Volatile Organic Compounds Markers Research Articles

Volatile organic compounds produced by thermophilic and non-thermophilic ampylobacter spp.: Influence of growth phase and nutrient composition

Bacteria produce a plethora of volatile organic compounds (VOCs) into the atmosphere as a means of interacting with their habitats, as well as for intra- and interkingdom communication, and to survive and thrive in nature and inside their hosts. Campylobacter, which is commonly found in poultry and ruminants, has demonstrated remarkable endurance in aquatic settings, making it one of the world's most hazardous foodborne pathogens that kill thousands of humans every year. In the present work, the VOCs released by both thermophilic (C. jejuni, C. coli, and C. lari) and non-thermophilic (C. fetus) Campylobacter of clinical significance, which were influenced by nutrient composition (media) and growth phase, were profiled using an active sampling approach, with active charcoal adsorbent and gas chromatography-mass spectrometry. Alcohols and ketones were detected only in the thermophilic Campylobacter strains, C. jejuni subsp. jejuni (1-heptadecanol; 1,8-nonadien-3-ol; 3,7,11-trimethyl-3-dodecanol; 1s,4R,7R,11R-1,3,4,7-tetramethyltricyclo [5.3.1.0(4,11)] undec-2-en-8-one; and isophorone), C. coli (isophorone and 3,5-bis(1,1-dimethylethyl)-phenol), and C. lari (3,7,11-trimethyl-3-dodecanol and 1s,4R,7R,11R-1,3,4,7-tetramethyltricyclo [5.3.1.0(4,11)] undec-2-en-8-one) between early stationary and stationary growth phases. The non-thermophilic C. fetus produced only a range of unidentified compounds that need to be investigated further in the future. The results from the principal component analysis showed distinctive clustering of VOC markers between the four bacteria taxa and within the strains of C. jejuni, including distinguishable groupings of VOCs throughout the growth phase of each bacterium and between different culture media. This demonstrates the influence of bacterial growth and media composition on the volatilome of the studied Campylobacter spp. Overall, the VOC profiling of these foodborne pathogens, under influencing factors of growth phase and media, paves the way for future rapid identification of Campylobacter spp. in food matrices.

Comparative study of volatile organic compound profiles in aromatic and non-aromatic rice cultivars using HS-GC–IMS and their correlation with sensory evaluation

Analyzing of volatile organic compounds (VOCs) is important in rice quality control and breeding aromatic cultivars. This study utilized HS-GC–IMS, known for its simplicity, high sensitivity, and low cost, to analyze VOCs in 59 aromatic and 6 non-aromatic rice cultivars. The aromatic intensity of each rice cultivar was determined by artificial sensory evaluation, thus the correlation between sensory evaluation scores and VOC peak volumes was explored. A total of 77 VOCs were identified, with aromatic cultivars exhibiting prevalent short-chain aliphatic aldehydes, alcohols, and ketones, while non-aromatic samples contained higher concentrations of esters, furans, terpenes, and benzene derivatives. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) based on VOC data effectively distinguished the two rice types, and 35 VOCs were regarded as the marker VOCs contributing to the volatile variations. Furthermore, the correlation analysis between sensory evaluation and VOC markers revealed that most of these VOCs had a positive correlation with the sensory evaluation scores, with 1-pentanol, 2-acetyl-1-pyrroline (D), and 1-hexanol (M) exhibiting the highest correlation coefficients. Meanwhile, most VOC markers also exhibited positive correlations with other volatiles. The results confirm the suitability of HS-GC–IMS for VOC detection and rice category discrimination.

