Volatile Organic Compounds Patterns Research Articles

Development and validation of an innovative headspace collection technique: volatile organic compound patterns emitted by different developmental stages of Halyomorpha halys

Over the past two decades, several headspace collection techniques have been used to detect and identify volatile organic compounds (VOCs) emitted by plants, pests, air, and soil. Volatiles emitted by pests and infected plants are usually found at low concentrations. The important challenge is to be able to capture an exact collection of relative quantities of the relevant VOCs. Here we present an innovative headspace collecting device (HSCD) for sampling VOCs, which ensures an exact regulation of mass flow velocity and collected total gas volume allowing besides qualitative analysis of collected VOCs, an exact comparison of their relative quantities in plant or insect headspace samples. The HSCD possess six parallel odor collection systems each consisting of a digital mass flow detector and controller connected to a vacuum pump, which are mounted in a trolley suitcase, connected by tubes, and wired electrically. The programming of the channels, can be done by a digital control unit. Using the HSCD, VOCs emitted by the brown marmorated stink bug (BMSB), Halyomorpha halys, from its different developmental stages including egg, nymphal stages, nymphal exuvia, and adults were collected on thermal desorption tubes and analyzed using an automated thermal desorber connected to a gas chromatography-mass spectrometry system. Forty-five VOCs were identified in total, which mainly consisted of tridecane (4.36-69.33%), E-2-decenal (4.24-26.48%), 2-undecenal (0.63-50.03%), and E-4-oxo-2-hexenal (1.22-20.58%). The random forest analysis revealed three different chemical patterns among BMSB life stages samples. In conclusion, these results indicate that the new developed HSCD, a mobile, easy to use, and reliable instrument, has a high potential to sample relevant VOCs of a specific life stage of an insect both qualitatively and quantitatively. It was demonstrated that this information can be used for identifying specific chemical signatures, which fit to specific life stages of the BMSB, and may be used as biomarker for on-site detection of this pest e.g. in shipping containers or agricultural areas.

Unveiling the hidden impact: How biodegradable microplastics influence CO2 and CH4 emissions and Volatile Organic Compounds (VOCs) profiles in soil ecosystems

Biodegradable plastics promise eco-friendliness, yet their transformation into microplastics (bio-MPs) raises environmental alarms. However, how those bio-MPs affect the greenhouse gases (GHGs) and volatile organic compounds (VOCs) in soil ecosystems remains largely unexplored. Here, we investigated the effects of diverse bio-MPs (PBAT, PBS, and PLA) on GHGs and VOCs emission in typical paddy or upland soils. We monitored the carbon dioxide (CO2) and methane (CH4) fluxes in-situ using the self-developed portable optical gas sensor and analyzed VOC profiles using a proton-transfer reaction mass spectrometer (PTR-MS). Our study has revealed that, despite their biodegradable nature, bio-MPs do not always promote soil GHG emissions as previously thought. Specifically, PBAT and PLA significantly increased CO2 and CH4 emissions up to 1.9–7.5 and 115.9–178.5 fold, respectively, compared to the control group. While PBS exhibited the opposite trend, causing a decrease of up to 39.9% for CO2 and up to 39.9% for CH4. In addition, different types of bio-MPs triggered distinct soil VOC emission patterns. According to the Mann-Whitney U-test and Partial Least Squares Discriminant Analysis (PLS-DA), a recognizable VOC pattern associated with different bio-MPs was revealed. This study claims the necessity of considering polymer-specific responses when assessing the environmental impact of Bio-MPs, and providing insights into their implications for climate change.

Colorectal Cancer Diagnosis through Breath Test Using a Portable Breath Analyzer-Preliminary Data.

