Publications by authors named "Reza Aalizadeh"

37 Publications

Safety and potency of BIV1-CovIran inactivated vaccine candidate for SARS-CoV-2: A preclinical study.

Rev Med Virol 2021 Oct 26:e2305. Epub 2021 Oct 26.

Department of Life Science Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran.

The development of effective and safe COVID-19 vaccines is a major move forward in our global effort to control the SARS-CoV-2 pandemic. The aims of this study were (1) to develop an inactivated whole-virus SARS-CoV-2 candidate vaccine named BIV1-CovIran and (2) to determine the safety and potency of BIV1-CovIran inactivated vaccine candidate against SARS-CoV-2. Infectious virus was isolated from nasopharyngeal swab specimen and propagated in Vero cells with clear cytopathic effects in a biosafety level-3 facility using the World Health Organization's laboratory biosafety guidance related to COVID-19. After characterisation of viral seed stocks, the virus working seed was scaled-up in Vero cells. After chemical inactivation and purification, it was formulated with alum adjuvant. Finally, different animal species were used to determine the toxicity and immunogenicity of the vaccine candidate. The study showed the safety profile in studied animals including guinea pig, rabbit, mice and monkeys. Immunisation at two different doses (3 or 5 μg per dose) elicited a high level of SARS-CoV-2 specific and neutralising antibodies in mice, rabbits and nonhuman primates. Rhesus macaques were immunised with the two-dose schedule of 5 or 3 μg of the BIV1-CovIran vaccine and showed highly efficient protection against 10 TCID50 of SARS-CoV-2 intratracheal challenge compared with the control group. These results highlight the BIV1-CovIran vaccine as a potential candidate to induce a strong and potent immune response that may be a promising and feasible vaccine to protect against SARS-CoV-2 infection.
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http://dx.doi.org/10.1002/rmv.2305DOI Listing
October 2021

SARS-CoV-2 wastewater surveillance data can predict hospitalizations and ICU admissions.

Sci Total Environ 2022 Jan 7;804:150151. Epub 2021 Sep 7.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, University Campus, Zografou, 15771, Athens, Greece. Electronic address:

We measured SARS-CoV-2 RNA load in raw wastewater in Attica, Greece, by RT-qPCR for the environmental surveillance of COVID-19 for 6 months. The lag between RNA load and pandemic indicators (COVID-19 hospital and intensive care unit (ICU) admissions) was calculated using a grid search. Our results showed that RNA load in raw wastewater is a leading indicator of positive COVID-19 cases, new hospitalization and admission into ICUs by 5, 8 and 9 days, respectively. Modelling techniques based on distributed/fixed lag modelling, linear regression and artificial neural networks were utilized to build relationships between SARS-CoV-2 RNA load in wastewater and pandemic health indicators. SARS-CoV-2 mutation analysis in wastewater during the third pandemic wave revealed that the alpha-variant was dominant. Our results demonstrate that clinical and environmental surveillance data can be combined to create robust models to study the on-going COVID-19 infection dynamics and provide an early warning for increased hospital admissions.
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http://dx.doi.org/10.1016/j.scitotenv.2021.150151DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8421077PMC
January 2022

MALDI-TOF-MS integrated workflow for food authenticity investigations: An untargeted protein-based approach for rapid detection of PDO feta cheese adulteration.

Food Chem 2022 Feb 6;370:131057. Epub 2021 Sep 6.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece. Electronic address:

Advances in Matrix-assisted Laser Desorption/Ionization -Time-Of-Flight Mass Spectrometry (MALDI-TOF-MS) have led to its supremacy for complex assessment of food authenticity studies, like dairy products fraud, holding promise for the discovery of potential authenticity (bio)markers. In this study, an integrated untargeted protein-based workflow in combination with advanced chemometrics is presented, to address authenticity challenges in PDO feta cheese which is legally manufactured by the mixture of sheep/goat milk. Potential markers attributed to specific animal origin were found from protein profiles acquired for authentic feta and white cheeses (prepared from cow milk), belonging to 4 kDa-18.5 kDa mass area. Rapid detection of feta cheese adulteration from cow milk was also achieved down to 1% adulteration level. The discriminative models showed high predictive ability for feta cheese authenticity (Q = 0.920, RMSEE = 0.053) and its adulteration (Q = 0.835, RMSEE = 0.121), introducing a reliable approach in routine analysis. The methodology was successfully applied in detection of cow milk in sheep yoghurt.
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http://dx.doi.org/10.1016/j.foodchem.2021.131057DOI Listing
February 2022

Removal of drug losartan in environmental aquatic matrices by heat-activated persulfate: Kinetics, transformation products and synergistic effects.

Chemosphere 2022 Jan 20;287(Pt 1):131952. Epub 2021 Aug 20.

