Glyphosate and Glufosinate Residues in Honey and Other Hive Products

Hive products have numerous beneficial properties; however, the hive’s health is affected by the surrounding environment. The widespread use of herbicides in agriculture, such as glyphosate and glufosinate, has raised alarm among consumers, beekeepers, and environmentalists due to their potential to harm bees and humans through the consumption of bee products. This review aims to provide a comprehensive overview of the presence of glyphosate, glufosinate, and their metabolites in hive products, collecting and comparing available data from peer-reviewed research and surveys conducted across several countries. Moreover, it analyzes and discusses the potential impacts of these substances on human and bee health, analytical aspects, and recent regulatory developments. The data has revealed that these substances can be present in the different matrices tested, but the concentrations found are usually lower than the maximum residue limits set. However, the use of different methodologies with non-uniform analytical performances, together with an incomplete search for regulated analytes, leads to heterogeneity and makes comparisons challenging. In addition to the completion of studies on the toxicology of herbicide active ingredients, further monitoring actions are necessary, harmonizing analytical methodologies and data management procedures

Outcomes of self-control plans on acrylamide levels in processed food

In 2002, researchers from Stockholm University discovered the presence of acrylamide (AA) in processed foods. This substance has been classified as “probably carcinogenic to humans” by the International Agency for Research on Cancer. In response to the alarming finding, the European Commission issued recommendations (2004/394/EC, 2010/307/EU, and 2013/647/EU), guiding food business operators, raising awareness, and promoting good manufacturing practices to minimize AA formation. These efforts laid the foundation for the comprehensive measures in Regulation (EU) 2017/2158. The Regulation implemented specific measures during production to reduce the amount of AA in food. This study monitored the AA levels in 15,674 samples from 12 processed food commodities. Potato-based products and coffee were found to be the main sources of AA exposure. The “baby foods” and “soft bread” food categories had the lowest contamination levels. The data were then compared to the information previously published by the European Food Safety Authority to assess the trend over time and the effectiveness of the mitigation measures. The results showed a decrease in AA contamination levels for most food categories, particularly for baby foods

Oligomeric derivatives of spirobifluorene, their preparation and use

SBF derivatives, represented with the following formula: SBF-X wherein: with m=0, 1, 2 or 3; p=positive integer,; n=positive integer; L: is the same or different and independently represents C, PR, AsR, SbR, BiR, S, Se, Te, S=Y, Se=Y or Te=Y; Y: is the same or different and independently represents O, S, Se or Te; K: is the same or different and independently represents a chemical bond or a group selected from O, S, BR(2-p), N, NR(2-p), R(2-p)P=O, B3O3, (PR)3N3, CR(3-p), CR(3-p)(C6H4)(p+1), SiR(3-p)(C6H4)(p+1) alkyne, substituted alkyne, alkyne, substituted alkyne, aromatic or R substituted aromatic, heteroaromatic-or a combination of two, three or four of the above mentioned groups; SBF: spiro-compound of formula (I): R, A, B, C, D: is the same or different and independently represents H, deuterium, F, Cl, Br, I, CN, a linear, branched or cyclic alkyl, alkoxy or thioalkoxy chain, or a combination from two, three or four of these systems; two or more substituents R can form a further monocyclic or polycyclic aliphatic or aromatic ring system with each other

Oligomeric derivatives of spirobifluorene, their preparation and use

Oligomeric derivatives of spirobifluorene, their preparation and use in the field of molecular electronics

Analysis of Cobalamin (Vit B12) in Ripened Cheese by Ultra-High-Performance Liquid Chromatography Coupled with Mass Spectrometry

The analysis of natural cobalamins in dairy products still represents an analytical challenge. The matrix’s complexity, low concentration level, light sensitivity, and binding to proteins are just some of the aspects that make their quantification a difficult goal to achieve. Vitamin B12 plays a fundamental role in human nutrition, and its intake is closely linked to a diet that includes the consumption of food of animal origin. In the current literature, few studies have been carried out on the quantitation of cobalamin in ripened cheeses. A sensitive, selective, and robust ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS) method was developed, validated, and applied on ripened cheeses from different species (cow, sheep, and goat) purchased from local Italian markets, highlighting species-dependent differences in vitamin B12 concentrations. The vitamin B12 extraction procedure was performed by converting all cobalamins to the cyanocobalamin form. Furthermore, solid-phase extraction was used for matrix clean-up and analyte preconcentration. The proposed method showed good performance in terms of linearity, sensitivity, reproducibility, and repeatability. The mean vitamin B12 content ranged from <LOQ to 38.9 ng/g. Sheep cheese showed the highest concentrations of vitamin B12, with a mean content of 29.0 ng/g

Does the Integration of Pre-Coded Information with Narratives Improve in-Hospital Falls’ Surveillance?

To evaluate the value added by information reported in narratives (extracted through text mining techniques) in enhancing the characterization of falls patterns. Data on falls notified to the Risk Management Service of a Local Health Authority in Italy were considered in the analysis. Each record reported detailed pre-coded information about patient and fall’s characteristics, together with a narrative description of the fall. At first, multiple correspondence analysis (MCA) was performed on pre-coded information only. Then, it was re-run on the pre-coded data augmented with a variable representing the output analysis of the narrative records. This second analysis required a pre-processing of the narratives followed by text mining. Finally, a Hierarchical Clustering on the two MCA was carried out to identify distinct fall patterns. The dataset included 202 falls’ records. Three clusters corresponding to three distinct profiles of falls were identified through the Hierarchical Clustering performed using only pre-coded information. Hierarchical Clustering with the topic variable provided overlapping results. The present findings showed that the cluster analysis is effective in characterizing fall patterns; however, they do not sustain the hypothesis that the analysis of free-text information improves our understanding of such phenomenon