Screening methods available for colorectal cancer (CRC) to date are burdened by poor reliability and low patient adherence and compliance. An altered pattern of volatile organic compounds (VOCs) in exhaled breath has been proposed as a non-invasive potential diagnostic tool for distinguishing CRC patients from healthy controls (HC). The aim of this study was to evaluate the reliability of an innovative portable device containing a micro-gas chromatograph in enabling rapid, on-site CRC diagnosis through analysis of patients' exhaled breath. In this prospective trial, breath samples were collected in a tertiary referral center of colorectal surgery, and analysis of the chromatograms was performed by the Biomedical Engineering Department. The breath of patients with CRC and HC was collected into Tedlar bags through a Nafion filter and mouthpiece with a one-way valve. The breath samples were analyzed by an automated portable gas chromatography device. Relevant volatile biomarkers and discriminant chromatographic peaks were identified through machine learning, linear discriminant analysis and principal component analysis. A total of 68 subjects, 36 patients affected by histologically proven CRC with no evidence of metastases and 32 HC with negative colonoscopies, were enrolled. After testing a training set (18 CRC and 18 HC) and a testing set (18 CRC and 14 HC), an overall specificity of 87.5%, sensitivity of 94.4% and accuracy of 91.2% in identifying CRC patients was found based on three VOCs. Breath biopsy may represent a promising non-invasive method of discriminating CRC patients from HC.

Abstract 4433: Secondary electrospray ionization mass spectrometry for volatile analysis of lung cancer

Abstract Lung cancer remains a leading cause of cancer-related mortality globally, necessitating innovative approaches for early detection and improved understanding of its metabolic landscape and consequences. Secondary Electrospray Ionization Mass Spectrometry (SESI-MS), an innovative analytical technique, has emerged as a powerful tool for the analysis of volatile organic compounds (VOCs) associated with various diseases, from metabolic disorders to bacterial infections. In this proof-of-concept study, we first utilized SESI-MS analyses of four representative lung cancer cells of both non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) to demonstrate its capability to profile VOCs released by lung cancer cells. The technique allows for real-time, non-invasive analysis of the headspace above cultured cells, enabling the detection of unique VOC signatures associated with different lung cancer subtypes. Meanwhile, SESI-MS also facilitated the discrimination specific cells based on distinct VOC patterns. Furthermore, we also performed cisplatin treatment experiments and observed the metabolic signature shift post drug treatment. These results collectively offered potential applications in early diagnosis and personalized treatment strategies. Next, we continued with in vivo investigations to further extend the utility of SESI-MS in lung cancer research. Animal models, mimicking human lung cancer pathophysiology, have been subjected to SESI-MS analysis to identify volatile biomarkers indicative of tumor development and progression. Several representative cancer drug treatments were performed to the lung cancer mice model, and the drug-induced responses were also monitored via SESI-MS breath analyses. The in vivo SESI-MS approach detected many interesting breath VOC features that could provide valuable insights into the dynamic changes in VOC profiles during various stages of lung cancer, and therefore has the potential to offer a deeper understanding of the disease's metabolic alterations and potential avenues for targeted therapeutic interventions. In conclusion, SESI-MS-based volatile analysis presents a robust and versatile approach for investigating lung cancer, and our ongoing work has the potential to bridge the gap between in vitro and in vivo models for better translational research outcomes. The detection of unique VOC signatures associated with lung cancer cells and tumors holds significant promise for early detection, subtype classification, and monitoring of treatment responses. As technology continues to advance, SESI-MS stands poised to play a pivotal role in transforming the landscape of lung cancer diagnostics and research. Citation Format: Jiangjiang (Chris) Zhu, Fouad Choueiry. Secondary electrospray ionization mass spectrometry for volatile analysis of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4433.

Soil processes modify the composition of volatile organic compounds (VOCs) from CO2- and CH4-dominated geogenic and landfill gases: A comprehensive study

Degradation mechanisms affecting non-methane volatile organic compounds (VOCs) during gas uprising from different hypogenic sources to the surface were investigated through extensive sampling surveys in areas encompassing a high enthalpy hydrothermal system associated with active volcanism, a CH4-rich sedimentary basin and a municipal waste landfill. For a comprehensive framework, published data from medium-to-high enthalpy hydrothermal systems were also included. The investigated systems were characterised by peculiar VOC suites that reflected the conditions of the genetic environments in which temperature, contents of organic matter, and gas fugacity had a major role. Differences in VOC patterns between source (gas vents and landfill gas) and soil gases indicated VOC transformations in soil. Processes acting in soil preferentially degraded high-molecular weight alkanes with respect to the low-molecular weight ones. Alkenes and cyclics roughly behaved like alkanes. Thiophenes were degraded to a larger extent with respect to alkylated benzenes, which were more reactive than benzene. Furan appeared less degraded than its alkylated homologues. Dimethylsulfoxide was generally favoured with respect to dimethylsulfide. Limonene and camphene were relatively unstable under aerobic conditions, while α-pinene was recalcitrant. O-bearing organic compounds (i.e., aldehydes, esters, ketones, alcohols, organic acids and phenol) acted as intermediate products of the ongoing VOC degradations in soil. No evidence for the degradation of halogenated compounds and benzothiazole was observed. This study pointed out how soil degradation processes reduce hypogenic VOC emissions and the important role played by physicochemical and biological parameters on the effective VOC attenuation capacity of the soil.

