Approaches to determine pesticides in marine bivalves.

Due to agricultural runoff, pesticides end up in aquatic ecosystems and some accumulate in marine bivalves. As filter feeders, bivalves can accumulate high concentrations of chemicals in their tissue representing a potential risk to the health of human and aquatic ecosystems. So far, most of the studies dealing with pesticide contamination in marine bivalves, for example, in the French Atlantic and English Channel coasts, have focused on the old generation of pesticides. Only a few investigated the newly emerging pesticides partly due to methodological challenges. A better understanding of the most sensitive and reliable methods is thus essential for accurately determining a wide variety of environmentally relevant pesticides in marine bivalves. The review highlighted the use of more environmentally friendly and efficient materials such as sorbents and the "quick easy cheap effective rugged safe" extraction procedure to extract pesticides from bivalve matrices, as they appeared to be the most efficient while being the safest. Moreover, this method combined with the high-resolution mass spectrometry (MS) technique offers promising perspectives by highlighting a wide range of pesticides including those that are not usually sought. Finally, recent developments in the field of ultra-high-performance liquid chromatography coupled to MS, such as two-dimensional chromatography and ion mobility spectrometry, will improve the analysis of pesticides in complex matrices.

Monitoring and factors affecting levels of airborne and water bromoform in chlorinated seawater swimming pools.

Water and air quality of eight seawater swimming pools using chlorine disinfection was measured during four sampling campaigns, spread on one full-year, and in four thalassotherapy centers located in Southeast of France. Concentrations of trihalomethanes (THMs) in air and in water as well as concentrations of parameters, including nonpurgeable organic carbon (NPOC), free residual chlorine (Clf), pH, Kjeldhal Nitrogen (KN), salinity, conductivity, bromide ions and, water and air temperature, were measured. Water and air samples were collected in triplicates morning - at the opening of the pools -, noon and night - at the closing of the pools -, in summer and winter. Data analysis was performed by Principal Component Analysis (PCA) and rotated component matrix, from both data quality and other parameters such as TOC, aromaticity (UV254), pH, hygrometry, and free residual chlorine (Clf). This statistical analysis demonstrates a high correlation between TOC, Clf and UV254 and THM levels found in air and water, particularly for the major ones (CHBr3 in water: 300.0µg/L mean, 1029.0µg/L maximum; CHBr3 in air: 266.1µg/m3 mean, 1600.0µg/m3 maximum, and CHClBr2 in water: 18.9µg/L mean, 81.0µg/L maximum; CHClBr2 in air: 13.6µg/m3 mean, 150.0µg/m3 maximum). These high levels of bromoform (CHBr3) are particularly worrisome in such health institutions, even these levels do not exceed the Permissible Exposure Limit (PEL) of 5mg/m3 as an 8hour time-weighted average currently fixed by various administrations, such as Occupational Safety and Health Administration (OSHA).

Insights into Mechanistic Models for Evaporation of Organic Liquids in the Environment Obtained by Position-Specific Carbon Isotope Analysis.

Position-specific isotope effects (PSIEs) have been measured by isotope ratio monitoring (13)C nuclear magnetic resonance spectrometry during the evaporation of 10 liquids of different polarities under 4 evaporation modes (passive evaporation, air-vented evaporation, low pressure evaporation, distillation). The observed effects are used to assess the validity of the Craig-Gordon isotope model for organic liquids. For seven liquids the overall isotope effect (IE) includes a vapor-liquid contribution that is strongly position-specific in polar compounds but less so in apolar compounds and a diffusive IE that is not position-specific, except in the alcohols, ethanol and propan-1-ol. The diffusive IE is diminished under forced evaporation. The position-specific isotope pattern created by liquid-vapor IEs is manifest in five liquids, which have an air-side limitation for volatilization. For the alcohols, undefined processes in the liquid phase create additional PSIEs. Three other liquids with limitations on the liquid side have a lower, highly position-specific, bulk diffusive IE. It is concluded that evaporation of organic pollutants creates unique position-specific isotope patterns that may be used to assess the progress of remediation or natural attenuation of pollution and that the Craig-Gordon isotope model is valid for the volatilization of nonpolar organic liquids with air-side limitation of the volatilization rate.

