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To avoid fraudulent practices, LC-Orbitrap and FT-NIRS combined with multivariate analysis was used to distinguish between 53 Korean and foreign Boston butt samples; forty were used to establish the calibration model and 13 were used as an external validation set. Twenty metabolites were determined to be good indicators of geographic origin. Both LC-Orbitrap with CDA model based on 20 metabolites and FT-NIRS with PLS achieved 100% efficiency in identifying Korean and foreign samples; overall predictive rates for LC-Orbitrap (94.9%) and FT-NIRS (100%). Thus, combined use of LC-Orbitrap and FT-NIRS could be proposed to determine reliably discriminate geographic origins of pork samples.

Mycotoxins’ exposure by inhalation and/or dermal contact can occur in different branches of industry especially where heavily dusty settings are present and the handling of dusty commodities is performed. This study aims to explore the possible contribution of the occupational exposure to aflatoxins by analysing urine samples for the presence of aflatoxins B1 and M1 and aflatoxin B1-N7-guanine adduct. The study was conducted in 2017 on two groups of volunteers, the workers group, composed by personnel employed in an Italian feed plant (n = 32), and a control group (n = 29), composed by the administrative employees of the same feed plant; a total of 120 urine samples were collected and analysed. A screening method and a quantitative method with high-resolution mass spectrometry determination were developed and fully validated. Limits of detections were 0.8 and 1.5 pg/mLurine for aflatoxin B1 and M1, respectively. No quantitative determination was possible for the adduct aflatoxin B1-N7-guanine. Aflatoxin B1 and its adduct were not detected in the analysed samples, and aflatoxin M1, instead, was found in 14 samples (12%) within the range 1.9–10.5 pg/mLurine. Only one sample showed a value above the limit of quantification (10.5 pg/mLurine). The absence of a statistical difference between the mean values for workers and the control group which were compared suggests that in this specific setting, no professional exposure occurs. Furthermore, considering the very low level of aflatoxin M1 in the collected urine samples, the contribution from the diet to the overall exposure is to be considered negligible.

Early identification of disease onset is regarded as an important factor for successful medical intervention. However, cancer and other long-term latency diseases are rare and may take years to manifest clinically. As such, there are no gold standards with which to immediately validate proposed preclinical screening methodologies. There is evidence that dogs can sort samples reproducibly into yes/no categories based on case-control training, but the basis of their decisions is unknown. Because dogs are sniffing air, the distinguishing chemicals must be either in the gas-phase or attached to aerosols and/or airborne particles. Recent biomonitoring research has shown how to extract and analyze semi- and non-volatile compounds from human breath in exhaled condensates and aerosols. Further research has shown that exhaled aerosols can be directly collected on standard hospital-style olefin polypropylene masks and that these masks can be used as a simple sampling scheme for canine screening. In this article, detailed liquid chromatography-high resolution mass spectrometry (LC-HR-MS) with Orbitrap instrumentation and gas chromatography-mass spectrometry (GC-MS) analyses were performed on two sets of masks sorted by consensus of a four-dog cohort as either cancer or control. Specifically, after sorting by the dogs, sample masks were cut into multiple sections and extracted for LC-MS and GC-MS non-targeted analyses. Extracts were also analyzed for human cytokines, confirming the presence of human aerosol content above levels in blank masks. In preliminary evaluations, 345 and 44 high quality chemical features were detected by LC-MS and GC-MS analyses, respectively. These features were used to develop provisional orthogonal projection to latent structures-discriminant analysis (OPLS-DA) models to determine if the samples classified as cancer (case) or non-cancer (control) by the dogs could be separated into the same groups using analytical instrumentation. While the OPLS-DA model for the LC-HR-MS data was able to separate the two groups with statistical significance, although weak explanatory power, the GC-MS model was not found to be significant. These results suggest that the dogs may rely on the less volatile compounds from breath aerosol that were analyzed by LC-HR-MS than the more volatile compounds observed by GC-MS to sort mask samples into groups. These results provide justification for more expansive studies in the future that aim to characterize specific chemical features, and the role(s) of these features in maintaining homeostatic biological processes.