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Abstract Background Prioritisation of chemical pollutants is a major challenge for environmental managers and decision-makers alike, which is essential to help focus the limited resources available for monitoring and mitigation actions on the most relevant chemicals. This study extends the original NORMAN prioritisation scheme beyond target chemicals, presenting the integration of semi-quantitative data from retrospective suspect screening and expansion of existing exposure and risk indicators. The scheme utilises data retrieved automatically from the NORMAN Database System (NDS), including candidate substances for prioritisation, target and suspect screening data, ecotoxicological effect data, physico-chemical data and other properties. Two complementary workflows using target and suspect screening monitoring data are applied to first group the substances into six action categories and then rank the substances using exposure, hazard and risk indicators. The results from the ‘target’ and ‘suspect screening’ workflows can then be combined as multiple lines of evidence to support decision-making on regulatory and research actions. Results As a proof-of-concept, the new scheme was applied to a combined dataset of target and suspect screening data. To this end, > 65,000 substances on the NDS, of which 2579 substances supported by target wastewater monitoring data, were retrospectively screened in 84 effluent wastewater samples, totalling > 11 million data points. The final prioritisation results identified 677 substances as high priority for further actions, 7455 as medium priority and 326 with potentially lower priority for actions. Among the remaining substances, ca. 37,000 substances should be considered of medium priority with uncertainty, while it was not possible to conclude for 19,000 substances due to insufficient information from target monitoring and uncertainty in the identification from suspect screening. A high degree of agreement was observed between the categories assigned via target analysis and suspect screening-based prioritisation. Suspect screening was a valuable complementary approach to target analysis, helping to prioritise thousands of substances that are insufficiently investigated in current monitoring programmes. Conclusions This updated prioritisation workflow responds to the increasing use of suspect screening techniques. It can be adapted to different environmental compartments and can support regulatory obligations, including the identification of specific pollutants in river basins and the marine environments, as well as the confirmation of environmental occurrence levels predicted by modelling tools. Graphical Abstract

Abstract Background After the occurrence of the COVID-19 pandemic, detection of other disseminated respiratory viruses using highly sensitive molecular methods was declared essential for monitoring the spread of health-threatening viruses in communities. The development of multiplex molecular assays are essential for the simultaneous detection of such viruses even at low concentrations. In the present study, a highly sensitive and specific multiplex one-step droplet digital PCR (RT-ddPCR) assay was developed for the simultaneous detection and absolute quantification of influenza A (IAV), influenza B (IBV), respiratory syncytial virus (RSV), and beta-2-microglobulin transcript as an endogenous internal control (IC B2M). Results The assay was first evaluated for analytical sensitivity and specificity, linearity, reproducibility, and recovery rates with excellent performance characteristics and then applied to 37 wastewater samples previously evaluated with commercially available and in-house quantitative real-time reverse transcription PCR (RT-qPCR) assays. IAV was detected in 16/37 (43%), IBV in 19/37 (51%), and RSV in 10/37 (27%) of the wastewater samples. Direct comparison of the developed assay with real-time RT-qPCR assays showed statistically significant high agreement in the detection of IAV (kappa Cohen’s correlation coefficient: 0.834, p = 0.001) and RSV (kappa: 0.773, p = 0.001) viruses between the two assays, while the results for the detection of IBV (kappa: 0.355, p = 0.27) showed good agreement without statistical significance. Conclusions Overall, the developed one-step multiplex ddPCR assay is cost-effective, highly sensitive and specific, and can simultaneously detect three common respiratory viruses in the complex matrix of wastewater samples even at low concentrations. Due to its high sensitivity and resistance to PCR inhibitors, the developed assay could be further used as an early warning system for wastewater monitoring.

Τhyreostats (TSs) are veterinary drugs used in livestock farming for fattening. Their administration is banned in the European Union since 1981, and their monitoring for food quality and safety control requires sensitive and confirmatory methods. The present study describes the development and validation of a hydrophilic interaction liquid chromatography tandem mass spectrometry (HILIC-MS/MS) method for the simultaneous determination of 2-thiouracil (TU), 6-methyl-2-thiouracil (MTU), 6-propyl-2-thiouracil (PTU), 6-phenyl-2-thiouracil (PhTU), tapazole (TAP), and 2-mercaptobenzimidazole (MBI) in bovine muscle tissues. Investigation of the retention mechanism of the six analytes on the selected amide-based stationary phase showed that hydrophilic partition was the dominant interaction. The sample preparation included extraction with ACN/H2O (80/20), followed by dispersive solid-phase extraction (d-SPE) with C18 sorbent and hexane partitioning. The method was validated according to European guidelines using internal standards, including isotopically labelled ones. The method’s LODs ranged between 2.8 ng g−1 (6-phenyl-2-thiouracil) and 4.1 ng g−1 (2-thiouracil). Application of the proposed method to 48 bovine tissue samples showed non-detectable results.

Abstract Increasing production and use of chemicals and awareness of their impact on ecosystems and humans has led to large interest for broadening the knowledge on the chemical status of the environment and human health by suspect and non-target screening (NTS). To facilitate effective implementation of NTS in scientific, commercial and governmental laboratories, as well as acceptance by managers, regulators and risk assessors, more harmonisation in NTS is required. To address this, NORMAN Association members involved in NTS activities have prepared this guidance document, based on the current state of knowledge. The document is intended to provide guidance on performing high quality NTS studies and data interpretation while increasing awareness of the promise but also pitfalls and challenges associated with these techniques. Guidance is provided for all steps; from sampling and sample preparation to analysis by chromatography (liquid and gas—LC and GC) coupled via various ionisation techniques to high-resolution tandem mass spectrometry (HRMS/MS), through to data evaluation and reporting in the context of NTS. Although most experience within the NORMAN network still involves water analysis of polar compounds using LC–HRMS/MS, other matrices (sediment, soil, biota, dust, air) and instrumentation (GC, ion mobility) are covered, reflecting the rapid development and extension of the field. Due to the ongoing developments, the different questions addressed with NTS and manifold techniques in use, NORMAN members feel that no standard operation process can be provided at this stage. However, appropriate analytical methods, data processing techniques and databases commonly compiled in NTS workflows are introduced, their limitations are discussed and recommendations for different cases are provided. Proper quality assurance, quantification without reference standards and reporting results with clear confidence of identification assignment complete the guidance together with a glossary of definitions. The NORMAN community greatly supports the sharing of experiences and data via open science and hopes that this guideline supports this effort.