Fate of chlordecone during home cooking processes - Transfer into the liquid and aerial phases by conventional thermal processes.

This study focuses on the fate of chlordecone (CLD) during cooking processes. Neat CLD was subjected to thermogravimetric analysis, which revealed that the vast majority of the compound (79 %) was vaporised at temperatures between 55 and 245 °C. In order to monitor the behaviour of CLD during cooking processes, a QuEChERS extraction protocol was optimised for vegetable cooking oil and a heating kinetics experiment was conducted at 195 °C on CLD-spiked cooking oil. The results showed a strong decrease in CLD over time and, for the first time to our knowledge, transformation of CLD into chlordecol. Finally, a comparison was conducted between the cooking of uncured pork with and without vegetable oil. The use of vegetable oil led to a significant decrease in CLD content, but revealed that a fraction of the CLD transferred into the cooking oil. This study provides data that shed light on the fate of CLD during cooking.

Optimization of an HPLC-MS/MS method to analyze chlordecone in bovine serum and correlations with levels in liver, muscle and fat.

Chlordecone is an organochlorine pesticide used from 1972 to 1993 in the French West Indies. Its extensive use and high persistence in soils induced massive contamination of the environment and of the food chain, especially in cattle through contaminated soil ingestion. To ensure suitability for consumption of bovine meat, monitoring plans are set up based on perirenal fat concentrations after slaughtering. In the present study, we have investigated an in-vivo monitoring approach by measuring chlordecone levels in serum samples. For this purpose, a sensitive high-performance liquid-chromatography-tandem mass spectrometry (HPLC-MS/MS) method following a QuEChERS extraction method was successfully optimized and validated, reaching a limit of quantification of 0.05 ng g-1 fresh weight. This method was applied to 121 serum samples collected from bovines originating from contaminated areas of Martinique and Guadeloupe. Chlordecone was detected in 88% of the samples, and quantified in 77% of the samples, with concentrations ranging from 0.05 to 22 ng g-1. Perirenal fat, liver, and muscle were also sampled on the same animals and the measured concentrations of chlordecone were statistically correlated to the levels determined in serum. Mean concentration ratios of 6.5 for fat/serum, 27.5 for liver/serum, and 3.3 for muscle/serum were calculated, meaning that chlordecone was not only distribute in fat (as expected), muscle and liver, but also in serum. Good correlations were found to allow prediction of chlordecone concentrations in muscle based on concentrations measured in serum. This study opens the door to possible pre-control of bovines before slaughter. In cases of probable non-compliance with maximum residue levels (MRLs), farm management could proceed to allow for depuration under controlled conditions. This would have a strong impact on both economic and food safety management measures.

Microwave-enhanced thermal removal of organochlorine pesticide (chlordecone) from contaminated soils.

Soil contamination with chlordecone, an organochlorine pesticide, is causing serious health problems, affecting crop production and local livestock valorization in the French West Indies. In-situ chemical reduction (ISCR) processes for soil remediation have shown promise but need improvement in terms of time, cost and effective treatment, particularly for andosol soil types. Our study shows that a 10-min microwave treatment significantly reduces chlordecone concentrations (50-90%) in contaminated andosol and nitisol soils. Dry andosol soils show the highest removal yields and reach a higher final temperature (350 °C). Microwave treatment is in all cases more effective or at least as effective as 60 min of conventional heating at a target temperature of 200 °C. The thermal response of andosol and nitisol to microwave exposure is different, as the former is likely to undergo thermal runaway, reaching high temperatures in a short time, resulting in highly efficient thermal removal of chlordecone. These results encourage further scale-up, particularly for the treatment of andosol soils due to their strong microwave response.

Chlordecone-induced hepatotoxicity and fibrosis are mediated by the proteasomal degradation of septins.

