Analysis Of Volatile Organic Compounds Research Articles

Profiles of Killer Systems and Volatile Organic Compounds of Rowanberry and Rosehip-Inhabiting Yeasts Substantiate Implications for Biocontrol

Yeasts produce numerous antimicrobial agents such as killer toxins, volatile organic compounds (VOCs), and other secondary metabolites, establishing themselves in developing natural and sustainable biocontrol strategies for agriculture and food preservation. This study addressed the biocontrol potential of yeasts, isolated from spontaneous fermentations of rosehips (Rosa canina L.) and rowanberries (Sorbus aucuparia L.), focusing on their killer phenotypes and VOCs production. Yeasts were isolated using spontaneous fermentations with Hanseniaspora uvarum and Metschnikowia pulcherrima identified as the dominant species, comprising approximately 70% of the yeast population. Among 163 isolated strains, 20% demonstrated killing activity, with Saccharomyces cerevisiae exhibiting the strongest killing efficiency, as well as Pichia anomala and M. pulcherrima showing broad-spectrum antagonistic activity. This study identified dsRNA-encoded killer phenotypes in S. cerevisiae, S. paradoxus, and Torulaspora delbrueckii, revealing multiple distinct killer toxin types. The biocontrol potential of wild berry-inhabiting yeasts was demonstrated in a real food system, grape juice, where the S. cerevisiae K2-type killer strain significantly reduced fungal contaminants. The selected H. uvarum, M. pulcherrima, S. cerevisiae, and S. paradoxus yeast strains representing both berries were applied for VOC analysis and identification by gas chromatography-linked mass spectrometry. It was revealed that the patterns of emitted volatiles are yeast species-specific. Statistically significant differences between the individual VOCs were observed among killing phenotype-possessing vs. non-killer S. paradoxus yeasts, thus revealing the involvement of killer systems in multi-level biocontrol enablement. The performed studies deepen our understanding of potential yeast biocontrol mechanisms, highlight the importance of produced antimicrobials and volatiles in ensuring antagonistic efficacy, and prove the relevance of isolated biocontrol yeasts for improving food safety.

A Study of Volatile Organic Compounds in Patients with Obstructive Sleep Apnea

Background: Obstructive Sleep Apnea (OSA) is a prevalent sleep disorder characterized by intermittent upper airway obstruction, leading to significant health consequences. Traditional diagnostic methods, such as polysomnography, are time-consuming and resource-intensive. Objectives: This study explores the potential of proton-transfer-reaction mass spectrometry (PTR-MS) in identifying volatile organic compound (VOC) biomarkers for the non-invasive detection of OSA. Methods: Breath samples from 89 participants, including 49 OSA patients and 40 controls, were analyzed using PTR-MS. Significance analysis was performed between OSA patients and controls to identify potential biomarkers for OSA. To as-sess the differences in VOC concentrations between OSA patients and control subjects, the Wilcoxon rank-sum test was employed. partial least squares discriminant analysis (PLS-DA) analysis and heatmap plot was conducted to visualize the differentiation between OSA patients and control subjects based on their VOC profiles.In order to further investigate the correlation between identified biomarkers and the severity of OSA measured by Apnea–Hypopnea Index (AHI), regression analysis was conducted between biomarkers and AHI Index. Results: The results identified specific VOCs, including m045 (acetaldehyde), m095.950, and m097.071, which showed significant differences between OSA patients and controls. Advanced statistical analyses, including PLS-DA and correlation mapping, highlighted the robustness of these biomarkers, with m045 (acetaldehyde) specifically emerging as a potential biomarker associated with the AHI Index. Conclusions: This study underscores the potential of VOCs as biomarkers for identifying patients with severe AHI levels. The analysis of VOCs using PTR-MS presents a rapid, non-invasive, and cost-effective method that could be seamlessly integrated into clinical practice, allowing clinicians to better stratify patients based on their need for polysomnography and prioritize those requiring earlier testing. Future studies are necessary to validate these findings in larger cohorts and to explore the integration of PTR-MS with other diagnostic modalities for improved accuracy and clinical utility.