Department of Chemical Engineering, University of Western Macedonia, GR-50132, Kozani, Greece. Electronic address:

In this study, the oxidative degradation of losartan (LOS), a widely administered medicine for high blood pressure by heat-activated persulfate was investigated. Increased temperature and persulfate concentration, as well as acidic conditions enhance the degradation efficiency of LOS, whose rate follows pseudo-first order kinetics. From the respective apparent rate constants in the range 40-60 °C, an apparent activation energy of 112.70 kJ/mol was computed. Radical scavenging tests demonstrated that both HO and [Formula: see text] contribute towards LOS degradation. LOS degradation was suppressed in real water matrices including bottled water (BW) and secondary wastewater effluent (WW), while other experiments indicated that the presence of bicarbonates and humic acid negatively affected its oxidation. Instead, the addition of chloride ions at 250 mg/L resulted in a positive effect on LOS removal. The combination of heat-activated PS with low-frequency ultrasound exhibited a synergistic effect, with the ratio S being 2.29 in BW and 1.52 in WW. Five transformation products of LOS were identified through HRMS suspect and non-target screening approaches, among which two are reported for the first time. Using the in-house risk assessment program, ToxTrAMs was revealed that most of the identified TPs present higher toxicity than LOS against Daphnia magna.
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http://dx.doi.org/10.1016/j.chemosphere.2021.131952DOI Listing
January 2022

Inter-laboratory mass spectrometry dataset based on passive sampling of drinking water for non-target analysis.

Sci Data 2021 08 24;8(1):223. Epub 2021 Aug 24.

Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences (SLU), SE-75007, Uppsala, Sweden.

Non-target analysis (NTA) employing high-resolution mass spectrometry is a commonly applied approach for the detection of novel chemicals of emerging concern in complex environmental samples. NTA typically results in large and information-rich datasets that require computer aided (ideally automated) strategies for their processing and interpretation. Such strategies do however raise the challenge of reproducibility between and within different processing workflows. An effective strategy to mitigate such problems is the implementation of inter-laboratory studies (ILS) with the aim to evaluate different workflows and agree on harmonized/standardized quality control procedures. Here we present the data generated during such an ILS. This study was organized through the Norman Network and included 21 participants from 11 countries. A set of samples based on the passive sampling of drinking water pre and post treatment was shipped to all the participating laboratories for analysis, using one pre-defined method and one locally (i.e. in-house) developed method. The data generated represents a valuable resource (i.e. benchmark) for future developments of algorithms and workflows for NTA experiments.
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http://dx.doi.org/10.1038/s41597-021-01002-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8384892PMC
August 2021

Development and Application of Liquid Chromatographic Retention Time Indices in HRMS-Based Suspect and Nontarget Screening.

Anal Chem 2021 08 12;93(33):11601-11611. Epub 2021 Aug 12.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 157 71 Athens, Greece.

There is an increasing need for comparable and harmonized retention times () in liquid chromatography (LC) among different laboratories, to provide supplementary evidence for the identity of compounds in high-resolution mass spectrometry (HRMS)-based suspect and nontarget screening investigations. In this study, a rigorously tested, flexible, and less system-dependent unified retention time index (RTI) approach for LC is presented, based on the calibration of the elution pattern. Two sets of 18 calibrants were selected for each of ESI+ and ESI-based on the maximum overlap with the retention times and chemical similarity indices from a total set of 2123 compounds. The resulting calibration set, with RTI set to range between 1 and 1000, was proposed as the most appropriate RTI system after rigorous evaluation, coordinated by the NORMAN network. The validation of the proposed RTI system was done externally on different instrumentation and LC conditions. The RTI can also be used to check the reproducibility and quality of LC conditions. Two quantitative structure-retention relationship (QSRR)-based models were built based on the developed RTI systems, which assist in the removal of false-positive annotations. The applicability domains of the QSRR models allowed completing the identification process with higher confidence for substances within the domain, while indicating those substances for which results should be treated with caution. The proposed RTI system was used to improve confidence in suspect and nontarget screening and increase the comparability between laboratories as demonstrated for two examples. All RTI-related calculations can be performed online at http://rti.chem.uoa.gr/.
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http://dx.doi.org/10.1021/acs.analchem.1c02348DOI Listing
August 2021

Change in the chemical content of untreated wastewater of Athens, Greece under COVID-19 pandemic.

Sci Total Environ 2021 Dec 30;799:149230. Epub 2021 Jul 30.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece. Electronic address:

COVID-19 pandemic spread rapidly worldwide with unanticipated effects on mental health, lifestyle, stability of economies and societies. Although many research groups have already reported SARS-CoV-2 surveillance in untreated wastewater, only few studies evaluated the implications of the pandemic on the use of chemicals by influent wastewater analysis. Wide-scope target and suspect screening were used to monitor the effects of the pandemic on the Greek population through wastewater-based epidemiology. Composite 24 h influent wastewater samples were collected from the wastewater treatment plant of Athens during the first lockdown and analyzed by liquid chromatography mass spectrometry. A wide range of compounds was investigated (11,286), including antipsychotic drugs, illicit drugs, tobacco compounds, food additives, pesticides, biocides, surfactants and industrial chemicals. Mass loads of chemical markers were estimated and compared with the data obtained under non-COVID-19 conditions (campaign 2019). The findings revealed increases in surfactants (+196%), biocides (+152%), cationic quaternary ammonium surfactants (used as surfactants and biocides) (+331%), whereas the most important decreases were estimated for tobacco (-33%) and industrial chemicals (-52%). The introduction of social-restriction measures by the government affected all aspects of life.
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http://dx.doi.org/10.1016/j.scitotenv.2021.149230DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8321698PMC
December 2021

Patterns of pharmaceuticals use during the first wave of COVID-19 pandemic in Athens, Greece as revealed by wastewater-based epidemiology.

