VOC Profiles of Saliva in Assessment of Halitosis and Submandibular Abscesses Using HS-SPME-GC/MS Technique

Qualitative and quantitative rapid detection of VOCs differentially released by VAP-associated bacteria using PTR-MS and FGC-PTR-MS

Ventilator-associated pneumonia (VAP) is a prevalent disease caused by microbial infection, resulting in significant morbidity and mortality within the intensive care unit (ICU). The rapid and accurate identification of pathogenic bacteria causing VAP can assist clinicians in formulating timely treatment plans. In this study, we attempted to differentiate bacterial species in VAP by utilizing the volatile organic compounds (VOCs) released by pathogens. We cultured 6 common bacteria in VAP in vitro, including Acinetobacter baumannii, Enterobacter cloacae, Escherichia coli, Pseudomonas aeruginosa, Stenotrophomonas maltophilia, and Staphylococcus aureus, which covered most cases of VAP infection in clinic. After the VOCs released by bacteria were collected in sampling bags, they were quantitatively detected by a proton transfer reaction-mass spectrometry (PTR-MS), and the characteristic ions were qualitatively analyzed through a fast gas chromatography-proton transfer reaction-mass spectrometry (FGC-PTR-MS). After conducting principal component analysis (PCA) and analysis of similarities (ANOSIM), we discovered that the VOCs released by 6 bacteria exhibited differentiation following 3 h of quantitative cultivation in vitro. Additionally, we further investigated the variations in the types and concentrations of bacterial VOCs. The results showed that by utilizing the differences in types of VOCs, 6 bacteria could be classified into 5 sets, except for A. baumannii and E. cloacae which were indistinguishable. Furthermore, we observed significant variations in the concentration ratio of acetaldehyde and methyl mercaptan released by A. baumannii and E. cloacae. In conclusion, the VOCs released by bacteria could effectively differentiate the 6 pathogens commonly associated with VAP, which was expected to assist doctors in formulating treatment plans in time and improve the survival rate of patients.

Lactobacillus paracasei ET-22 and derived postbiotics reduce halitosis and modulate oral microbiome dysregulation - a randomized, double-blind placebo-controlled clinical trial

Oral microbial dysbiosis is the primary etiologic factor for halitosis and may be the critical preventive target for halitosis. This study included randomized controlled trials (RCTs) assessing the effects of Lactobacillus paracasei ET-22 live and heat-killed bacteria on halitosis and the related oral microbiome. 68 halitosis subjects were divided into placebo, ET-22 live (ET-22.L) and ET-22 heat-killed (ET-22.HK) groups. Subjects took different lozenges three times a day for 4 weeks and underwent saliva collection and assessment of breath volatile sulfur compound (VSC) levels at the beginning and end of the intervention. Salivary volatile organic compounds were measured using HS-SPME-GC/MS, and the microbiome profile was determined by 16S rRNA gene amplicon sequencing. A positive decrease in breath volatile sulfur compound (VSC) levels was observed in the means of both ET-22.L and ET-22.HK groups after 4 weeks of intervention, being more marked in the ET-22.L group (p = 0.0148). Moreover, ET-22.L and ET-22.HK intervention remarkably changed the composition of total salivary volatile organic compounds (VOCs) and aroma-active VOCs. Key undesirable VOCs, such as indole, pyridine, nonanoic acid, benzothiazole, and valeric acid, were significantly reduced. Meanwhile, ET-22.L or ET-22.HK also altered the taxonomic composition of the salivary microbiome. The halitosis pathogens Rothia and Streptococcus were significantly reduced in the ET-22.HK group and the pathogenic Solobacterium and Peptostreptococcus were significantly inhibited in the ET-22.L group. Collectively, our study suggests that both ET-22.L and ET-22.HK can significantly inhibit the production of undesirable odor compounds in subjects with halitosis, which may be related to the changes of the oral microbiome.