Volatile Organic Metabolites as Potential Biomarkers for Genitourinary Cancers: Review of the Applications and Detection Methods

Cancer is one of the leading causes of death globally, and is ranked second in the United States. Early detection is crucial for more effective treatment and a higher chance of survival rates, reducing burdens on individuals and societies. Genitourinary cancers, in particular, face significant challenges in early detection. Finding new and cost-effective diagnostic methods is of clinical need. Metabolomic-based approaches, notably volatile organic compound (VOC) analysis, have shown promise in detecting cancer. VOCs are small organic metabolites involved in biological processes and disease development. They can be detected in urine, breath, and blood samples, making them potential candidates for sensitive and non-invasive alternatives for early cancer detection. However, developing robust VOC detection methods remains a hurdle. This review outlines the current landscape of major genitourinary cancers (kidney, prostate, bladder, and testicular), including epidemiology, risk factors, and current diagnostic tools. Furthermore, it explores the applications of using VOCs as cancer biomarkers, various analytical techniques, and comparisons of extraction and detection methods across different biospecimens. The potential use of VOCs in detection, monitoring disease progression, and treatment responses in the field of genitourinary oncology is examined.

Characterization and comparative analysis of volatile organic compounds in four aromatic wild strawberry species using HS-SPME-GC-MS.

Strawberries are valued for their aroma, which is mainly determined by volatile organic compounds (VOCs). Wild strawberries, with broader and more intense VOC profiles, are especially important in breeding programs. Using HS-SPME-GC-MS, 126 VOCs were identified in the ripe fruit of 22 cultivars from four wild strawberry species. Significant interspecies differences were found, with Fragaria mandshurica and F. nilgerrensis showing several times higher VOC levels than F. vesca and F. viridis, primarily due to high lactone content (up to 79.71% of total VOCs). Phylogenetic analysis revealed conserved VOC profiles within species and genotype-aroma correlations. PCA and PLS-DA identified 60 biomarkers explaining 37.07% of the variance, with 10 biomarkers validated for species identification, achieving 100% accuracy. Key biomarkers for F. mandshurica included furaneol and perillyl acetate, while butanoic acid butyl ester was characteristic of F. vesca. This study emphasizes the role of VOCs as biomarkers for species differentiation and their potential in strawberry breeding.

Thermal Desorption Hyphenated to Comprehensive Two-Dimensional Gas Chromatography-Time-of-Flight Mass Spectrometry for Trace Analysis in Raw Renewable Gases-Application to Hydrothermal Gasification.

In the context of the energy transition, European countries pursue the common goal of increasing the share of renewable gases (from anaerobic digestion, pyrogasification, and hydrothermal gasification for instance) in the gas mix. Although produced gases are mainly composed of methane after upgrading, impurities of various natures and quantities may also be present in the produced raw gases and still after upgrading, including volatile organic compounds (VOCs) at trace levels that may have an impact on different stages of the gas chain even at low concentrations. These new renewable and/or low-carbon gases imply the need to develop new analytical tools to deeply characterize them, and thus fully manage their integration into the gas value chain. In this study focused on VOC analysis, a sampling approach using pre-concentration on an adsorbent phase was developed for gas sampling to ensure rapid collection, requiring only a small volume (≈100mL). Traces were then analyzed by thermal desorption hyphenated to a comprehensive two-dimensional gas chromatography time-of-flight mass spectrometer. After identifying the compounds, a semi-quantification method was developed to provide an estimation of the concentration of VOCs for each chemical family. The method was first developed on a biomethane sample before being successfully applied to a raw gas produced by hydrothermal gasification, in which around 250 compounds were detected at a trace level (total concentration equivalent at 200µg/L).

Targeted Analysis of VOCS in Exhaled Breath of Coal Workers' Pneumoconiosis Patients, An Exploratory Study.

Pneumoconiosis represents the most prevalent occupational disease in China, with coal workers' pneumoconiosis (CWP) showing the highest incidence. Analysis of volatile organic compounds (VOCs) in the exhaled breath of CWP patients may provide novel insights into its pathogenesis. Study data were collected through questionnaires and medical examinations. Thermal desorption-gas chromatography-mass spectrometry was employed for targeted VOC analysis. Differential VOCs were identified using OPLS-DA, the Mann-Whitney U test, and fold change analysis. The discriminatory efficacy of differential VOCs was evaluated using receiver operating characteristic (ROC) curves. Spearman correlation analysis explored relationships between differential VOCs, lung function indices, and blood cell levels. The pneumoconiosis group showed elevated concentrations of 10 compounds, including isopentane, n-pentane, and isoprene, while four compounds, including 2,4-dimethylpentane, methylcyclohexane, 2,3,4-trimethylpentane, and 2-methylheptane showed decreased concentrations. Combined univariate and multivariate statistical analyses identified six significant VOCs, including isopentane and pentane. Notably, isopentane and n-pentane demonstrated negative correlations with forced vital capacity and levels, while 2-methylheptane showed positive correlations. Clear metabolic differences in VOCs exist between CWP patients and non-dust-exposed healthy controls. Six compounds - isopentane, n-pentane, 3-methylpentane, n-hexane, cyclohexane, and 2-methylheptane - in exhaled breath demonstrate potential as biomarkers for CWP.