Sci Total Environ 2021 Dec 21;798:149014. Epub 2021 Jul 21.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece. Electronic address:

Since 2019, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), impaired public health with considerable morbidity and mortality due to the lack of vaccines and effective treatment. The severe disease mainly harmed adults with predisposing medical comorbidities (such as heart disease, hypertension, chronic lung disease), while it can occur in healthy individuals that may be asymptomatic. Wastewater-based Epidemiology (WBE), a non-invasive, objective, chemical tool was used to monitor and estimate the changes in drug's consumption and prescription patterns under normal conditions (2019) and under COVID-19 pandemic conditions (2020). NSAIDs, antihypertensives, diuretics, antiepileptics, antilipidemics, antibiotics, analgesics, antivirals, anticancer drugs, contrast iodinated drugs, antidiabetics, antiallergic drugs, antiulcers and other pharmaceuticals were studied in wastewater and revealed the application of various treatments during the first wave of the pandemic in Athens, Greece. Data were correlated with COVID-19 infection therapeutical plans. The result of the analysis revealed a remarkable increase for antiviral drugs (170%), hydroxychloroquine (387%), and antibiotics (57%), which were the most applied treatments against COVID-19 during the first wave in Greece. In agreement with related authorities urge, NSAIDs presented decrease (27%) during the first lockdown, while paracetamol demonstrated a remarkable increase (198%). The use levels for Angiotensin II receptor blockers such as valsartan, and co-administrated diuretics, such as hydrochlorothiazide, were reduced during 2020, by 32% and 26% respectively.
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http://dx.doi.org/10.1016/j.scitotenv.2021.149014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8294694PMC
December 2021

Non-target trend analysis for the identification of transformation products during ozonation experiments of citalopram and four of its biodegradation products.

J Hazard Mater 2021 10 15;419:126401. Epub 2021 Jun 15.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece. Electronic address:

During ozonation in wastewater treatment plants, ozone reacts with emerging pollutants, which are partially removed through the secondary treatment, as long as, with their biotransformation products, triggering the formation of ozonation transformation products (TPs). Although the transformation of parent compounds (PCs) and their metabolites has been reported in the literature, the probable transformation of biotransformation products has not been investigated so far. This study evaluates the fate of citalopram (CTR) and four of its biotransformation products (DESCTR, CTRAM, CTRAC and CTROXO) during ozonation experiments. A Gaussian curve-based trend analysis was performed for the first time for the automated detection of TPs in ozone concentrations ranging from 0.06 to 12 mg/L. In total 46 ozonation TPs were detected; 7 TPs of CTR, 10 of DESCTR, 9 of CTRAM, 12 of CTRAC and 8 of CTROXO and were structurally elucidated based on their high resolution tandem mass spectra interpretation and tandem mass spectra similarity with the respective PC. Results have demonstrated that the examined compounds follow common transformation pathways in reaction with ozone and that common TPs were formed through the ozonation of different structurally-alike compounds. Moreover, the toxicity of the identified TPs was predicted with an in-house risk assessment program.
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http://dx.doi.org/10.1016/j.jhazmat.2021.126401DOI Listing
October 2021

Honey Phenolic Compound Profiling and Authenticity Assessment Using HRMS Targeted and Untargeted Metabolomics.

Molecules 2021 May 8;26(9). Epub 2021 May 8.

Analytical Chemistry Laboratory, Chemistry Department, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15771 Athens, Greece.

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 ( = 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.
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http://dx.doi.org/10.3390/molecules26092769DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8125859PMC
May 2021

Development of a Wine Metabolomics Approach for the Authenticity Assessment of Selected Greek Red Wines.

Molecules 2021 May 11;26(10). Epub 2021 May 11.

Laboratory of Food Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece.

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 and 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.
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http://dx.doi.org/10.3390/molecules26102837DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8150368PMC
May 2021

Development and Application of a Novel Semi-quantification Approach in LC-QToF-MS Analysis of Natural Products.

J Am Soc Mass Spectrom 2021 Jun 24;32(6):1412-1423. Epub 2021 May 24.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece.

Use of high-resolution mass spectrometry (HRMS) including a MS calibration method has enabled simultaneous identification and quantification of knowns/unknowns. This has expanded our knowledge about the existing sample relevant chemical space in a way beyond reconciliation with a quantification task. This is largely due to fact that reference standards are not always available to achieve quantitative analysis. In this scenario, a semi-quantitative approach can fill the gap and provide a rough estimation of concentration. This research aimed to develop and compare several semi-quantification approaches based on chemical similarity or properties. The ionization efficiency scale was created for several groups of natural products. Advanced modeling approach based on a support vector machine was conducted to learn from the experimental ionization efficiency and apply it to unknowns or suspected compounds to predict their ionization efficiency in electrospray ionization mode. The developed semi-quantification workflows could be useful in most HRMS based "omics" areas, especially in natural products discovery.
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http://dx.doi.org/10.1021/jasms.1c00032DOI Listing
June 2021

Chemical characterisation of Pelargonium sidoides root based on LC-QToF-MS non-target screening strategies.

Phytochem Anal 2021 May 22. Epub 2021 May 22.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Athens, Greece.

Introduction: Pelargonium sidoides is a member of the Geraniaceae family and it originates from the coastal regions of South Africa. In the last decades, Pelargonium sidoides root has been subjected to several surveys due to the assertion of its health benefits, such as the relief of symptoms of acute bronchitis, common cold and acute rhinosinusitis. Many studies have been conducted to reveal its naturally occurring bioactive chemicals, yet no wide-scope chemical characterisation strategies have been done using mass spectrometry.