Antibiotic treatment and supplemental hemin availability affect the volatile organic compounds produced by P. gingivalis in vitro

We have measured the changes in the production of volatile organic compounds (VOCs) by the oral pathogen Porphyromonas gingivalis, when treated in vitro with the antibiotic amoxicillin. We have also measured the VOC production of P. gingivalis grown in the presence and absence of supplemental hemin. Planktonic bacterial cultures were treated with different amounts of amoxicillin in the lag phase of the bacterial growth. Planktonic bacteria were also cultured with and without supplemental hemin in the culture medium. Concentrations of VOCs were measured with proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) and further molecular identification was done with gas chromatography-mass spectrometry (GC-MS) using solid phase microextraction (SPME) for sampling. The cell growth of P. gingivalis in the cultures was estimated with optical density measurements at the wavelength of 600 nm (OD₆₀₀). We found that the production of methanethiol, hydrogen sulfide and several short- to medium-chain fatty acids was decreased with antibiotic treatment using amoxicillin. Compounds found to increase with the antibiotic treatment were butyric acid and indole. In cultures without supplemental hemin, indole and short- to medium-chain fatty acid production was significantly reduced. Acetic acid production was found to increase when supplemental hemin was not available. Our results suggest that the metabolic effects of both antibiotic treatment and supplemental hemin availability are reflected in the VOCs produced by P. gingivalis and could be used as markers for bacterial cell growth and response to threat. Analysis of these volatiles from human samples, such as the exhaled breath, could be used in the future to rapidly monitor response to antibacterial treatment.

Volatile composition of the morning breath

We have measured the composition of volatile organic compounds (VOCs) in the morning breath of 30 healthy individuals before and after tooth brushing. The concentrations of VOCs in the breath samples were measured with proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) and further identification was performed with a combination of solid phase microextraction (SPME) and offline gas chromatography-mass spectrometry (GC-MS). We hypothesize that compounds, whose concentrations significantly decreased in the breath after tooth brushing are largely of microbial origin. In this study, we found 35 such VOCs. Out of these, 33 have been previously connected to different oral niches, such as salivary and subgingival bacteria. We also compared the concentrations of the 35 VOCs found in increased amounts in the morning breath to their respective odor thresholds to evaluate their ability to cause odor. Compounds that could contribute to the breath odor include many volatile sulfur compounds, such as methanethiol, hydrogen sulfide, dimethyl sulfide, and 2-methyl-1-propanethiol, but also other VOCs, such as acetic acid, butyric acid, valeric acid, acetaldehyde, octanal, phenol, indole, ammonia, isoprene, and methyl methacrylate.

Detection of volatile sulfur compounds (VSCs) in exhaled breath as a potential diagnostic method for oral squamous cell carcinoma

Background

Oral squamous cell carcinoma causes a significant proportion of global cancer morbidity and mortality. The aim of this study is to investigate whether the exhaled breath test can be a new, non-invasive, and effective method for diagnosing oral squamous cell carcinoma.

Methods

A comparative analysis of exhaled breath between patients with oral squamous cell carcinoma (OSCC) and healthy controls (HC) was performed with the Twin Breasor II™, a simple gas chromatography system.

Results

Both hydrogen sulfide (H₂S) and methyl mercaptan (Ch₃SH) were significantly higher in the OSCC group than in the HC group. The total sulfur concentration was also higher in the OSCC group, but there was no significant difference in the ratio of Ch₃SH to H₂S between the two groups. Using logistic regression, we constructed a new variable with an area under the curve (AUC) of 0.740, 68.0% sensitivity, and 72.0% specificity.

Conclusions

Exhaled gas analysis via simple gas chromatography can potentially serve as an accessory non-invasive method for OSCC diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-022-02301-3.