Spatiotemporal variations, sources, and atmospheric transformation potential of volatile organic compounds in an industrial zone based on high-resolution measurements in three plants

Industrial emissions are significant sources of volatile organic compounds (VOCs). This study conducted a field campaign at high temporal and spatial resolution to monitor VOCs within three plants in an industrial park in southern China. VOC concentrations showed significant spatial variability in this industrial zone, with median concentrations of 75.22, 40.53, and 29.41 μg/m3 for the total VOCs in the three plants, respectively, with oxygenated VOCs (OVOCs) or aromatics being the major VOCs. Spatial variability within each plant was also significant but VOC-dependent. Seasonal variations in the VOC levels were governed by their industrial emissions, meteorological conditions, and photochemical losses, and they were different for the four groups of VOCs. The temporal and spatial variations in the VOC compositions suggest similar sources of each class of VOCs during different periods of the year in each plant. The diurnal patterns of VOCs (unimodal or bimodal) clearly differed from those at most industrial/urban locations previously, reflecting a dependence on industrial activities. The secondary transformation potential of VOCs also varied temporally and spatially, and aromatics generally made the predominant contributions in this industrial park. The loss rate of OH radicals and ozone formation potential were highly correlated, but the linear relationship substantially changed in summer and autumn due to the intensive emissions of an OVOC species. The lifetime cancer and non-cancer risks via occupational inhalation of the VOCs in the plants were acceptable but merit attention. Taking the secondary transformation potential and health risks into consideration, styrene, xylene, toluene, trichloroethylene, and benzene were proposed to be the priority VOCs regulated in the plants.

Diel variation of seawater volatile organic compounds, DMSP-related compounds, and microbial plankton inside and outside a tropical coral reef ecosystem

Biogenic volatile organic compounds (VOCs) play key roles in coral reef ecosystems, where, together with dimethylated sulfur compounds, they are indicators of ecosystem health and are used as defense strategies and infochemicals. Assessment and prediction of the exchange rates of VOCs between the oceans and atmosphere, with implications for atmospheric reactivity and climate, are hampered by poor knowledge of the regulating processes and their temporal variability, including diel cycles. Here, we measured the variation over 36h of the concentrations of DMSPCs (dimethylsulfoniopropionate (DMSP)-related compounds, namely DMSP, dimethylsulfoxide, acrylate, dimethylsulfide, and methanethiol as dimethyl disulfide) and VOCs (COS, CS2, isoprene, the iodomethanes CH3I and CH2ClI, and the bromomethanes CHBr3 and CH2Br2), in surface waters inside the shallow, northern coral-reef lagoon of Mo’orea (French Polynesia) and 4 km offshore, in the tropical open ocean. Comparisons with concurrent measurements of sea surface temperature, solar radiation, biogeochemical variables (nutrients, organic matter), and the abundances and taxonomic affiliations of microbial plankton were conducted with the aim to explain interconnections between DMSPCs, VOCs, and their environment across diel cycles. In open ocean waters, deeper surface mixing and low nutrient levels resulted in low phytoplankton biomass and bacterial activity. Consequently, the diel patterns of VOCs were more dependent on photochemical reactions, with daytime increases for several compounds including dissolved dimethylsulfoxide, COS, CS2, CH3I, and CH2ClI. A eukaryotic phytoplankton assemblage dominated by dinoflagellates and haptophytes provided higher cell-associated DMSP concentrations, yet the occurrence of DMSP degradation products (dimethylsulfide, dimethyl disulfide) was limited by photochemical loss. Conversely, in the shallow back reef lagoon the proximity of seafloor sediments, corals and abundant seaweeds resulted in higher nutrient levels, more freshly-produced organic matter, higher bacterial activity, and larger algal populations of Mamiellales, diatoms and Cryptomonadales. Consequently, DMSP and dimethylsulfoxide concentrations were lower but those of most VOCs were higher. A combination of photobiological and photochemical processes yielded sunny-daytime increases and nighttime decreases of dimethylsulfide, dimethyl disulfide, COS, isoprene, iodomethanes and bromomethanes. Our results illustrate the important role of solar radiation in DMSPC and VOC cycling, and are relevant for the design of sampling strategies that seek representative and comparable measurements of these compounds.