Pathway mapping of exhaled volatile organic compounds associated with blood and ruminal fluid metabolites to describe the nutritional and metabolic status of lactating dairy cows.

Exhaled breath offers an interesting matrix of low invasive sampling of potentially relevant information about the organism's metabolism in the form of volatile organic compounds (VOC). The VOC can be exhaled by the ructus (Islam et al., 2023) or passed the blood-lung barrier for expiration through the lungs. In this work, we consider exhaled breath as a mixture of VOC derived from the lungs and from the upper gastrointestinal tract. However, the informative value of exhaled breath in ruminants remains largely unstudied. The aim of this study was to identify exhaled VOC that could be used to assess the nutritional and metabolic status of dairy cows. To do so, we performed untargeted analysis of exhaled VOC from dairy cows, investigated their correlations with commonly analyzed blood and ruminal fluid metabolites and the calculated energy balance (EB), and explored the underlying pathways of correlated exhaled VOC. This was done as part of a feeding experiment in which 32 lactating Holstein dairy cows were assigned to 2 basal diets for 12 weeks. Half of the cows were fed a hay-based diet, and the other half were fed a silage-based diet. During experimental wk 1-8, half of the cows in each basal diet group were supplemented with a control concentrate, and the other half received an experimental concentrate containing essential oils. During experimental wk 9-12, all cows received the control concentrate. Exhaled breath, blood, and ruminal fluid samples were collected every 4 experimental weeks (W4, 8, and 12) on 3 consecutive sampling days. Exhaled breath was analyzed for VOC, ruminal fluid for VFA and ammonia, and serum samples for albumin, total protein, urea, glucose, cholesterol, BHB, and nonesterified fatty acid (NEFA) concentrations. Pearson correlations were calculated to assess the associations between exhaled VOC and concentrations of blood and ruminal fluid metabolites and the calculated EB. Fifteen correlations were found between exhaled VOC (tetradecanal and γ-hydroxybutyrate (GHB), 3-penten-2-one, 4-hydroxy-4-methylpentan-2-one, 2-ethylhexanal, 2-ethylhexan-1-ol, p-cymene) and ruminal fluid (acetate, butyrate, valerate, and ammonia) and blood metabolite concentrations (BHB, NEFA, glucose, urea, and cholesterol) across the cow groups. The underlying pathways of 3-penten-2-one, GHB, and tetradecanal were mainly related to fat and protein catabolism and therefore to the actual animal metabolism. The correlations with the other 4 exhaled VOC, 4-hydroxy-4-methylpentan-2-one, p-cymene, 2-ethyl-hexan-1-ol, and 2-ethylhexanal, were diet- or time-related, specifically due to differences in feed ingredients. The results demonstrate the associations of single exhaled VOC with the nutritional and metabolic status of healthy dairy cows. Their potential as new biomarkers should be further investigated in cows in various nutritional and metabolic states.

Comprehensive Analysis of Volatile Organic Compounds and Their Impact on Apple Quality Following Some Essential Oil Treatments Against Botrytis cinerea