ANTİ-HALİTOSİS GARGARALARININ REZİN BAZLI RESTORATİF DENTAL MATERYALLERİN YÜZEY ÖZELLİKLERİ ÜZERİNE ETKİSİ

Amaç: Bu in-vitro çalışmanın amacı anti-halitosis etkili beş farklı ağız gargarasının iki farklı restoratif materyalin renk stabilitesi ve yüzey pürüzlülüğü üzerine olan etkisinin araştırılmasıdır. Gereç ve Yöntemler: Çalışmada nano-hibrit (Filtek Z550, 3M ESPE) ve giomer (Beautifill II, Shofu Dental) yapıda olan iki çeşit reçine bazlı restoratif materyal kullanılmıştır. Her iki materyalden test edilmek üzere toplam 120 adet kompozit disk üretici talimatları doğrultusunda 10x2mm ebatlarında silindir kalıplar kullanılarak hazırlanmıştır. Rastgele seçilen örnekler, 5 farklı ağız gargarası (Listerine Fresh Burst, Listerine Total Care, Colgate Plax, Oderol, Halitosil) ve 1 kontrol grubunda (distile su) bekletilmek üzere toplam 6 farklı gruba ayrılmıştır. Başlangıç renk koordinatları CIELAB renk sistemine göre spektrofotometre (Easyshade Compact) ile yüzey pürüzlülük değerleri (Ra) ise kontakt profilometre (Surtronic 25) ile ölçülmüştür. Tüm örnekler 37°C'de ağız gargaralarında 12boyunca bekletilmiş ardından renk ve pürüzlülük ölçüm prosedürleri aynı şekilde gerçekleştirilmiştir. Elde edilen veriler SPSS 24.0 programı ile Kruskal-Wallis H ve Bonferroni Post Hoc testleri kullanılarak 0.05 anlamlılık düzeyinde analiz edilmiştir. Bulgular: Bu çalışmanın sonuçları, yüzey pürüzlülük değerlerinde istatistiksel olarak anlamlı bir artış olmadığını göstermiştir. Ağız gargaralarında bekletilen Beautifil II materyallerinin tamamında CIELAB değerlerinde önemli bir değişiklik olmuştur (P

Profiling volatile compounds from culture supernatants of periodontal bacteria using gas chromatography/mass spectrometry/olfactometry analysis with a monolithic silica gel adsorption device

Halitosis is formed mainly by the volatile compounds produced by periodontal bacteria. Three volatile sulfur compounds (VSCs), hydrogen sulfide, methanethiol, and dimethyl sulfide, have attracted attention as major components of halitosis. However, these compounds cannot account for all odors. In this study, we profiled volatile compounds from the culture supernatants of periodontal bacteria using gas chromatography/mass spectrometry/olfactometry analysis with a monolithic silica gel adsorption device to investigate the potential odorous compounds. Periodontal bacteria have been found to produce volatile compounds belonging to various classes, such as alcohols, ketones, fatty acids, and aromatic compounds, in addition to VSCs. In addition, VSCs different from hydrogen sulfide and methanethiol, which are considered important causative compounds, may also influence to halitosis.

A Literature Review and Framework Proposal for Halitosis Assessment in Cigarette Smokers and Alternative Nicotine-Delivery Products Users

Halitosis is a health condition which counts cigarette smoking (CS) among its major risk factors. Cigarette smoke can cause an imbalance in the oral bacterial community, leading to several oral diseases and conditions, including intraoral halitosis. Although the best approach to decrease smoking-related health risks is quitting smoking, this is not feasible for many smokers. Switching to potentially reduced-risk products, like electronic vapor products (EVP) or heated tobacco products (HTP), may help improve the conditions associated with CS. To date, there have been few systematic studies on the effects of CS on halitosis and none have assessed the effects of EVP and HTP use. Self-assessment studies have shown large limitations owing to the lack of reliability in the participants' judgment. This has compelled the scientific community to develop a strategy for meaningful assessment of these new products in comparison with cigarettes. Here, we compiled a review of the existing literature on CS and halitosis and propose a 3-layer approach that combines the use of the most advanced breath analysis techniques and multi-omics analysis to define the interactions between oral bacterial species and their role in halitosis both in vitro and in vivo. Such an approach will allow us to compare the effects of different nicotine-delivery products on oral bacteria and quantify their impact on halitosis. Defining the impact of alternative nicotine-delivery products on intraoral halitosis and its associated bacteria will help the scientific community advance a step further toward understanding the safety of these products and their potentiall risks for consumers.

Marine Bioactive Compounds as Nutraceutical and Functional Food Ingredients for Potential Oral Health

Oral diseases have received considerable attention worldwide as one of the major global public health problems. The development of oral diseases is influenced by socioeconomic, physiological, traumatic, biological, dietary and hygienic practices factors. Currently, the main prevention strategy for oral diseases is to inhibit the growth of biofilm-producing plaque bacteria. Tooth brushing is the most common method of cleaning plaque, aided by mouthwash and sugar-free chewing gum in the daily routine. As the global nutraceutical market grows, marine bioactive compounds are becoming increasingly popular among consumers for their antibacterial, anti-inflammatory and antitumor properties. However, to date, few systematic summaries and studies on the application of marine bioactive compounds in oral health exist. This review provides a comprehensive overview of different marine-sourced bioactive compounds and their health benefits in dental caries, gingivitis, periodontitis, halitosis, oral cancer, and their potential use as functional food ingredients for oral health. In addition, limitations and challenges of the application of these active ingredients are discussed and some observations on current work and future trends are presented in the conclusion section.