Wine quality and safety is affected by the food contact materials (FCMs) used. These materials are expected to protect the beverage from any chemical, physical, or biological hazard and preserve its composition stable throughout its shelf-life. However, the migration of chemical substances from FCMs is a known phenomenon and requires monitoring. This review distinguishes the migrating chemical substances to those of (i) industrial origin with potential safety effects and those of (ii) natural occurrence, principally in cork (ex. tannins) with organoleptic quality effects. The review focuses on the migration of industrial chemical contaminants. Migration testing has been applied only for cork stoppers and tops, while other materials like polyethylene terephthalate (PET) bottles with aluminum cups, paperboard cartons, stainless steel vats, and oak casks have been examined for the presence of chemical migrating substances only by wine analysis without migration testing. The dominant analytical techniques applied are gas and liquid chromatography coupled to mass spectrometry (MS) for the determination of organic compounds and Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES) and ICP-MS for elemental analysis. Targeted approaches are mostly applied, while limited non-target methodologies are reported. The identified migrating substances include authorized substances like phthalate plasticizers, monomers (bisphenol A), antioxidants (Irganox 1010), known but non-authorized substances (butylparaben), break-down products, oxidation products (nonylphenol), polyurethane adhesive by-products, oligomers, ink photoinitiators, and inorganic elements. A preliminary investigation of microplastics’ migration has also been reported. It is proposed that further research on the development of comprehensive workflows of target, suspect, and non-target analysis is required to shed more light on the chemical world of migration for the implementation of an efficient risk assessment and management of wine contact materials.

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.

This article examines the multidimensional problem of energy poverty, focusing on its connections to climate change and its manifestation at rural and urban scales across selected European countries and Israel. The study examined 31 locations in eight countries with diverse geographical and economic backgrounds: Bosnia and Herzegovina, Greece, North Macedonia, The Netherlands, Portugal, Spain, Slovakia, and Israel. The article aims to understand how winter energy vulnerability in rural and urban locations in these countries could be identified using selected energy poverty indicators and how it evolves under the influence of climate change. A set of sociodemographic, infrastructural, and economic variables, combined with climate analysis, were selected and assessed for their impact on energy poverty. We found that energy poverty in most countries depends significantly on location and regional development. Due to a combination of factors influencing energy poverty, rural households tend to be more vulnerable. Furthermore, climate change consequences will likely leave rural areas more likely to experience energy poverty in the future.

Abstract Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources.

Abstract Alzheimer’s disease (AD) poses a profound human, social, and economic burden. Previous studies suggest that extra virgin olive oil (EVOO) may be helpful in preventing cognitive decline. Here, we present a network machine learning method for identifying bioactive phytochemicals in EVOO with the highest potential to impact the protein network linked to the development and progression of the AD. A balanced classification accuracy of 70.3 ± 2.6% was achieved in fivefold cross-validation settings for predicting late-stage experimental drugs targeting AD from other clinically approved drugs. The calibrated machine learning algorithm was then used to predict the likelihood of existing drugs and known EVOO phytochemicals to be similar in action to the drugs impacting AD protein networks. These analyses identified the following ten EVOO phytochemicals with the highest likelihood of being active against AD: quercetin, genistein, luteolin, palmitoleate, stearic acid, apigenin, epicatechin, kaempferol, squalene, and daidzein (in the order from the highest to the lowest likelihood). This in silico study presents a framework that brings together artificial intelligence, analytical chemistry, and omics studies to identify unique therapeutic agents. It provides new insights into how EVOO constituents may help treat or prevent AD and potentially provide a basis for consideration in future clinical studies.

The determination of volatile compounds is essential for the chemical characterisation of honey's aroma and its correlation to its sensory profile and botanical origin. The present study describes the development, optimization and validation of a new, simple and reliable method for the determination of volatile compounds in honey using headspace solid-phase microextraction combined with gas chromatography/mass spectrometry (HS-SPME-GC-MS). The optimization of the SPME conditions showed that the ratio of honey: water (2:1) and the incubation temperature (60 °C) are the most critical parameters. Gas chromatography was performed with medium polar Varian CP-Select 624 column and the experimental Retention Index for a number of compounds was determined as an additional identification feature for suspect analysis. The simultaneous use of four internal standards chlorobenzene, benzophenone, 2-pentanol and 4-methyl-2-pentanone and matrix matched calibration enhanced method accuracy achieving recoveries 73–114 % and repeatability ranging between 3.9 and 19 % relative standard deviations. Furthermore, the superiority of the HS-SPME to static head space technique was verified exhibiting four-to nine-fold higher sensitivity. Target and suspect screening were applied to 30 Greek honey samples and 53 volatile compounds belonging to different chemical classes, such as alkanes, aldehydes, ketones, alcohols, and esters were identified with quantified concentrations ranging between 3.1 μg kg−1 (Limonene) up to 20 mg kg−1 (Benzeneacetaldehyde). Among the new findings is the detection of Myrtenol in Greek pine honey and 2,3-butanediol in Greek oak honey. The developed analytical protocol can be a valuable tool in order to chemically characterize honey based on the volatile content.