The susceptibility of apples to post-harvest decay by the fungus Botrytis cinerea has prompted innovative research into alternative preservation methods. In this regard, essential oils (EOs) have emerged as promising candidates due to their natural origin and potential antimicrobial properties. Investigating the biological significance of EO blends is crucial for understanding their potential antimicrobial mechanisms and evaluating their capacity to modulate metabolic responses that could inhibit post-harvest fungal decay in fruit tissues. This study delves into the intricate chemistry of apples when subjected to various EO treatments, shedding light on the profound changes in alcohols, esters, C6 compounds, terpenes, and volatile compounds. Based on our results, terpene concentrations exhibit significant variations with α-Pinene ranging from 13.4 µg L−1 in Fungus + Thymol + 1,8-Cineole treatment (Fun+Thy+Cin) to 28.7 µg L−1 in Fungus + Thymol + 1,8-Cineole + Eugenol treatment (Fun+Thy+Cin+Eug), and β-Pinene concentrations spanning 19.3 µg L−1 in Fungus + 1,8-Cineole + Eugenol treatment (Fun+Cin+Eug) to 45.5 µg L−1 in Fungus + Thymol + 1,8-Cineole + Eugenol treatment (Fun+Thy+Cin+Eug). Ester elaboration presents marked changes, with ethyl octanoate peaking at 715.7 µg L−1 in Fungus + Thymol + 1,8-Cineole + Eugenol treatment (Fun+Thy+Cin+Eug) and ethyl propionate reaching 152.9 µg L−1 in Fungus + Thymol treatment (Fun+Thy). The volatile compound dynamics also demonstrate significant variations, with hexanoic acid concentrations ranging from 0.1 to 0.2 among treatments and 3-Methylbutanal displaying concentrations from 0.8 to 6.4, with the highest concentration observed in the Control. The essential oil combination of Thymol, Eugenol, and 1,8-Cineol (Fun+Thy+Cin+Eug) had the most significant impact on the volatile compound content in the fruits. The findings from this study unveil the intricate responses of apple chemistry to various EO treatments. These insights hold promise for enhancing post-harvest apple preservation strategies through the modulation of EO treatments.

Quality Evaluation and Shipping Export Potential of ‘Eliteggul’ Korean Melon (Cucumis melo var. makuwa) to Singapore Using MAP Technology

Korean melons (Cucumis melo var. makuwa), which have a short shelf life and are prone to browning, face challenges when exported over long-distance via maritime shipping. However, the high firmness and low suture browning rate of the ‘Eliteggul’ cultivar suggest its potential suitability for long-distance export. This study aimed to evaluate the export suitability of ‘Eliteggul’ by comparing it to the widely grown cultivar ‘Alchankkul’. Consumer preferences were assessed based on fragrance, sweetness, overall preference, appearance, and firmness. Both cultivars were grown and harvested in a commercial greenhouse in Seongju-gun, South Korea. After being treated with modified atmosphere film, the fruits were stored at 6 °C for 1 day, transported to Singapore in a shipping container at 7.4 °C for 13 days, and distributed at 22 °C for 3 days. After 14 days of storage, analysis in Singapore showed that ‘Eliteggul’ maintained a significantly higher firmness at 12.9 ± 0.3 kg·cm2 compared to ‘Alchankkul’, which showed firmness at 8.1 ± 0.4 kg·cm2. Additionally, ‘Eliteggul’ exhibited less browning on the white sutures at 1.3 ± 0.1, indicating better preservation of its quality than ‘Alchankkul’, at 2.0 ± 0.3. Even at 14 + 3 days, ‘Eliteggul’ maintained a firmness of 12.8 ± 0.2 kg·cm2, which was significantly higher than that of ‘Alchankkul’, which showed a firmness of 7.7 ± 0.5 kg·cm2. Consumer preference surveys (n = 78) conducted in the local market revealed that customers favored the fragrance and sweetness of ‘Alchankkul’. Correspondingly, an analysis of volatile organic compounds (VOCs) from melon juice using a Twister stir bar method showed that ‘Alchankkul’ had significantly higher levels of ethyl(methylthio)acetate, ethyl propanoate, and benzyl alcohol, known to contribute to a sweet flavor. Furthermore, a thermal desorption tube VOCs test indicated that hexyl acetate and 2-methylbutyl 2-methylbutyrate were also significantly higher in ‘Alchankkul’. Despite this result, there was no significant difference in the overall preference scores between the two cultivars. This study indicates that ‘Eliteggul’, with a superior firmness, reduced browning, and high consumer acceptance, is ideal for long-distance export, offering foundational data to bridge the research gap in export-oriented melons and support the broader distribution of Korean cultivars.

Comparison of Untargeted and Markers Analysis of Volatile Organic Compounds with SIFT-MS and SPME-GC-MS to Assess Tea Traceability.