Portable hydrogel kit based on Michael addition reaction for (E)-2-hexenal gas detection

Plants exhibit rapid responses to biotic and abiotic stresses by releasing a range of volatile organic compounds (VOCs). Monitoring changes in these VOCs holds the potential for the early detection of plant diseases. This study proposes a method for identifying late blight in potatoes based on the detection of (E)-2-hexenal, one of the major VOC markers released during plant infection by Phytophthora infestans. By combining the Michael addition reaction with cysteine-mediated etching of aggregation-induced emission gold nanoclusters (Au NCs), we have developed a portable hydrogel kit for on-site detection of (E)-2-hexenal. The Michael addition reaction between (E)-2-hexenal and cysteine effectively alleviates the etching of cysteine-mediated Au NCs, leading to a distinct fluorescence color change in the Au NCs, enabling a detection limit of 0.61 ppm. Utilizing the superior loading and diffusion characteristics of the three-dimensional structure of agarose hydrogel, our sensor demonstrated exceptional performance in terms of sensitivity, selectivity, reaction time, and ease of use. Moreover, quantitative measurement of (E)-2-hexenal was made easier by using ImageJ software to transform fluorescent images from the hydrogel kit into digital data. Such method was effectively used for the early detection of potato late blight. This study presents a low-cost, portable fluorescent analytical tool, offering a new avenue for on-site detection of plant diseases.

A better representation of volatile organic compound chemistry in WRF-Chem and its impact on ozone over Los Angeles

Abstract. The declining trend in vehicle emissions has underscored the growing significance of volatile organic compound (VOC) emissions from volatile chemical products (VCPs). However, accurately representing VOC chemistry in simplified chemical mechanisms remains challenging due to its chemical complexity including speciation and reactivity. Previous studies have predominantly focused on VOCs from fossil fuel sources, leading to an underrepresentation of VOC chemistry from VCP sources. We developed an integrated chemical mechanism, RACM2B-VCP, that is compatible with WRF-Chem and is aimed at enhancing the representation of VOC chemistry, particularly from VCP sources, within the present urban environment. Evaluation against the Air Quality System (AQS) network data demonstrates that our model configured with RACM2B-VCP reproduces both the magnitude and spatial variability of O3 and PM2.5 in Los Angeles. Furthermore, evaluation against comprehensive measurements of O3 and PM2.5 precursors from the Reevaluating the Chemistry of Air Pollutants in California (RECAP-CA) airborne campaign and the Southwest Urban NOx and VOC Experiment (SUNVEx) ground site and mobile laboratory campaign confirm the model's accuracy in representing NOx and many VOCs and highlight remaining biases. Although there exists an underprediction in the total VOC reactivity of observed VOC species, our model with RACM2B-VCP exhibits good agreement for VOC markers emitted from different sectors, including biogenic, fossil fuel, and VCP sources. Through sensitivity analyses, we probe the contributions of VCP and fossil fuel emissions to total VOC reactivity and O3. Our results reveal that 52 % of the VOC reactivity and 35 % of the local enhancement of MDA8 O3 arise from anthropogenic VOC emissions in Los Angeles. Significantly, over 50 % of this anthropogenic fraction of either VOC reactivity or O3 is attributed to VCP emissions. The RACM2B-VCP mechanism created, described, and evaluated in this work is ideally suited for accurately representing ozone for the right reasons in the present urban environment where mobile, biogenic, and VCP VOCs are all important contributors to ozone formation.

Identification and biotransformation analysis of volatile markers during the early stage of Salmonella contamination in chicken

Salmonella is one of the most prevalent foodborne pathogens in poultry and its products. Its rapid detection based on volatile organic compounds (VOC) has been widely accepted. However, the variation in the VOCs of Salmonella-contaminated chicken during the early stage (48 h) remains uncertain. Headspace-SPME-gas chromatography-mass spectrometry (HS-SPME-GC–MS) and headspace-gas chromatography-ion migration spectroscopy (HS-GC-IMS) were used to identify VOCs and their variations after the chicken meat was contaminated with Salmonella. Chemometric and KEGG enrichment analyses were performed to identify VOC markers and their potential metabolic pathways. A total of 64 volatile compounds were detected using HS-GC-IMS, which showed a better differentiation than HS-SPME-GC–MS (45 volatile compounds) based on principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA). Fatty acid degradation was the main cause of VOC variation. 2-Propanol, hexadecane, 3-methylbutanol, acetic acid, propyl acetate, acetic acid methyl ester, and 3-butenenitrile were identified as VOC markers in the middle stage of decomposition, and 1-octen-3-ol was recognized as a VOC marker of Salmonella-contaminated chicken during the first 48 h of contamination. This provides a theoretical basis for the study of Salmonella contamination VOC markers in poultry meat.