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

The packaging has proven to be a source of some serious food contaminants, with several chemicals migrating from the food contact material into the food. Therefore, efficient means of control of the migration extend and identification of the migrating substances must be established. The necessity of migration tests has been underlined by the European Union (EU) Regulation No. 10/2011, requiring the evaluation of the presence of intentionally and non-intentionally added substances. To facilitate this purpose, highly sensitive, multi-analyte methods are required. Targeting a wide range of volatile migrating compounds, we developed and validated a GC-EI-QqQ-MS and a GC-APCI-QTOF-MS method for the simultaneous determination of 131 and 126 food packaging substances, respectively. Even though the GC-EI-QqQ-MS method presented increased sensitivity for several of the investigated compounds, covering the existing EU requirements and specific migration limits (SMLs) for all targeted analytes; the complementary high-resolution method inherently enables the possibility of further utilization of the obtained raw data among others for retrospective analysis. The applicability of both methods was tested using 95% v/v aqueous ethanol food simulant, representative for the worst foreseeable conditions of intended use for many food contact material applications. Real food packaging samples belonging to different types of plastic materials were tested toward chemical migration, utilizing different migration protocols, depending on the sample characteristics. The favorable analytical features of both methods enable their use for the direct analysis of the investigated food simulant, overcoming the need for sample preparation. Thus, labor intensive and/or time-consuming pre-concentration procedures, which would furthermore restrict the applicability of the methods to certain groups of analytes and add to the uncertainty of the overall results, could be eliminated.

This paper performs a comprehensive analysis of the wind energy potential of onshore regions in Greece with emphasis on quantifying the volume risk and the spatial covariance structure. Optimization techniques are employed to derive efficient wind capacity allocation plans (also known as generation portfolios) incorporating different yield aspirations. The generation profile of minimum variance and other optimal portfolios along the efficient frontier are subject to rigorous evaluation using a fusion of descriptive and statistical methods. In particular, principal component analysis is employed to estimate factor models and investigate the spatiotemporal properties of wind power generation, providing valuable insights into the persistence of volume risk. The overarching goal of the study is to employ a set of statistical and mathematical programming tools guiding investors, aggregators and policy makers in their selection of wind energy generating assets. The findings of this research challenge the effectiveness of current policies and industry practices, offering a new perspective on wind energy harvesting with a focus on the management of volume risk.

Preterm delivery (PTD) is a notable pregnancy complication, affecting one out of every ten births. This study set out to investigate whether analyzing the metabolic composition of amniotic fluid (AF) collected from pregnant women during the second trimester of pregnancy could offer valuable insights into prematurity. The research employed 1H–NMR metabolomics to examine AF samples obtained from 17 women who gave birth prematurely (between 29+0 and 36+5 weeks of gestation) and 43 women who delivered at full term. The application of multivariate analysis revealed metabolites (dimethylglycine, glucose, myo-inositol, and succinate) that can serve as possible biomarkers for the prognosis and early diagnosis of preterm delivery. Additionally, pathway analysis unveiled the most critical metabolic pathways relevant to our research hypothesis. In summary, these findings suggest that the metabolic composition of AF in the second trimester can be a potential indicator for identifying biomarkers associated with the risk of PTD.

Inflammatory mediators constitute a recently coined term in the field of metal-based complexes with antiplatelet activities. Our strategy targets Platelet-Activating Factor (PAF) and its receptor, which is the most potent lipid mediator of inflammation. Thus, the antiplatelet (anti-PAF) potency of any substance could be exerted by inhibiting the PAF-induced aggregation in washed rabbit platelets (WRPs), which internationally is a well-accepted methodology. Herein, a series of mononuclear (mer-[Cr(pqx)Cl3(H2O]) (1), [Co(pqx)Cl2(DMF)] (2) (DMF = N,N′-dimethyl formamide), [Cu(pqx)Cl2(DMSO)] (3) (DMSO = dimethyl sulfoxide), [Zn(pqx)Cl2] (4)) and dinuclear complexes ([Mn(pqx)(H2O)2Cl2]2 (5), [Fe(pqx)Cl2]2 (6) and [Ni(pqx)Cl2]2 (7)) incorporating the 2-(2′-pyridyl)quinoxaline ligand (pqx), were biologically evaluated as inhibitors of the PAF- and thrombin-induced aggregation in washed rabbit platelets (WRPs). The molecular structure of the five-co-ordinate analog (3) has been elucidated by single-crystal X-ray diffraction revealing a trigonal bipyramidal geometry. All complexes are potent inhibitors of the PAF-induced aggregation in WRPs in the micromolar range. Complex (6) displayed a remarkable in vitro dual inhibition against PAF and thrombin, with IC50 values of 1.79 μM and 0.46 μM, respectively. Within the series, complex (5) was less effective (IC50 = 39 μM) while complex (1) was almost 12-fold more potent against PAF, as opposed to thrombin-induced aggregation. The biological behavior of complexes 1, 6 and 7 on PAF’s basic metabolic enzymatic pathways reveals that they affect key biosynthetic and catabolic enzymes of PAF underlying the anti-inflammatory properties of the relevant complexes. The in vitro cytotoxic activities of all complexes in HEK293T (human embryonic kidney cells) and HeLa cells (cervical cancer cells) are described via the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay. The results reveal that complex 3 is the most potent within the series.