Composition and Reactivity of Volatile Organic Compounds and the Implications for Ozone Formation in the North China Plain

Enhanced ozone (O3) pollution has emerged as a pressing environmental concern in China, particularly for densely populated megacities and major city clusters. However, volatile organic compounds (VOCs), the key precursors to O3 formation, have not been routinely measured. In this study, we characterize the spatial and temporal patterns of VOCs and examine the role of VOCs in O3 production in five cities (Dongying (DY), Rizhao (RZ), Yantai (YT), Weihai (WH), and Jinan (JN)) in the North China Plain (NCP) for two sampling periods (June and December) in 2021 through continuous field observations. Among various VOC categories, alkanes accounted for the largest proportion of VOCs in the cities. For VOCs, chemical reactivities, aromatic hydrocarbons, and alkenes were dominant contributors to O3 formation potential (OFP). Unlike inland regions, the contribution to OFP from OVOCs increased greatly at high O3 concentrations in coastal regions (especially YT). Model simulations during the O3 episode show that the net O3 production rates were 27.87, 10.24, and 10.37 ppbv/h in DY, RZ, and JN. The pathway of HO2 + NO contributed the most to O3 production in JN and RZ, while RO2 + NO was the largest contributor to O3 production in DY. The relative incremental reactivity (RIR) revealed that O3 formation in DY was the transitional regime, while it was markedly the VOC-limited regime in JN and RZ. The O3 production response is influenced by NOx concentration and has a clear daily variation pattern (the sensitivity is greater from 15:00 to 17:00). The most efficiencies in O3 reduction could be achieved by reducing NOx when the NOx concentration is low (less than 20 ppbv in this study). This study reveals the importance of ambient VOCs in O3 production over the NCP and demonstrates that a better grasp of VOC sources and profiles is critical for in-depth O3 regulation in the NCP.

Correlation between microbial communities and volatile organic compounds in an urban soil provides clues on soil quality towards sustainability of city flowerbeds

Soil functionality is critical to the biosphere as it provides ecosystem services relevant for a healthy planet. The soil microbial composition is significantly impacted by anthropogenic activities, including urbanization. In this context, the study of soil microorganisms associated to urban green spaces has started to be crucial toward sustainable city development. Microbes living in the soil produce and degrade volatile organic compounds (VOCs). The VOC profiles may be used to distinguish between soils with various characteristics and management practices, reflecting variations in the activity of soil microbes that use a variety of metabolic pathways. Here, a combined approach based on DNA metabarcoding and GC-MS analysis was used to evaluate the soil quality from urban flowerbeds in Prato (Tuscany, Italy) in terms of microbial biodiversity and VOC emission profiles, with the final aim of evaluating the possible correlation between composition of microbial community and VOC patterns. Results showed that VOCs in the considered soil originated from anthropic and biological activity, and significant correlations between specific microbial taxa and VOCs were detected. Overall, the study demonstrated the feasibility of the use of microbe-VOC correlation as a proxy for soil quality assessment in urban soils.

Determination of Volatile Organic Compounds and Endogenous Extracts and Study of Expression Patterns of TPS and BSMT in the Flowers of Seven Lilium Cultivars.