Tea is one of the most consumed beverages in the world and presents a great aromatic diversity depending on the origin of the production and the transformation process. Volatile organic compounds (VOCs) greatly contribute to the sensory perception of tea and are excellent markers for traceability and quality. In this work, we analyzed the volatile organic compounds (VOCs) emitted by twenty-six perfectly traced samples of tea with two analytical techniques and two data treatment strategies. First, we performed headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) as the most widely used reference method for sanitary and quality controls of food. Next, we analyzed the samples with selected-ion flow-tube mass spectrometry (SIFT-MS), an emerging method for direct analysis of food products and aroma. We compared the performances of both techniques to trace the origin and the transformation processes. We selected the forty-eight most relevant markers with HS-SPME-GC-MS and evaluated their concentrations with a flame ionization detector (FID) on the same instrument. This set of markers permitted separation of the origins of samples but did not allow the samples to be differentiated based on the color. The same set of markers was measured with SIFT-MS instrument without success for either origin separation or color differentiation. Finally, a post-processing treatment of raw data signals with an untargeted approach was applied to the GC-MS and SIFT-MS dataset. This strategy allowed a good discrimination of origin and color with both instruments. Advantages and drawbacks of volatile profiles with both instruments were discussed for the traceability and quality assessment of food.

Machine Learning Model Discriminate Ischemic Heart Disease Using Breathome Analysis.

Background: Ischemic heart disease (IHD) impacts the quality of life and is the most frequently reported cause of morbidity and mortality globally. Aims: To assess the changes in the exhaled volatile organic compounds (VOCs) in patients with vs. without ischemic heart disease (IHD) confirmed by stress computed tomography myocardial perfusion (CTP) imaging. Objectives: IHD early diagnosis and management remain underestimated due to the poor diagnostic and therapeutic strategies including the primary prevention methods. Materials and Methods: A single center observational study included 80 participants. The participants were aged ≥ 40 years and given an informed written consent to participate in the study and publish any associated figures. Both groups, G1 (n = 31) with and G2 (n = 49) without post stress-induced myocardial perfusion defect, passed cardiologist consultation, anthropometric measurements, blood pressure and pulse rate measurements, echocardiography, real time breathing at rest into PTR-TOF-MS-1000, cardio-ankle vascular index, bicycle ergometry, and immediately after performing bicycle ergometry repeating the breathing analysis into the PTR-TOF-MS-1000, and after three minutes from the end of the second breath, repeat the breath into the PTR-TOF-MS-1000, then performing CTP. LASSO regression with nested cross-validation was used to find the association between the exhaled VOCs and existence of myocardial perfusion defect. Statistical processing performed with R programming language v4.2 and Python v.3.10 [^R], STATISTICA program v.12, and IBM SPSS v.28. Results: The VOCs specificity 77.6% [95% confidence interval (CI); 0.666; 0.889], sensitivity 83.9% [95% CI; 0.692; 0.964], and diagnostic accuracy; area under the curve (AUC) 83.8% [95% CI; 0.73655857; 0.91493173]. Whereas the AUC of the bicycle ergometry 50.7% [95% CI; 0.388; 0.625], specificity 53.1% [95% CI; 0.392; 0.673], and sensitivity 48.4% [95% CI; 0.306; 0.657]. Conclusions: The VOCs analysis appear to discriminate individuals with vs. without IHD using machine learning models. Other: The exhaled breath analysis reflects the myocardiocytes metabolomic signature and related intercellular homeostasis changes and regulation perturbances. Exhaled breath analysis poses a promise result to improve the diagnostic accuracy of the physical stress tests using machine learning models.

Respiratory quaternary ammonium and volatile organic compound exposures experienced by home care aides during residential bathroom cleaning using conventional and green products.