Significant efforts have been spent in the modern era towards implementing environmentally friendly procedures like composting to mitigate the negative effects of intensive agricultural practices. In this context, a novel fertilizer was produced via the hydrolysis of an onion-derived compost, and has been previously comprehensively chemically characterized. In order to characterize its efficacy, the product was applied to tomato plants at five time points to monitor plant health and growth. Control samples were also used at each time point to eliminate confounding parameters due to the plant’s normal growth process. After harvesting, the plant leaves were extracted using aq. MeOH (70:30, v/v) and analyzed via UPLC-QToF-MS, using a C18 column in both ionization modes (±ESI). The data-independent (DIA/bbCID) acquisition mode was employed, and the data were analyzed by MS-DIAL. Statistical analysis, including multivariate and trend analysis for longitudinal monitoring, were employed to highlight the differentiated features among the controls and treated plants as well as the time-point sequence. Metabolites related to plant growth belonging to several chemical classes were identified, proving the efficacy of the fertilizer product. Furthermore, the efficiency of the analytical and statistical workflows utilized was demonstrated.

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.

Antioxidants play a significant role in human health, protecting against a variety of diseases. Therefore, the development of products with antioxidant activity is becoming increasingly prominent in the human lifestyle. New antioxidant drinks containing different percentages of pomegranate, blackberries, red grapes, and aronia have been designed, developed, and manufactured by a local industry. The comprehensive characterization of the drinks’ constituents has been deemed necessary to evaluate their bioactivity. Thus, LC-qTOFMS has been selected, due to its sensitivity and structure identification capability. Both data-dependent and -independent acquisition modes have been utilized. The data have been treated according to a novel, newly designed workflow based on MS-DIAL and MZmine for suspect, as well as target screening. The classical MS-DIAL workflow has been modified to perform suspect and target screening in an automatic way. Furthermore, a novel methodology based on a compiled bioactivity-driven suspect list was developed and expanded with combinatorial enumeration to include metabolism products of the highlighted metabolites. Compounds belonging to ontologies with possible antioxidant capacity have been identified, such as flavonoids, amino acids, and fatty acids, which could be beneficial to human health, revealing the importance of the produced drinks as well as the efficacy of the new in-house developed workflow.

The increasing use of chemicals in the European Union (EU) has resulted in environmental emissions and wildlife exposures. For approving a chemical within the EU, producers need to conduct an environmental risk assessment, which typically relies on data generated under laboratory conditions without considering the ecological and landscape context. To address this gap and add information on emerging contaminants and chemical mixtures, we analysed 30 livers of white-tailed sea eagles (Haliaeetus albicilla) from northern Germany with high resolution-mass spectrometry coupled to liquid and gas chromatography for the identification of >2400 contaminants. We then modelled the influence of trophic position (δ15N), habitat (δ13C) and landscape on chemical residues and screened for persistent, bioaccumulative and toxic (PBT) properties using an in silico model to unravel mismatches between predicted PBT properties and observed exposures. Despite having generally low PBT scores, most detected contaminants were medicinal products with oxfendazole and salicylamide being most frequent. Chemicals of the Stockholm Convention such as 4,4′-DDE and PCBs were present in all samples below toxicity thresholds. Among PFAS, especially PFOS showed elevated concentrations compared to other studies. In contrast, PFCA levels were low and increased with δ15N, which indicated an increase with preying on piscivorous species. Among plant protection products, spiroxamine and simazine were frequently detected with increasing concentrations in agricultural landscapes. The in silico model has proven to be reliable for predicting PBT properties for most chemicals. However, chemical exposures in apex predators are complex and do not solely rely on intrinsic chemical properties but also on other factors such as ecology and landscape. We therefore recommend that ecological contexts, mixture toxicities, and chemical monitoring data should be more frequently considered in regulatory risk assessments, e.g. in a weight of evidence approach, to trigger risk management measures before adverse effects in individuals or populations start to manifest.

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.

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.

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.

The occurrence of antibiotics in the environment could result in the development of antibiotic-resistant bacteria, which could result in a public health crisis. The occurrence of 676 antibiotics and the main transformation products (TPs) was investigated in the 48 wastewater treatment plants (WWTPs) from 11 countries (Germany, Romania, Serbia, Croatia, Slovenia, Hungary, Slovakia, Czechia, Austria, Cyprus, and Greece) by target and suspect screening. Target screening involved the investigation of antibiotics with reference standards (40 antibiotics). Suspect screening covered 676 antibiotics retrieved from the NORMAN Substance Database (antibiotic list on NORMAN network). Forty-seven antibiotics were detected in effluent wastewater samples: thirty-two by target screening and fifteen additional ones by suspect screening. An ecotoxicological risk assessment was performed based on occurrence data and predicted no effect concentration (PNEC), which involved the derivation of frequency of appearance (FoA), frequency of PNEC exceedance (FoE), and extent of PNEC exceedance (EoE). Azithromycin, erythromycin, clarithromycin, ofloxacin, and ciprofloxacin were prioritized as the calculated risk score was above 1. The median of antibiotics’ load to freshwater ecosystems was 0.59 g/day/WWTP. The detection of antibiotics across countries indicates the presence of antibiotics in the ecosystems of Europe, which may trigger unwanted responses from the ecosystem, including antibiotic resistance.

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.

In this paper, we consider spatially and technologically diversified portfolios of renewable energy resources (RES) on a European scale. These portfolios efficiently allocate wind and solar production capacity with a view on matching load and restricting conventional generation capacity in each country. We investigate the composition of optimal portfolios taking into account the existing cross-border transmission capacity as well as future expansion scenarios. For the purposes of our analysis, we develop several multi-criteria optimization models and apply them to a rich dataset of daily electricity load, RES capacity factors, and transmission capacity constraints for 32 European countries during the period 2010–2015. By exploring different scenarios for the composition of efficient portfolios and cross-border network connectivity, we quantify the effectiveness of the resource aggregation strategy in terms of reducing the energy production deficit or surplus in each country. Empirical evidence shows that the portfolio perspective provides a solid basis for strategic planning on the future expansion of the European grid.

