Assessing the pharmaceutical residues as hotspots of the main rivers of Catalonia, Spain.

The global increase in pharmaceutical consumption, driven by factors such as aging populations and chronic diseases, has raised concerns regarding the environmental impact of pharmaceutical contaminants. Europe, and more specifically Catalonia (Spain), exhibits high pharmaceutical consumption rates, potentially exacerbating environmental contamination. Pharmaceuticals enter rivers through various pathways, persisting after wastewater treatment plants and posing risks to aquatic organisms and human health. Llobregat and Besòs Rivers in Catalonia, crucial water sources, demonstrate detectable pharmaceutical levels, necessitating comprehensive analysis. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) proves effective in detecting pharmaceutical residues, facilitating their risk assessment. This paper reviews the occurrence, fate, and risks associated with 78 pharmaceuticals and metabolite in Llobregat and Besòs Rivers, using LC-MS/MS for analysis. Understanding pharmaceutical impacts on Catalonian River ecosystems is essential for developing mitigation strategies.

Advanced mass spectrometry profiling of phenolic and minerals compounds in herbal beverages.

The global pandemic of COVID-19 has led to an increased interest in herbal infusions as natural remedies since 2020. This has also heightened the need for controlling the composition of these dietary supplements to ensure consumer health and prevent food fraud. In the present work, various mass spectrometry techniques were used to analyze the organic and inorganic composition of 23 herbal infusion samples. UHPLC-ESI-QTOF-MS was used to determine target, suspect, and nontarget polyphenolic compounds. Thus, 8 phenolic compounds were identified in the target analysis and additionally, 80 extra-compounds were identified through suspect and nontargeted screening. ICP-MS was used to monitor the metals released during tea leaf infusion, providing a complete mineral composition of each sample. Principal Component Analysis (PCA) and Discriminant Analysis (DA) were utilized to identify relevant compounds for differentiating and grouping the samples, thus serving as specific markers to detect potential food fraud.