Volatile organic compounds (VOCs) have been studied in biological samples in order to be related to the presence of diseases. Sweat can represent substances existing in blood, has less complex composition (compared with other biological matrices) and can be obtained in a non-invasive way. In this work, sweat patches were collected from healthy controls and volunteers with cancer. Static Headspace was used for VOCs extraction, analysis was performed by gas chromatography coupled with mass spectrometry. Principal Components Analysis was used to investigate data distribution. Random Forest was employed to develop classificatory models. Controls and positive cases could be distinguished with maximum sensitivity and specificity (100% of accuracy) in a model based on the incidence of 2-ethyl-1-hexanol, hexanal and octanal. Discrimination between controls, primary tumors and metastasis was achieved using a panel with 11 VOCs. Balanced accuracy of more than 70% was obtained for the classification of a neoplasm site. Total n-aldehydes presented to be strongly correlated with staging of adenocarcinomas, while phenol and 2,6-dimethyl-7-octen-2-ol were correlated with Gleason score. These findings corroborate with the development of accessible screening tools based on VOC analysis and highlight sweat as a promising matrix to be studied in a clinical context for cancer diagnosis.

Halitosis and submandibular abscesses are examples of mouth-related diseases with the possible bacterial origin. Salivary volatile organic compounds (VOCs) are potential biomarkers of them, once they can be addressed as metabolites of bacterial activity. Healthy patients (n = 15), subjects with submandibular abscesses located in fascial deep space (n = 10), and subjects with halitosis (n = 5) were enrolled in the study. Saliva samples were subjected to headspace solid-phase microextraction (HS-SPME) and gas chromatography coupled to mass spectrometry (GC/MS) analysis. A total number of 164 VOCs was detected by the developed methodology, 23 specific for halitosis and 41 for abscess. Halitosis’ profiles were characterized by a larger number of sulfur compounds, while for abscess they had a higher variety of alcohols, aldehydes, and hydrocarbons—biomarkers of inflammatory processes. Principal components analysis allowed visualization of clusters formed according to the evaluated conditions. Kruskal-Wallis test indicated that 39 VOCs presented differentiated responses between the studied groups, with statistical relevance (p < 0.05). Random forest was applied, and a prediction model based on eight VOCs (2-butanone, methyl thioacetate, 2-methylbutanoic acid, S-methyl pentanethioate, dimethyl tetrasulfide, indolizine, pentadecane, and octadecanal) provided 100% of sensitivity, 82% of specificity, and 91% of balanced accuracy, indicating the specific presence of submandibular abscess.

Simple tests using sniff analysis that have the ability of diagnosing and rapidly distinguishing between infections due to different bacteria are urgently required by medical community worldwide. Professionals interested in this topic wish for these tests to be simultaneously cheap, fast, easily applicable, non-invasive, robust, reliable, and sensitive. Current analytical instrumentation has already the ability for performing real time (minutes or a few dozens of minutes) analysis of volatile bacterial biomarkers (the VOCs emitted by bacteria). Although many articles are available, a review displaying an objective evaluation of the current status in the field is still needed. This review tries to present an overview regarding the bacterial biomarkers released from in vitro cultivation of various bacterial strains and also from different biological matrices investigated, over the last 10 years. We have described results of relevant studies, which used modern analytical techniques to evaluate specific biomarker profiles associated with bacterial infections. Our purpose was to present a comprehensive view of available possibilities for detection of emitted bacterial VOCs from different matrices. We intend that this review to be of general interest for both medical doctors and for all researchers preoccupied with bacterial infectious diseases and their rapid diagnosis using analytical instrumentation.

Escherichia coli and salivary Klebsiella oxytoca and Staphylococcus saccharolyticus were subjected to different concentrations of silver nanoparticles (AgNPs), namely: 12.5, 50, and 100 µg mL⁻¹. Matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry (MALDI-TOF MS) spectra were acquired after specified periods: 0, 1, 4, and 12 h. For study of volatile metabolites, headspace solid-phase microextraction coupled to gas chromatography/mass spectrometry (HS-SPME-GC-MS) was employed—AgNPs were added to bacteria cultures and the headspace was analyzed immediately and after 12 h of incubation. Principal components analysis provided discrimination between clusters of protein profiles belonging to different strains. Canonical correlation, network analysis, and multiple linear regression approach revealed that dimethyl disulfide, dimethyl trisulfide, 2-heptanone, and dodecanal (related to the metabolism of sulfur-containing amino acids and fatty acids synthesis) are exemplary molecular indicators, whose response variation deeply correlated to the interaction with bacteria. Therefore, such species can serve as biomarkers of the agent’s effectiveness. The present investigation pointed out that the used approaches can be useful in the monitoring of response to therapeutic treatment based on AgNPs. Furthermore, biochemical mechanisms enrolled in the bactericidal action of nanoparticles can be applied in the development of new agents with enhanced properties.

Ayahuasca, a hallucinogenic beverage used in religious rituals in South America, has become a global phenomenon. Its main active components are the β-carbolines alkaloids, harmine (HRM) and harmaline (HRL), as well as the potent hallucinogen N,N-dimethyltryptamine (DMT). Despite its rising consumption, information regarding possible clinical applications and toxicological effects of ayahuasca is still limited. This study presents the first investigation of the use of sweat for the determination of DMT, HRM and HRL in ayahuasca users during a religious ritual. Sweat is an alternative matrix with advantages over many conventional biological samples, mainly because the collection procedure is non-invasive, easy and simple and samples can be collected without disturbing the religious ritual. In the study, solid-phase extraction was performed under basic conditions. Linearity was observed ranging from 20 to 1500 ng/patch with coefficients of determination (R²) higher than 0.99 for all analytes. The results indicated high selectivity for all investigated analytes, with extraction efficiency exceeding 70%, accuracy ranging from 87.5 to 102.4%, intra-assay precision of 1.85–9.44% and inter-assay precision between 3.34 and 9.85%. The limits of detection were 15 ng/patch for HRM and HRL and 10 ng/patch for DMT. The sweat proved to be a viable option to monitor ayahuasca use.

A combination of electrochemistry (EC) and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (off-line EC-MALDI-TOF-MS) was applied for determination of the studied biologically active compounds (D-glucose, D-fructose, D-galactose, D-pinitol, L-chiro-inositol, and myo-inositol) and their possible electrochemical metabolites. In this work, boron-doped diamond electrode (BDD) was used as a working electrode. MALDI-TOF-MS experiments were carried out (both in positive and negative ion modes and using two matrices) to identify the structures of electrochemical products. This was one of the first applications of the EC system for the generation of electrochemical products produced from saccharides and cyclitols. Moreover, exploratory data analysis approaches (correlation networks, hierarchical cluster analysis, weighted plots) were used in order to present differences/similarities between the obtained spectra, regarding the class of analyzed compounds, ionization modes, and used matrices. This work presents the investigation and comparison of fragmentation patterns of sugars, cyclitols, and their respective products generated through the electrochemistry (EC) process.