Micro-Chamber/Thermal Extractor (µ-CTE) as a new sampling system for VOCs emitted by feces

VOCs (volatile organic compounds) are increasingly wished to be used in diagnosis of diseases. They present strategic advantages, when compared to classical methods used, such as simplicity and current availability of performant non-invasive sample collection methods/systems. However, standardized sampling methods are required in order to achieve reproducible results. In the current study we developed a method to be used for feces sampling using a Micro-Chamber/Thermal Extractor (µ-CTE). Design Expert software (with Box-Behnken design) was used to predict the solutions. Therefore, by using the simulation experimental plan that was further experimentally verified, extraction time of 19.6 min, at extraction temperature of 30.6 °C by using a flow rate of 48.7 mL/min provided the higher response. The developed method was validated by using correlation tests and Network analysis, which both proved the validity of the developed model.

Identification of Volatile Sulfur Compounds Produced by Schizophyllum commune

Schizophyllum commune is a causative agent of allergic bronchopulmonary mycosis, allergic fungal rhinosinusitis, and basidiomycosis. Diagnosis of these diseases remains difficult because no commercially available tool exists to identify the pathogen. Unique volatile organic compounds produced by a pathogen might be useful for non-invasive diagnosis. Here, we explored microbial volatile organic compounds produced by S. commune. Volatile sulfur compounds, dimethyl disulfide (48 of 49 strains) and methyl ethyl disulfide (49 of 49 strains), diethyl disulfide (34 of 49 strains), dimethyl trisulfide (40 of 49 strains), and dimethyl tetrasulfide (32 of 49 strains) were detected from headspace air in S. commune cultured vials. Every S. commune strain produced at least one volatile sulfur compound analyzed in this study. Those volatile sulfur compounds were not detected from the cultures of Aspergillus spp. (A. fumigatus, A. flavus, A. niger, and A. terreus), which are other major causative agents of allergic bronchopulmonary mycosis. The last, we examined H₂S detection using lead acetate paper. Headspace air from S. commune rapidly turned the lead acetate paper black. These results suggest that those volatile sulfur compounds are potent targets for the diagnosis of S. commune and infectious diseases.

Identification of Salivary Microorganisms and Metabolites Associated with Halitosis

Halitosis is mainly caused by the action of oral microbes. The purpose of this study was to investigate the differences in salivary microbes and metabolites between subjects with and without halitosis. Of the 52 participants, 22 were classified into the halitosis group by the volatile sulfur compound analysis on breath samples. The 16S rRNA gene amplicon sequencing and metabolomics approaches were used to investigate the difference in microbes and metabolites in saliva of the control and halitosis groups. The profiles of microbiota and metabolites were relatively different between the halitosis and control groups. The relative abundances of Prevotella, Alloprevotella, and Megasphaera were significantly higher in the halitosis group. In contrast, the relative abundances of Streptococcus, Rothia, and Haemophilus were considerably higher in the control group. The levels of 5-aminovaleric acid and n-acetylornithine were significantly higher in the halitosis group. The correlation between identified metabolites and microbiota reveals that Alloprevotella and Prevotella might be related to the cadaverine and putrescine pathways that cause halitosis. This study could provide insight into the mechanisms of halitosis.

A literature survey of all volatiles from healthy human breath and bodily fluids: the human volatilome