Objective: This research aimed to comprehensively characterise the chemical profile of Pelargonium sidoides root via high-resolution mass spectrometry.

Methodology: The Pelargonium sidoides root was extracted by a mixture of methanol: water in the proportion of 80:20. The extraction procedure included vortexing, shaking as well as the use of an ultrasound sonication bath under 40°C. After centrifugation, the supernatant was evaporated to dryness. The dry residue was reconstituted with a mixture of methanol/water (50:50, v/v), filtered and injected into an ultra-high-pressure liquid chromatography-quadruple time-of-flight mass spectrometer.

Results: Overall, 33 compounds were identified in the root using suspect and non-target screening. These compounds were originated from different classes of compounds such as amino acids, phenolic acids, α-hydroxy-acids, vitamins, polyphenols, flavonoids, coumarins, coumarins glucosides, coumarin sulphates and nucleotides. Quantitative results were provided for the identified compounds, where their reference standards were available.

Conclusion: Some important compounds were elucidated, belonging to different classes of compounds such as antioxidants (coumarins and phenolic compounds), amino acids, nucleotides and vitamins revealing the importance of the bioactive content of this root.
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http://dx.doi.org/10.1002/pca.3059DOI Listing
May 2021

Application of High Resolution Mass Spectrometric methods coupled with chemometric techniques in olive oil authenticity studies - A review.

Anal Chim Acta 2020 Oct 30;1134:150-173. Epub 2020 Jul 30.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens. Panepistimiopolis Zografou, 15 771 Athens, Greece. Electronic address:

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.
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http://dx.doi.org/10.1016/j.aca.2020.07.029DOI Listing
October 2020

Authentication of Table Olives: A Novel Non-Target High Resolution Mass Spectrometric Approach.

Molecules 2020 Jun 24;25(12). Epub 2020 Jun 24.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15771 Athens, Greece.

Food science continually requires the development of novel analytical methods to prevent fraudulent actions and guarantee food authenticity. Greek table olives, one of the most emblematic and valuable Greek national products, are often subjected to economically motivated fraud. In this work, a novel ultra-high-performance liquid chromatography-quadrupole time of flight tandem mass spectrometry (UHPLC-QTOF-MS) analytical method was developed to detect the mislabeling of , and thereby establish their authenticity. A non-targeted screening workflow was applied, coupled to advanced chemometric techniques such as Principal Component Analysis (PCA) and Partial Least Square Discriminant Analysis (PLS-DA) in order to fingerprint and accurately discriminate Greek olives from olives from Egypt and Chile. The method performance was evaluated using a target set of phenolic compounds and several validation parameters were calculated. Overall, 65 table olive samples from Greece, Egypt, and Chile were analyzed and processed for the model development and its accuracy was validated. The robustness of the chemometric model was tested using 11 Greek olive samples that were produced during the following crop year, 2018, and they were successfully classified as Greek olives from Kalamata. Twenty-six characteristic authenticity markers were indicated to be responsible for the discrimination of olives of different geographical origins.
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http://dx.doi.org/10.3390/molecules25122919DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355929PMC
June 2020

Sonochemical degradation of trimethoprim in water matrices: Effect of operating conditions, identification of transformation products and toxicity assessment.

Ultrason Sonochem 2020 Oct 22;67:105139. Epub 2020 Apr 22.

Department of Chemical Engineering, University of Patras, Caratheodory 1, University Campus, GR 26504 Patras, Greece. Electronic address:

The sonochemical degradation of trimethoprim (TMP), a widely used antibiotic, in various water matrices was investigated. The effect of several parameters, such as initial TMP concentration (0.5-3 mg/L), actual power density (20-60 W/L), initial solution pH (3-10), inorganic ions, humic acid and water matrix on degradation kinetics was examined. The pseudo-first order degradation rate of TMP was found to increase with increasing power density and decreasing pH, water complexity (ultrapure water > bottled water > secondary wastewater) and initial TMP concentration. TMP degradation is accompanied by the formation of several transformation products (TPs) as evidenced by LC-QToF-MS analysis. Nine such TPs were successfully identified and their time-trend profiles during degradation were followed. An in silico toxicity evaluation was performed showing that several TPs could potentially be more toxic than the parent compound towards Daphnia magna, Pimephales promelas and Pseudokirchneriella subcapitata.
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http://dx.doi.org/10.1016/j.ultsonch.2020.105139DOI Listing
October 2020

Explaining the rationale behind the risk assessment of surfactants by Freeling et al. (2019).

Sci Total Environ 2020 06 25;721:136828. Epub 2020 Jan 25.

TZW: DVGW-Technologiezentrum Wasser (German Water Centre), Karlsruher Str. 84, 76139 Karlsruhe, Germany. Electronic address:

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http://dx.doi.org/10.1016/j.scitotenv.2020.136828DOI Listing
June 2020

Wide-scope target screening of >2000 emerging contaminants in wastewater samples with UPLC-Q-ToF-HRMS/MS and smart evaluation of its performance through the validation of 195 selected representative analytes.