Data-driven design of a multiplexed, peptide-sensitized transistor to detect breath VOC markers of COVID-19.

Exhaled human breath contains a rich mixture of volatile organic compounds (VOCs) whose concentration can vary in response to disease or other stressors. Using simulated odorant-binding proteins (OBPs) and machine learning methods, we designed a multiplex of short VOC- and carbon-binding peptide probes that detect a characteristic "VOC fingerprint". Specifically, we target VOCs associated with COVID-19 in a compact, molecular sensor array that directly transduces vapor composition into multi-channel electrical signals. Rapidly synthesizable, chimeric VOC- and solid-binding peptides were derived from selected OBPs using multi-sequence alignment with protein database structures. Selective peptide binding to targeted VOCs and sensor surfaces was validated using surface plasmon resonance spectroscopy and quartz crystal microbalance. VOC sensing was demonstrated by peptide-sensitized, exposed-channel carbon nanotube transistors. The data-to-device pipeline enables the development of novel devices for non-invasive monitoring, diagnostics of diseases, and environmental exposure assessment.

Two years of volatile organic compound online in situ measurements at the Site Instrumental de Recherche par Télédétection Atmosphérique (Paris region, France) using proton-transfer-reaction mass spectrometry

Abstract. Volatile organic compounds (VOCs) have direct influences on air quality and climate. They indeed play a key role in atmospheric chemistry as precursors of secondary pollutants, such as ozone (O3) and secondary organic aerosols (SOA). In this respect, long-term datasets of in situ atmospheric measurements are crucial for characterizing the variability of atmospheric chemical composition, its sources, and trends. The ongoing establishment of the Aerosols, Cloud, and Trace gases Research InfraStructure (ACTRIS) allows implementation of the collection and provision of such high-quality datasets. In this context, online and continuous measurements of O3, nitrogen oxides (NOx), and aerosols have been carried out since 2012 at the SIRTA (Site Instrumental de Recherche par Télédétection Atmosphérique) observatory, located in the Paris region, France. Within the last decade, VOC measurements were conducted offline at SIRTA, until the implementation of real-time monitoring which started in January 2020 using a proton-transfer-reaction quadrupole mass spectrometer (PTR-Q-MS). The dataset acquired during the first 2 years of online VOC measurements provides insights into their seasonal and diurnal variabilities. The additional long-term datasets obtained from co-located measurements (NOx, aerosol physical and chemical properties, meteorological parameters) are used to better characterize the atmospheric conditions and to further interpret the obtained results. Results also include insights into VOC main sources and the influence of meteorological conditions and air mass origin on their levels in the Paris region. Due to the COVID-19 pandemic, the year 2020 notably saw a quasi-total lockdown in France in spring and a lighter one in autumn. Therefore, the focus is placed on the impact of these lockdowns on the VOC variability and sources. A change in the behaviour of VOC markers for anthropogenic sources was observed during the first lockdown, reflecting a change in human activities. A comparison with gas chromatography data from the Paris city centre consolidates the regional representativity of the SIRTA station for benzene, while differences are observed for shorter-lived compounds with a notable impact of their local sources. This dataset could be further used as input for atmospheric models and can be found at https://doi.org/10.14768/f8c46735-e6c3-45e2-8f6f-26c6d67c4723 (Simon et al., 2022a).

Multigroup prediction in lung cancer patients and comparative controls using signature of volatile organic compounds in breath samples.