This paper comprises an updated version of the 2014 review which reported 1846 volatile organic compounds (VOCs) identified from healthy humans. In total over 900 additional VOCs have been reported since the 2014 review and the VOCs from semen have been added. The numbers of VOCs found in breath and the other bodily fluids are: blood 379, breath 1488, faeces 443, milk 290, saliva 549, semen 196, skin 623 and urine 444. Compounds were assigned CAS registry numbers and named according to a common convention where possible. The compounds have been included in a single table with the source reference(s) for each VOC, an update on our 2014 paper. VOCs have also been grouped into tables according to their chemical class or functionality to permit easy comparison. Careful use of the database is needed, as a number of the identified VOCs only have level 2-putative assignment, and only a small fraction of the reported VOCs have been validated by standards. Some clear differences are observed, for instance, a lack of esters in urine with a high number in faeces and breath. However, the lack of compounds from matrices such a semen and milk compared to breath for example could be due to the techniques used or reflect the intensity of effort e.g. there are few publications on VOCs from milk and semen compared to a large number for breath. The large number of volatiles reported from skin is partly due to the methodologies used, e.g. by collecting skin sebum (with dissolved VOCs and semi VOCs) onto glass beads or cotton pads and then heating to a high temperature to desorb VOCs. All compounds have been included as reported (unless there was a clear discrepancy between name and chemical structure), but there may be some mistaken assignations arising from the original publications, particularly for isomers. It is the authors' intention that this work will not only be a useful database of VOCs listed in the literature but will stimulate further study of VOCs from healthy individuals; for example more work is required to confirm the identification of these VOCs adhering to the principles outlined in the metabolomics standards initiative. Establishing a list of volatiles emanating from healthy individuals and increased understanding of VOC metabolic pathways is an important step for differentiating between diseases using VOCs.

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

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

Ion Mobility–Mass Spectrometry for Bioanalysis

This paper aims to cover the main strategies based on ion mobility spectrometry (IMS) for the analysis of biological samples. The determination of endogenous and exogenous compounds in such samples is important for the understanding of the health status of individuals. For this reason, the development of new approaches that can be complementary to the ones already established (mainly based on liquid chromatography coupled to mass spectrometry) is welcomed. In this regard, ion mobility spectrometry has appeared in the analytical scenario as a powerful technique for the separation and characterization of compounds based on their mobility. IMS has been used in several areas taking advantage of its orthogonality with other analytical separation techniques, such as liquid chromatography, gas chromatography, capillary electrophoresis, or supercritical fluid chromatography. Bioanalysis is not one of the areas where IMS has been more extensively applied. However, over the last years, the interest in using this approach for the analysis of biological samples has clearly increased. This paper introduces the reader to the principles controlling the separation in IMS and reviews recent applications using this technique in the field of bioanalysis.

Role of the oral microbiome, metabolic pathways, and novel diagnostic tools in intra-oral halitosis: a comprehensive update

Halitosis or oral malodor is one of the most common reasons for the patients' visit to the dental clinic, ranking behind only dental caries and periodontitis. In the present times, where social and professional communications are becoming unavoidable, halitosis has become a concern of growing importance. Oral malodor mostly develops due to the putrefaction of substrates by the indigenous bacterial populations. Although culture-based studies have provided adequate information on halitosis, the high throughput omics technologies have amplified the resolution at which oral microbial community can be examined and has led to the detection of a broader range of taxa associated with intra-oral halitosis (IOH). These microorganisms are regulated by the interactions of their ecological processes. Thus to develop effective treatment strategies, it is important to understand the microbial basis of halitosis. In the current review, we provide an update on IOH in context to the role of the oral microbiome, metabolic pathways involved, and novel diagnostic tools, including breathomics. Understanding oral microbiota associated with halitosis from a broader ecological perspective can provide novel insights into one's oral and systemic health. Such information can pave the way for the emergence of diagnostic tools that can revolutionize the early detection of halitosis and various associated medical conditions.

A tongue features fusion approach to predicting prediabetes and diabetes with machine learning

BACKGROUND

Diabetics has become a serious public health burden in China. Multiple complications appear with the progression of diabetics pose a serious threat to the quality of human life and health. We can prevent the progression of prediabetics to diabetics and delay the progression to diabetics by early identification of diabetics and prediabetics and timely intervention, which have positive significance for improving public health.

OBJECTIVE

Using machine learning techniques, we establish the noninvasive diabetics risk prediction model based on tongue features fusion and predict the risk of prediabetics and diabetics.

METHODS

Applying the type TFDA-1 Tongue Diagnosis Instrument, we collect tongue images, extract tongue features including color and texture features using TDAS, and extract the advanced tongue features with ResNet-50, achieve the fusion of the two features with GA_XGBT, finally establish the noninvasive diabetics risk prediction model and evaluate the performance of testing effectiveness.

