Wastewater-based epidemiology (WBE) is a powerful tool to gather epidemiological insights at the community level, providing objective data on population exposure to harmful substances. A considerable portion of the human exposure to these potentially harmful chemicals occurs unintentionally, unlike substances such as pharmaceuticals, illicit drugs, or alcohol. In this context, this comprehensive review analyzes WBE studies focused on classes of organic chemicals to which humans are unintentionally exposed, namely organophosphorus flame retardants, per- and polyfluoroalkyl substances (PFAS), benzotriazoles and benzothiazoles, phthalates and terephthalates, benzophenones, pesticides, bisphenols, and parabens. The review highlights some advantages of WBE for public health surveillance, e.g., non-invasive analysis, predictive capability, nearly real-time data, population-wide insights, no ethical approval, and unbiased sampling. It also discusses challenges and future research directions in WBE regarding exposure to harmful chemicals from various sources. The review emphasizes the critical role of wastewater sampling, sample preparation, quality control, and instrumental analysis in achieving accurate and reliable results. Furthermore, it examines the selection of human biomarkers for WBE studies and explores strategies to link WBE with human biomonitoring (HBM), which together enhance both the precision and effectiveness of exposure assessments.

Organometallic complexes of the formula [Ru(N^N)(p-cymene)Cl][X] (N^N = bidentate polypyridyl ligands, p-cymene = 1-methyl-4-(1-methylethyl)-benzene, X = counter anion), are currently studied as possible candidates for the potential treatment of cancer. Searching for new organometallic compounds with good to moderate cytotoxic activities, a series of mononuclear water-soluble ruthenium(II)–arene complexes incorporating substituted pyridine–quinoline ligands, with pending -CH₂OH, -CO₂H and -CO₂Me groups in the 4-position of quinoline ring, were synthesized, for the first time, to study their possible effect to modulate the activity of the ruthenium p-cymene complexes. These include the [Ru(η⁶-p-cymene)(pqhyme)Cl][X] (X = Cl⁻ (1-Cl), PF₆⁻ (1-PF₆), pqhyme = 4-hydroxymethyl-2-(pyridin-2-yl)quinoline), [Ru(η⁶-p-cymene)(pqca)Cl][Cl] ((2-Cl), pqca = 4-carboxy-2-(pyridin-2-yl)quinoline), and [Ru(η⁶-p-cymene)(pqcame)Cl][X] (X = Cl⁻ (3-Cl), PF₆⁻ (3-PF₆), pqcame = 4-carboxymethyl-2-(pyridin-2-yl)quinoline) complexes, respectively. Identification of the complexes was based on multinuclear NMR and ATR-IR spectroscopic methods, elemental analysis, conductivity measurements, UV–Vis spectroscopic, and ESI-HRMS techniques. The solid-state structures of 1-PF₆ and 3-PF₆ have been elucidated by single-crystal X-ray diffraction revealing a three-legged piano stool geometry. This is the first time that the in vitro cytotoxic activities of these complexes are studied. These were conducted in HEK293T (human embryonic kidney cells) and HeLa cells (cervical cancer cells) via the MTT assay. The results show poor in vitro anticancer activities for the HeLa cancer cell lines and 3-Cl proved to be the most potent (IC₅₀ > 80 μΜ). In both cell lines, the cytotoxicity of the ligand precursor pqhyme is significantly higher than that of cisplatin.

Reliable identification of contaminants in complex matrices remains hampered by low-abundance signals, complex spectra, and coeluting isobars in liquid chromatography–high-resolution mass spectrometry (LC-HRMS) analyses with data-independent acquisitions. Moreover, wide-scope target screening workflows covering hundreds to thousands of known compounds from reference standards analyses often fail to fully exploit the acquired data, leading to false positives and false negatives. Herein, trapped ion mobility spectrometry (TIMS) was integrated into LC-HRMS, and an enriched database and an analyte-specific framework were introduced for enhanced identification confidence. The database including 1948 contaminants incorporated all MS and MS/MS qualifier ions together with their CCS values and mobility filtering windows, alongside the principal ion. Specific qualifiers were designated as mandatory for the first time by evaluating their relative intensity compared to the principal ion (≥50%), with the established identification points systems being refined accordingly to increase confidence. Regarding TIMS data, ∼2500 CCS values were determined, exhibiting high repeatability (RSD ≤ 0.70%) and interinstrument reproducibility (|ΔCCS|≤ 2%). Comparison with literature data across different IMS-HRMS platforms showed CCS accuracy within 2% for 89% of the ions. In matrix spiking experiments (raptor’s eggs, human urine, wastewater), the cleaner mobility-filtered spectra resulted in improved selectivity for several contaminants’ qualifiers, which improved detection at low concentrations, minimizing false negatives. Additionally, both differentiation based on CCS values (e.g., atenolol–practolol) and mandatory detection of predefined qualifiers (e.g., prometryn–terbutryn) decreased false positives. By incorporating the TIMS dimension and mandatory qualifiers as additional identification information, this work provides a robust framework for high-throughput environmental monitoring and human exposure assessment.

Micro-estuaries receive elevated loads of organic contaminants, yet the influence of water-column structure on their vertical distribution remains unclear. We investigated contaminant dynamics in three structurally distinct micro-estuaries during the dry season using monthly water-column and sediment sampling. Across 63 samples, 274 organic contaminants were detected. Contaminant mixtures shifted seasonally from runoff-to baseflow-dominated conditions, transitioning from pesticide-dominated profiles to more persistent industrial and effluent-derived compounds, including PFAS and sucralose. Water-column stratification strongly influenced contaminant partitioning: strongly stratified systems showed surface accumulation, while well-mixed systems exhibited uniform vertical distributions. Intermediate systems displayed partial segregation, reflecting intermittent mixing and prolonged deep-water residence times. Sediment–deep water distribution coefficients did not correlate with the sediment organic carbon content, suggesting that the dynamic estuarine conditions prevent steady-state sorption–desorption equilibrium. These findings demonstrate that stratification shapes contaminant persistence and biological exposure, underscoring the need for monitoring and risk assessments that incorporate vertical structure.