规整的蜂窝状有序多孔结构.研究了聚合物溶液浓度对孔径的影响,并与水蒸汽氛围制备的孔结构进行了比较.结果表明,甲醇气氛下制备的多孔膜的孔径比水蒸汽氛围下的大,且孔的断面形貌呈“U”形;孔径随着溶液浓度的增大而减小.该研究有利于呼吸图法制备有序结构材料技术的进一步发展,有助于人们更加准确与全面地认识呼吸图机理.     

The Impact of a Graded Maximal Exercise Protocol on Exhaled Volatile Organic Compounds: A Pilot Study

Exhaled volatile organic compounds (VOCs) are of interest due to their minimally invasive sampling procedure. Previous studies have investigated the impact of exercise, with evidence suggesting that breath VOCs reflect exercise-induced metabolic activity. However, these studies have yet to investigate the impact of maximal exercise to exhaustion on breath VOCs, which was the main aim of this study. Two-litre breath samples were collected onto thermal desorption tubes using a portable breath collection unit. Samples were collected pre-exercise, and at 10 and 60 min following a maximal exercise test (VO_2MAX). Breath VOCs were analysed by thermal desorption-gas chromatography-mass spectrometry using a non-targeted approach. Data showed a tendency for reduced isoprene in samples at 10 min post-exercise, with a return to baseline by 60 min. However, inter-individual variation meant differences between baseline and 10 min could not be confirmed, although the 10 and 60 min timepoints were different (p = 0.041). In addition, baseline samples showed a tendency for both acetone and isoprene to be reduced in those with higher absolute VO_2MAX scores (mL(O₂)/min), although with restricted statistical power. Baseline samples could not differentiate between relative VO_2MAX scores (mL(O₂)/kg/min). In conclusion, these data support that isoprene levels are dynamic in response to exercise.     

基于气相离子迁移谱研究肺隐球病患者呼出气中特征挥发性有机物

该文采用气相色谱离子迁移谱(GC-IMS)对81例受试者呼出气样品进行了检测,包括临床确诊的20例肺隐球菌病患者,以及28例临床确诊的肺曲霉病患者和33例健康个体的对照样品,单个样品分析仅需10 min。结果显示,所有呼气样品中共检出19种挥发性有机物(VOCs)。通过主成分(PCA)分析发现,肺隐球病患者呼气中VOCs与健康对照组差异显著,但与肺曲霉病患者呼气中VOCs差异不显著。正交偏最小二乘判别模型(OPLS-DA)分析显示,与健康人群相比,肺隐球菌病患者呼气中特征VOCs为2-甲基-1-丙醛、异丙苯、2-戊酮、4-甲基-2-戊酮、丁醛和己醛;肺曲霉病患者的呼气特征VOCs为2-丁酮、2-戊酮、异丙苯、2-甲基-1-丙醛、4-甲基-2-戊酮和3-戊酮。此外,2种肺部感染患者呼气中特征性VOCs均包括2-甲基-1-丙醛、异丙苯、4-甲基-2-戊酮和2-戊酮,这表明丁醛和己醛在肺隐球菌病患者呼气中特异性略强,而2-丁酮和3-戊酮在肺曲霉病患者呼气中特异性更好。综上,采用GC-IMS可快速检出肺隐球病患者呼气中的VOCs,可用于后续数百例甚至数千例大样本分析,为更客观地评价呼气用于肺部真菌感染诊断的可行性提供必要的基础数据。     

Effect of polar groups of polystyrenes on the self-assembly of breath figure arrays

The breath figure (BF) process has been widely used to prepare patterned porous films. The mechanism remains to be further elucidated, especially how polymer architectures affect the stability of water droplets and the pore structure. Polystyrenes (PS) was functionalized with a series of polar groups both in chain middle and chain end, which was synthesized by using difunctional atom transfer radical polymerization (ATRP) initiators with the combination of nucleophilic substitution of the end bromine. It is found that PS with polar groups, which help to reduce interfacial tension, tends to form regular patterns at low concentration and to generate multilayered pores. The coalescence resistance measurement was performed to characterize the stabilization of water droplets from polymers by precipitation. The results show opposite trend with the results of the BF process, indicating a minor role played by polymer precipitation on microdroplets stabilization. We reveal that addition of only an oxyethyl group in the chain middle of PS contributes to the formation of ordered patterns. This study helps to shed light on the impact of polymer architectures on the self-assembly behavior in the BF process.     

Needle Trap Device-GC-MS for Characterization of Lung Diseases Based on Breath VOC Profiles

Volatile organic compounds (VOCs) have been assessed in breath samples as possible indicators of diseases. The present study aimed to quantify 29 VOCs (previously reported as potential biomarkers of lung diseases) in breath samples collected from controls and individuals with lung cancer, chronic obstructive pulmonary disease and asthma. Besides that, global VOC profiles were investigated. A needle trap device (NTD) was used as pre-concentration technique, associated to gas chromatography-mass spectrometry (GC-MS) analysis. Univariate and multivariate approaches were applied to assess VOC distributions according to the studied diseases. Limits of quantitation ranged from 0.003 to 6.21 ppbv and calculated relative standard deviations did not exceed 10%. At least 15 of the quantified targets presented themselves as discriminating features. A random forest (RF) method was performed in order to classify enrolled conditions according to VOCs’ latent patterns, considering VOCs responses in global profiles. The developed model was based on 12 discriminating features and provided overall balanced accuracy of 85.7%. Ultimately, multinomial logistic regression (MLR) analysis was conducted using the concentration of the nine most discriminative targets (2-propanol, 3-methylpentane, (E)-ocimene, limonene, m-cymene, benzonitrile, undecane, terpineol, phenol) as input and provided an average overall accuracy of 95.5% for multiclass prediction.