RESULTS

Cross-validation suggests the best performance of GA_XGBT model with fusion features, whose average CA is 0.821, the average AUROC is 0.924, the average AUPRC is 0.856, the average Precision is 0.834, the average Recall is 0.822, the average F1-score is 0.813. Test set suggests the best testing performance of GA_XGBT model, whose average CA is 0.81, the average AUROC is 0.918, the average AUPRC is 0.839, the average Precision is 0.821, the average Recall is 0.81, the average F1-score is 0.796. When we test prediabetics with GA_XGBT model, we find that the AUROC is 0.914, the Precision is 0.69, the Recall is 0.952, the F1-score is 0.8. When we test diabetics with GA_XGBT model, we find that the AUROC is 0.984, the Precision is 0.929, the Recall is 0.951, the F1-score is 0.94.

CONCLUSIONS

Based on tongue features, the study uses classical machine learning algorithm and deep learning algorithm to maximum the respective advantages. We combine the prior knowledge and potential features together, establish the noninvasive diabetics risk prediction model with features fusion algorithm, and detect prediabetics and diabetics noninvasively. Our study presents a feasible method for establishing the association between diabetics and the tongue image information and prove that tongue image information is a potential marker which facilitates effective early diagnosis of prediabetics and diabetics.

Feasibility study on exhaled-breath analysis by untargeted Selected-Ion Flow-Tube Mass Spectrometry in children with cystic fibrosis, asthma, and healthy controls: Comparison of data pretreatment and classification techniques

Selected-Ion Flow-Tube Mass Spectrometry (SIFT-MS) has been applied in a clinical context as diagnostic tool for breath samples using target biomarkers. Exhaled breath sampling is non-invasive and therefore much more patient friendly compared to bronchoscopy, which is the golden standard for evaluating airway inflammation. In the actual pilot study, 55 exhaled breath samples of children with asthma, cystic-fibrosis and healthy individuals were included. Rather than focusing on the analysis of target biomarkers or on the identification of biomarkers, different data analysis strategies, including a variety of pretreatment, classification and discrimination techniques, are evaluated regarding their capacity to distinguish the three classes based on subtle differences in their full scan SIFT-MS spectra. Proper data-analysis strategies are required because these full scan spectra contain much external, i.e. unwanted, variation. Each SIFT-MS analysis generates three spectra resulting from ion-molecule reactions of analyte molecules with H₃O⁺, NO⁺ and O₂⁺. Models were built with Linear Discriminant Analysis, Quadratic Discriminant Analysis, Soft Independent Modelling by Class Analogy, Partial Least Squares - Discriminant Analysis, K-Nearest Neighbours, and Classification and Regression Trees. Perfect models, concerning overall sensitivity and specificity (100% for both) were found using Direct Orthogonal Signal Correction (DOSC) pretreatment. Given the uncertainty related to the classification models associated with DOSC pretreatments (i.e. good classification found also for random classes), other models are built applying other preprocessing approaches. A Partial Least Squares - Discriminant Analysis model with a combined pre-processing method considering single value imputation results in 100% sensitivity and specificity for calibration, but was less good predictive. Pareto scaling prior to Quadratic Discriminant Analysis resulted in 41/55 correctly classified samples for calibration and 34/55 for cross-validation. In future, the uncertainty with DOSC and the applicability of the promising preprocessing methods and models must be further studied applying a larger representative data set with a more extensive number of samples for each class. Nevertheless, this pilot study showed already some potential for the untargeted SIFT-MS application as a rapid pattern-recognition technique, useful in the diagnosis of clinical breath samples.

Evaluation of salivary VOC profile composition directed towards oral cancer and oral lesion assessment

OBJECTIVES

Endogenous substances have been analyzed in biological samples in order to be related with metabolic dysfunctions and diseases. The study aimed to investigate profiles of volatile organic compounds (VOCs) from fresh and incubated saliva donated by healthy controls, individuals with oral tissue lesions and with oral cancer, in order to assess case-specific biomarkers of oxidative stress.

MATERIALS AND METHODS

VOCs were pre-concentrated using headspace-solid phase microextraction and analyzed using gas chromatography-mass spectrometry. Then, VOCs positively modulated by incubation process were subtracted, yielding profiles with selected features. Principal component analysis and hierarchical cluster analysis were used to inspect data distribution, while univariate statistics was applied to indicate potential markers of oral cancer. Machine learning algorithm was implemented, aiming multiclass prediction.

RESULTS

The removal of bacterial contribution to VOC profiles allowed the obtaining of more specific case-related patterns. Artificial neural network model included 9 most relevant compounds (1-octen-3-ol, hexanoic acid, E-2-octenal, heptanoic acid, octanoic acid, E-2-nonenal, nonanoic acid, 2,4-decadienal and 9-undecenoic acid). Model performance was assessed using 10-fold cross validation and receiver operating characteristic curves. Obtained overall accuracy was 90%. Oral cancer cases were predicted with 100% of sensitivity and specificity.