Chlordecone (CLD) is a pesticide persisting in soils and contaminating food webs. CLD is sequestered in the liver and poorly metabolized into chlordecol (CLDOH). In vitro liver cell models were used to investigate the fate and mechanistic effects of CLD and CLDOH using multiomics. A 3D-cell model was used to investigate whether CLD and CLDOH can affect susceptibility to the metabolic dysfunction-associated steatotic liver disease (MASLD). Hepatocytes were more sensitive to CLD than CLDOH. CLDOH was intensively metabolized into a glucuronide conjugate, whereas CLD was sequestered. CLD but not CLDOH induced a depletion of Septin-2,- 7,- 9,- 10,- 11 due to proteasomal degradation. Septin binding with CLD and CLDOH was confirmed by surface plasmon resonance. CLD disrupted lipid droplet size and increased saturated long-chain dicarboxylic acid production by inhibiting stearoyl-CoA desaturase (SCD) abundance. Neither CLD nor CLDOH induced steatosis, but CLD induced fibrosis in the 3D model of MASLD. To conclude, CLD hepatoxicity is specifically driven by the degradation of septins. CLDOH, was too rapidly metabolized to induce septin degradation. We show that the conversion of CLD to CLDOH reduced hepatotoxicity and fibrosis in liver organoids. This suggests that protective strategies could be explored to reduce the hepatotoxicity of CLD.

Innovative analytical methodologies for characterizing chemical exposure with a view to next-generation risk assessment.

The chemical burden on the environment and human population is increasing. Consequently, regulatory risk assessment must keep pace to manage, reduce, and prevent adverse impacts on human and environmental health associated with hazardous chemicals. Surveillance of chemicals of known, emerging, or potential future concern, entering the environment-food-human continuum is needed to document the reality of risks posed by chemicals on ecosystem and human health from a one health perspective, feed into early warning systems and support public policies for exposure mitigation provisions and safe and sustainable by design strategies. The use of less-conventional sampling strategies and integration of full-scan, high-resolution mass spectrometry and effect-directed analysis in environmental and human monitoring programmes have the potential to enhance the screening and identification of a wider range of chemicals of known, emerging or potential future concern. Here, we outline the key needs and recommendations identified within the European Partnership for Assessment of Risks from Chemicals (PARC) project for leveraging these innovative methodologies to support the development of next-generation chemical risk assessment.

Modelling geosmin concentrations in three sources of raw water in Quebec, Canada.

The presence of off-flavour compounds such as geosmin, often found in raw water, significantly reduces the organoleptic quality of distributed water and diverts the consumer from its use. To adapt water treatment processes to eliminate these compounds, it is necessary to be able to identify them quickly. Routine analysis could be considered a solution, but it is expensive and delays associated with obtaining the results of analysis are often important, thereby constituting a serious disadvantage. The development of decision-making tools such as predictive models seems to be an economic and feasible solution to counterbalance the limitations of analytical methods. Among these tools, multi-linear regression and principal component regression are easy to implement. However, due to certain disadvantages inherent in these methods (multicollinearity or non-linearity of the processes), the use of emergent models involving artificial neurons networks such as multi-layer perceptron could prove to be an interesting alternative. In a previous paper (Parinet et al., Water Res 44: 5847-5856, 2010), the possible parameters that affect the variability of taste and odour compounds were investigated using principal component analysis. In the present study, we expand the research by comparing the performance of three tools using different modelling scenarios (multi-linear regression, principal component regression and multi-layer perceptron) to model geosmin in drinking water sources using 38 microbiological and physicochemical parameters. Three very different sources of water, in terms of quality, were selected for the study. These sources supply drinking water to the Québec City area (Canada) and its vicinity, and were monitored three times per month over a 1-year period. Seven different modelling methods were tested for predicting geosmin in these sources. The comparison of the seven different models showed that simple models based on multi-linear regression provide sufficient predictive capacity with performance levels comparable to those obtained with artificial neural networks. The multi-linear regression model (R(2) = 0.657, <0.001) used only four variables (phaeophytin, sum of green algae, chlorophyll-a and potential Redox) in comparison with ten variables (potassium, heterotrophic bacteria, organic nitrogen, total nitrogen, phaeophytin, total organic carbon, sum of green algae, potential Redox, UV absorbance at 254 nm and atypical bacteria) for the best model obtained with artificial neural networks (R(2) = 0.843).

Wide-scope screening of multi-class contaminants in seafood using a novel sample preparation (QuEChUP) procedure coupled with UHPLC-Q-TOF-MS: Application for semi-quantitation of real seafood samples.

