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The market for illicit drugs and new psychoactive substances (NPS) has grown significantly and people attending festivals have been identified as being at high risk (high extent and frequency of substance use). Traditional public health surveillance data sources have limitations (high costs, long implementation times, and ethical issues) and wastewater-based epidemiology (WBE) can cost-effectively support surveillance efforts. Influent wastewater samples were analyzed for NPS and illicit drug consumption collected during New Year period (from 29-Dec-2021 to 4-Jan-2022) and a summer Festival (from 29-June-2022 to 12-July-2022) in a large city in Spain. Samples were analyzed for phenethylamines, cathinones, opioids, benzodiazepines, plant-based NPS, dissociatives, and the illicit drugs methamphetamine, MDA, MDMA, ketamine, heroin, cocaine, and pseudoephedrine by liquid chromatography mass spectrometry. High consumption rates of specific NPS and established illicit drugs were identified at the peak of each event. Furthermore, a dynamic change in NPS use (presence and absence of substances) was detected over a period of six months. Eleven NPS, including synthetic cathinones, benzodiazepines, plant-based NPS and dissociatives, and seven illicit drugs were found across both the New Year and summer Festival. Statistically significant differences (p < 0.05) were seen for 3-MMC (New Year vs summer Festival), eutylone (New Year vs summer Festival), cocaine (summer Festival vs normal week and summer Festival vs New Year), MDMA (New Year vs normal week and summer Festival vs normal week), heroin (summer Festival vs New Year) and pseudoephedrine (summer Festival vs New Year). This WBE study assessed the prevalence of NPS and illicit drugs at festivals following the reduction of the COVID-19 pandemic restrictions highlighting the high use of specific substances at the peak of each event. This approach identified in a cost-effective and timely manner without any ethical issues the most used drugs and changes in use patterns and, thus, can complement public health information., The authors sincerely thank the wastewater treatment plant operators for their help in collecting samples. The authors also thank SCIEX for the use of their instruments. Nikolaos Rousis: This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska–Curie Grant Agreement No. 896141. Richard Bade: The Queensland Alliance for Environmental Health Sciences, The University of Queensland, gratefully acknowledges the financial support of the Queensland Department of Health. R. B. is the recipient of an Australian Research Council Discovery Early Career Award (project number DE220100381), and J. M. is the recipient of an Australian Research Council Australian Laureate Fellowship (project number FL200100028) funded by the Australian Government. Emma Gracia-Lor: This work was supported by the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with Complutense University in the line Program to Stimulate Research for Young Doctors in the context of the V PRICIT (Regional Programme of Research and Technological Innovation, project number PR65/19-22432). Iván Romero-Sánchez acknowledges the Complutense University of Madrid for his predoctoral grant [CT63/19-CT64/19]. The views expressed in this article are those of the author(s) and not necessarily those of the funding agencies.

The presence of 220 emerging contaminants belonging to different classes (artificial sweeteners, personal care products, coffee and tobacco-related compounds, and industrial chemicals) was investigated in hospital wastewater for the first time. Twenty samples were collected within two sampling periods from two points of a Greek General Hospital. Target compounds were analyzed using a solid-phase extraction protocol followed by UHPLC-ESI-QToF-MS analysis. Analytical results showed that 23 micropollutants were detected at least once in hospital wastewater samples in Period 1, while 27 compounds were detected at least once in Period 2. The coffee and tobacco-related compounds were the most frequently detected substances, followed by artificial sweeteners, parabens, and industrial chemicals. The highest mean concentrations were recorded for the artificial sweeteners cyclamic acid (377 μg/L) and saccharine (295 μg/L), followed by caffeine (193 μg/L), nicotine (162 μg/L), and the industrial chemical lauryl diethanolamide (153 μg/L). The group of artificial sweeteners contributed up to 55.1% (Point A/Period 1) to the total concentration of studied chemicals. The detection of high concentrations of artificial sweeteners in hospital effluents reveals that hospitals should be considered as important point-sources of these contaminants.

Oregano is native to the Mediterranean region and it has been reported to contain several phenolic compounds particularly flavonoids that have been related with multiple bioactivities towards certain diseases. Oregano is cultivated in the island of Lemnos where the climate promotes its growth and thus it could be further used in promoting local economy. The aim of the present study was to establish a methodology for the extraction of total phenolic content along with the antioxidant capacity of oregano by using response surface methodology. A Box–Behnken design was applied to optimize the extraction conditions with regard to the extraction time, temperature, and solvent mixture with the use of ultrasound-assisted extraction. For the optimized extracts, identification of the most abundant flavonoids (luteolin, kaempferol, and apigenin) was performed with an analytical HPLC-PDA and UPLC-Q-TOF MS methodology. The predicted optimal conditions of the statistical model were identified, and the predicted values confirmed. The linear factors evaluated, temperature, time, and ethanol concentration, all showed significant effect (p < 0.05), and the regression coefficient (R2) presented a good correlation between predicted and experimental data. Actual values under optimum conditions were 362.1 ± 1.8 and 108.6 ± 0.9 mg/g dry oregano with regard to total phenolic content and antioxidant activity based on 2,2-Diphenyl-1-picrylhydrazyl (DPPH) assay, respectively. Additionally, further antioxidant activities by 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) (115.2 ± 1.2 mg/g dry oregano), Ferric Reducing Antioxidant Power (FRAP) (13.7 ± 0.8 mg/g dry oregano), and Cupric Reducing Antioxidant Capacity (CUPRAC) (1.2 ± 0.2 mg/g dry oregano) assays were performed for the optimized extract. The extract acquired under the optimum conditions contain an adequate quantity of phenolic compounds that could be used in the production of functional foods by food enrichment procedure.

