Assessment of endocrine disruptor pollutants and their metabolites in environmental water samples using a sustainable natural deep eutectic solvent-based analytical methodology

Distinguishing the botanical origins of rare honey through untargeted metabolomics and machine learning interpreting flavonoid profiles

Distinguishing the botanic origins of monofloral honey is the foremost concern in ensuring its authentication. In this work, an innovative, green, and comprehensive approach was developed to distinguish the botanic origins of four types of rare honey, and the strategy involved in the following aspects: Based on theoretical design, suitable natural deep eutectic solvent (NADES) was screened to extract flavonoids from honey samples; after NADES extracts were directly analyzed by high-resolution mass spectrometry, the discrimination models of monofloral honey were established by untargeted metabolomics combined with machine learning. Based on the comparison of various models, the Random Forest algorithm had higher prediction accuracy for four types of monofloral honey, and characteristic compounds for each rare monofloral honey were screened based on SHapley Additive exPlanations values. This work provides a new perspective on the use of AI technology and green chemistry to control the quality of honey.

Unraveling the levels of emerging contaminants along the eastern Mediterranean Sea

The Eastern Mediterranean Sea, rich in environmental and cultural heritage, faces increasing threats from emerging contaminants like toxic metals and phthalates. This study evaluates their occurrence across 40 Lebanese Mediterranean coastal hotspots using advanced techniques such as Inductively Coupled Plasma Mass Spectrometry (ICP-MS), X-ray Fluorescence Spectroscopy (XRF) and Gas Chromatography-Mass Spectrometry (GC-MS). Widespread contamination was detected in both water and sediments near landfills, sewage discharges, and industrial areas. Metal concentrations varied, with chromium (Cr) reaching 20.3 µg/L, arsenic (As) 12.1 µg/L, and lead (Pb) 30.6 µg/L, indicating pollution from urban and industrial activities. Manganese (Mn) and zinc (Zn) were within safe limits, while selenium (Se) and arsenic posed ecological risks. Among 13 phthalates, diethylhexyl phthalate (DEHP) was the most prevalent, ranging from 15.57 to 72.88 µg/L. Sediments showed elevated calcium, strontium, and barium levels, exceeding safety thresholds. Statistical analysis revealed correlations between contaminants and spatial variability driven by industrial, agricultural, and urban activities. These findings highlight the need for proper regulations and routine monitoring to protect marine ecosystems and public health.

Detection of Dibutyl Phthalate in Surface Water by Fluorescence Polarization Immunoassay

Dibutyl phthalate (DBP) is widely used as a plasticizer in the production of polymeric materials to give them flexibility, strength and extensibility. However, due to its negative impact on human health, in particular reproductive functions and fetal development, the content of DBP must be controlled in food and the environment. The present study aims to develop a sensitive, fast and simple fluorescence polarization immunoassay (FPIA) using monoclonal antibodies derived against DBP (MAb-DBP) for its detection in open waters. New conjugates of DBP with various fluorescein derivatives were obtained and characterized: 5-aminomethylfluorescein (AMF) and dichlorotriazinylaminofluorescein (DTAF). The advantages of using the DBP-AMF conjugate in the FPIA method are shown, the kinetics of binding of this chemical with antibodies are studied, the analysis is optimized, and the concentration of monoclonal antibodies is selected for sensitivity analysis-16 nM. The calibration dependence of the fluorescence polarization signal for the detection of DBP was obtained. The observed IC50 (DBP concentration at which a 50% decrease in the fluorescence polarization signal occurs, 40 ng/mL) and the limit of detection (LOD, 7.5 ng/mL) values were improved by a factor of 45 over the previously described FPIA using polyclonal antibodies. This technique was tested by the recovery method, and the high percentage of DBP discovery in water ranged from 85 to 110%. Using the developed method, real water samples from Lake Onega were tested, and a good correlation was shown between the results of the determination of DBP by the FPIA method and GC-MS. Thus, the FPIA method developed in this work can be used to determine DBP in open-water reservoirs.