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.

Stevia rebaudiana Bertoni is a plant cultivated worldwide due to its use as a sweetener. The sweet taste of stevia is attributed to its numerous steviol glycosides, however, their use is still limited, due to their bitter aftertaste. The transglycosylation of steviol glycosides, aiming at the improvement of their taste, has been reported for many enzymes, however, glycosyl hydrolases are not extensively studied in this respect. In the present study, a β-glucosidase, MtBgl3a, and a β-galactosidase, TtbGal1, have been applied in the transglycosylation of two steviol glycosides, stevioside and rebaudioside A. The maximum conversion yields were 34.6 and 33.1% for stevioside, while 25.6 and 37.6% were obtained for rebaudioside A conversion by MtBgl3a and TtbGal1, respectively. Low-cost industrial byproducts were employed as sugar donors, such as cellulose hydrolyzate and acid whey for TtbGal1- and MtBgl3a- mediated bioconversion, respectively. LC-HRMS analysis identified the formation of mono- and di- glycosylated products from stevioside and rebaudioside A. Overall, the results of the present work indicate that both biocatalysts can be exploited for the design of a cost-effective process for the modification of steviol glycosides.

Averaged 7-day composite effluent wastewater samples from twelve wastewater treatment plants (WWTPs) in nine countries (Romania, Serbia, Hungary, Slovenia, Croatia, Slovakia, Czechia, Austria, Germany) in the Danube River Basin were collected. WWTPs' selection was based on countries' dominant technology and a number of served population with the aim to get a representative holistic view of the pollution status. Samples were analyzed for 2248 chemicals of emerging concern (CECs) by wide-scope target screening employing LC-ESI-QTOF-MS. 280 compounds were detected at least in one sample and quantified. Spatial differences in the concentrations and distribution of the compounds classes were discussed. Additionally, samples were analyzed for the possible agonistic/antagonistic potencies using a panel of in vitro transactivation reporter gene CALUX® bioassays including ERα (estrogenics), anti-AR (anti-androgens), GR (glucocorticoids), anti-PR (anti-progestins), PPARα and PPARγ (peroxisome proliferators) and PAH assays. The potency of the wastewater samples to cause oxidative stress and induce xenobiotic metabolism was determined using the Nrf2 and PXR CALUX® bioassays, respectively. The signals from each of the bioassays were compared with the recently developed effect-based trigger values (EBTs) and thus allowed for allocating the wastewater effluents into four categories based on their measured toxicity, proposing a putative action plan for wastewater operators. Moreover, samples were analyzed for antibiotics and 13 antibiotic-resistant genes (ARGs) and one mobile genetic element (intl1) with the aim to assess the potential for antibiotic resistance. All data collected from these various types of analysis were stored in an on-line database and can be viewed via interactive map at https://norman-data.eu/EWW_DANUBE. Keywords: Emerging substances, Wide-scope target screening, Effluent wastewater, Bioassays, Antibiotic resistant genes, Danube River Basin

Abstract Background The main representatives of hemicellulose are xylans, usually decorated β-1,4-linked d-xylose polymers, which are hydrolyzed by xylanases. The efficient utilization and complete hydrolysis of xylans necessitate the understanding of the mode of action of xylan degrading enzymes. The glycoside hydrolase family 30 (GH30) xylanases comprise a less studied group of such enzymes, and differences regarding the substrate recognition have been reported between fungal and bacterial GH30 xylanases. Besides their role in the utilization of lignocellulosic biomass for bioenergy, such enzymes could be used for the tailored production of prebiotic xylooligosaccharides (XOS) due to their substrate specificity. Results The expression of a putative GH30_7 xylanase from the fungus Thermothelomyces thermophila (synonyms Myceliophthora thermophila, Sporotrichum thermophile) in Pichia pastoris resulted in the production and isolation of a novel xylanase with unique catalytic properties. The novel enzyme designated TtXyn30A, exhibited an endo- mode of action similar to that of bacterial GH30 xylanases that require 4-O-methyl-d-glucuronic acid (MeGlcA) decorations, in contrast to most characterized fungal ones. However, TtXyn30A also exhibited an exo-acting catalytic behavior by releasing the disaccharide xylobiose from the non-reducing end of XOS. The hydrolysis products from beechwood glucuronoxylan were MeGlcA substituted XOS, and xylobiose. The major uronic XOS (UXOS) were the aldotriuronic and aldotetrauronic acid after longer incubation indicating the ability of TtXyn30A to cleave linear parts of xylan and UXOS as well. Conclusions Hereby, we reported the heterologous production and biochemical characterization of a novel fungal GH30 xylanase exhibiting endo- and exo-xylanase activity. To date, considering its novel catalytic properties, TtXyn30A shows differences with most characterized fungal and bacterial GH30 xylanases. The discovered xylobiohydrolase mode of action offers new insights into fungal enzymatic systems that are employed for the utilization of lignocellulosic biomass. The recombinant xylanase could be used for the production of X2 and UXOS from glucuronoxylan, which in turn would be utilized as prebiotics carrying manifold health benefits.