Non-target screening (NTS) methods are rapidly gaining in popularity, empowering researchers to search for an ever-increasing number of chemicals. Given this possibility, communicating the confidence of identification in an automated, concise and unambiguous manner is becoming increasingly important. In this study, we compiled several pieces of evidence necessary for communicating NTS identification confidence and developed a machine learning approach for classification of the identifications as reliable and unreliable. The machine learning approach was trained using data generated by four laboratories equipped with different instrumentation. The model discarded substances with insufficient identification evidence efficiently, while revealing the relevance of different parameters for identification. Based on these results, a harmonized IP-based system is proposed. This new NTS-oriented system is compatible with the currently widely used five level system. It increases the precision in reporting and the reproducibility of current approaches via the inclusion of evidence scores, while being suitable for automation., PGF acknowledges his Ramon y Cajal fellowship (RYC2019-027913-I) from the AEI-MICI. ELS is supported by the Luxembourg National Research Fund (FNR) for project A18/BM/12341006.

Per- and polyfluoroalkyl substances (PFASs) are a class of persistent organic pollutants (POPs).

Petroselinum crispum is native to the Mediterranean region and has been reported to contain several phenolic compounds in addition to the highest quantity of apigenin among several natural raw materials. The aim of the present study was to establish an extraction method for the most abundant phenolic compounds of Petroselinum crispum leaves by using response surface methodology. A Box–Behnken design was applied to optimize the extraction conditions with regards to the extraction time, temperature, solvent mixture, and sample to solvent ratio with the use of ultrasound-assisted extraction. An analytical HPLC-PDA methodology was developed to accurately quantify the phenolic compounds in the extracts. Identification of the most abundant phenolic compounds (luteolin, caffeic acid, and apigenin) was also performed with an UPLC-Q-TOF MS methodology. The predicted optimal conditions of the statistical model were identified, and the predicted values confirmed. Actual values of 23.92 ± 1.86 with 100 mL/g, 40% ethanol, 70 °C and 40 min, 19.10 ± 0.75 with 20 mL/g, 0% ethanol, 70 °C and 40 min, and 25.29 ± 1.82 μg/g dry parsley with and 100 mL/g, 0% ethanol, 25 °C and 40 min of luteolin, caffeic acid, and apigenin respectively, were estimated. Total phenolic content and antioxidant activities by DPPH, ABTS, FRAP, and CUPRAC assays were performed for the extracts. The extracts acquired under the optimum conditions contain an adequate quantity of phenolic compounds that could be used in the production of functional foods by food enrichment prcedure.

The occurrence of 200 multiclass contaminants of emerging concern (CECs) encompassing 168 medicinal products and transformation products (TPs), 5 artificial sweeteners, 12 industrial chemicals, and 15 other compounds was investigated in influent and effluent wastewater samples collected during 7 consecutive days from 5 wastewater treatment plants (WWTPs) located in Cyprus. The methodology included a generic solid-phase extraction protocol using mixed-bed cartridges followed by Ultra-High Performance Liquid Chromatography coupled with Quadrupole-Time of Flight Mass Spectrometry (UHPLC-QTOF-MS) analysis. A total of 63 CECs were detected at least in one sample, with 52 and 55 out of the 200 compounds detected in influents and effluents, respectively. Ten (10) out of the 24 families of parent compounds and associated TPs were found in the wastewater samples (influent or effluent).\ud \ud 1-H-benzotriazole, carbamazepine, citalopram, lamotrigine, sucralose, tramadol, and venlafaxine (>80 % frequency of appearance in effluents) were assessed with respect to their bioavailability in soil as part of different scenarios of irrigation with reclaimed water following a qualitative approach. A high score of 12 (high probability) was predicted for 2 scenarios, a low score of 3 (rare occasions) for 2 scenarios, while the rest 28 scenarios had scores 5–8 (unlikely or limited possibility) and 9–11 (possibly).\ud \ud Retrospective screening was performed with the use of a target database of 2466 compounds and led to the detection of 158 additional compounds (medicinal products (65), medicinal products TPs (15), illicit drugs (7), illicit drugs TPs (3), industrial chemicals (11), plant protection products (25), plant protection products TPs (10), and various other compounds (22).\ud \ud This work aspires to showcase how the presence of CECs in wastewater could be investigated and assessed at WWTP level, including an expert-based methodology for assessing the soil bioavailability of CECs, with the aim to develop sustainable practices and enhance reclaimed water reuse.