US home care (HC) aide visits to clients' homes typically involve cleaning and disinfecting (C&D) environmental surfaces, particularly in bathrooms. Some ingredients in C&D products are associated with respiratory illness: sodium hypochlorite (bleach), quaternary ammonium compounds (QACs), and volatile organic compounds (VOCs). This study assessed and compared aides' respiratory exposures to specific VOCs and QACs while using 2 conventional and 1 "green" household C&D spray products during bathroom cleaning. Measured exposures were compared to ingredients listed on publicly available sources. Three C&D products were selected with principal active disinfecting ingredients: 1% to 5% sodium hypochlorite by weight ("bleach-based"); 0.1% to 1% QACs ("QACs-based"); and 0.05% thymol ("green"). Twenty-two aides were recruited to perform C&D tasks in a simulated residential bathroom constructed in an environmental monitoring laboratory. A balanced experimental study design involved each aide visiting the lab 4 times to perform typical cleaning tasks with the 3 products and distilled water (as a control), randomly assigned across the 4 visits. Aides wore air sampling equipment for breathing zone samples: canisters to collect whole air for VOC analyses and filter cassettes for QACs analyses. Aides performed 84 cleaning visits contributing approximately 20 air samples each for VOCs and QACs, for each of the 3 products and distilled water. In total, 38 unique VOCs were identified in the canister whole air samples: 20 in the QACs-based product samples, 15 in the bleach-based, and 10 in the green. Most VOCs were not listed in publicly available sources of cleaning product ingredients. Toxicity information was limited. Few VOCs had occupational exposure limits. The QACs-based product generated QACs aerosol: benzalkonium chloride (BAC)12 (geometric mean (GM) = 6.98 µg/m3), BAC14 (GM=2.97 µg/m3), BAC16 (GM=0.78 µg/m3); and the 3 QACs summed (GM=10.86 µg/m3). The use of C&D spray products for residential cleaning can generate respiratory exposures to complex mixtures of volatile and nonvolatile compounds. Notably, we measured aerosols containing QACs during the use of the QACs-based product. Dermal is usually considered the main route of exposure because QACs are nonvolatile salts. This study provides evidence that QACs inhalation exposure should be recognized and minimized in addition to the well-accepted dermal exposure routes. The green product generated the fewest VOCs. However, more toxicity information is needed on the health impacts of green C&D products. Spraying of C&D products, conventional and green, should be avoided. Aides' respiratory health should be protected from chemical exposures while performing C&D in home care.

Non-invasive detection of early-stage lung cancer through exhaled breath volatile organic compound analysis

Non-invasive detection of early-stage lung cancer through exhaled breath volatile organic compound analysis

Microbial diversity and cover plants in de-sealed urban soil as strategies for mitigating anthropogenic volatile organic compounds

Urbanization exacerbates soil degradation, compromising global soil health and biodiversity. To reduce this, strategies for soil de-sealing and bioremediation are necessary. In a mesocosm experiment using a de-sealed soil from an urban site as substrate, an inoculum of arbuscular mycorrhizal fungi (AMF) and two cover plants, Cynara cardunculus L. and Trifolium repens L., were utilized to assess their effects on volatile organic compound (VOC) emissions and soil microbial community dynamics. The soil status was investigated employing soil VOC and metabarcoding analyses. Our results showed that the soil VOC emission was mainly composed by anthropogenic derived VOCs, especially arene and furan classes. These two classes were shown to be less concentrated in C. cardunculus soils, with and without AM fungal inoculation, suggesting a positive impact of these conditions on soil health restoration. Additionally, AM fungal inoculation of C. cardunculus resulted in increased bacterial alpha diversity, with enhanced Proteobacteria/Acidobacteria, Cyanobacteria/Chloroflexi, and Fungi/Bacteria ratios, suggesting an improvement in soil quality conditions. In our experimental conditions, order Chloroflexales and specific bacterial genera, including Ralstonia, Delftia, Ramlibacter, were identified as contributors to VOC degradation, highlighting their adaptability in contaminated environments. Overall, this study provided evidence on the importance of integrating AM fungal inoculation and specific flowerbed/ornamental plants in urban soil management after de-sealing processes.

A simple and effective non-invasive method for the analysis of volatile organic compounds in exhaled air

