Multi-elemental composition of botanical preparations and probabilistic evaluation of toxic metals and metalloids intake upon dietary exposure.

The aim of this study was to evaluate the inorganic elemental composition (49 elements) of 29 botanical preparations obtained from fruits, leaves, peels, seeds, roots, fungi, and spirulina by using inductively coupled-mass spectrometry and a mercury analyzer. Simultaneously, the risk associated with the chronic dietary exposure to 12 toxic metals and metalloids among the European population was evaluated by using a probabilistic approach based on Monte Carlo simulations. The analysis revealed worrying intake levels of Al, As, and Ni, primarily stemming from the consumption of spirulina-, peel-, and leaf-based botanicals by younger age groups. The intake of As from all analyzed botanicals posed a significant risk for infants, yielding margins of exposure (MOEs) below 1, while those deriving from peel-based botanicals raised concerns across all age groups (MOEs = 0.04-2.3). The consumption of peel-based botanicals contributed substantially (13-130%) also to the tolerable daily intake of Ni for infants, toddlers, and children, while that of spirulina-based botanicals raised concerns related to Al intake also among adults, contributing to 11-176% of the tolerable weekly intake of this element. The findings achieved underscore the importance of implementing a monitoring framework to address chemical contamination of botanicals, thus ensuring their safety for regular consumers.

Cadmium, lead, and mercury in two commercial squid species from the north Adriatic Sea (central Mediterranean): contamination levels and health risk assessment.

In this study, lead (Pb), cadmium (Cd), and total mercury (Hg) concentrations in European squids (Loligo vulgaris) and flying squids (Todarodes sagittatus) from the northern Adriatic Sea (Italy) were analyzed. The risk of the Italian population being exposed to potentially hazardous metal concentrations through the consumption of these products was also assessed. Compared to European squids, flying squids showed three times higher total Hg concentrations and one hundred times higher Cd concentrations to the point that more than 6 and 25% of the samples exceeded the maximum Hg and Cd limits established by the current legislation. From the evaluation of dietary exposure levels, it emerged that the consumption of flying squids was associated with the highest Pb intake by children and, consequently, with the lower margin of exposure values in relation to the risk of neurotoxicity (margin of exposure=33). Consumption of flying squids, especially by children, was also associated with higher intakes of Cd, inorganic, and methyl-Hg, which, respectively, accounted for 156, 113, and 23% of the tolerable weekly intakes established for these contaminants at European level. The obtained results raise concern and it may be necessary to provide specific dietary advice on the moderate dietary consumption of some cephalopod species, especially to the youngest and most vulnerable segment of the population. However, besides the highly conservative deterministic method adopted in this study, a refined consumer exposure assessment should be performed through the probabilistic methodology, which is more suitable to represent the real exposure scenario.

Classification of transformed anchovy products based on the use of element patterns and decision trees to assess traceability and country of origin labelling.

Quadrupole inductively coupled plasma mass spectrometry (Q-ICP-MS) and direct mercury analysis were used to determine the elemental composition of 180 transformed (salt-ripened) anchovies from three different fishing areas before and after packaging. To this purpose, four decision trees-based algorithms, corresponding to C5.0, classification and regression trees (CART), chi-squareautomatic interaction detection (CHAID), and quick unbiased efficient statistical tree (QUEST) were applied to the elemental datasets to find the most accurate data mining procedure to achieve the ultimate goal of fish origin prediction. Classification rules generated by the trained CHAID model optimally identified unlabelled testing bulk anchovies (93.9% F-score) by using just 6 out of 52 elements (As, K, P, Cd, Li, and Sr). The finished packaged product was better modelled by the QUEST algorithm which recognised the origin of anchovies with F-score of 97.7%, considering the information carried out by 5 elements (B, As, K. Cd, and Pd). Results obtained suggested that the traceability system in the fishery sector may be supported by simplified machine learning techniques applied to a limited but effective number of inorganic predictors of origin.