A large number of apex predator samples are available in European research collections, environmental specimen banks and natural history museums that could be used in chemical monitoring and regulation. Apex predators bioaccumulate pollutants and integrate contaminant exposure over large spatial and temporal scales, thus providing key information for risk assessments. Still, present assessment practices under the different European chemical legislations hardly use existing chemical monitoring data from top predators. Reasons include the lack of user-specific guidance and the fragmentation of data across time and space. The European LIFE APEX project used existing sample collections and applied state-of-the-art target and non-target screening methods, resulting in the detection of > 4,560 pollutants including legacy compounds. We recommend establishing infrastructures that include apex predators as an early warning system in Europe. Chemical data of apex species from freshwater, marine and terrestrial compartments should become an essential component in future chemical assessment and management across regulations, with the purpose to (1) validate registration data with ‘real world’ measurements and evaluate the predictability of current models; (2) identify and prioritise hazardous chemicals for further assessment; (3) use data on food web magnification as one line of evidence to assess biomagnification; (4) determine the presence of (bio)transformations products and typical chemical mixtures, and (5) evaluate the effectiveness of risk management measures by trend analysis. We highlight the achievements of LIFE APEX with regard to novel trend and mixture analysis tools and prioritisation schemes. The proposed advancements complement current premarketing regulatory assessments and will allow the detection of contaminants of emerging concern at an early stage, trigger risk management measures and evaluations of their effects with the ultimate goal to protect humans and the environment. This is the second policy brief of the LIFE APEX project.

There is a growing need for indexing and harmonizing retention time (tR) data in liquid chromatography derived under different conditions to aid in the identification of compounds in high resolution mass spectrometry (HRMS) based suspect and nontarget screening of environmental samples. In this study, a rigorously tested, inexpensive, and simple system-independent retention index (RI) approach is presented for liquid chromatography (LC), based on the cocamide diethanolamine homologous series (C(

The purpose of this study was to examine the effects of two different feeding systems, a control or a flaxseed and lupin diet (experimental), for a sheep flock, on the microbiota and metabolome of Kefalograviera cheese samples produced by their milk. In particular, the microbiota present in Kefalograviera cheese samples was analyzed using 16S rRNA gene sequencing, while ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) was applied to investigate the chemical profile of the cheeses, considering the different feeding systems applied. The metagenomic profile was found to be altered by the experimental feeding system and significantly correlated to specific cheese metabolites, with Streptococcaceae and Lactobacillaceae establishing positive and negative correlations with the discriminant metabolites. Overall, more than 120 features were annotated and identified with high confidence level across the samples while most of them belonged to specific chemical classes. Characteristic analytes detected in different concentrations in the experimental cheese samples including arabinose, dulcitol, hypoxanthine, itaconic acid, L-arginine, L-glutamine and succinic acid. Therefore, taken together, our results provide an extensive foodomics approach for Kefalograviera cheese samples from different feeding regimes, investigating the metabolomic and metagenomic biomarkers that could be used to foresee, improve, and control cheese ripening outcomes, demonstrating the quality of the experimental Kefalograviera cheese.

There is currently a paucity of scientific data in Africa on the analysis and occurrence of emerging contaminants in sewage sludge. In this work, the occurrence of European Union (EU) Water Framework Directive priority substances and wide-range emerging contaminants were investigated and discussed comprehensively in the sewage sludge samples from three different wastewater treatment plants (WWTPs) in Lagos, Nigeria. The identification strategy was implemented by target and suspect screening in liquid chromatography-high resolution mass spectrometry. 250 compounds were identified in the sewage sludge samples from the investigated WWTPs. From 250 detected compounds, 182 compounds were quantified, and 78 compounds significantly show high environmental risk score (calculated from provisional no-effect concentrations values (PNEC) as well as their environmental quality data (EQs)). Most of contaminants detected at high amount belong to pharmaceuticals and are from hospital WWTP. While the highest concentration (72.4 mg kg

Monitoring data from apex predators were key drivers in the development of early chemicals legislations due to the population declines of many species during the twentieth century, which was linked to certain persistent organic pollutants (POPs). Besides triggering the development of global treaties (e.g. the Stockholm Convention), chemical monitoring data from apex predators have been particularly important for identifying compounds with bioaccumulative properties under field conditions. Many apex predators are protected species and only a few environmental specimen banks (ESBs) regularly collect samples as many ESBs were established during the 1980–1990s when apex predators were scarce. Today, many POPs have been banned, which contributed to the recovery of many apex predator populations. As a consequence, apex predator samples are now available in research collections (RCs) and natural history museums (NHMs). These samples can be used for routine analysis as well as for screening studies using novel analytical techniques and advanced data treatment workflows, such as suspect and non-target screening. The LIFE APEX project has demonstrated how these samples can be used in a cost-efficient way to generate data on legacy compounds and contaminants of emerging concern. Furthermore, it has described quality assurance/control measures to ensure high quality and comparable data, with a view to uses in chemicals risk assessment and management. To increase the visibility of available sample collections and monitoring data from apex predators we developed accessible online database systems. Additionally, the acquired high-resolution mass spectrometric data were stored in a digital sample freezing platform that allows retrospective suspect screening in previously analysed samples for substances that may be of concern/under assessment in the future. These databases provide open access to a wide range of chemical data, for use by regulators, researchers, industry and the general public, and contribute to a stronger link between science and policy.