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 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 occurrence of chemical and biological contaminants of emerging concern (CECs) was investigated in treated wastewater intended for reuse in agriculture. An agarose hydrogel diffusion-based passive sampler was exposed to the outlet of a wastewater treatment plant (WWTP) located in Cyprus, which is equipped with membrane bioreactor (MBR). Passive samplers in triplicate were exposed according to a time-series exposure plan with maximum exposure duration of 28 days. Composite flow-proportional wastewater samples were collected in parallel with the passive sampling exposure plan and were processed by solid phase extraction using HORIZON SPE-DEX 4790 and the same sorbent material (Oasis HLB) as in the passive sampler. The analysis of passive samplers and wastewater samples enabled (i) the field-scale calibration of the passive sampler prototype by the calculation of in situ sampling rates of target substances, and (ii) the investigation of in silico predicted transformation products of the four most ecotoxicologically hazardous antibiotics (azithromycin, clarithromycin, erythromycin, ofloxacin). Additionally, the wastewater samples were subjected to the analysis of seven preselected antibiotic resistant genes (ARGs) and one mobile resistant element (int1). All extracts were analyzed for chemicals in a single batch using a highly sensitive method for pharmaceuticals, antibiotics and illicit drugs by liquid chromatography tandem MS/MS (LC-QQQ) and for various other target compounds (2316 compounds in total) by liquid chromatography high-resolution mass spectrometry (LC-HRMS). 279 CECs and all investigated ARGs (except for blaCTX-M−32) were detected, highlighting potential chemical and biological hazards related to wastewater reuse practices. 16 CECs were prioritized following ecotoxicological risk assessment, whereas sul1 and the mobile resistant element (int1) showed the highest abundance. Comprehensive monitoring efforts using novel sampling methods such as passive sampling, wide-scope target screening and molecular analysis are required to assure safe application of wastewater reuse and avoid spread and crop uptake of potentially hazardous chemicals. Keywords: Hydrogel-based passive sampler, Wastewater reuse, Contaminants of emerging concern, Transformation products, Antibiotics, Antibiotic resistance genes

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.

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.

Aflatoxin M1(AFM1), a major metabolite of Aflatoxin B1(AFB1), has been identified as a potential contaminant in dairy products. Because of its possible carcinogenicity, the legislation limits as set by Commission Regulation (EC) No. 1881/2006 are very strict, namely 0.050 μg kg−1 in milk and 0.025 μg kg−1 in infant formulas. To meet these requirements, a sensitive and accurate method was developed, employing liquid chromatography tandem mass spectrometry (UPLC-MS/MS). Ιmmunoaffinity columns (R-Biopharm) were used for sample purification and preconcentration of the analyte of interest. The quantification of AFM1 was conducted using fortified milk samples, while Aflatoxin B2 (AFB2) was used as an internal standard (IS). The method was validated in terms of linearity, precision, trueness, limits of detection and quantification and uncertainty. The performance criteria for the method were evaluated based on European Commission Regulation (EC) No. 401/2006 and its most recent amendment, as well as the suggested criteria for revision by the EU Reference Laboratory for Mycotoxins and Plant Toxins. The recovery was in the range of 77.9–81.0% for all fortification levels (0.025–0.050–0.075 μg kg−1), with RSDR values (Relative Standard Deviation of intermediate precision) ranging from 6.1% to 12%. The method’s detection and quantification limits were 0.0027 μg kg−1 and 0.0089 μg kg−1, respectively. The occurrence of AFM1 was investigated in 40 samples of different animal origin (cow, goat and sheep milk) provided by Greek producers.

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.

We estimate fundamental pricing relationships in selected European day-ahead electricity markets. Using a fractionally integrated panel data model with unobserved common effects, we quantify the responsiveness of hourly electricity prices to two fundamental leading indicators of day-ahead markets: the predicted load and renewable generation. The application of fractional cointegration analysis techniques gives further insight into the pricing mechanism of power delivery contracts, enabling us to measure the persistence of fundamental shocks.

Pesticides have been used in large amounts around the world for decades and are responsible for environmental pollution and various adverse effects on human health. Analysis of untreated wastewater can deliver useful information on pesticides’ use in a particular area and allow the assessment of human exposure to certain substances. A wide-scope screening method, based on liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry, was applied, using both target and suspect screening methodologies. Daily composite influent wastewater samples were collected for seven or eight consecutive days in Athens between 2014 and 2020 and analyzed for 756 pesticides, their environmental transformation products and their human metabolites. Forty pesticides were quantified at mean concentrations up to 4.9 µg/L (tralkoxydim). The most abundant class was fungicides followed by herbicides, insect repellents, insecticides and plant growth regulators. In addition, pesticide transformation products and/or metabolites were detected with high frequency, indicating that research should be focused on them. Human exposure was evaluated using the wastewater-based epidemiology (WBE) approach and 3-ethyl-carbamoyl benzoic acid and cis-1,2,3,6-tetrahydrophthalimide were proposed as potential WBE biomarkers. Wastewater analysis revealed the presence of unapproved pesticides and indicated that there is an urgent need to include more transformation products in target databases.

Olive oil is famous due to the nutritional properties and beneficial health effects. The exceptional properties of virgin (VOO) and extra virgin olive oil (EVOO) are credited to the bioactive constituents of their polar fraction, the phenolic compounds. The concentration and composition of biophenols can be influenced by the geographical origin, the cultivar, as well as several agronomic and technological parameters. In this study, an ultra-high-performance liquid chromatography coupled to quadrupole-time of flight tandem mass spectrometry (UHPLC-QTOF-MS) method was used to determine biophenols in Greek EVOOs from five islands originating from the North Aegean Region (Chios, Fournoi, Ikaria, Lesvos, and Samos) through target and suspect screening. In total, 14 suspect and 5 target compounds were determined in the analyzed EVOOs. The quantitative and semiquantitative results were compared to investigate discriminations between different regions. Significant differences were found between the islands based on the overall phenolic content and the concentration levels of individual compounds, as well. In the case of Lesvos, the territory was separated in subdivisions (zones), and each zone was studied individually.