CONCLUSIONS

The selected VOCs were ascribed to lipid oxidation mechanism and presented potential to differentiate oral cancer from other inflammatory conditions.

CLINICAL RELEVANCE

These results highlight the importance of interpretation of saliva composition and the clinical value of salivary VOCs. Elucidated metabolic alterations have the potential to aid the early detection of oral cancer and the monitoring of oral lesions.

Volatile Organic Compounds in Exhaled Breath as Fingerprints of Lung Cancer, Asthma and COPD

Lung cancer, chronic obstructive pulmonary disease (COPD) and asthma are inflammatory diseases that have risen worldwide, posing a major public health issue, encompassing not only physical and psychological morbidity and mortality, but also incurring significant societal costs. The leading cause of death worldwide by cancer is that of the lung, which, in large part, is a result of the disease often not being detected until a late stage. Although COPD and asthma are conditions with considerably lower mortality, they are extremely distressful to people and involve high healthcare overheads. Moreover, for these diseases, diagnostic methods are not only costly but are also invasive, thereby adding to people’s stress. It has been appreciated for many decades that the analysis of trace volatile organic compounds (VOCs) in exhaled breath could potentially provide cheaper, rapid, and non-invasive screening procedures to diagnose and monitor the above diseases of the lung. However, after decades of research associated with breath biomarker discovery, no breath VOC tests are clinically available. Reasons for this include the little consensus as to which breath volatiles (or pattern of volatiles) can be used to discriminate people with lung diseases, and our limited understanding of the biological origin of the identified VOCs. Lung disease diagnosis using breath VOCs is challenging. Nevertheless, the numerous studies of breath volatiles and lung disease provide guidance as to what volatiles need further investigation for use in differential diagnosis, highlight the urgent need for non-invasive clinical breath tests, illustrate the way forward for future studies, and provide significant guidance to achieve the goal of developing non-invasive diagnostic tests for lung disease. This review provides an overview of these issues from evaluating key studies that have been undertaken in the years 2010–2019, in order to present objective and comprehensive updated information that presents the progress that has been made in this field. The potential of this approach is highlighted, while strengths, weaknesses, opportunities, and threats are discussed. This review will be of interest to chemists, biologists, medical doctors and researchers involved in the development of analytical instruments for breath diagnosis.

Volatile organic compounds in a headspace sampling system and asthmatics sputum samples

Background:The headspace of a biological sample contains exogenous VOCs present within the sampling environment which represent the background signal.Study aims:This study aimed to characterise the background signal generated from a headspace sampling system in a clinical site, to evaluate intra- and inter-day variation of background VOC and to understand the impact of a sample itself upon commonly reported background VOC using sputum headspace samples from severe asthmatics.Methods:The headspace, in absence of a biological sample, was collected hourly from 11am to 3pm within a day (time of clinical samples acquisition), and from Monday to Friday in a week, and analysed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Chemometric analysis identified 1120 features, 37 of which were present in at least the 80% of all the samples. The analyses of intra- and inter-day background variations were performed on thirteen of the most abundant features, ubiquitously present in headspace samples. The concentration ratios relative to background were reported for the selected abundant VOC in 36 asthmatic sputum samples, acquired from 36 stable severe asthma patients recruited at Glenfield Hospital, Leicester, UK.Results:The results identified no significant intra- or inter-day variations in compounds levels and no systematic bias of z-scores, with the exclusion of benzothiazole, whose abundance increased linearly between 11am and 3pm with a maximal intra-day fold change of 2.13. Many of the identified background features are reported in literature as components of headspace of biological samples and are considered potential biomarkers for several diseases. The selected background features were identified in headspace of all severe asthma sputum samples, albeit with varying levels of enrichment relative to background.Conclusion:Our observations support the need to consider the background signal derived from the headspace sampling system when developing and validating headspace biomarker signatures using clinical samples.