Highly sensitive methodologies for SARS-CoV-2 detection are essential for the control of COVID-19 pandemic. We developed and analytically validated a highly sensitive and specific five-plex one-step RT-ddPCR assay for SARS-CoV-2. We first designed in-silico novel primers and probes for the simultaneous absolute quantification of three different regions of the nucleoprotein (

β-Galactosidases are key enzymes in the food industry. Apart from the hydrolysis of the saccharide bond of lactose, they also catalyze transgalactosylation reactions, producing galactooligosaccharides (GOS) with prebiotic activity. Here we report the heterologous production in Pichia pastoris of a novel β-galactosidase from the fungus Thermothielavioides terrestris. The enzyme (TtbGal1) was purified and characterized, showing optimal activity at 60 °C and pH 4. TtbGal1 is thermostable, retaining almost full activity for 24 h at 50 °C. It was applied to the production of GOS from defined lactose solutions and acid whey, a liquid waste from the Greek yoghurt industry, reaching yields of 19.4 % and 14.8 %, respectively. HILIC-ESI-QTOF-MS analysis revealed the production of GOS with up to 4 saccharide monomers. The results demonstrate efficient GOS production catalyzed by TtbGal1, valorizing acid whey, a waste with a heavy polluting load from the dairy industry.

Honey is a highly consumed commodity due to its potential health benefits upon certain consumption, resulting in a high market price. This fact indicates the need to protect honey from fraudulent acts by delivering comprehensive analytical methodologies. In this study, targeted, suspect and non-targeted metabolomic workflows were applied to identify botanical origin markers of Greek honey. Blossom honey samples (n = 62) and the unifloral fir (n = 10), oak (n = 24), pine (n = 39) and thyme (n = 34) honeys were analyzed using an ultra-high-performance liquid chromatography hybrid quadrupole time-of-flight mass spectrometry (UHPLC-q-TOF-MS) system. Several potential authenticity markers were revealed from the application of different metabolomic workflows. In detail, based on quantitative targeted analysis, three blossom honey markers were found, namely, galangin, pinocembrin and chrysin, while gallic acid concentration was found to be significantly higher in oak honey. Using suspect screening workflow, 12 additional bioactive compounds were identified and semi-quantified, achieving comprehensive metabolomic honey characterization. Lastly, by combining non-targeted screening with advanced chemometrics, it was possible to discriminate thyme from blossom honey and develop binary discriminatory models with high predictive power. In conclusion, a holistic approach to assessing the botanical origin of Greek honey is presented, highlighting the complementarity of the three applied metabolomic approaches.

The ionization efficiency of emerging contaminants was modeled for the first time in gas chromatography-high-resolution mass spectrometry (GC-HRMS) which is coupled to an atmospheric pressure chemical ionization source (APCI). The recent chemical space has been expanded in environmental samples such as soil, indoor dust, and sediments thanks to recent use of high-resolution mass spectrometric techniques; however, many of these chemicals have remained unquantified. Chemical exposure in dust can pose potential risk to human health, and semiquantitative analysis is potentially of need to semiquantify these newly identified substances and assist with their risk assessment and environmental fate. In this study, a rigorously tested semiquantification workflow was proposed based on GC-APCI-HRMS ionization efficiency measurements of 78 emerging contaminants. The mechanism of ionization of compounds in the APCI source was discussed via a simple connectivity index and topological structure. The quantitative structure-property relationship (QSPR)-based model was also built to predict the APCI ionization efficiencies of unknowns and later use it for their quantification analyses. The proposed semiquantification method could be transferred into the household indoor dust sample matrix, and it could include the effect of recovery and matrix in the predictions of actual concentrations of analytes. A suspect compound, which falls inside the application domain of the tool, can be semiquantified by an online web application, free of access at http://trams.chem.uoa.gr/semiquantification/.

Raptors are ideal indicators for biomonitoring studies using wildlife in order to assess the environmental pollution in the terrestrial ecosystem, since they are placed in the highest trophic position in the food webs and their life expectancy is relatively long. In this study, 26 eggs of 4 bird species (Peregrine falcon, Eurasian curlew, Little owl and Eagle owl) collected in Germany, were investigated for the presence of persistent organic pollutants (POPs) and thousands of contaminants of emerging concern (CECs). Generic sample preparation protocols were followed for the extraction of the analytes and the purification of the extracts, and the samples were analyzed both by liquid (LC) and gas chromatography (GC) coupled to high resolution mass spectrometry (HRMS), for capturing a wide range of organic micropollutants with different physicochemical properties. State-of-the-art screening methodologies were applied in the acquired HRMS data, including wide-scope target analysis of 2448 known pollutants and suspect screening of over 65,000 environmentally relevant compounds. Overall, 58 pollutants from different chemical classes, such as plant protection products, per- and polyfluoroalkyl substances and medicinal products, as well as their transformation products, were determined through target analysis. Most of the detected compounds were lipophilic (logP2), although the presence of (semi)polar contaminants should not be overlooked, underlying the need for holistic analytical approaches in environmental monitoring studies. p,p'-DDE, PCB 153 and PCB138, PFOS and methylparaben were the most frequently detected compounds. 50 additional substances were identified and semi-quantified through suspect screening workflows, including mainly compounds of industrial use with high production volume.