Lily is one of the most important cut flowers in the world, with a rich floral fragrance. To further explore the fragrance emission mechanisms of lily cultivars, headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and organic solvent extraction-gas chromatography-mass spectrometry (OSE-GC-MS) were used to unveil the volatile organic compounds (VOCs) and endogenous extracts of seven lily cultivars. Furthermore, real-time quantitative PCR (qRT-PCR) was used to determine the expression levels of two key genes (TPS and BSMT) related to the biosynthesis of monoterpenoids and methyl benzoate. The results show that forty-five VOCs were detected in the petals of seven lily cultivars, and the main compounds were monoterpenoids and phenylpropanoids/benzenoids. Dichloromethane was the best solvent for extracting the endogenous extracts of Lilium 'Viviana' petals and eighteen endogenous extracts were detected using dichloromethane to extract the petals of seven lily cultivars. Each compound's emission ratio (natural logarithm of the ratio of VOC content to endogenous extract content) was calculated, and linear regression analyses between emission ratios and boiling points were conducted. Significant linear negative correlations existed between the emission ratios and boiling points of compounds, and the regression equations' coefficients of determination (R2) were all greater than 0.7. TPS was expressed highly in 'Viviana', 'Pink News', and 'Palazzo', and BSMT was expressed highly in 'Pink News' and 'Palazzo'. Correlation analyses between the gene expression levels and the monoterpenoids and methyl benzoate contents found that the TPS expression levels have strong positive correlations with monoterpenoids content, while no correlations were found between the expression levels of BSMT and the contents of methyl benzoate. This study lays the foundation for research on the release patterns of VOCs in the flowers of Lilium, and the breeding of lilies for their floral fragrance.

Detection of volatile organic compounds in headspace of Klebsiella pneumoniae and Klebsiella oxytoca colonies

IntroductionEarly diagnosis of infections and sepsis is essential as adequate therapy improves the outcome. Unfortunately, current diagnostics are invasive and time-consuming, making diagnosis difficult, especially in neonatology. Novel non-invasive analytical methods might be suitable to detect an infection at an early stage and might even allow identification of the pathogen. Our aim is to identify specific profiles of volatile organic compounds (VOCs) of bacterial species.MethodsUsing multicapillary column-coupled ion mobility spectrometry (MCC/IMS), we performed headspace measurements of bacterial cultures from skin and anal swabs of premature infants obtained during weekly screening for bacterial colonization according to KRINKO. We analyzed 25 Klebsiella pneumoniae (KP) cultures on MacConkey (MC) agar plates, 25 Klebsiella oxytoca (KO) cultures on MC agar and 25 bare MC agar plates as a control group.ResultsUsing MCC/IMS, we identified a total of 159 VOC peaks. 85 peaks allowed discriminating KP and bare MC agar plates, and 51 peaks comparing KO and bare MC agar plates and 6 peaks between KP and KO (significance level of p < 0.05 after Bonferroni post hoc analysis), respectively. Peaks P51 (n-Decane) and P158 (Phenylethyl Alcohol), showed the best sensitivity/specificity/ positive predictive value/negative predictive value of 99.9% each (p < 0.001) for KP. P158 showed the best sensitivity/specificity/positive predictive value/negative predictive value of 99.9% each (p < 0.001) for KO. Comparing KP and KO, best differentiation was enabled using peaks P72, P97 and P16 with sensitivity/specificity/positive predictive value/negative predictive value of 76.0%, 84.0%, 82.6%, 77.8%, respectively (p < 0.05).DiscussionWe developed a method for the analysis of VOC profiles of bacteria. Using MCC/IMS, we demonstrated that VOCs derived from bacteria are clearly distinguishable from a bare agar plate. Characteristic peaks obtained by MCC/IMS are particularly suitable for the species-specific identification and differentiation of KP and KO. Thus, MCC/IMS might be a useful tool for in vitro diagnostics. Future studies must clarify whether similar patterns of VOCs can be detected in vivo in patients that are colonized or infected with KP or KO to enable rapid and accurate diagnosis of bacterial colonization.