A Review of GC-Based Analysis of Non-Invasive Biomarkers of Colorectal Cancer and Related Pathways

Colorectal cancer (CRC) is the third most commonly diagnosed cancer in the world. In Europe, it is the second most common cause of cancer-related deaths. With the advent of metabolomics approaches, studies regarding the investigation of metabolite profiles related to CRC have been conducted, aiming to serve as a tool for early diagnosis. In order to provide further information about the current status of this field of research, 21 studies were systematically reviewed, regarding their main findings and analytical aspects. A special focus was given to the employment of matrices obtained non-invasively and the use of gas chromatography as the analytical platform. The relationship between the reported volatile and non-volatile biomarkers and CRC-related metabolic alterations was also explored, demonstrating that many of these metabolites are connected with biochemical pathways proven to be involved in carcinogenesis. The most commonly reported CRC indicators were hydrocarbons, aldehydes, amino acids and short-chain fatty acids. These potential biomarkers can be associated with both human and bacterial pathways and the analysis based on such species has the potential to be applied in the clinical practice as a low-cost screening method.

The Role of Oral Microbiota in Intra-Oral Halitosis

Halitosis is a common ailment concerning 15% to 60% of the human population. Halitosis can be divided into extra-oral halitosis (EOH) and intra-oral halitosis (IOH). The IOH is formed by volatile compounds, which are produced mainly by anaerobic bacteria. To these odorous substances belong volatile sulfur compounds (VSCs), aromatic compounds, amines, short-chain fatty or organic acids, alcohols, aliphatic compounds, aldehydes, and ketones. The most important VSCs are hydrogen sulfide, dimethyl sulfide, dimethyl disulfide, and methyl mercaptan. VSCs can be toxic for human cells even at low concentrations. The oral bacteria most related to halitosis are Actinomyces spp., Bacteroides spp., Dialister spp., Eubacterium spp., Fusobacterium spp., Leptotrichia spp., Peptostreptococcus spp., Porphyromonas spp., Prevotella spp., Selenomonas spp., Solobacterium spp., Tannerella forsythia, and Veillonella spp. Most bacteria that cause halitosis are responsible for periodontitis, but they can also affect the development of oral and digestive tract cancers. Malodorous agents responsible for carcinogenesis are hydrogen sulfide and acetaldehyde.

Unravelling the Potential of Salivary Volatile Metabolites in Oral Diseases. A Review

Fostered by the advances in the instrumental and analytical fields, in recent years the analysis of volatile organic compounds (VOCs) has emerged as a new frontier in medical diagnostics. VOCs analysis is a non-invasive, rapid and inexpensive strategy with promising potential in clinical diagnostic procedures. Since cellular metabolism is altered by diseases, the resulting metabolic effects on VOCs may serve as biomarkers for any given pathophysiologic condition. Human VOCs are released from biomatrices such as saliva, urine, skin emanations and exhaled breath and are derived from many metabolic pathways. In this review, the potential of VOCs present in saliva will be explored as a monitoring tool for several oral diseases, including gingivitis and periodontal disease, dental caries, and oral cancer. Moreover, the analytical state-of-the-art for salivary volatomics, e.g., the most common extraction techniques along with the current challenges and future perspectives will be addressed unequivocally.

Rapid and accurate determination of trace volatile sulfur compounds in human halitosis by an adaptable active sampling system coupling with gas chromatography

Halitosis with the main components of trace volatile sulfur compounds widely affects the quality of life. In this study, an adaptable active sampling system with two sample-collection modes of direct injection and solid-phase microextraction was developed for the rapid and precise determination of trace volatile sulfur compounds in human halitosis coupled with gas chromatography-flame photometric detection. The active sampling system was well designed and produced for efficiently sampling and precisely determining trace volatile targets in halitosis under the optimized sampling and detection conditions. The analytical method established was successfully applied for the determination of trace targets in halitosis. The limits of detection of H₂ S, CH₃ SH, and CH₃ SCH₃ by direct injection were 0.0140-23.0 μg/L with good recoveries ranging from 82.2 to 118% and satisfactory relative standard deviations of 0.4-9.5% (n = 3), respectively. The limit of detections of CH₃ SH and CH₃ SCH₃ by solid-phase microextraction were 2.03 and 0.186 × 10^-3  μg/L with good recoveries ranging from 98.3 to 108% and relative standard deviations of 5.9-9.0% (n = 3). Trace volatile targets in positive real samples could be actually found and quantified by combination of direct injection and solid-phase microextraction. This method was reliable and efficient for the determination of trace volatile sulfur compounds in halitosis.