The increasing demands of agriculture and the food market have resulted in intensive agricultural practices using synthetic fertilizers to maximize production. However, significant efforts have been made to implement more environmentally friendly procedures, such as composting, to overcome the adverse impact of these invasive practices. In the terms of this research, composting was applied to the production of two biofertilizers, using onion and mushroom by-products as raw materials respectively. The main purposes of this work were to identify the compounds that pass from the raw materials to the final products (onion-based and mushroom-based), as well as the characterization of the chemical profile of these final products following suspect and non-target screening workflows via UPLC-qToF-MS. Overall, 14 common compounds were identified in the onion and its final product, while 12 compounds were found in the mushroom and its corresponding product. These compounds belong to fatty acids, organic acids, and flavonoids, which could be beneficial to plant health. The determination of parameters, such as the pH, conductivity, organic matter, nitrogen content, and elemental analysis, were conducted for the overall characterization of the aforementioned products.

The concentrations of available and total Mn were determined in the soils of three different forest ecosystems, i.e. a maquis forest, a beech forest and fir one. The concentrations of total Mn in the deeper mineral horizons reflected the type of patent material, but in the surface layers, the more acidic soil (in the beech forest) had the higher concentrations. This was due to the high concentrations of Mn in the standing leaves and litterfall of beech trees, which brought about high litterfall fluxes of Mn in that forest. However, the concentrations of (DTPA) available Mn was significantly higher in the soil under beech only in the 0–10 cm layer, whereas the fast decomposition of organic matter in the Mediterranean zone resulted in higher concentrations of available Mn in the Ofh soil horizon of the maquis plot. The available Mn did not correlate with soil pH. These findings mean that high concentrations of available Mn do not always entail higher uptake. The soil pH played a predominant role for the high concentrations in the vegetation of the beech forest.

Mahaleb, which is a spice with culinary use in Eastern and Mediterranean countries, is a natural source of coumarin. Its presence in bakery ware has not yet been studied, despite the fact that it i...

Wastewater treatment plants (WWTPs) represent an important input of contaminants in the environment. Therefore, it is critical to continuously monitor the performance of WWTPs to take appropriate action and avoid an influx of contaminants in the environment. In this study, a battery of seven in vitro bioassays covering a selected spectrum of toxicity effects is proposed for quality control of wastewater effluents. The bioassays address mixture toxicity, which is the combined adverse effect of multiple contaminants and can act as an early warning system. The proposed battery was applied to samples from 11 WWTPs of representative technology from the Danube River Basin (DRB). The order of toxic effects in terms of extent of exceedance of effect-based trigger values (EBTs) was PAH (PAH activity) > PXR (xenobiotic metabolism) > ERα (estrogenic activity) > PPARγ > Nrf2 (oxidative stress) > anti-AR > GR. A mitigation plan for WWTP operators based on EBT exceedance is proposed. This study demonstrates that the proposed effect-based monitoring battery is a complementary tool to the chemical analysis approach. A regular application of such time- and cost-effective bioanalytical tools in the WWTPs of the DRB is proposed to provide a ‘safety net’ for aquatic ecosystems.

Alcohol consumption is a global healthcare problem with enormous social, economic, and clinical consequences. The liver sustains the earliest and the greatest degree of tissue injury due to chronic alcohol consumption and it has been estimated that alcoholic liver disease (ALD) accounts for almost 50% of all deaths from cirrhosis in the world. In this study, we used a modified Lieber-DeCarli (LD) diet to treat mice with alcohol and simulate chronic alcohol drinking. Using an untargeted metabolomics approach, our aim was to identify the various metabolites and pathways that are altered in the early stages of ALD. Histopathology showed minimal changes in the liver after 6 weeks of alcohol consumption. However, untargeted metabolomics analyses identified 304 metabolic features that were either up- or down-regulated in the livers of ethanol-consuming mice. Pathway analysis revealed significant alcohol-induced alterations, the most significant of which was in the FXR/RXR activation pathway. Targeted metabolomics focusing on bile acid biosynthesis showed elevated taurine-conjugated cholic acid compounds in ethanol-consuming mice. In summary, we showed that the changes in the liver metabolome manifest very early in the development of ALD, and when minimal changes in liver histopathology have occurred. Although alterations in biochemical pathways indicate a complex pathology in the very early stages of alcohol consumption, bile acid changes may serve as biomarkers of the early onset of ALD.

