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Background: Bulk milk samples from 69 dairy buffalo farms of the Campania Region, Italy were drawn for the determination of 20 selected elements by ICP-MS. The main goal was to ascertain how the agricultural soil geo-chemistry could influence the milk pattern with respect to feeding practices. Methods: Local forages (N = 207) and groundwater (N = 486) were analyzed too to recover the feeding-to-milk carry-over rates (COR) of selected elements and identify the main contributors to milk contamination. Left censored data >10% limited to 11 elements (Mn, As, Se, Sr, Zn, Cr, Fe, Co, Ni, Cu, and V) the multivariate system approach based on cluster and factor analysis. Results: We identified 8/11 elements - Sr, Mn, Zn, Co, Se, Cr, Fe, and V - explaining the main quote of variation observed among farms milk pattern. In particular, Co resulted as discriminant for specific villages of the Salerno Province. On median values, cereals (34%) and feed supplement (31%) represented the main contributors to Cr intake; for V, hay (46%) and water (42%); for Fe, water (46%); for Se, Co and Zn, mineral supplements (67; 73; 82%); for Sr, hay (71%), for Mn, mineral supplements (36%) and water (30%). Median CORs rates (%) were the following: Se and Cr: 40; V: 13; Mn: 5.2; Sr: 4.7; Zn: 3.7; Co: 3.4; Fe: 1.6; respectively. Conclusion: The factor analysis could trace the geographical origin of buffalo milk at farm level, according to similar management practices, partially irrespective of the municipality/province level.

Honeybees and hive products have long been recognized as excellent bio-indicators, as they provide valuable information on the state of the environments concerned. As yet, however, no tool is capable of contextually assessing the level of pollution of different environmental matrices in order to create maps of areas in which to place hives. In this paper, a possible method of creating a regional map to support the implementation of targeted monitoring plans on beekeeping is described. We obtained and identified related-activity pressure factors, which were subsequently combined by means of a multi-criteria approach through the analytic hierarchy process method (AHP). The different levels used were drawn up by first attributing qualitative values; these were converted into quantitative values through scoring elaborations and pair comparisons and then elaborated and standardized by means of different techniques in order to create an index with a spatial distribution of five risk classes throughout the region. To verify the correct execution of the procedure, a consistency ratio method was implemented on this index and validated the reliability of the application as the main source of information for sampling activities on beekeeping products. Creation of the specific environmental risk index enabled us to construct a map displaying the areas of greatest impact on beekeeping activities and a representation of the cumulative effects generated by the different pollutants in the air, water, soil and subsoil compartments. This index may, therefore, constitute an essential tool to support beekeepers in choosing sites for their apiaries.

The aim of the present study is to assess saliva as a reliable specimen for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection by real-time reverse transcription-PCR (RT-PCR), especially in community mass screening programs. The performance analysis considered 1,221 total samples [nasopharyngeal (NP) swabs and corresponding saliva], tested by means of a reference diagnostic real-time RT-PCR assay. Conflicting results were further investigated with a second, more sensitive, reference assay. Analysis of agreement showed a good concordance (95.82%), with a k coefficient value of.74 (p < 0.001); moreover, a follow-up analysis revealed the presence of viral gene targets in saliva samples at the time point the corresponding NP swabs turned negative. Data obtained prove the reliability of this alternative biofluid for SARS-CoV-2 detection in real-time RT-PCR. Considering the role of saliva in the coronavirus disease 2019 (COVID-19) transmission and pathogenesis, and the advantages in the use of salivary diagnostics, the present validation supports the use of saliva as an optimal choice in large-scale population screening and monitoring of the SARS-CoV-2 virus.