A high-resolution mass spectrometry screening method was developed and validated based on EU SANTE/11312/2021 guidelines for the analysis of 850 multi-class contaminants in commercial seafood samples. Samples were extracted using a novel sequential QuEChUP preparation method that combines the QuEChERS and QuPPe procedures. The screening detection limits (SDLs) and limits of identification (LOIs) were equal to or lower than 0.01 mg·kg-1 for 92% and 78% of contaminants, respectively. This screening procedure was ultimately applied for a target screening analysis of 24 seafood samples. The concentrations of identified contaminants were assessed using semi-quantitative approach. Two identified contaminants, diuron and diclofenac, showed the highest estimated average concentrations: 0.076 and 0.068 mg·kg-1 respectively in mussel samples. Suspect screening was also performed. Target and suspect screening led to the identification of mixtures of contaminants (pesticides, veterinary products, industrial chemicals and personal care products) and the assessment of their frequencies of appearance (FoA).

Optimisation and implementation of QuEChERS-based sample preparation for identification and semi-quantification of 694 targeted contaminants in honey, jam, jelly, and syrup by UHPLC-Q/ToF high-resolution mass spectrometry.

A screening and semi-quantitative method was developed for the analysis of 694 various contaminants in honey, jam, jelly and syrup samples by ultrahigh-performance liquid chromatography and quadrupole time-of-flight mass spectrometry. Sample preparation, which was optimised using split factorial design, was based on acetate-buffered version of QuEChERS, followed by a clean-up step and a concentration step to enhance sensitivity of analytes. The method was validated according to SANTE/11312/2021 guidelines. The screening detection and limits of identification were established as being less than or equal to 0.05 mg.kg-1 for 89% and 74% of the contaminants, respectively. The validated screening method was applied to 50 concentrated sugary products. Overall, 46% of the samples were positive to pesticide residues. Most of the positive samples (78%) contained mixtures of pesticide residues. Three time-and-cost saving convenient strategies suitable for high-throughput analysis were proposed for the targeted semi-quantification of the previously contaminants identified in samples.

Towards comprehensive identification of pesticide degradation products following thermal processing below and above 120 °C: A review.

Characterising pesticide residues from a qualitative and quantitative point of view is key to both risk assessment in the framework of pesticide approval and risk management. In the European Union (EU), these concerns are addressed during the evaluation of active substances at the European level prior to marketing authorisation. In the framework of this review, we will focus on one specific item of the residue section, namely the effect of process (industrial or domestic transformation of the raw commodities) on the nature of the residue in food. A limited number of hydrolysis conditions defined by three parameters (temperature, pH and time) are set to be "representative of the most widely used industrial and domestic food processing technologies". These hydrolysis conditions, however, do not cover processes at temperatures higher than 120 °C, such as cooking with a conventional oven or in a pan, frying or using a microwave oven.

Seasonal variations of low pesticides contamination and biomarker responses in marine bivalves from French estuaries.

Biomarkers involved in detoxification process (GST), oxidative stress (SOD and MDA), immune response (Laccase) and neurotoxic disorders (AChE) were analysed in Pacific oysters and blue mussels collected from 4 locations within the Pertuis sea (France). Seasonal variations of total pesticide mean concentrations were found in seawater with metolachlor being the main pesticide measured (up to 32 ng/L). The majority of pesticide concentrations in sediment were below the LOD. Seasonal contamination differences were evidenced for chlortoluron, especially in mussels where concentrations reached 16 ng/g (wet weight) during the winter, in the Charente estuary, but no relationships with any of the biomarkers selected arisen. Actually, low concentrations of alpha-, beta-BHC and alachlor were correlated to GST activity, and low levels of hexachlorobenzene were linked to the AChE activity and MDA content in oysters. In mussels, low concentrations of methylparathion, parathion and beta-BHC were correlated to laccase.

Improving the monitoring of multi-class pesticides in baby foods using QuEChERS-UHPLC-Q-TOF with automated identification based on MS/MS similarity algorithms.