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) and gas chromatography-high resolution mass spectrometry (GC-HRMS) have revolutionized analytical chemistry among many other disciplines. These advanced instrumentations allow to theoretically capture the whole chemical universe that is contained in samples, giving unimaginable opportunities to the scientific community. Laboratories equipped with these instruments produce a lot of data daily that can be digitally archived. Digital storage of data opens up the opportunity for retrospective suspect screening investigations for the occurrence of chemicals in the stored chromatograms. The first step of this approach involves the prediction of which data is more appropriate to be searched. In this study, we built an optimized multi-label classifier for predicting the most appropriate instrumental method (LC-HRMS or GC-HRMS or both) for the analysis of chemicals in digital specimens. The approach involved the generation of a baseline model based on the knowledge that an expert would use and the generation of an optimized machine learning model. A multi-step feature selection approach, a model selection strategy, and optimization of the classifier’s hyperparameters led to a model with accuracy that outperformed the baseline implementation. The models were used to predict the most appropriate instrumental technique for new substances. The scripts are available at GitHub and the dataset at Zenodo.

There is an increasing need for developing a strategy to quantify the newly identified substances in environmental samples, where there are not always reference standards available. The semi-quantitative analysis can assist risk assessment of chemicals and their environmental fate. In this study, a rigorously tested and system-independent semi-quantification workflow is proposed based on ionization efficiency measurement of emerging contaminants analyzed in liquid chromatography-high-resolution mass spectrometry. The quantitative structure-property relationship (QSPR)-based model was built to predict the ionization efficiency of unknown compounds which can be later used for their semi-quantification. The proposed semi-quantification method was applied and tested in real environmental seawater samples. All semi-quantification-related calculations can be performed online and free of access at http://trams.chem.uoa.gr/semiquantification/ .

Extra virgin olive oil (EVOO) is a key component of the Mediterranean diet, with several health benefits derived from its consumption. Moreover, due to its eminent market position, EVOO has been thoroughly studied over the last several years, aiming at its authentication, but also to reveal the chemical profile inherent to its beneficial properties. In the present work, a comparative study was conducted to assess Greek EVOOs’ quality and authentication utilizing different analytical approaches, both targeted and untargeted. 173 monovarietal EVOOs from three emblematic Greek cultivars (Koroneiki, Kolovi and Adramytiani), obtained during the harvesting years of 2018–2020, were analyzed and quantified as per their fatty acids methyl esters (FAMEs) composition via the official method (EEC) No 2568/91, as well as their bioactive content through liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) methodology. In addition to FAMEs analysis, EVOO samples were also analyzed via HRMS-untargeted metabolomics and optical spectroscopy techniques (visible absorption, fluorescence and Raman). The data retrieved from all applied techniques were analyzed with Machine Learning methods for the authentication of the EVOOs’ variety. The models’ predictive performance was calculated through test samples, while for further evaluation 30 commercially available EVOO samples were also examined in terms of variety. To the best of our knowledge, this is the first study where different techniques from the fields of standard analysis, spectrometry and optical spectroscopy are applied to the same EVOO samples, providing strong insight into EVOOs chemical profile and a comparative evaluation through the different platforms.

Extra Virgin Olive Oil (EVOO), the emblematic food of the Mediterranean diet, is recognized for its nutritional value and beneficial health effects. The main authenticity issues associated with EVOO's quality involve the organoleptic properties (EVOO or defective), mislabeling of production type (organic or conventional), variety and geographical origin, and adulteration. Currently, there is an emerging need to characterize EVOOs and evaluate their genuineness. This can be achieved through the development of analytical methodologies applying advanced "omics" technologies and the investigation of EVOOs chemical fingerprints. The objective of this review is to demonstrate the analytical performance of High Resolution Mass Spectrometry (HRMS) in the field of food authenticity assessment, allowing the determination of a wide range of food constituents with exceptional identification capabilities. HRMS-based workflows used for the investigation of critical olive oil authenticity issues are presented and discussed, combined with advanced data processing, comprehensive data mining and chemometric tools. The use of unsupervised classification tools, such as Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA), as well as supervised classification techniques, including Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Partial Least Square Discriminant Analysis (PLS-DA), Orthogonal Projection to Latent Structure-Discriminant Analysis (OPLS-DA), Counter Propagation Artificial Neural Networks (CP-ANNs), Self-Organizing Maps (SOMs) and Random Forest (RF) is summarized. The combination of HRMS methodologies with chemometrics improves the quality and reliability of the conclusions from experimental data (profile or fingerprints), provides valuable information suggesting potential authenticity markers and is widely applied in food authenticity studies.