Early detection of lung cancer is a crucial factor for increasing its survival rates among the detected patients. The presence of carbonyl volatile organic compounds (VOCs) in exhaled breath can play a vital role in early detection of lung cancer. Identifying these VOC markers in breath samples through innovative statistical and machine learning techniques is an important task in lung cancer research. Therefore, we proposed an experimental approach for generation of VOC molecular concentration data using unique silicon microreactor technology and further identification and characterization of key relevant VOCs important for lung cancer detection through statistical and machine learning algorithms. We reported several informative VOCs and tested their effectiveness in multi-group classification of patients. Our analytical results indicated that seven key VOCs, including C4H8O2, C13H22O, C11H22O, C2H4O2, C7H14O, C6H12O, and C5H8O, are sufficient to detect the lung cancer patients with higher mean classification accuracy (92%) and lower standard error (0.03) compared to other combinations. In other words, the molecular concentrations of these VOCs in exhaled breath samples were able to discriminate the patients with lung cancer (n = 156) from the healthy smoker and nonsmoker controls (n = 193) and patients with benign pulmonary nodules (n = 65). The quantification of carbonyl VOC profiles from breath samples and identification of crucial VOCs through our experimental approach paves the way forward for non-invasive lung cancer detection. Further, our experimental and analytical approach of VOC quantitative analysis in breath samples may be extended to other diseases, including COVID-19 detection.

Leaf Volatiles and Relevant Gene Expression as the Specific Characteristics in Citrus depressa Accession Discrimination

Citrus depressa Hayata is the native and widespread citrus species in Taiwan. The notable character is that C. depressa has a distinct aroma different from local citrus. The ex situ germplasm of scions from different collection regions has variant leaf shapes and different odor characteristics. Establishing volatile biomarkers for classifying the local C. depressa is beneficial to commercial development. Volatile organic compounds (VOCs) of fresh leaves from seven C. depressa accessions which were collected from different locations in Taiwan were extracted by headspace solid-phase microextraction and analyzed by GC-MS. The volatile compositions from each season showed the diversity, and linalool, of which the average relative content is 52.7%, was the most volatile component in any season. The other main VOCs of leaves of C. depressa were γ-terpinene, limonene, β-ocimene, and α-terpineol. The result of linear discriminant analysis by VOC markers shows that there are two main different types which are (1) accessions from the central and the east of Taiwan and (2) accessions which are closer to C. depressa in Okinawa, Japan. Five major VOC-related synthase genes were selected and the gene expression was used to classify the varieties. The clustering result is the same with VOC-based discrimination. Our results reveal leaf volatile profiling is capable of being the discrimination markers, and the possibility for constructing molecular markers is directly related to characteristics from secondary metabolites phenotyping.

Wintertime haze and ozone at Dinosaur National Monument

ABSTRACT Dinosaur National Monument (DINO) is located near the northeastern edge of the Uinta Basin and often experiences elevated levels of wintertime ground-level ozone. Previous studies have shown that high ozone mixing ratios in the Uinta Basin are driven by elevated levels of volatile organic compounds (VOCs) and nitrogen oxides (NOx) from regional oil and gas development coupled with temperature inversions and enhanced photochemistry from persistent snow cover. Here, we show that persistent snow cover and temperature inversions, along with abundant ammonia, also lead to wintertime haze in this region. A study was conducted at DINO from November 2018 through May 2020 where ozone, speciated fine and coarse aerosols, inorganic gases, and VOCs were measured. Three National Ambient Air Quality Standards (NAAQS) ozone exceedances were observed in the first winter, and no exceedances were observed in the second winter. In contrast, elevated levels of particulate matter were observed both winters, with 24-h averaged particle light extinction exceeding 100 Mm−1. These haze events were dominated by ammonium nitrate, and particulate organics were highly correlated with ammonium nitrate. Ammonium nitrate formation was limited by nitric acid in winter. As such, reductions in regional NOx emissions should reduce haze levels and improve visibility at DINO in winter. Long-term measurements of particulate matter from nearby Vernal, Utah, suggest that visibility impairment is a persistent issue in the Uinta Basin in winter. From April through October 2019, relatively clean conditions occurred, with average particle extinction of ~10 Mm−1. During this period, ammonium nitrate concentrations were lower by more than an order of magnitude, and contributions from coarse mass and soil to haze levels increased. VOC markers indicated that the high levels of observed pollutants in winter were likely from local sources related to oil and gas extraction activities. Implications: Elevated ground-level ozone and haze levels were observed at Dinosaur National Monument in winter. Haze episodes were dominated by ammonium nitrate, with 24-h averaged particle light extinction exceeding 100 Mm−1, reducing visual range near the surface to ~35 km. Despite elevated ammonium nitrate concentrations, additional gas-phase ammonia was available, such that any increase in NOx emissions in the region is likely to lead to even greater haze levels.