J Hazard Mater 2020 04 18;387:121712. Epub 2019 Nov 18.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15771 Athens, Greece. Electronic address:

This study presents the development and validation of a comprehensive quantitative target methodology for the analysis of 2316 emerging pollutants in water based on Ultra-Performance Liquid Chromatography Quadrupole-Time-Of-Flight Mass Spectrometry (UPLC-Q-ToF-HRMS/MS). Target compounds include pesticides, pharmaceuticals, drugs of abuse, industrial chemicals, doping compounds, surfactants and transformation products, among others. The method was validated for 195 analytes, chosen to be representative of the chemical space of the target list, enabling the assessment of the performance of the method. The method involves a generic sample preparation based on mixed mode solid phase extraction, a UPLC-QTOF-MS/MS screening method using Data Independent Acquisition (DIA) mode, which provides MS and MS/MS spectra simultaneously and an elaborate strong post-acquisition evaluation of the data. The processing method was optimized to provide a successful identification rate >95 % and to minimize the number of false positive results (< 5 %). Decision limit (CCα) and detection capability (CCβ) were also introduced in the validation scheme to provide more realistic metrics on the performance of a HRMS-based wide-scope screening method. A new system of identification points (IPs) based on the one described in the Commission Decision 2002/657/EC was applied to communicate the confidence level in the identification of the analytes. This system considers retention time, mass accuracy, isotopic fit and fragmentation; taking full advantage of the capacities of the HRMS instruments. Finally, 398 contaminants were detected and quantified in real wastewater.
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http://dx.doi.org/10.1016/j.jhazmat.2019.121712DOI Listing
April 2020

Wide-scope target and suspect screening methodologies to investigate the occurrence of new psychoactive substances in influent wastewater from Athens.

Sci Total Environ 2019 Oct 12;685:1058-1065. Epub 2019 Jun 12.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece. Electronic address:

Almost all licit and illicit drugs consumed by the society end up either unchanged or as a mixture of metabolites in the sewage systems. The analysis of influent wastewater samples and the estimation of drug consumption is the field of wastewater-based epidemiology (WBE). A new trend of WBE is the estimation of the consumption of New Psychoactive Substances (NPS), which are legal replacements of established narcotic and psychotropic drugs with slightly modified chemical structures and similar or new effects. To investigate the occurrence of NPS, 30 composite daily influent wastewater samples from the wastewater treatment plant (WWTP) of Athens (Greece) were collected in a four-year sampling campaign (2015-2018). A generic four-sorbent solid-phase extraction (SPE) sample preparation protocol able to retain compounds with wide physicochemical properties was used. Extracts were analyzed by liquid-chromatography coupled to quadrupole-time-of-flight mass spectrometry (LC-QTOF-MS) using target screening for 278 NPS and suspect screening for 451 NPS. Target screening method was validated for a subset of 49 representative NPS and illicit drugs with similar structures with the NPS. 24 NPS and related compounds were detected by target screening and two compounds were tentatively identified based on mass accuracy, prediction of retention time using in-house QSRR prediction models, isotopic pattern and HRMS/MS fragmentation, whereas the excreted mass loads were also calculated. The results indicated an occasional and low occurrence of NPS in wastewater during the week and over the years, whereas the estimation of the exact sources and the evaluation of the patterns in wastewater were critically discussed.
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http://dx.doi.org/10.1016/j.scitotenv.2019.06.173DOI Listing
October 2019

Targeted and Untargeted Metabolomics as an Enhanced Tool for the Detection of Pomegranate Juice Adulteration.

Foods 2019 Jun 14;8(6). Epub 2019 Jun 14.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15771 Athens, Greece.

Pomegranate juice is one of the most popular fruit juices, is well-known as a "superfood", and plays an important role in healthy diets. Due to its constantly growing demand and high value, pomegranate juice is often targeted for adulteration, especially with cheaper substitutes such as apple and red grape juice. In the present study, the potential of applying a metabolomics approach to trace pomegranate juice adulteration was investigated. A novel methodology based on high-resolution mass spectrometric analysis was developed using targeted and untargeted screening strategies to discover potential biomarkers for the reliable detection of pomegranate juice adulteration from apple and red grape juice. Robust classification and prediction models were built with the use of unsupervised and supervised techniques (principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA)), which were able to distinguish pomegranate juice adulteration to a level down to 1%. Characteristic markers were detected, indicating pomegranate juice adulteration, and several marker compounds were identified. The results obtained from this study clearly demonstrate that Mass Spectrometry (MS)-based metabolomics have the potential to be used as a reliable screening tool for the rapid determination of food adulteration.
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http://dx.doi.org/10.3390/foods8060212DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6617410PMC
June 2019

Occurrence and potential environmental risk of surfactants and their transformation products discharged by wastewater treatment plants.

Sci Total Environ 2019 Sep 4;681:475-487. Epub 2019 May 4.

