Exploring the Chemical Space of the Exposome: How Far Have We Gone?

Around two-thirds of chronic human disease can not be explained by genetics alone. The Lancet Commission on Pollution and Health estimates that 16% of global premature deaths are linked to pollution. Additionally, it is now thought that humankind has surpassed the safe planetary operating space for introducing human-made chemicals into the Earth System. Direct and indirect exposure to a myriad of chemicals, known and unknown, poses a significant threat to biodiversity and human health, from vaccine efficacy to the rise of antimicrobial resistance as well as autoimmune diseases and mental health disorders. The exposome chemical space remains largely uncharted due to the sheer number of possible chemical structures, estimated at over 1060 unique forms. Conventional methods have cataloged only a fraction of the exposome, overlooking transformation products and often yielding uncertain results. In this Perspective, we have reviewed the latest efforts in mapping the exposome chemical space and its subspaces. We also provide our view on how the integration of data-driven approaches might be able to bridge the identified gaps.

Exploring the chemical subspace of RPLC: A data driven approach.

BACKGROUND: The chemical space is comprised of a vast number of possible structures, of which an unknown portion comprises the human and environmental exposome. Such samples are frequently analyzed using non-targeted analysis via liquid chromatography (LC) coupled to high-resolution mass spectrometry often employing a reversed phase (RP) column. However, prior to analysis, the contents of these samples are unknown and could be comprised of thousands of known and unknown chemical constituents. Moreover, it is unknown which part of the chemical space is sufficiently retained and eluted using RPLC. RESULTS: We present a generic framework that uses a data driven approach to predict whether molecules fall 'inside', 'maybe' inside, or 'outside' of the RPLC subspace. Firstly, three retention index random forest (RF) regression models were constructed that showed that molecular fingerprints are able to predict RPLC retention behavior. Secondly, these models were used to set up the dataset for building an RPLC RF classification model. The RPLC classification model was able to correctly predict whether a chemical belonged to the RPLC subspace with an accuracy of 92% for the testing set. Finally, applying this model to the 91 737 small molecules (i.e., ≤1 000 Da) in NORMAN SusDat showed that 19.1% fall 'outside' of the RPLC subspace. SIGNIFICANCE AND NOVELTY: The RPLC chemical space model provides a major step towards mapping the chemical space and is able to assess whether chemicals can potentially be measured with an RPLC method (i.e., not every RPLC method) or if a different selectivity should be considered. Moreover, knowing which chemicals are outside of the RPLC subspace can assist in reducing potential candidates for library searching and avoid screening for chemicals that will not be present in RPLC data.

Apportioning sources of chemicals of emerging concern along an urban river with inverse modelling.

Concentrations of chemicals in river water provide crucial information for assessing environmental exposure and risks from fertilisers, pesticides, heavy metals, illicit drugs, pathogens, pharmaceuticals, plastics and perfluorinated substances, among others. However, using concentrations measured along waterways (e.g., from grab samples) to identify sources of contaminants and understand their fate is complicated by mixing of chemicals downstream from diverse diffuse and point sources (e.g., agricultural runoff, wastewater treatment plants). To address this challenge, a novel inverse modelling approach is presented. Using waterway network topology, it quantifies locations and concentrations of contaminant sources upstream by inverting concentrations measured in water samples. It is computationally efficient and quantifies uncertainty. The approach is demonstrated for 13 contaminants of emerging concern (CECs) in an urban stream, the R. Wandle (London, UK). Mixing (the forward problem) was assumed to be conservative, and the location of sources and their concentrations were treated as unknowns to be identified. Calculated CEC source concentrations, which ranged from below detection limit (a few ng/L) up to 1µg/L, were used to predict concentrations of chemicals downstream. Using this approach, >90% of data were predicted within observational uncertainty. Principal component analysis of calculated source concentrations revealed signatures of two distinct chemical sources. First, pharmaceuticals and insecticides were associated with a subcatchment containing a known point source of treated effluent from a wastewater treatment plant. Second, illicit drugs and salicylic acid were associated with multiple sources, interpreted as input from untreated sewage including Combined Sewer Overflows (CSOs), misconnections, runoff and direct disposal throughout the catchment. Finally, a simple algorithmic approach that incorporates network topology was developed to design sampling campaigns to improve resolution of source apportionment. Inverse modelling of contaminant measurements can provide objective means to apportion sources in waterways from spot samples in catchments on a large scale.