Breath analysis is a cutting-edge technique that collects significant medical information by analyzing the substances found in exhaled breath. Fluctuations in the levels of chemicals such as acetone can serve as indicators of medical ailments or contact with hazardous substances such as occupational exposure. In order to detect acetone in exhaled air, techniques such as needle trap coupled with gas chromatography have been devised. This procedure involves the use of a nanocomposite called Mil101(Fe)@Fe3O4@SiO2.The nanocomposite is synthesized using a chemical hydrothermal method. In order to examine the properties of the Mil101(Fe)@Fe3O4@SiO2 nanocomposite, researchers utilized a range of analytical techniques including scanning electron microscopy (SEM), thermal analysis (TGA), x-ray analysis (EDX), Brunauer-Emmett-Teller (BET) method, and Fourier Transform Infrared Spectroscopy (FT-IR). The efficiency of the NTD-GC-FID method depends on several parameters, such as temperature, desorption time, fracture passage volume, sampling time, sample temperature, and sampling flow rate. These parameters have been studied using the simplex method to optimize the process. The optimal conditions yielded a limit of detection (LODs) of 0.4 µg/L and a limit of quantification (LOQs) of 1.1 µg/L. The calibration curve for the NTD-GC-FID method ranged from 0.011 to 10 mgl−1 with an acceptable error range. Moreover, the method demonstrated good repeatability and reproducibility, with calculated values of 3.9 and 4.6 %, respectively. The proposed method was successfully employed in this study to identify and measure acetone in the exhaled air of individuals with diabetes, yielding satisfactory results. The needle trap tool was used over 100 times without any decline in its efficiency for adsorbing acetone. In summary, this research presents a new analytical approach, namely the NTD-GC-FID method, to detect and measure acetone in exhaled air. Compared to the other methods for analyzing acetone, the application of Mil101(Fe)@Fe3O4@SiO2 nanocomposite demonstrated promising results in detection of diabetes.

Detection of Mycobacterium avium subsp. paratuberculosis in Australian Cattle and Sheep by Analysing Volatile Organic Compounds in Faeces.

Paratuberculosis is a debilitating disease of ruminants that causes significant economic loss in both cattle and sheep. Early detection of the disease is crucial to controlling the disease; however, current diagnostic tests lack sensitivity. This study evaluated the potential for volatile organic compounds (VOCs) detected by gas chromatography and an electronic nose (eNose) for use as diagnostic tools to differentiate between Map-infected and non-infected cattle and sheep. Solid-phase micro-extraction gas chromatography-mass spectrometry (SPME GC-MS) was used to quantify VOCs from the headspace of faecal samples (cattle and sheep), and partial least squares-discriminant analysis (PLS-DA) was used to determine the suitability as a diagnostic tool. Both the cattle and sheep models had high specificity and sensitivity, 98.1% and 92.3%, respectively, in cattle, and both were 100% in sheep. The eNose was also able to discriminate between Map-infected and non-infected sheep and cattle with 88.9% specificity and 100% sensitivity in sheep and 100% specificity and sensitivity in cattle. This is the first time that VOC analysis by eNose and GCMS has been used for identification of Map in cattle and sheep faeces. GCMS also allowed the identification of putative disease biomarkers, and the eNose diagnostic capability suggests it is a promising tool for point-of-care diagnosis for Map detection on farms.

Review of source analyses of ambient volatile organic compounds considering reactive losses: methods of reducing loss effects, impacts of losses, and sources

Abstract. Chemical losses of ambient reactive volatile organic compounds (VOCs) is a long-term issue yet to be resolved in VOC source apportionments. These losses substantially reduce the concentrations of highly reactive species in the apportioned factor profiles and result in the underestimation of source contributions. This review assesses the common methods and existing issues in ways to reduce losses and loss impacts in source analyses and suggests research directions for improved VOC source apportionments. Positive matrix factorization (PMF) is now the main VOC source analysis method compared to other mathematical models. The issue in using any apportionment tool is the processing of the data to be analyzed to reduce the impacts of reactive losses. Estimating the initial concentrations of ambient VOCs based on photochemical age has become the primary approach to reduce reactive loss effects in PMF, except for selecting low-reactivity species or nighttime data into the analysis. Currently, the initial concentration method only considers daytime reactions with hydroxyl (⚫OH) radicals. However, the ⚫OH rate constants vary with temperature, and that has not been considered. Losses from reactions with O3 and NO3 radicals, especially for alkene species, remain to be included. Thus, the accuracy of the photochemical age estimation is uncertain. Beyond developing accurate quantitative approaches for reactive losses, source analyses methods for the consumed VOCs and the accurate quantification of different source contributions to O3 and secondary organic aerosols are important additional directions for future research.

Analysis of the Urine Volatilome of COVID-19 Patients and the Possible Metabolic Alterations Produced by the Disease.