Background Acquired azole resistance (AR) in Aspergillus fumigatus emphasizes the importance of the One Health multisectorial approach. The prevalence of azole-resistant A. fumigatus in the environment of Greece is unknown. Methods Between October 2016 and September 2017, a total of 716 soil samples were collected from 23 provinces and screened for AR using azole-containing agar plates. Recovered isolates were macro-/microscopically identified and colonies were counted. Azole susceptibility testing of A. fumigatus species complex (SC) isolates was performed (EUCAST E.DEF9.3.1). Azole-resistant A. fumigatus isolates were subjected to confirmatory molecular identification and sequencing of the cyp51A gene. Results No yeasts were recovered, while multiple moulds grew on 695 (97%) samples. Overall, zygomycetes (most non-Mucor genera) grew on 432 (60%) samples, while Aspergillus spp. grew on 500 (70%) [410 (57%) Aspergillus niger SC; 120 (17%) Aspergillus terreus SC; 101 (14%) A. fumigatus SC; 34 (5%) Aspergillus flavus SC]. The mean ± SD soil load of Aspergillus spp. was 2.23 ± 0.41 log10 cfu/g (no differences among species). No azole-resistant non-A. fumigatus spp. isolate was detected. Itraconazole, voriconazole, isavuconazole and posaconazole MIC50/MIC90 (MIC range) of A. fumigatus SC strains were 0.25/0.5 (0.25 to >8), 0.5/1 (0.25 to >8), 1/1 (0.125 to >8) and 0.06/0.125 (0.06–1) mg/L, respectively. Overall, 1/500 (0.2%) of Aspergillus isolates, and 1/101 (1%) of A. fumigatus SC isolates, was pan-azole-resistant (itraconazole, voriconazole, isavuconazole and posaconazole MIC >8, >8, >8 and 1 mg/L, respectively). The resistant isolate was recovered from organically grown raisin grapes treated with homemade compost and it was an A. fumigatus sensu stricto isolate harbouring the TR46/Y121F/T289A mutation. The soil’s load was higher compared with azole-susceptible strains (3.74 versus 2.09 log10 cfu/g). Conclusions This is the first known report of environmental pan-azole-resistant A. fumigatus in Greece. Since data on Greek clinical isolates are lacking, this finding must alarm the systematic local surveillance of AR in medical settings.

Uncertainty arising from sampling is nowadays a controversial issue, if it is necessary to be taken into account in total uncertainty. As in the quantification of analysis uncertainty, there are two principal approaches in order to estimate uncertainty of sampling: the bottom-up and the top-down approach. A novel top-down approach for sampling uncertainty is proposed in this study using nested analysis of variance (ANOVA). Determination of the oxytetracycline (OTC) content in feed was utilized for estimating uncertainty arising from sampling using the new approach. The advantage of nested ANOVA is that the effect of every factor on the total uncertainty can be calculated. In the present study, factors such as physical preparation of sample, lots of production and particle diameter were examined in the experimental design. It was found that the effect of different lots had the highest uncertainty among the factors. Finally, the results of nested ANOVA were compared with the uncertainty calculated using other top-down approaches. Classical ANOVA and robust ANOVA (RANOVA) did not show significant differences in their results. On the other hand, nested ANOVA estimated higher uncertainty of sampling in comparison with the other approaches.

Irbesartan (IRB) exerts beneficial effects either alone or in combination with other drugs on numerous diseases, such as cancer, diabetes, and hypertension. However, due to its high lipophilicity, IRB does not possess the optimum pharmacological efficiency. To circumvent this problem, a drug delivery system with 2-hydroxypropyl-β-cyclodextrin (2-HP-β-CD) was explored. The 1:1 complex between IRB and 2-HP-β-CD was identified through ESI QTF HRMS. Dissolution studies showed a higher dissolution rate of the lyophilized IRB-2-HP-β-CD complex than the tablet containing IRB at pH = 1.2. DSC results revealed the differences of the thermal properties between the complex and various mixtures consisting of the two components, namely IRB and 2-HP-β-CD. Interestingly, depending on the way the mixture preparation was conducted, different association between the two components was observed. Molecular dynamics (MD) simulations predicted the favorable formation of the above complex and identified the dominant interactions between IRB and 2-HP-β-CD. In vitro pharmacological results verified that the inclusion complex not only preserves the binding affinity of IRB for AT1R receptor, but also it slightly increases it. As the complex formulation lacks the problems of the tablet, our approach is a promising new way to improve the efficiency of IRB.

The quality of the Dniester River Basin has been seriously impacted by the chemicals released by agriculture, industry, and wastewater discharges. To assess its current chemical pollution status, a transboundary monitoring campaign was conducted in May 2019. Thirteen surface water, 13 sediment, and three biota samples were collected and analyzed using generic sample preparation methods for the determination of organic substances by liquid chromatography high-resolution mass spectrometry (LC-HRMS) and metals by inductively coupled plasma mass spectrometry (ICP-MS). Wide-scope target and suspect screening resulted in detection of Water Framework Directive (WFD) priority substances and emerging contaminants, whereas the raw data were stored in NORMAN Digital Sample Freezing Platform (DSFP) for future retrospective screening. Furthermore, risk assessment was performed to prioritize detected substances and propose a draft list of river basin–specific pollutants. All studied metals (As, Hg, Zn, Cu, Cr, Cd, Pb, Ni) were detected in the surface water and sediments. In total, 139 organic contaminants belonging to various chemical classes (pesticides, pharmaceuticals, drugs of abuse, stimulants, sweeteners, industrial chemicals, and their transformation products) were detected. The highest cumulative concentration of contaminants was observed in surface water from the Byk River, a tributary of the Dniester (Moldova). Concentrations of WFD priority substances diuron and mercury and EU Watch List neonicotinoid compounds imidacloprid and thiamethoxam exceeded their environmental quality standards (EQS), whereas concentrations of 23 emerging substances exceeded their predicted no-effect concentration (PNEC) at minimum one site. Emerging contaminants telmisartan, metolachlor, terbuthylazine, and 4-acetamidoantipyrine were prioritized as potential river basin–specific pollutants.