TZW: DVGW-Technologiezentrum Wasser, Karlsruher Str. 84, 76139 Karlsruhe, Germany. Electronic address:

Seven-day composite effluent samples from a German monitoring campaign including 33 conventional wastewater treatment plants (WWTP) were analyzed for linear alkylbenzene sulfonates (LAS) and alkyl ethoxysulfates (AES) and were screened by wide-scope suspect screening for 1564 surfactants and their transformation products (TPs) by UHPLC-ESI-QTOF-MS. Corresponding seven-day composite influent samples of selected WWTPs showed high influent concentrations as well as very high removal rates for LAS and AES. However, average total LAS and AES effluent concentrations were still 14.4 μg/L and 0.57 μg/L, respectively. The LAS-byproducts di-alkyl tetralin sulfonates (DATSs), the TPs sulfophenyl alkyl carboxylic acids (SPACs) and sulfo-tetralin alkyl carboxylic acids (STACs) reached maximum effluent concentrations of 19 μg/L, 17 μg/L and 5.3 μg/L, respectively. In many cases the sum of the concentration of all LAS-related byproducts and TPs surpassed the concentration of the precursors. High concentrations of up to 7.4 μg/L were found for 41 polyethylenoglycol homologs. Quantified surfactants and their TPs and by-products together accounted for concentrations up to 82 μg/L in WWTP effluents. To determine the risk of individual surfactants and their mixtures, single homologs were grouped by a "weighted carbon number approach" to derive normalized Predicted No-Effect Concentrations (PNEC), based on experimental ecotoxicity data from existing risk assessments, complemented by suitable Quantitative Structure-Activity Relationships (QSAR) predictions. Predicted Environmental Concentrations (PEC) were derived by dividing effluent concentrations of surfactants by local dilution factors. Risks for all analyzed surfactants were below the commonly accepted PEC/PNEC ratio of 1 for single compounds, while contributions to mixture toxicity effects from background levels of LAS and DATS cannot be excluded. Maximum LAS concentrations exceeded half of its PNEC, which may trigger country-wide screening to investigate potential environmental risks.
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http://dx.doi.org/10.1016/j.scitotenv.2019.04.445DOI Listing
September 2019

The strength in numbers: comprehensive characterization of house dust using complementary mass spectrometric techniques.

Anal Bioanal Chem 2019 Apr 4;411(10):1957-1977. Epub 2019 Mar 4.

Environment and Climate Change Canada, Ottawa, ON, K1V 1C7, Canada.

Untargeted analysis of a composite house dust sample has been performed as part of a collaborative effort to evaluate the progress in the field of suspect and nontarget screening and build an extensive database of organic indoor environment contaminants. Twenty-one participants reported results that were curated by the organizers of the collaborative trial. In total, nearly 2350 compounds were identified (18%) or tentatively identified (25% at confidence level 2 and 58% at confidence level 3), making the collaborative trial a success. However, a relatively small share (37%) of all compounds were reported by more than one participant, which shows that there is plenty of room for improvement in the field of suspect and nontarget screening. An even a smaller share (5%) of the total number of compounds were detected using both liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS). Thus, the two MS techniques are highly complementary. Most of the compounds were detected using LC with electrospray ionization (ESI) MS and comprehensive 2D GC (GC×GC) with atmospheric pressure chemical ionization (APCI) and electron ionization (EI), respectively. Collectively, the three techniques accounted for more than 75% of the reported compounds. Glycols, pharmaceuticals, pesticides, and various biogenic compounds dominated among the compounds reported by LC-MS participants, while hydrocarbons, hydrocarbon derivatives, and chlorinated paraffins and chlorinated biphenyls were primarily reported by GC-MS participants. Plastics additives, flavor and fragrances, and personal care products were reported by both LC-MS and GC-MS participants. It was concluded that the use of multiple analytical techniques was required for a comprehensive characterization of house dust contaminants. Further, several recommendations are given for improved suspect and nontarget screening of house dust and other indoor environment samples, including the use of open-source data processing tools. One of the tools allowed provisional identification of almost 500 compounds that had not been reported by participants.
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http://dx.doi.org/10.1007/s00216-019-01615-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6458998PMC
April 2019

Development and application of retention time prediction models in the suspect and non-target screening of emerging contaminants.

J Hazard Mater 2019 02 18;363:277-285. Epub 2018 Sep 18.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15771, Athens, Greece. Electronic address:

Hydrophilic interaction liquid chromatography (HILIC) and reversed phase LC (RPLC) coupled to high resolution mass spectrometry (HRMS) are widely used for the identification of suspects and unknown compounds in the environment. For the identification of unknowns, apart from mass accuracy and isotopic fitting, retention time (t) and MS/MS spectra evaluation is required. In this context, a novel comprehensive workflow was developed to study the t behavior of large groups of emerging contaminants using Quantitative Structure-Retention Relationships (QSRR). 682 compounds were analyzed by HILIC-HRMS in positive Electrospray Ionization mode (ESI). Moreover, an extensive dataset was built for RPLC-HRMS including 1830 and 308 compounds for positive and negative ESI, respectively. Support Vector Machines (SVM) was used to model the t data. The applicability domains of the models were studied by Monte Carlo Sampling (MCS) methods. The MCS method was also used to calculate the acceptable error windows for the predicted t from various LC conditions. This paper provides validated models for predicting t in HILIC/RPLC-HRMS platforms to facilitate identification of new emerging contaminants by suspect and non-target HRMS screening, and were applied for the identification of transformation products (TPs) of emerging contaminants and biocides in wastewater and sludge.
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http://dx.doi.org/10.1016/j.jhazmat.2018.09.047DOI Listing
February 2019

Application of an advanced and wide scope non-target screening workflow with LC-ESI-QTOF-MS and chemometrics for the classification of the Greek olive oil varieties.