Down-the-drain pathways for fipronil and imidacloprid applied as spot-on parasiticides to dogs: Estimating aquatic pollution.

Fipronil and imidacloprid have been widely detected in UK surface waters in recent years, often at concentrations that ecotoxicological studies have shown can harm aquatic life. Down-the-drain (DTD) passage of pet flea and tick treatments are being implicated as an important source, with many of the UK's 22 million cats and dogs receiving routine, year-round preventative doses containing these parasiticides. The UK Water Industry's 3rd Chemical Investigation Programme (UKWIR CIP3) has confirmed wastewater as a major entry pathway for these chemicals into surface waters, but the routes by which they enter the wastewater system remain unclear. We addressed this knowledge gap by conducting the first quantification of DTD emissions from 98 dogs treated with spot-on ectoparasiticides containing fipronil or imidacloprid, through bathing, bed washing and washing of owners' hands. Both chemicals were detected in 100 % of washoff samples, with bathing accounting for the largest emissions per event (up to 16.8 % of applied imidacloprid and 24.5 % of applied fipronil). Modelled to account for the frequency of emitting activities, owner handwashing was identified as the largest source of DTD emissions from the population overall, with handwash emissions occurring for at least 28 days following product application and an estimated 4.9 % of imidacloprid and 3.1 % of fipronil applied in dog spot-ons passing down-the-drain via this route. The normalised daily per capita emissions for all routes combined were 8.7 µg/person/day for imidacloprid and 2.1 µg/person/day for fipronil, equivalent to 20-40 % of the daily per capita load in wastewater, as estimated from UKWIR CIP3 data. Within the current international regulatory framework adhered to by the UK, the environmental exposure of veterinary medicines intended for use in small companion animals is assumed to be low, and DTD pathways are not considered. We recommend a systematic review of regulations and practices to address this overlooked pollution pathway.

Advancing Alzheimer's Therapeutics: Exploring the Impact of Physical Exercise in Animal Models and Patients.

Alzheimer's disease (AD) is the main neurodegenerative disorder characterized by several pathophysiological features, including the misfolding of the tau protein and the amyloid beta (Aß) peptide, neuroinflammation, oxidative stress, synaptic dysfunction, metabolic alterations, and cognitive impairment. These mechanisms collectively contribute to neurodegeneration, necessitating the exploration of therapeutic approaches with multiple targets. Physical exercise has emerged as a promising non-pharmacological intervention for AD, with demonstrated effects on promoting neurogenesis, activating neurotrophic factors, reducing Aß aggregates, minimizing the formation of neurofibrillary tangles (NFTs), dampening inflammatory processes, mitigating oxidative stress, and improving the functionality of the neurovascular unit (NVU). Overall, the neuroprotective effects of exercise are not singular, but are multi-targets. Numerous studies have investigated physical exercise's potential in both AD patients and animal models, employing various exercise protocols to elucidate the underlying neurobiological mechanisms and effects. The objective of this review is to analyze the neurological therapeutic effects of these exercise protocols in animal models and compare them with studies conducted in AD patients. By translating findings from different approaches, this review aims to identify opportune, specific, and personalized therapeutic windows, thus advancing research on the use of physical exercise with AD patients.

A One-Health environmental risk assessment of contaminants of emerging concern in London's waterways throughout the SARS-CoV-2 pandemic.