Antibiotic residues in milk are a major health threat for the consumer and a hazard to the dairy industry, causing significant economic losses. This study aims to assess the presence of antibiotic residues in raw milk comparatively by a rapid screening test (BetaStar® Combo) and Liquid Chromatography coupled with Tandem Mass Spectrometry (LC-MS/MS). A total of 445 samples were collected from 3 dairy companies of north-central Algeria (Algiers, Blida, Boumerdes), and they were rapidly screened for β-lactams and tetracyclines; 52 samples, comprising 34 positive tanker-truck milk and 18 negative bulk-tank milk were tested by LC-MS/MS, which revealed 90.4% were contaminated (n = 47) and 55.3% exceeded the Maximum Residue Limit (MRL). The β-lactams as parent compounds and their metabolites were the most frequently detected with maximum value for cloxacillin (1231 µg/kg) and penicillin G (2062 µg/kg). Under field condition, the false-positive results, particularly for tetracyclines, seems to be related to milk samples displaying extreme acidity values (≥19°D) or fat-level fluctuations (2.7 g/100 mL and 5.6–6.2 g/100 mL). Despite a relatively low prevalence (7.64%) of residues using the rapid test, the detection by LC-MS/MS of flumequine (52 µg/kg), cefaclor (maximum 220 µg/kg) and metabolites of β-lactams at high levels should lead to reflections on the control of their human and environmental toxicological effects.

Apex predators are good indicators of environmental pollution since they are relatively long-lived and their high trophic position and spatiotemporal exposure to chemicals provides insights into the persistent, bioaccumulative and toxic (PBT) properties of chemicals. Although monitoring data from apex predators can considerably support chemicals’ management, there is a lack of pan-European studies, and longer-term monitoring of chemicals in organisms from higher trophic levels. The present study investigated the occurrence of contaminants of emerging concern (CECs) in 67 freshwater, marine and terrestrial apex predators and in freshwater and marine prey, gathered from four European countries. Generic sample preparation protocols for the extraction of CECs with a broad range of physicochemical properties and the purification of the extracts were used. The analysis was performed utilizing liquid (LC) chromatography coupled to high resolution mass spectrometry (HRMS), while the acquired chromatograms were screened for the presence of more than 2,200 CECs through wide-scope target analysis. In total, 145 CECs were determined in the apex predator and their prey samples belonging in different categories, such as pharmaceuticals, plant protection products, per- and polyfluoroalkyl substances, their metabolites and transformation products. Higher concentration levels were measured in predators compared to prey, suggesting that biomagnification of chemicals through the food chain occurs. The compounds were prioritized for further regulatory risk assessment based on their frequency of detection and their concentration levels. The majority of the prioritized CECs were lipophilic, although the presence of more polar contaminants should not be neglected. This indicates that holistic analytical approaches are required to fully characterize the chemical universe of biota samples. Therefore, the present survey is an attempt to systematically investigate the presence of thousands of chemicals at a European level, aiming to use these data for better chemicals management and contribute to EU Zero Pollution Ambition.

Analysis of untreated municipal wastewater is recognized as an innovative approach to assess population exposure to or consumption of various substances. Currently, there are no published wastewater-based studies investigating the relationships between catchment social, demographic, and economic characteristics with chemicals using advanced non-targeted techniques. In this study, fifteen wastewater samples covering 27% of the Australian population were collected during a population Census. The samples were analysed with a workflow employing liquid chromatography high-resolution mass spectrometry and chemometric tools for non-target analysis. Socioeconomic characteristics of catchment areas were generated using Geospatial Information Systems software. Potential correlations were explored between pseudo-mass loads of the identified compounds and socioeconomic and demographic descriptors of the wastewater catchments derived from Census data. Markers of public health (e.g., cardiac arrhythmia, cardiovascular disease, anxiety disorder and type 2 diabetes) were identified in the wastewater samples by the proposed workflow. They were positively correlated with descriptors of disadvantage in education, occupation, marital status and income, and negatively correlated with descriptors of advantage in education and occupation. In addition, markers of polypropylene glycol (PPG) and polyethylene glycol (PEG) related compounds were positively correlated with housing and occupation disadvantage. High positive correlations were found between separated and divorced people and specific drugs used to treat cardiac arrhythmia, cardiovascular disease, and depression. Our robust non-targeted methodology in combination with Census data can identify relationships between biomarkers of public health, human behaviour and lifestyle and socio-demographics of whole populations. Furthermore, it can identify specific areas and socioeconomic groups that may need more assistance than others for public health issues. This approach complements important public health information and enables large-scale national coverage with a relatively small number of samples., This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska–Curie Grant Agreement No. 896141.