Extra virgin olive oil (EVOO) is recognized for its nutritional virtues and the beneficial health effects deriving from its hydrophilic fraction (phenolic acids, phenolic alcohols, flavonoids, and secoiridoids). The phenolic compounds of EVOOs possess multiple biological properties such as antioxidant, antimicrobial, anticarcinogenic, and anti-inflammatory properties, among others. Considering that EVOOs produced in Greece are recognized as high-quality products due to their rich phenolic content, it is imperative to characterize Greek monovarietal EVOOs and ensure that their uniqueness is closely linked to their botanical and territorial origin. In this work, an ultra-high-performance liquid chromatography–quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS) analytical method combined with target and suspect screening was used to characterize monovarietal EVOOs of the Kolovi variety from Lesvos, and thereby establish their phenolic fingerprint. Overall, 25 phenols were determined, and the total quantification and semi-quantification results ranged between 251 and 1230 mg/kg, highlighting the high phenolic content of the Kolovi variety from the island of Lesvos in the North Aegean.

Considering the lack of effective treatments against COVID-19, wastewater-based epidemiology (WBE) is emerging as a cost-effective approach for real-time population-wide SARS-CoV-2 monitoring. Here, we report novel molecular assays for sensitive detection and mutational/variant analysis of SARS-CoV-2 in wastewater. Highly stable regions of SARS-CoV-2 RNA were identified by RNA stability analysis and targeted for the development of novel nested PCR assays. Targeted DNA sequencing (DNA-seq) was applied for the analysis and quantification of SARS-CoV-2 mutations/variants, following hexamers-based reverse transcription and nested PCR-based amplification of targeted regions. Three-dimensional (3D) structure models were generated to examine the predicted structural modification caused by genomic variants. WBE of SARS-CoV-2 revealed to be assay dependent, and significantly improved sensitivity achieved by assay combination (94%) vs. single-assay screening (30%–60%). Targeted DNA-seq allowed the quantification of SARS-CoV-2 mutations/variants in wastewater, which agreed with COVID-19 patients’ sequencing data. A mutational analysis indicated the prevalence of D614G (S) and P323L (RdRP) variants, as well as of the Β.1.1.7/alpha variant of concern, in agreement with the frequency of Β.1.1.7/alpha variant in clinical samples of the same period of the third pandemic wave at the national level. Our assays provide an innovative cost-effective platform for real-time monitoring and early-identification of SARS-CoV-2 variants at community/population levels.

Major, minor and trace elements in wines from Greece were determined by inductively coupled plasma–mass spectrometry (ICP–MS). The concentrations of 44 elements (Na, Mg, P, K, Ca, Cu, Co, Cr, Zn, Sn, Fe, Mn, Li, Be, B, V, Sr, Ba, Al, Ag, Ni, As, Sn, Hg, Pb, Sb, Cd, Ti, Ga, Zr, Nb, Pd, Te, La, Sm, Ho, Tm, Yb, W, Os, Au, Tl, Th, U) in 90 white and red wines from six different regions in Greece for two consecutive vinification years, 2017 and 2018, were determined. Results for the elements aforementioned were evaluated by multivariate statistical methods, such as discriminant analysis and cluster analysis, and the wines were discriminated according to wine variety and geographical origin. Due to the specific choice of the analytes for multivariate statistical investigation, a prediction rate by cross-validation of 98% could be achieved. The aim of this study was not only to reveal specific relationships between the wine samples or between the chemical variables in order to classify the wines from different regions and varieties according to their elemental profile (wine authentication), but also to observe the annual fluctuation in the mineral content of the studied wine samples.

We describe herein the synthesis and laccase mediated oxidation of six novel 1,4-dihydropyridine (DHP)-based hexahydroquinolines (DHP1-DHP3) and decahydroacridines (DHP4-DHP6). We employed different laccase enzymes with varying redox potential to convert DHP1-DHP3 and DHP4-DHP6 to the corresponding pyridine-containing tetrahydroquinoline and octahydroacridine derivatives, respectively. Intensively coloured products were detected in all biocatalytic reactions using laccase from Trametes versicolor (TvLacc), possibly due to the presence of conjugated chromophores formed in products after oxidation. The NMR assessment confirmed that the oxidation product of DHP1 was its corresponding pyridine-bearing tetrahydroquinoline derivative. Laccase from Bacillus subtillis (BacillusLacc) was the most efficient enzyme for this group of substrates using HPLC assessment. Overall, it could be concluded that DHP2 and DHP5, bearing catecholic structures, were easily oxidized by all tested laccases, while DHP3 and DHP6 containing electron-withdrawing nitro-groups are not readily oxidized by laccases. DHP4 with decahydroacridine moiety consisting of three condensed six-membered rings that contribute not only to the volume but also to the higher redox potential of the substrate rendered this compound not to be biotransformed with any of the mentioned enzymes. Overall, we showed that multiple analytical approaches are needed in order to assess biocatalytical reactions.

Honey consumption is attributed to potentially advantageous effects on human health due to its antioxidant capacity as well as anti-inflammatory and antimicrobial activity, which are mainly related to phenolic compound content. Phenolic compounds are secondary metabolites of plants, and their content in honey is primarily affected by the botanical and geographical origin. In this study, a high-resolution mass spectrometry (HRMS) method was applied to determine the phenolic profile of various honey matrices and investigate authenticity markers. A fruitful sample set was collected, including honey from 10 different botanical sources (n = 51) originating from Greece and Poland. Generic liquid–liquid extraction using ethyl acetate as the extractant was used to apply targeted and non-targeted workflows simultaneously. The method was fully validated according to the Eurachem guidelines, and it demonstrated high accuracy, precision, and sensitivity resulting in the detection of 11 target analytes in the samples. Suspect screening identified 16 bioactive compounds in at least one sample, with abscisic acid isomers being the most abundant in arbutus honey. Importantly, 10 markers related to honey geographical origin were revealed through non-targeted screening and the application of advanced chemometric tools. In conclusion, authenticity markers and discrimination patterns were emerged using targeted and non-targeted workflows, indicating the impact of this study on food authenticity and metabolomic fields.