The SARS-CoV-2 pandemic had huge impacts on global urban populations, activity and health, yet little is known about attendant consequences for urban river ecosystems. We detected significant changes in occurrence and risks from contaminants of emerging concern (CECs) in waterways across Greater London (UK) during the pandemic. We were able to rapidly identify and monitor large numbers of CECs in n = 390 samples across 2019-2021 using novel direct-injection liquid chromatography-mass spectrometry methods for scalable targeted analysis, suspect screening and prioritisation of CEC risks. A total of 10,029 measured environmental concentrations (MECs) were obtained for 66 unique CECs. Pharmaceutical MECs decreased during lockdown in 2020 in the R. Thames (p ≤ 0.001), but then increased significantly in 2021 (p ≤ 0.01). For the tributary rivers, the R. Lee, Beverley Brook, R. Wandle and R. Hogsmill were the most impacted, primarily via wastewater treatment plant effluent and combined sewer overflows. In the R. Hogsmill in particular, pharmaceutical MEC trends were generally correlated with NHS prescription statistics, likely reflecting limited wastewater dilution. Suspect screening of âˆ¼ 1,200 compounds tentatively identified 25 additional CECs at the five most impacted sites, including metabolites such as O-desmethylvenlafaxine, an EU Watch List compound. Lastly, risk quotients (RQs) ≥ 0.1 were calculated for 21 compounds across the whole Greater London freshwater catchment, of which seven were of medium risk (RQ ≥ 1.0) and three were in the high-risk category (RQ ≥ 10), including imidacloprid (RQ = 19.6), azithromycin (15.7) and diclofenac (10.5). This is the largest spatiotemporal dataset of its kind for any major capital city globally and the first for Greater London, representing âˆ¼ 16 % of the population of England, and delivering a foundational One-Health case study in the third largest city in Europe across a global pandemic.

International Comparison, Risk Assessment, and Prioritisation of 26 Endocrine Disrupting Compounds in Three European River Catchments in the UK, Ireland, and Spain.

Endocrine-disrupting compounds (EDCs) constitute a wide variety of chemistries with diverse properties that may/can pose risks to both humans and the environment. Herein, a total of 26 compounds, including steroids, flame retardants, and plasticizers, were monitored in three major and heavily urbanized river catchments: the R. Liffey (Ireland), the R. Thames (UK), and the R. Ter (Spain), by using a single solid-phase extraction liquid chromatography-mass spectrometry (SPE-LC-MS/MS) method. Occurrence and frequency rates were investigated across all locations over a 10-week period, with the highest concentration obtained for the flame retardant tris(2-chloroethyl) phosphate (TCEP) at 4767 ng∙L-1 in the R. Thames in Central London. Geographical variations were observed between sites and were partially explained using principal component analysis (PCA) and hierarchical cluster analysis (HCA). In particular, discrimination between the R. Ter and the R. Thames was observed based on the presence and concentration of flame retardants, benzotriazole, and steroids. Environmental risk assessment (ERA) across sites showed that caffeine, a chemical marker, and bisphenol A (BPA), a plasticizer, were classified as high-risk for the R. Liffey and R. Thames, based on relative risk quotients (rRQs), and that caffeine was classified as high-risk for the R. Ter, based on RQs. The total risks at each location, namely ΣRQriver, and ΣrRQriver, were: 361, 455, and 723 for the rivers Liffey, Thames, and Ter, respectively. Caffeine, as expected, was ubiquitous in all 3 urban areas, though with the highest RQ observed in the R. Ter. High contributions of BPA were also observed across the three matrices. Therefore, these two compounds should be prioritized independently of location. This study represents a comprehensive EDC monitoring comparison between different European cities based on a single analytical method, which allowed for a geographically independent ERA prioritization to be performed.

Effects of Voluntary Physical Exercise on the Neurovascular Unit in a Mouse Model of Alzheimer's Disease.

Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide. Histopathologically, AD presents two pathognomonic hallmarks: (1) neurofibrillary tangles, characterized by intracellular deposits of hyperphosphorylated tau protein, and (2) extracellular amyloid deposits (amyloid plaques) in the brain vasculature (cerebral amyloid angiopathy; CAA). It has been proposed that vascular amyloid deposits could trigger neurovascular unit (NVU) dysfunction in AD. The NVU is composed primarily of astrocytic feet, endothelial cells, pericytes, and basement membrane. Although physical exercise is hypothesized to have beneficial effects against AD, it is unknown whether its positive effects extend to ameliorating CAA and improving the physiology of the NVU. We used the triple transgenic animal model for AD (3xTg-AD) at 13 months old and analyzed through behavioral and histological assays, the effect of voluntary physical exercise on cognitive functions, amyloid angiopathy, and the NVU. Our results show that 3xTg-AD mice develop vascular amyloid deposits which correlate with cognitive deficits and NVU alteration. Interestingly, the physical exercise regimen decreases amyloid angiopathy and correlates with an improvement in cognitive function as well as in the underlying integrity of the NVU components. Physical exercise could represent a key therapeutic approach in cerebral amyloid angiopathy and NVU stability in AD patients.