Food Chem 2018 Aug 21;256:53-61. Epub 2018 Feb 21.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece. Electronic address:

An optimized and validated LC-ESI-QTOF-MS method with an integrated non-target screening workflow was applied in the investigation of the metabolomic profile of 51 Greek monovarietal extra virgin olive oils (EVOOs) from the varieties: Manaki, Ladoelia, Koroneiki, Amfissis, Chalkidikis and Kolovi. Data processing was carried out with the R language and XCMS package. A local database consisting of 1608 compounds naturally occurring in different organs of Olea Europa L. was compiled in order to accelerate the identification workflow. The preliminary examination of the distribution of EVOOs toward their cultivars was achieved by Principal Component Analysis (PCA). Ant Colony Optimization-Random Forest (ACO-RF) was developed to prioritize over 250 features and to establish a classification tree. Apigenin, vanillic acid, luteolin 7-methyl ether and oleocanthal were suggested as the markers responsible for the classification of Greek EVOOs' cultivars.
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http://dx.doi.org/10.1016/j.foodchem.2018.02.101DOI Listing
August 2018

QSAR Study of 17β-HSD3 Inhibitors by Genetic Algorithm-Support Vector Machine as a Target Receptor for the Treatment of Prostate Cancer.

Iran J Pharm Res 2017 ;16(3):966-980

Department of Chemistry, Kazerun Branch, Islamic Azad University, Kazerun, Iran.

The 17β-HSD3 enzyme plays a key role in treatment of prostate cancer and small inhibitors can be used to efficiently target it. In the present study, the multiple linear regression (MLR), and support vector machine (SVM) methods were used to interpret the chemical structural functionality against the inhibition activity of some 17β-HSD3inhibitors. Chemical structural information were described through various types of molecular descriptors and genetic algorithm (GA) was applied to decrease the complexity of inhibition pathway to a few relevant molecular descriptors. Non-linear method (GA-SVM) showed to be better than the linear (GA-MLR) method in terms of the internal and the external prediction accuracy. The SVM model, with high statistical significance (R = 0.938; R = 0.870), was found to be useful for estimating the inhibition activity of 17β-HSD3 inhibitors. The models were validated rigorously through leave-one-out cross-validation and several compounds as external test set. Furthermore, the external predictive power of the proposed model was examined by considering modified R and concordance correlation coefficient values, Golbraikh and Tropsha acceptable model criteria's, and an extra evaluation set from an external data set. Applicability domain of the linear model was carefully defined using Williams plot. Moreover, Euclidean based applicability domain was applied to define the chemical structural diversity of the evaluation set and training set.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5610752PMC
January 2017

Investigating the organic and conventional production type of olive oil with target and suspect screening by LC-QTOF-MS, a novel semi-quantification method using chemical similarity and advanced chemometrics.

Anal Bioanal Chem 2017 Sep 25;409(23):5413-5426. Epub 2017 May 25.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771, Athens, Greece.

The discrimination of organic and conventional production has been a critical topic of public discussion and constitutes a scientific issue. It remains a challenge to establish a correlation between the agronomical practices and their effects on the composition of olive oils, especially the phenolic composition, since it defines their organoleptic and nutritional value. Thus, a liquid chromatography-electrospray ionization-quadrupole time of flight tandem mass spectrometric method was developed, using target and suspect screening workflows, coupled with advanced chemometrics for the identification of phenolic compounds and the discrimination between organic and conventional extra virgin olive oils. The method was optimized by one-factor design and response surface methodology to derive the optimal conditions of extraction (methanol/water (80:20, v/v), pure methanol, or acetonitrile) and to select the most appropriate internal standard (caffeic acid or syringaldehyde). The results revealed that extraction with methanol/water (80:20, v/v) was the optimum solvent system and syringaldehyde 1.30 mg L was the appropriate internal standard. The proposed method demonstrated low limits of detection in the range of 0.002 (luteolin) to 0.028 (tyrosol) mg kg. Then, it was successfully applied in 52 olive oils of Kolovi variety. In total, 13 target and 24 suspect phenolic compounds were identified. Target compounds were quantified with commercially available standards. A novel semi-quantitation strategy, based on chemical similarity, was introduced for the semi-quantification of the identified suspects. Finally, ant colony optimization-random forest model selected luteolin as the only marker responsible for the discrimination, during a 2-year study. Graphical abstract Investigation of the organic and conventional production type of olive oil by LC-QTOF-MS.
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http://dx.doi.org/10.1007/s00216-017-0395-6DOI Listing
September 2017

Prediction of acute toxicity of emerging contaminants on the water flea Daphnia magna by Ant Colony Optimization-Support Vector Machine QSTR models.

Environ Sci Process Impacts 2017 Mar;19(3):438-448

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece.