Multi-Statistical Approach for the Study of Volatile Compounds of Industrial Spoiled Manzanilla Spanish-Style Table Olive Fermentations.

Table olives can suffer different types of spoilage during fermentation. In this work, a multi-statistical approach (standard and compositional data analysis) was used for the study of the volatile organic compounds (VOCs) associated with altered (butyric, sulfidic, and putrid) and non-altered (normal) Manzanilla Spanish-style table olive fermentations. Samples were collected from two industrial fermentation yards in Seville (Spain) in the 2019/2020 season. The VOC profiles of altered (n = 4) and non-altered (n = 6) samples were obtained by headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME-GC-MS). Ninety-one VOCs were identified and grouped into alcohols (30), esters (21), carbonyl compounds (12), acids (10), terpenes (6), phenols (6), sulfur compounds (2), and others (4). The association of the VOCs with spoilage samples depended on the standard or compositional statistical methodology used. However, butyric spoilage was strongly linked by several techniques to methyl butanoate, ethyl butanoate, and butanoic acid; sulfidic spoilage with 2-propyl-1-pentanol, dimethyl sulfide, methanol, 2-methylbutanal, 2-methyl-2-butenal, ethanol, 2-methyl-3-buten-2-ol, and isopentanol, while putrid was mainly related to D-limonene and 2-pentanol. Our data contribute to a better characterisation of non-zapatera spoiled table olive fermentations and show the convenience of using diverse statistical techniques for a most robust selection of spoilage VOC markers.

Volatile Organic Compounds in Sweet Passito Wines as Markers of Grape Dehydration/Withering/Drying Process

Twenty-four sweet Passito wines from Italy were analyzed through gas chromatography-mass spectrometry. Apart from the vinification process, which was unknown, the Passito wines differed in the water loss technique used, the grape variety, and the latitude/orography of provenance. Two volatile organic compound markers, ethyl acetate and furfural, were identified, characterizing wines produced with the technique of Vin Santo, wines from sun drying, and wines from late harvest. These compounds were found at low concentrations in wines produced with grapes dehydrated in “fruttaio” (closed facility), under controlled or uncontrolled conditions. Wines from Muscat varieties had more esters and terpenes, but the wines produced from grapes dehydrated in fruttaio in North Italy, particularly those grown on high mountains, had more than Muscat wines produced in South Italy or using sun drying. Primary and secondary aroma compounds are reported for each wine. A controlled environment during dehydration, preferably at low temperature, better preserves the aroma of grapes for wine production.

Discrimination of Virgin and Recycled Polyethylene Based on Volatile Organic Compounds Using a Headspace GC-MS Coupled with Chemometrics Approach

A method of headspace gas chromatography coupled to mass spectrometry (HS-GC-MS) followed by multivariate statistical analysis was applied to identify recycled and virgin polyethylene (PE). Under the optimized conditions, a total of 47 volatile organic compounds (VOCs) were detected, which can be categorized as aliphatic hydrocarbons, additives, contaminants and miscellaneous. Among them, 16 volatile markers for discrimination between virgin and recycled PE were selected based on orthogonal partial least squares discriminant analysis (OPLS-DA) and non-parametric test. Most of these compounds were aliphatic hydrocarbons, which are rich in virgin samples. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were sequentially established to discriminate between recycled and virgin PE based on VOC markers. Our findings indicate that there are significant differences in VOCs between recycled and virgin PE, and HS-GC-MS in combination with multivariate statistical analysis can be a reliable tool for discrimination of recycled and virgin PE.