A screening method was developed for the multi-residue analysis of pesticides in baby foods using QuEChERS and UHPLC-Q-TOF. For sample preparation, the two-buffered versions of QuEChERS and different purification procedures were studied. False negatives and false positives were determined using different thresholds mentioned in the literature on the retention time and accurate mass measurement detection criteria. To reach unequivocal identification, the fragmentation spectra of the pesticides were used. The information-dependant-acquisition (IDA) mode was optimized with a precursor-inclusion list (PIL) to limit the loss of MS/MS data. Then, the experimental fragmentation spectra were compared to those included in a homemade library, by assessing different MS/MS algorithms and similarity scores. The optimised method was validated according to SANTE/11312/2021 guidelines. 95% and 73% of the pesticides presented a screening detection limit (SDL) and a limit of identification (LOI) ≤ 0.1 mg.kg-1. One plasticizer was found in the investigated samples by a suspect-screening approach.

Development and validation according to the SANTE guidelines of a QuEChERS-UHPLC-QTOF-MS method for the screening of 204 pesticides in bivalves.

A qualitative screening high resolution mass spectrometry method was developed and validated according to the EU SANTE/12682/2019 guidelines for the analysis of 204 pesticides in seven commercial bivalve species spiked at three concentrations (0.01, 0.05 and, 0.1 mg.kg-1). Samples were extracted using QuEChERS and analysed using ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. The QuEChERS method was optimised by the Taguchi Orthogonal Array approach. The best conditions were obtained with pure ACN, MgSO4/NaCl as extraction salts, MgSO4/PSA/C18 as clean-up, and the non-dilution of extracts. The impact of different HRMS acquisition modes on detection and identification rates were also evaluated. The screening detection limits were determined to be 0.01 mg.kg-1 and 0.1 for 66% and 87% of pesticides, respectively. These screening procedure was finally applied to different bivalve samples using target and suspect analysis. This allowed the identification of diuron and its metabolite 1-(3,4-dichlorophenyl)-3-methylurea in the investigated samples.

Predicting reversed-phase liquid chromatographic retention times of pesticides by deep neural networks.

To be able to predict reversed phase liquid chromatographic (RPLC) retention times of contaminants is an asset in order to solve food contamination issues. The development of quantitative structure-retention relationship models (QSRR) requires selection of the best molecular descriptors and machine-learning algorithms. In the present work, two main approaches have been tested and compared, one based on an extensive literature review to select the best set of molecular descriptors (16), and a second with diverse strategies in order to select among 1545 molecular descriptors (MD), 16 MD. In both cases, a deep neural network (DNN) were optimized through a gridsearch.

Prediction of pesticide retention time in reversed-phase liquid chromatography using quantitative-structure retention relationship models: A comparative study of seven molecular descriptors datasets.

Predicting chromatographic retention times of pesticides has become more and more important for suspect and non-target screening. Indeed, high-resolution mass spectrometry hyphenated (HRMS) to liquid chromatography (LC) are of growing interest for research and monitoring of pesticides, their metabolites and transformation products. The development of quantitative structure-retention relationship models require selecting the most adequate and best set of molecular descriptors and the best machine-learning algorithm. Here, we used seven molecular descriptor sets extracted from four well-known studies and applied them to roughly 800 pesticides and their chromatographic reversed-phase retention times. We used and optimized five different machine-learning algorithms with these descriptor sets to carry out predictions. Our results show that a support-vector machine regression algorithm with only eight molecular descriptors gave the best compromise between the number of molecular descriptors, processing time and model complexity to optimize prediction performance for this specific gradient LC method.

Correlation between endemic chlordecone concentrations in three bovine tissues determined by isotopic dilution liquid chromatography-tandem mass spectrometry.

Chlordecone (CLD) is an organochlorine pesticide widely used from the 1970s to the 1990s in the French West Indies that induced long-term pollution of the ecosystem. Due to involuntary soil ingestion, some species bred in open-air areas can be contaminated. As CLD is distributed in various tissues depending on the breeding species, this study focuses on the distribution of CLD in bovines. For this purpose, three tissues, i.e. fat, muscle, and liver, from 200 bovines originating from Martinique and Guadeloupe were sampled in 2016 to determine their endemic contamination levels. Analyses were performed with the official method for veterinary controls, isotopic dilution liquid chromatography-tandem mass spectrometry, which has been fully validated and which reaches a limit of quantification of 3 µg.kg-1 fresh weight (fw). Irrespective of the matrices, CLD was detected in 68% of samples (404 samples above the LOD) and quantified in 59% of samples (332 samples above the LOQ). Regarding contamination levels, the liver had a broader range of concentrations (LOQ up to 420.6 µg.kg-1 fw) than fat (LOQ up to 124.6 µg.kg-1 fw) and muscle (LOQ up to 67.6 µg.kg-1 fw). This confirms the atypical behaviour of CLD compared to other persistent organochlorine pollutants. Statistical processing demonstrated a correlation between CLD concentrations among the three studied tissues. The CLD concentration ratios were 0.54 for muscle/fat, 3.75 for liver/fat, and 0.14 for muscle/liver.