According to the European REACH Directive, the acute toxicity towards Daphnia magna should be assessed for any industrial chemical with a market volume of more than 1 t/a. Therefore, it is highly recommended to determine the toxicity at a certain confidence level, either experimentally or by applying reliable prediction models. To this end, a large dataset was compiled, with the experimental acute toxicity values (pLC) of 1353 compounds in Daphnia magna after 48 h of exposure. A novel quantitative structure-toxicity relationship (QSTR) model was developed, using Ant Colony Optimization (ACO) to select the most relevant set of molecular descriptors, and Support Vector Machine (SVM) to correlate the selected descriptors with the toxicity data. The proposed model showed high performance (Q = 0.695, R = 0.920 and R = 0.831) with low root mean square errors of 0.498 and 0.707 for the training and test set, respectively. It was found that, in addition to hydrophobicity, polarizability and summation of solute-hydrogen bond basicity affected toxicity positively, while minimum atom-type E-state of -OH influenced toxicity values in Daphnia magna inversely. The applicability domain of the proposed model was carefully studied, considering the effect of chemical structure and prediction error in terms of leverage values and standardized residuals. In addition, a new method was proposed to define the chemical space failure for a compound with unknown toxicity to avoid using these prediction results. The resulting ACO-SVM model was successfully applied on an additional evaluation set and the prediction results were found to be very accurate for those compounds that fall inside the defined applicability domain. In fact, compounds commonly found to be difficult to predict, such as quaternary ammonium compounds or organotin compounds were outside the applicability domain, while five representative homologues of LAS (non-ionic surfactants) were, on average, well predicted within one order of magnitude.
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http://dx.doi.org/10.1039/c6em00679eDOI Listing
March 2017

Olive oil authenticity studies by target and nontarget LC-QTOF-MS combined with advanced chemometric techniques.

Anal Bioanal Chem 2016 Nov 1;408(28):7955-7970. Epub 2016 Sep 1.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimioupolis Zografou, 15771, Athens, Greece.

Food analysis is continuously requiring the development of more robust, efficient, and cost-effective food authentication analytical methods to guarantee the safety, quality, and traceability of food commodities with respect to legislation and consumer demands. Hence, a novel reversed-phase ultra high performance liquid chromatography-electrospray ionization quadrupole time of flight tandem mass spectrometry analytical method was developed that uses target, suspect, and nontarget screening strategies coupled with advanced chemometric tools for the investigation of the authenticity of extra virgin olive oil. The proposed method was successfully applied in real olive oil samples for the identification of markers responsible for the sensory profile. The proposed target analytical method includes the determination of 14 phenolic compounds and demonstrated low limits of detection ranging from 0.015 μg mL (apigenin) to 0.039 μg mL (vanillin) and adequate recoveries (96-107 %). A suspect list of 60 relevant compounds was compiled, and suspect screening was then applied to all the samples. Semiquantitation of the suspect compounds was performed with the calibration curves of target compounds having similar structures. Then, a nontarget screening workflow was applied with the aim to identify additional compounds so as to differentiate extra virgin olive oils from defective olive oils. Robust classification-based models were built with the use of supervised discrimination techniques, partial least squares-discriminant analysis and counterpropagation artificial neural networks, for the classification of olive oils into extra virgin olive oils or defective olive oils. Variable importance in projection scores were calculated to select the most significant features that affect the discrimination. Overall, 51 compounds were identified and suggested as markers, among which 14, 26, and 11 compounds were identified by target, suspect, and nontarget screening respectively. Retrospective analysis was also performed and identified 19 free fatty acids. Graphical Abstract Development of a novel RP-LC-ESI-QTOFMS analytical method employing target, suspect and non-target screening strategies coupled to advanced chemometric tools for the investigation of markers responsible for the sensory profile of extra virgin olive oil and guarantee authenticity.
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http://dx.doi.org/10.1007/s00216-016-9891-3DOI Listing
November 2016

Identification of biotransformation products of citalopram formed in activated sludge.

Water Res 2016 10 14;103:205-214. Epub 2016 Jul 14.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771, Athens, Greece. Electronic address:

Citalopram (CTR) is a worldwide highly consumed antidepressant which has demonstrated incomplete removal by conventional wastewater treatment. Despite its global ubiquitous presence in different environmental compartments, little is known about its behaviour and transformation processes during wastewater treatment. The present study aims to expand the knowledge on fate and transformation of CTR during the biological treatment process. For this purpose, batch reactors were set up to assess biotic, abiotic and sorption losses of this compound. One of the main objectives of the study was the identification of the formed transformation products (TPs) by applying suspect and non-target strategies based on liquid chromatography quadrupole-time-of-flight mass spectrometry (LC-QTOF-MS). The complementary use of reversed phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) for the identification of polar TPs, and the application of in-house developed quantitative structure-retention relationship (QSRR) prediction models, in addition to the comprehensive evaluation of the obtained MS/MS spectra, provided valuable information to support identification. In total, fourteen TPs were detected and thirteen of them were tentatively identified. Four compounds were confirmed (N-desmethylCTR, CTR amide, CTR carboxylic acid and 3-oxo-CTR) through the purchase of the corresponding reference standard. Probable structures based on diagnostic evidence were proposed for the additional nine TPs. Eleven TPs are reported for the first time. A transformation pathway for the biotransformation of CTR was proposed. The presence of the identified TPs was assessed in real wastewater samples through retrospective analysis, resulting in the detection of five compounds. Finally, the potential ecotoxicological risk posed by CTR and its TPs to different trophic levels of aquatic organisms was evaluated by means of risk quotients.
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http://dx.doi.org/10.1016/j.watres.2016.07.029DOI Listing
October 2016

Quantitative Structure-Retention Relationship Models To Support Nontarget High-Resolution Mass Spectrometric Screening of Emerging Contaminants in Environmental Samples.

J Chem Inf Model 2016 07 17;56(7):1384-98. Epub 2016 Jun 17.

Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens , Panepistimiopolis Zografou, 15771 Athens, Greece.

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http://dx.doi.org/10.1021/acs.jcim.5b00752DOI Listing
July 2016
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