Abstract 744: Volatile organic compounds (VOCs) from exhaled Breath for lung cancer Staging using TD-GC-MS

Abstract Background: Breath analysis is a promising noninvasive screening technique that offers a wide range of probable possibilities to facilitate early diagnosis of lung cancer (LC). Method: Exhaled breath samples of 352 subjects were analyzed to detect C6∼C30 VOCs through thermal desorption coupled with gas chromatography-mass spectrometry (TD-GC-MS). Data were divided into three categories Lung Cancer (LC), Benign Pulmonary Disease (BPD) and Healthy control (HC). Statistical classification models were used to analyze VOCs to distinguish between HC, BPD and LC patient's early and advanced stages. Receiver operator characteristics (ROC) curves were used to select different VOCs to evaluate the accuracy, specificity, and sensitivity of the diagnostic model. Results: The analysis resulted that 10,9,11 and 10 VOCs have a significant correlation to discriminate Histology, stage, BPD from LC and HC from LC. The diagnostic model predicted accuracy, sensitivity, and specificity of NSCLC vs. SCLC is 92%, 96% and 90% with area under curve AUC>0.913. As of ROC curve with AUC>0.819 has distinguished Stage I-II vs. stage III-IV with accuracy, sensitivity, and specificity 72%, 84%, and 80%. Whereas the ROC curve with AUC>0.795 has distinguished BPD from LC with accuracy, sensitivity, and specificity 83%, 89%, and 84%. While ROC curve with AUC>0.945, accuracy, sensitivity and specificity 92%, 96%, and 90% have distinguished HC from LC. Conclusion: This study confirms that TD GC-MS is a sensitive and dependable method to distinguish the VOCs in exhaled breath. We have witnessed significant differences in breath of BPD, HC and LC subjects. Where 10,8,11 and 10 VOCs have distinguished between early from the advance stage, NSCLC from SCLC, BPD from LC and HC from LC. These VOCs has the potential to help improve LC diagnosis and prognosis. However, with the expansion of multi centers to other regions could result in more vital findings and will help improve breath analysis and the diagnosis standard. Keywords: Breath Analysis, VOC markers, lung cancer, TD-GC-MS. Citation Format: Kanhar Ghulam Muhammad, Channa Madeeha, Fu Wei, Xu Lin Xin, Yanjie Hu, Kejing Ying, Jun Liu, Xing Chen. Volatile organic compounds (VOCs) from exhaled Breath for lung cancer Staging using TD-GC-MS [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 744.

Analysis of Apple Flavours: The Use of Volatile Organic Compounds to Address Cultivar Differences and the Correlation between Consumer Appreciation and Aroma Profiling

In the selection of apple (Malus domestica Borkh) fruits, consumers predominantly use visual and organoleptic responses, such as aroma and texture, as quality/preference markers. Previous studies profiling the sensory properties and aroma profiles of apple varieties have provided a lexicon describing important attributes within the modalities of aroma, texture, and flavour. The range of volatile organic compounds (VOCs) produced by four apple cultivars was assessed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). To facilitate automated dynamic headspace extraction of the VOCs from bulk samples, a small multichamber thermal extraction system was used. Forty compounds were detected and putatively identified by mass spectral comparison with NIST libraries. Eight compounds were not previously identified in apples. Permutational multivariate analysis of variance (PerMANOVA) and canonical analysis of principal coordinates (CAP) done on the whole volatile organic compound profiles show separation of the four cultivars. The use of random forest classification enabled the determination of a minimum set of fifteen potential VOC markers that successfully differentiate the cultivars under study. Trends across samples, VOCs, and sensory evaluation are revealed. The association between 4-hexen-1-ol acetate with texture/consistency, and crispiness, and correlation of 2-methylbut-2-en-1-yl acetate with juiciness and acidity is shown for the first time. These sensory correlations indicate that the compounds determined by this experiment could be used as objective markers for the consumer appreciation of fresh apples, enabling the optimum conditions for processing and storage of individual cultivars to be identified without recourse to expensive sensory panels in every case. Such tests could also be used as part of routine quality control by the producer and retailer, reducing costs and eliminating waste due to batches of inferior product.