Wine metabolomics constitutes a powerful discipline towards wine authenticity assessment through the simultaneous exploration of multiple classes of compounds in the wine matrix. Over the last decades, wines from autochthonous Greek grape varieties have become increasingly popular among wine connoisseurs, attracting great interest for their authentication and chemical characterization. In this work, 46 red wine samples from Agiorgitiko and Xinomavro grape varieties were collected from wineries in two important winemaking regions of Greece during two consecutive vintages and analyzed using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QToF-MS). A targeted metabolomics methodology was developed, including the determination and quantification of 28 phenolic compounds from different classes (hydroxycinnamic acids, hydroxybenzoic acids, stilbenes and flavonoids). Moreover, 86 compounds were detected and tentatively identified via a robust suspect screening workflow using an in-house database of 420 wine related compounds. Supervised chemometric techniques were employed to build an accurate and robust model to discriminate between two varieties.

Two liquid chromatographic systems, one coupled to atmospheric pressure chemical ionization and tandem mass spectrometric methods (UHPLC-APCI-MS/MS) and the other a high-performance liquid chromatographic coupled to diode array detector (HPLC-DAD) were used to develop and validate methods for the simultaneous determination of fat-soluble vitamins A, D3 and E in rice cereal baby foods. The chromatographic separation was performed on C18 columns with a mixture of methanol-acetonitrile as mobile phase for all methods. The extraction of fat-soluble vitamins included enzymatic hydrolysis with α-amylase, saponification, extraction with petroleum ether or n-hexane and purification with silica cartridge (only for vitamin D3). Quantification of vitamin D3 and E through UHPLC-APCI-MS/MS was performed by the use of internal standards (IS) D3-d3 and E-d6, respectively, while IS was not used for vitamin A. The methods were optimized and validated in terms of linearity, precision, trueness, limits of detection and quantification. The recoveries were in the range of 85.0–107% for retinol, 92.0–105% for α-tocopherol and 95.2–106% for cholecalciferol and the %RSD (Relative Standard Deviation) values ranged from 6.4% to 15%. The evaluation of the methods was also conducted through the estimation of uncertainties, the application in commercial samples and the participation in a proficiency test

The national infrastructure FoodOmicsGR_RI coordinates research efforts from eight Greek Universities and Research Centers in a network aiming to support research and development (R&D) in the agri-food sector. The goals of FoodOmicsGR_RI are the comprehensive in-depth characterization of foods using cutting-edge omics technologies and the support of dietary/nutrition studies. The network combines strong omics expertise with expert field/application scientists (food/nutrition sciences, plant protection/plant growth, animal husbandry, apiculture and 10 other fields). Human resources involve more than 60 staff scientists and more than 30 recruits. State-of-the-art technologies and instrumentation is available for the comprehensive mapping of the food composition and available genetic resources, the assessment of the distinct value of foods, and the effect of nutritional intervention on the metabolic profile of biological samples of consumers and animal models. The consortium has the know-how and expertise that covers the breadth of the Greek agri-food sector. Metabolomics teams have developed and implemented a variety of methods for profiling and quantitative analysis. The implementation plan includes the following research axes: development of a detailed database of Greek food constituents; exploitation of “omics” technologies to assess domestic agricultural biodiversity aiding authenticity-traceability control/certification of geographical/genetic origin; highlighting unique characteristics of Greek products with an emphasis on quality, sustainability and food safety; assessment of diet’s effect on health and well-being; creating added value from agri-food waste. FoodOmicsGR_RI develops new tools to evaluate the nutritional value of Greek foods, study the role of traditional foods and Greek functional foods in the prevention of chronic diseases and support health claims of Greek traditional products. FoodOmicsGR_RI provides access to state-of-the-art facilities, unique, well-characterised sample sets, obtained from precision/experimental farming/breeding (milk, honey, meat, olive oil and so forth) along with more than 20 complementary scientific disciplines. FoodOmicsGR_RI is open for collaboration with national and international stakeholders.

The huge interest in the health-related properties of foods to improve health has brought about the development of sensitive analytical methods for the characterization of natural products with functional ingredients. Greek olive leaves and drupes constitute a valuable source of biophenols with functional properties. A novel ultra-high-performance liquid chromatography–quadrupole time of flight tandem mass spectrometry (UHPLC-QTOF-MS) analytical method was developed to identify biophenols through target and suspect screening in Greek olive leaves and drupes of the varieties: Koroneiki, Throumbolia, Konservolia, Koutsourelia, Kalamon, Petrolia, Amigdalolia, Megaritiki, Mastoeidis, Agouromanakolia, Agrilia, Adramitiani and Kolovi. The method’s performance was evaluated using the target compounds: oleuropein, tyrosol and hydroxytyrosol. The analytes demonstrated satisfactory recovery efficiency for both leaves (85.9–90.5%) and drupes (89.7–92.5%). Limits of detection (LODs) were relatively low over the range 0.038 (oleuropein)–0.046 (hydroxytyrosol) and 0.037 (oleuropein)–0.048 (hydroxytyrosol) for leaves and drupes, respectively For leaves, the precision limit ranged between 4.7% and 5.8% for intra-day and between 5.8% and 6.5% for inter-day experiments, and for drupes, it ranged between 3.8% and 5.2% for intra-day and between 5.1 and 6.2% for inter-day experiments, establishing the good precision of the method. The regression coefficient (r2) was above 0.99 in all cases. Furthermore, the preparation of herbal tea from olive leaves is suggested after investigating the optimum infusion time of dried leaves in boiling water. Overall, 10 target and 36 suspect compounds were determined in leaves, while seven targets and thirty-three suspects were identified in drupes, respectively.