Origin and transformation of volatile organic compounds at a regional background site in Hong Kong: Varied photochemical processes from different source regions

Volatile organic compounds (VOCs) are important gaseous constituents in the troposphere, impacting local and regional air quality, human health, and climate. Oxidation of VOCs, with the participation of nitrogen oxides (NOx), leads to the formation of tropospheric ozone (O3). Accurately apportioning the emission sources and transformation processes of ambient VOCs, and effectively estimation of OH reactivity and ozone formation potential (OFP) will play an important role in reducing O3 pollution in the atmosphere and improving public health. In this study, field measurements were conducted at a regional background site (Hok Tsui; HT) in Hong Kong from October to November 2020 with proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS). VOC data coupled with air mass back trajectory cluster analysis and receptor modelling were applied to reveal the pollution pattern, emission sources and transformation of ambient VOCs at HT in autumn 2020. Seven sources were identified by positive matrix factorization (PMF) analysis, namely vehicular + industrial, solvent usage, primary oxygenated VOCs (OVOCs), secondary OVOCs 1, secondary OVOCs 2 (aged), biogenic emissions, and background + biomass burning. Secondary formation and vehicular + industrial emissions are the vital sources of ambient VOCs at HT supersite, contributing to 20.8 % and 46.7 % of total VOC mixing ratios, respectively. Integrated with backward trajectory analysis and correlations of VOCs with their oxidation products, short-range transport of air masses from inland regions of southeast China brought high levels of total VOCs but longer-range transport of air masses brought more secondary OVOCs in aged air masses. Photolysis of OVOCs was the most important contributor to OH reactivity and OFP, among which aldehyde was the dominant contributor. The results of this study highlight the photochemical processing of VOCs from different source regions which should be considered in strategy making for pollution reduction.

Alteration of the Exhaled Volatile Organic Compound Pattern in Colorectal Cancer Patients after Intentional Curative Surgery-A Prospective Pilot Study.

As current follow-up modalities for colorectal carcinoma (CRC) have restricted sensitivity, novel diagnostic tools are needed. The presence of CRC changes the endogenous metabolism, resulting in the release of a specific volatile organic compounds (VOC) pattern that can be detected with an electronic nose or AeonoseTM. To evaluate the use of an electronic nose in the follow-up of CRC, we studied the effect of curative surgery on the VOC pattern recognition using AeonoseTM. A prospective cohort study was performed, in which 47 patients diagnosed with CRC were included, all of whom underwent curative surgical resection. Breath testing was performed before and after surgery using the AeonoseTM. A machine learning model was developed by discerning between the 94 pre-and postoperative breath samples. The training model differentiated between the pre-and postoperative CRC breath samples with a sensitivity and specificity of 0.78 (95%CI 0.61-0.90) and 0.73 (95%CI 0.56-0.86), respectively, with an accuracy of 0.76 (95%CI 0.66-0.85), and an area under the curve of 0.79 (95%CI 0.68-0.89). The internal validation of the test set resulted in an accuracy of 0.75 (95%CI 0.51-0.91) and AUC of 0.82 (95%CI 0.61-1). In conclusion, our results suggest that the VOC pattern of CRC patients is altered by curative surgery in a short period, indicating that the exhaled VOCs might be closely related to the presence of CRC. However, to use AeonoseTM as a potential diagnostic tool in the clinical follow-up of CRC patients, the performance of the models needs to be improved through further large-scale prospective research.

Measurement report: Source apportionment and environmental impacts of volatile organic compounds (VOCs) in Lhasa, a highland city in China

Abstract. Hypoxia and adverse health outcomes might be affected by O3 pollution in the highland city of Lhasa. NOx emissions can amplify the role of volatile organic compounds (VOCs) in the secondary production of O3 under the conditions of high ultraviolet (UV) radiation levels and unfavourable dispersion patterns in the Lhasa River valley. Here, online C2–C11 VOC measurements, accompanied by other parameters concerning the O3 chemical budget, were first obtained and employed to identify the key VOC species and key sources of VOCs in terms of the loss rate against OH radicals (LOH), ozone formation potential (OFP), secondary organic aerosol potential (SOAP), and toxicity. Oxygenated VOCs (OVOCs) not only were the most abundant VOCs but also dominated LOH, OFP, and toxicity. Isoprene and anthropogenic VOCs were further identified as precursors of these OVOCs. Aromatics accounted for 5 % of the total VOCs (TVOCs) but contributed 88 % to the SOAP and 10 % to the toxicity. As the primary oxidative intermediates of aromatics were not well characterized by our measurements, the environmental impact of aromatics could be underestimated by our data. Source appointment and ternary analysis of benzene, toluene, and ethylbenzene confirmed the combined contribution of traffic emissions, solvent usage, and biomass burning. This suggests that O3 precursors are mainly from sources associated with residents' lives, except for solvent usage emissions which contribute to aromatics. Preliminary comparisons between source spectrums of transport sector emissions with positive matrix factorization (PMF)-decomposed ones and our measured ones suggest that vehicle emission patterns of VOCs at high altitude generally follow the ground-level impression. More quantitative data are required to further confirm this point though. Emission reduction strategy analysis for O3 pollution control highlighted multiple benefits of the simultaneous reduction in NOx originating from diesel vehicle emissions, biomass burning, and background sources (possibly dominated by incense burning). The notable biogenic emission contribution to the OFP was also first confirmed in our study, and this highlights the side effects of the government's pursuit of a greener city.