0450 Screening Method for Obstructive Sleep Apnea Syndrome by Patients’ Exhalant with TD-GC-MS System

Abstract Introduction Human exhaled breath test is getting more important for non-invasive health monitoring and detecting method nowadays. The diagnosis of obstructive sleep apnea syndrome (OSAS) is often difficult to be confirmed from the daytime presentation and usually need the overnight polysomnography. The methods for OSAS screening are therefore potentials for the clinical practice in the near future. Methods In this research, a method of thermal desorption (TD) tendon with gas chromatography-mass spectrometry (GC-MS) system has been developed for screeing of OSAS patients. We detected the volatile organic compounds (VOCs) from the special designed experimental bags which collected exhaled gas. Then we compared the VOCs from normal control and OSAS group in order to find out the biomarkers which could be used to screen OSAS patients. Furthermore, the Reliable Number(N) was used to see how often the VOC identified in all the experients in OSAS group and was defined as the times of a single VOC identified devided by the times of total experiment in a single OSAS patient. Results While the reliable number been set as ≥50%, we found 8 VOC markers, including Pentane and Cyclopentyl acetylene, appeared more often in OSAS patients. When we raise N to ≥70%, we have only 3 markers remaining. Conclusion Based on this result, we utilize the artificial intelligence method, deep learning, to figure out whether the peak intensity of different biomarkers are related to the severity of OSAS. Support Thanks for Da-Jeng Yao Lab’s support

Volatile non-intentionally added substances (NIAS) identified in recycled expanded polystyrene containers and their migration into food simulants

Abstract Recycled materials such as expanded polystyrene (EPS) are increasing in the food market and some hazardous chemicals may exist in recycled PS resins. Therefore, a method of solid-phase microextraction and gas chromatography coupled to mass spectrometry followed by chemometric tools applied to the data obtained allowed the identification of markers for virgin and recycled EPS. The multivariate statistical analysis was developed to characterize the profile of volatile organic compounds (VOCs) in virgin and recycled EPS containers, and identify the potential VOCs markers responsible for EPS containers discrimination. A total of 99 compounds were identified in virgin and recycled EPS containers. Among these, 17 compounds contributing the most to the discrimination, were selected based on their variables importance in the projection (VIP) values, including o-xylene, acetophenone, ethylbenzene, α-ethylstyrene, 2-phenylpropenal, propylbenzene, 2-phenyl-1-propene, undecanal, benzoic acid ethyl ester, 2-ethyl-1-hexanol, decanal, benzylcarboxaldehyde, isopropylbenzene, 2,4-diphenyl-1-butene, dodecanal, benzaldehyde and nonanal. To evaluate the health risk of EPS containers, migration tests from EPS containers into two food simulants (10% ethanol, 3% acetic acid) were conducted. It should be highlighted that high amount of styrene was detected. Nevertheless, analysed materials accomplish with current EU Regulation No.10/2011. The proposed method finds the differentiation markers and provides a reliable tool to discriminate virgin and recycled EPS containers, which could be an additional tool for quality control of EPS containers.

Colorectal cancer and adenoma screening using urinary volatile organic compound (VOC) detection: early results from a single-centre bowel screening population (UK BCSP)

BackgroundThe United Kingdom (UK) bowel cancer screening programme has reduced mortality from colorectal cancer (CRC), but poor uptake with stool-based tests and lack of specificity of faecal occult blood testing (FOBT), has prompted investigation for a more suitable screening test. The aim of this study was to investigate the feasibility of a urinary volatile organic compounds (VOC)-based screening tool for CRC.MethodsThe urine from FOBT-positive patients was analysed using field asymmetric ion mobility spectrometry (FAIMS) and gas chromatography coupled with ion mobility spectrometry (GC–IMS). Data were analysed using a machine learning algorithm to calculate the test accuracy for correct classification of CRC against adenomas and other gastrointestinal pathology.ResultsOne hundred and sixty-three patients were enrolled in the study. Test accuracy was high for differentiating CRC from control: area under the curve (AUC) 0.98 (95% CI 0.93–1) and 0.82 (95% CI 0.67–0.97) using FAIMS and GC–IMS respectively. Correct classification of CRC from adenoma was high with AUC range 0.83–0.92 (95% CI 0.43–1.0). Classification of adenoma from control was poor with AUC range 0.54–0.61 (95% CI 0.47–0.75) using both analytical modalities.ConclusionsCRC was correctly distinguished from adenomas or no bowel pathology using urinary VOC markers, within the bowel screening population. This pilot study demonstrates the potential of this method for CRC detection, with higher test uptake and superior sensitivity than FOBT. In addition, this is the first application of GC–IMS in CRC detection which has shown high test accuracy and usability.

