In spite of its positive repercussions on nutrition and environment, faba bean still remains an underutilized crop due to the presence of some undesired compounds. The pyrimidine glycosides vicine and convicine are precursors of the aglycones divicine and isouramil, the main factors of favism, a genetic condition which may lead to severe hemolysis after faba bean ingestion. The reduction of vicine and convicine has been targeted in several studies but little is known about their degradation. In this study, the hydrolysis kinetics of vicine and convicine and their derivatives during fermentation with L. plantarum DPPMAB24W was investigated. In particular, a specific HPLC method coupled to ESI-MS and MS/MS analysis, including the evaluation procedure of the results, was set up as the analytical approach to monitor the compounds. The degradation of the pyrimidine glycosides in the fermented flour was complete after 48 h of incubation and the aglycone derivatives could not be detected in any of the samples. The toxicity of the fermented faba bean was established through ex-vivo assays on human blood, confirming the experimental findings. Results indicate that mild and cost effective bioprocessing techniques can be applied to detoxify faba bean also for industrial applications.
The separation efficiency of hydrophilic interaction liquid chromatography and the high resolution/accuracy of electrospray ionization-Fourier transform MS were successfully applied to the detailed characterization of lyso-phosphatidylcholines (LPCs) and lyso-phosphatidylethanolamines (LPEs) contained in the lipid extracts of Mytilus galloprovincialis (Mediterranean mussel). As a result, 57 LPCs, including regio- and positional isomers, and 45 LPEs, including acyl and plasma(e)nyl species, were identified. Four lyso-phosphonocholines were also identified among mussel Lyso-Phospholipids. To the best of our knowledge this represents the first characterization, at a molecular level, ever reported for LPEs in mussels. No significant variation was observed in the composition of both LPCs and LPEs when mussels were refrigerated at +4°C for up to 48 h, i.e. under conditions usually employed for seafood transportation and storage. Treatments mimicking more severe thermal stresses, namely eight day-refrigeration at + 4°C, two week-freezing at -15°C and 6 h-storage at 25°C, resulted in a significant increase in the molar abundance of LPCs and LPEs (expressed with respect to that of their precursors, PCs and PEs, respectively) and was accompanied by the death of all or part of the molluscs. These results were interpreted invoking the generation of lyso-phospholipids, mediated by endogenous phospholipases, as an intermediate process toward the partial replacement of side chains in phospholipids, perhaps functional to a better adaptation of mussels to adverse temperature conditions. Interestingly, the relative abundances of specific compounds belonging to the LPC and LPE classes were found to follow the seasonal variations of sea temperature.
In the dairy industry one of the most common frauds is mixing high-value milk (sheep's and goats') with milk of lower value (cows'). This illegal practice has commercial, ethical, and serious sanitary consequences because consumers can be exposed to hidden allergens contained in the undeclared cows' milk. Here, we investigated the possibility of using matrix-assisted laser-desorption/ionization (MALDI)-time of flight (TOF) mass spectrometry (MS) as a rapid, sensitive, and accurate technique for detection of milk adulteration by analysis of phospholipid profiles. Lipid extracts of pure raw milk, commercial milk, and binary mixtures of cows' and goats' milk and cows' and sheep's milk (the concentrations of each milk varied from 0 % to 50 %) were analyzed with α-cyano-4-chlorocinnamic acid as matrix. The abundance ratio of the ions at m/z 703 and m/z 706 was found to be species-correlated and was used as marker of cows' milk in sheep's and goats' milk. Furthermore, the procedure could potentially be applied to cheese samples, because peaks at m/z 703 and 706 were also found in several commercial cheese samples. This approach proved to be an efficient, rapid, and inexpensive method of detecting milk fraud.
Malignant pleural mesothelioma (MPM) is a rare neoplasm, mainly caused by asbestos exposure, with a high mortality rate. The management of patients with MPM is controversial due to a long latency period between exposure and diagnosis and because of non-specific symptoms generally appearing at advanced stage of the disease. Breath analysis, aimed at the identification of diagnostic Volatile Organic Compounds (VOCs) pattern in exhaled breath, is believed to improve early detection of MPM. Therefore, in this study, breath samples from 14 MPM patients and 20 healthy controls (HC) were collected and analyzed by Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC/MS). Nonparametric test allowed to identify the most weighting variables to discriminate between MPM and HC breath samples and multivariate statistics were applied. Considering that MPM is an aggressive neoplasm leading to a late diagnosis and thus the recruitment of patients is very difficult, a promising data mining approach was developed and validated in order to discriminate between MPM patients and healthy controls, even if no large population data are available. Three different machine learning algorithms were applied to perform the classification task with a leave-one-out cross-validation approach, leading to remarkable results (Area Under Curve AUC = 93%). Ten VOCs, such as ketones, alkanes and methylate derivates, as well as hydrocarbons, were able to discriminate between MPM patients and healthy controls and for each compound which resulted diagnostic for MPM, the metabolic pathway was studied in order to identify the link between VOC and the neoplasm. Moreover, five breath samples from asymptomatic asbestos-exposed persons (AEx) were exploratively analyzed, processed and tested by the validated statistical method as blinded samples in order to evaluate the performance for the early recognition of patients affected by MPM among asbestos-exposed persons. Good agreement was found between the information obtained by gold-standard diagnostic methods such as computed tomography CT and model output.
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