Alterations in metabolism caused by SARS-CoV-2 infection have been highlighted in various investigations and have been used to search for biomarkers in different biological matrices. However, the selected biomarkers vary greatly across studies. Our objective is to provide a robust selection of biomarkers, including results from different sample treatments in the analysis of volatile organic compounds (VOCs) present in urine samples from patients with COVID-19. Between September 2021 and May 2022, urine samples were collected from 35 hospitalized COVID-19 patients and 32 healthy controls. The samples were analyzed by headspace (HS) solid phase microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC-MS). Analyses were conducted on untreated urine samples and on samples that underwent specific pretreatments: lyophilization and treatment with sulfuric acid. Partial Least Squares Linear Discriminant Analysis (PLS-LDA) and Subwindow Permutation Analysis (SPA) models were established to distinguish patterns between COVID-19 patients and healthy controls. The results identify compounds that are present in different proportions in urine samples from COVID-19 patients compared to those from healthy individuals. Analysis of urine samples using HS-SPME-GC-MS reveals differences between COVID-19 patients and healthy individuals. These differences are more pronounced when methods that enhance VOC formation are used. However, these pretreatments can cause reactions between sample components, creating additional products or removing compounds, so biomarker selection could be altered. Therefore, using a combination of methods may be more informative when evaluating metabolic alterations caused by viral infections and would allow for a better selection of biomarkers.

Olfactometer-measured responses of Listronotus bonariensis (Kuschel) (Coleoptera: Curculionidae) to feeding-induced grass volatiles and conspecific frass as influenced by the weevil’s seasonality

This contribution aimed to uncover the unique host plant-finding and spatial ecology of reproductive and diapausing Argentine stem weevil, Listronotus bonariensis, and its adaptive implications in Aotearoa-New Zealand pasture. Still-air two-armed olfactometers revealed the reproductive and diapausing L. bonariensis preferences for plant and weevil-derived volatiles. Winter-collected diapausing weevils were strongly attracted to host plant feeding damage by conspecifics and their frass. Such attraction disappeared when 20 stem weevils were added to the damaged ryegrass. This suggests that L. bonariensis on a damaged host plant above a certain density causes repellency probably avoiding over-exploitation of the host plant. Neither the weevils’ sex nor related physiological condition were found to impart any significant effects. Volatile organic compound (VOC) analysis showed that phenylacetaldehyde was the only de novo synthesised herbivore-induced volatile compound found resulting from diapausing L. bonariensis feeding damage. This study therefore found that the seasonal behaviour of L. bonariensis was very closely related to that of the rice water weevil Lissorhoptrus oryzophilus and its very similar responses to phenylacetaldehyde. In both cases the compound attracts spring populations (emerging from diapause) to their host plants and conspecifics. Thereafter, as with L. oryzophilus, L. bonariensis similarly on becoming reproductive, its sensitivity to phenylacetaldehyde ceases. Such close connection between L. bonariensis and L. oryzophilus seasonal responses to phenylacetaldehyde therefore greatly reenforces the concept of evolved L. bonariensis behaviour in its native range as being relict behaviour in New Zealand’s grassland ecosystem.

Detection of volatile organic compounds in soils (literature review)

Volatile organic compounds (VOC) are major environmental pollutants. Due to their high mobility, they penetrate into all environmental objects, pose an environmental threat and health risks. Getting into the soil, they deteriorate its quality. VOC content requires reliable control. There is presented a review of the literature, including methods of the US Environmental Protection Agency, and regulatory and methodological documents of the Russian Federation regulating methods of selection, storage, preparation and analysis of soil samples for VOC content. The dominant place among methods for monitoring for VOCs belongs to gas chromatography with various types of detectors. For multicomponent analysis of complex objects, gas chromatography with mass selective detection is used due to the wide capabilities provided by the mass detector. A universal mass spectrometry method used in analytical laboratories is electron impact ionization mass spectrometry. For research purposes, modern highly sensitive methods are used – mass spectrometry based on the proton transfer reaction PTR-MS, ion trap mass spectrometry PIT-MS, negative ion ionization mass spectrometry NI-PT-CIMS, time-of-flight mass spectrometry of the transfer reaction proton PTR-TOF-MS. The collection and storage of samples for VOC analysis requires compliance with regulations to prevent both loss of analytes and sample contamination. Sample preparation includes methods such as vacuum and azeotropic distillation, thermal desorption, liquid extraction, various options for static and dynamic headspace analysis.