Characterization and quantification of chlordecone elimination in ewes.

To reduce the exposure of the French West Indies population to the organochlorine insecticide chlordecone (Kepone; CLD), the contamination of currently consumed foodstuffs must be reduced. Depuration of contaminated animals before slaughter could be a strategy to obtain safe animal products. The aim of this study was to characterize and quantify CLD elimination in contaminated ewes during depuration process. Experiments A and B consisted in a single intravenous (i.v.) administration of CLD (n = 5) and CLDOH (chlordecol; n = 3) followed by a 84-d and 3-d depuration period respectively with collection of blood, faeces and urine samples. After CLD administration, CLD and conjugated-CLDOH (CLDOH-C) were quantified in serum and urine and CLD and CLDOH were quantified in faeces. Based on calculations of faecal, urinary and body clearances of CLD and CLDOH-C, faeces appeared as the major route of CLD excretion with 86 % of the CLD administered dose eliminated in faeces, either as CLD (51 %) or as CLDOH (35 %).

Multilaboratory Collaborative Study of a Nontarget Data Acquisition for Target Analysis (nDATA) Workflow Using Liquid Chromatography-High-Resolution Accurate Mass Spectrometry for Pesticide Screening in Fruits and Vegetables.

Nontarget data acquisition for target analysis (nDATA) workflows using liquid chromatography-high-resolution accurate mass (LC-HRAM) spectrometry, spectral screening software, and a compound database have generated interest because of their potential for screening of pesticides in foods. However, these procedures and particularly the instrument processing software need to be thoroughly evaluated before implementation in routine analysis. In this work, 25 laboratories participated in a collaborative study to evaluate an nDATA workflow on high moisture produce (apple, banana, broccoli, carrot, grape, lettuce, orange, potato, strawberry, and tomato). Samples were extracted in each laboratory by quick, easy, cheap, effective, rugged, and safe (QuEChERS), and data were acquired by ultrahigh-performance liquid chromatography (UHPLC) coupled to a high-resolution quadrupole Orbitrap (QOrbitrap) or quadrupole time-of-flight (QTOF) mass spectrometer operating in full-scan mass spectrometry (MS) data-independent tandem mass spectrometry (LC-FS MS/DIA MS/MS) acquisition mode. The nDATA workflow was evaluated using a restricted compound database with 51 pesticides and vendor processing software. Pesticide identifications were determined by retention time (tR, ±0.5 min relative to the reference retention times used in the compound database) and mass errors (δM) of the precursor (RTP, δM ≤ ±5 ppm) and product ions (RTPI, δM ≤ ±10 ppm). The elution profiles of all 51 pesticides were within ±0.5 min among 24 of the participating laboratories. Successful screening was determined by false positive and false negative rates of <5% in unfortified (pesticide-free) and fortified (10 and 100 µg/kg) produce matrices. Pesticide responses were dependent on the pesticide, matrix, and instrument. The false negative rates were 0.7 and 0.1% at 10 and 100 µg/kg, respectively, and the false positive rate was 1.1% from results of the participating LC-HRAM platforms. Further evaluation was achieved by providing produce samples spiked with pesticides at concentrations blinded to the laboratories. Twenty-two of the 25 laboratories were successful in identifying all fortified pesticides (0-7 pesticides ranging from 5 to 50 µg/kg) for each produce sample (99.7% detection rate). These studies provide convincing evidence that the nDATA comprehensive approach broadens the screening capabilities of pesticide analyses and provide a platform with the potential to be easily extended to a larger number of other chemical residues and contaminants in foods.