Variation in Volatile Organic Compounds in native, synanthropic accessions and cultivars of the musk strawberry (Fragaria moschata Duchesne ex Weston).

Prior to the world-wide dominance of F. ×ananassa in strawberry production, native species had been cultivated in European gardens for centuries. Especially the musk strawberry (F. moschata) had been highly appreciated due to its fruit size and extraordinary aroma. Detailed studies on the diversity of the species' fruit aroma are lacking, although breeding aims to improve strawberry aroma by complex crossings during recent years. Today a few cultivars, abandoned synanthropic occurrences and native populations of this species exist in Germany. Here we characterised aroma profiles of F. moschata accessions by analysing Volatile Organic Compounds. In particular, differences between native and cultivated accessions as well as the diversity in aroma profiles of native populations were investigated. Profiles of Volatile Organic Compounds were analysed by immersion stir bar sorptive extraction-gas chromatography-quadrupol mass spectrometry (imm-SBSE-GC-qMS). These data were compared with a genetic characterisation of samples based on eight microsatellite loci using univariate and multivariate statistical analyses. High amounts of furanones and the key compound methyl anthranilate were characteristic for the aroma profile of F. moschata. We detected a considerable diversity of Volatile Organic Compounds among accessions of F. moschata, particularly among genetically distinct samples from the same population. Native accessions contained more terpenoids but less esters and were moderately differentiated from cultivated samples. The observed patterns of Volatile Organic Compounds indicate that cultivated accessions had been selected for favourable aroma profiles and thus showing traces of domestication. Moreover, native populations harbour a great diversity of Volatile Organic Compounds, which could be also considered for future breeding efforts.

Volatile Organic Compounds Determination from Intestinal Polyps and in Exhaled Breath by Gas Chromatography–Mass Spectrometry

In this paper, a new protocol is described, based on solid phase microextraction (SPME) coupled with gas chromatography–mass spectrometry (GC-MS), to monitor ex vivo changes in endogenous volatile organic compounds (VOCs) released by surgically resected colonic tissues (normal colonic mucosa and adenomatous polyps) from seven patients undergoing operative colonoscopy to identify their molecular pattern. The exhalated volatile organic molecules from these patients were sampled by the ReCIVA® breath sampler, shortly before surgery, and analyzed by GC-MS. Comparing VOC patterns identified in the tissues and in the breath of the same patients, a possible correlation can be found between the levels of methylbenzene and benzaldehyde exhaled and the presence of colonic adenomatous polypoid lesions.

Isolation, (bio)synthetic studies and evaluation of antimicrobial properties of drimenol-type sesquiterpenes of Termitomyces fungi

Macrotermitinae termites have farmed fungi in the genus Termitomyces as a food source for millions of years. However, the biochemical mechanisms orchestrating this mutualistic relationship are largely unknown. To deduce fungal signals and ecological patterns that relate to the stability of this symbiosis, we explored the volatile organic compound (VOC) repertoire of Termitomyces from Macrotermes natalensis colonies. Results show that mushrooms emit a VOC pattern that differs from mycelium grown in fungal gardens and laboratory cultures. The abundance of sesquiterpenoids from mushrooms allowed targeted isolation of five drimane sesquiterpenes from plate cultivations. The total synthesis of one of these, drimenol, and related drimanes assisted in structural and comparative analysis of volatile organic compounds (VOCs) and antimicrobial activity testing. Enzyme candidates putatively involved in terpene biosynthesis were heterologously expressed and while these were not involved in the biosynthesis of the complete drimane skeleton, they catalyzed the formation of two structurally related monocyclic sesquiterpenes named nectrianolins.

