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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.

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The main goal of this study was to explore the phospholipid alterations associated with the development of prostate cancer (PCa) using two imaging methods: matrix-assisted laser desorption ionization with time-of-flight mass spectrometer (MALDI-TOF/MS), and electrospray ionization with triple quadrupole mass spectrometer (ESI-QqQ/MS). For this purpose, samples of PCa tissue (n = 40) were evaluated in comparison to the controls (n = 40). As a result, few classes of compounds, namely phosphatidylcholines (PCs), lysophosphatidylcholines (LPCs), sphingomyelins (SMs), and phosphatidylethanolamines (PEs), were determined. The obtained results were evaluated by univariate (Mann–Whitney U-test) and multivariate statistical analysis (principal component analysis, correlation analysis, volcano plot, artificial neural network, and random forest algorithm), in order to select the most discriminative features and to search for the relationships between the responses of these groups of substances, also in terms of the used analytical technique. Based on previous literature and our results, it can be assumed that PCa is linked with both the synthesis of fatty acids and lipid oxidation. Among the compounds, phospholipids, namely PC 16:0/16:1, PC 16:0/18:2, PC 18:0/22:5, PC 18:1/18:2, PC 18:1/20:0, PC 18:1/20:4, and SM d18:1/24:0, were assigned as metabolites with the best discriminative power for the tested groups. Based on the results, lipidomics can be found as alternative diagnostic tool for CaP diagnosis.

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.

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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.

Cyclitols are secondary metabolites with bioactive properties, naturally occurring in plants. Accumulation of such metabolites is directly connected with abiotic stressing factors. This article investigates the influence exercised by a series of abiotic factors including plant treatment with elicitors and cultivability in various regions of Europe, in some cases during two seasons, onto the amounts of cyclitols produced in alfalfa (Medicago sativa L.). The obtained results highlighted that NaCl elicitation acts to increase the quantity of cyclitols, while AgNO3 and Zn(NO3)2 generally decreased the obtained amount of cyclitols. When considering the seasonal impact, samples harvested in August presented a double amount of cyclitols in comparison with those collected in May. Correlation analysis proved that this phenomenon is related mainly to sunshine period versus low humidity. However, our investigation suggests that soil type, salinity level, lack of humidity, the number of sunny days, and plant elicitation play a role on the amount of cyclitols produced in alfalfa plant.