Volatolomics in Bacterial Ecotoxicology, A Novel Method for Detecting Signatures of Pesticide Exposure?

Volatile organic compounds (VOC) produced by microorganisms in response to chemical stressor showed recently increasing attention, because of possible environmental applications. In this work, we aimed to bring the first proof of concept that volatolomic (i.e., VOCs analysis) can be used to determine candidate VOC markers of two soil bacteria strains (Pseudomonas fluorescens SG-1 and Bacillus megaterium Mes11) exposure to pesticides. VOC determination was based on solid-phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS). Accordingly, we highlighted a set of bacterial VOCs modulated in each strains according to the nature of the pesticide used. Three out these VOCs were specifically modulated in P. fluorescens SG-1 when exposed with two pyrethroid pesticides (deltamethrine and cypermethrine): 2-hexanone; 1,3-ditertbutylbenzene and malonic acid, hexyl 3-methylbutyl ester. Our results thus suggest the possible existence of generic VOC markers of pyrethroids in this strain. Of particular interest, two out of these three VOCs, the 1,3-ditertbutylbenzene and the malonic acid, hexyl 3-methylbutyl ester were found also in B. megaterium Mes11 when exposed with cypermethrine. This result highlighted the possible existence of interspecific VOC markers of pyrethroid in these two bacteria. Altogether, our work underlined the relevance of volatolomic to detect signatures of pesticides exposure in microorganisms and more generally to microbial ecotoxicology. Based on these first results, considerations of volatolomics for the chemical risk assessment in environment such as soils can be indirectly explored in longer terms.

Confounding effect of benign pulmonary diseases in selecting volatile organic compounds as markers of lung cancer

Lung cancer (LC) is a leading cause of cancer-related morbidity and mortality globally, and exhaled breath testing has been considered as a fast, convenient and non-invasive way to diagnose LC in its early stages. Volatile organic compounds (VOCs), as markers of LC in exhaled breath, have been widely investigated for cancer diagnosis. However, few studies have reported on the interference of benign pulmonary diseases (BPD) in the selection of VOC markers for LC. During this study, 207 samples were analyzed using thermal desorption instrumentation/gas chromatography/mass spectrometry (TD-GCMS) to detect C6−C30 VOCs, and all samples were divided into four groups: LC group, BPD group, lung disease (LD) group (including LC group and BPD group) and healthy group. To make up for the deficiency of detecting low carbon hydrocarbons (<C6), 277 samples were analyzed using solid-phase micro-extraction/gas chromatography/mass spectrometry (SPME-GCMS), divided among the four groups. VOC markers were selected by reference to the receiver operating characteristics curve. With the comparisons among the LC group, BPD group and healthy group from TD-GCMS and SPME-GCMS results, we found that exhaled VOCs are capable of discriminating LC group versus healthy group and BPD group versus healthy group with a consistency of 70%–80%. However, no VOCs can be selected with good discrimination capability between the LC group and BPD group, indicating that BPD interferes significantly in VOC marker selection for LC. To discriminate breath samples from the LD group and healthy group, 11 VOCs, including ten selected from TD-GCMS and one from SPME-GCMS, were chosen as markers for LD diagnosis. The sensitivity, specificity and overall accuracy of the diagnostic model established using ten VOCs were 80.8%, 84% and 82.7%, and those of the model established by using one VOC were 75.6%, 78.9% and 76.7%. These results validate that LD patients can be effectively discriminated and diagnosed using exhaled VOC analysis. (Clinical trial registration number: ChiCTR-DCD-15007106.)