A detection model for cognitive dysfunction based on volatile organic compounds from a large Chinese community cohort.

We explored whether volatile organic compound (VOC) detection can serve as a screening tool to distinguish cognitive dysfunction (CD) from cognitively normal (CN) individuals. The cognitive function of 1467 participants was assessed and their VOCs were detected. Six machine learning algorithms were conducted and the performance was determined. The plasma neurofilament light chain (NfL) was measured. Distinguished VOC patterns existed between CD and CN groups. The CD detection model showed good accuracy with an area under the receiver-operating characteristic curve (AUC) of 0.876. In addition, we found that 10 VOC ions showed significant differences between CD and CN individuals (p<0.05); three VOCs were significantly related to plasma NfL (p<0.005). Moreover, a combination of VOCs with NfL showed the best discriminating power (AUC=0.877). Detection of VOCs from exhaled breath samples has the potential to provide a novel solution for the dilemma of CD screening.

Smart Miniature Mass Spectrometer Enabled by Machine Learning.

Similar to smartphones, smart or automatic level is also a critical feature for a miniature mass spectrometer. Compared to large-scale instruments, miniature mass spectrometers often have a lower mass resolution and larger mass drift, making it challenging to identify molecules with close mass-charge ratios. In this work, a miniature mass spectrometer (the Brick-V model) was combined with intelligent algorithms to realize rapid and accurate identification. This Brick-V mass spectrometer developed in our lab was equipped with a vacuum ultraviolet photoionization (VUV-PI) source, which ionizes volatile organic compounds (VOCs) with minor fragments. Machine learning would be especially helpful when analyzing samples with multiple characteristic peaks. Four machine learning algorithms were tested and compared in terms of precision, recall, balanced F score (F1 score), and accuracy. After optimization, the multilayer perceptron (MLP) method was selected and first applied for the automatic identification and differentiation of ten different fruits. By recognizing the pattern of multiple VOCs diffused from fruits, an average accuracy of 97% was achieved. This system was further applied to determine the freshness of strawberries, and strawberry picking at different times (especially during the first 24 h at room temperature of winter) could be well discriminated. After building a database of 63 VOCs, a rapid method to identify compounds in the database was established. In this method, molecular ions, fragment ions, and dimer ions in the full mass spectrum were all utilized in the machine learning program. A satisfactory prediction accuracy for the 63 VOCs could be achieved (>99%).

Liquid Biopsy-Based Volatile Organic Compounds from Blood and Urine and Their Combined Data Sets for Highly Accurate Detection of Cancer.

Liquid biopsy is seen as a prospective tool for cancer screening and tracking. However, the difficulty lies in effectively sieving, isolating, and overseeing cancer biomarkers from the backdrop of multiple disrupting cells and substances. The current study reports on the ability to perform liquid biopsy without the need to physically filter and/or isolate the cancer cells per se. This has been achieved through the detection and classification of volatile organic compounds (VOCs) emitted from the cancer cells found in the headspace of blood or urine samples or a combined data set of both. Spectrometric analysis shows that blood and urine contain complementary or overlapping VOC information on kidney cancer, gastric cancer, lung cancer, and fibrogastroscopy subjects. Based on this information, a nanomaterial-based chemical sensor array in conjugation with machine learning as well as data fusion of the signals achieved was carried out on various body fluids to assess the VOC profiles of cancer. The detection of VOC patterns by either Gas Chromatography-Mass Spectrometry (GC-MS) analysis or our sensor array achieved >90% accuracy, >80% sensitivity, and >80% specificity in different binary classification tasks. The hybrid approach, namely, analyzing the VOC datasets of blood and urine together, contributes an additional discrimination ability to the improvement (>3%) of the model's accuracy. The contribution of the hybrid approach for an additional discrimination ability to the improvement of the model's accuracy is examined and reported.