Enhanced selectivity for acidic contaminants in drinking water: From suspect screening to toxicity prediction.

A novel analytical workflow for suspect screening of organic acidic contaminants in drinking water is presented, featuring selective extraction by silica-based strong anion-exchange solid-phase extraction, mixed-mode liquid chromatography-high resolution accurate mass spectrometry (LC-HRMS), peak detection, feature reduction and compound identification. The novel use of an ammonium bicarbonate-based elution solvent extended strong anion-exchange solid-phase extraction applicability to LC-HRMS of strong acids. This approach performed with consistently higher recovery and repeatability (88 ± 7 % at 500 ng L-1), improved selectivity and lower matrix interference (mean = 12 %) over a generic mixed-mode weak anion exchange SPE method. In addition, a novel filter for reducing full-scan features from fulvic and humic acids was successfully introduced, reducing workload and potential for false positives. The workflow was then applied to 10 London municipal drinking water samples, revealing the presence of 22 confirmed and 37 tentatively identified substances. Several poorly investigated and potentially harmful compounds were found which included halogenated hydroxy-cyclopentene-diones and dibromomethanesulfonic acid. Some of these compounds have been reported as mutagenic in test systems and thus their presence here requires further investigation. Overall, this approach demonstrated that employing selective extraction improved detection and helped shortlist suspects and potentially toxic chemical contaminants with higher confidence.

A year-long study of the occurrence and risk of over 140 contaminants of emerging concern in wastewater influent, effluent and receiving waters in the Republic of Ireland.

Despite being a developed country in the European Union (EU), knowledge of the nature and extent of contamination of water bodies with contaminants of emerging concern (CECs) in Ireland is limited. In this study, >140 CECs including pharmaceuticals, pesticides and personal care products were monitored in monthly samples of wastewater treatment plant (WWTP) influent, effluent and receiving surface waters at both an urban and a rural location (72 samples in total) in Ireland over a 12-month period in 2018-2019. In total, 58 CECs were detected, including several EU Water Framework Directive Watch List compounds. Of all classes, the highest concentrations were measured for pharmaceuticals across all media, i.e., propranolol in surface waters (134 ng·L-1), hydrochlorothiazide in effluent (1067 ng·L-1) and venlafaxine in influent wastewater (8273 ng·L-1). Overall, high wastewater treatment removal was observed and a further reduction in CEC occurrence and concentration was measured via dilution in the receiving river environment. Lastly, an environmental risk assessment (ERA) was performed using risk quotients (RQ), which revealed that in surface waters, total RQ for all CECs was an order of magnitude lower than in effluents. The majority of CECs in surface waters posed a lower risk except E2 and EE2 which presented a medium risk (RQs of 3.5 and 1.1, respectively) in the rural area. This work represents the most comprehensive CEC monitoring dataset to date for Ireland which allowed for an ERA prioritisation to be performed for the first time.

Occurrence of Z-drugs, benzodiazepines, and ketamine in wastewater in the United States and Mexico during the Covid-19 pandemic.

Z-drugs, benzodiazepines and ketamine are classes of psychotropic drugs prescribed for treating anxiety, sleep disorders and depression with known side effects including an elevated risk of addiction and substance misuse. These drugs have a strong potential for misuse, which has escalated over the years and was hypothesized here to have been exacerbated during the COVID-19 pandemic. Wastewater-based epidemiology (WBE) constitutes a fast, easy, and relatively inexpensive approach to epidemiological surveys for understanding the incidence and frequency of uses of these drugs. In this study, we analyzed wastewater (n = 376) from 50 cities across the United States and Mexico from July to October 2020 to estimate drug use rates during a pandemic event. Both time and flow proportional composite and grab samples of untreated municipal wastewater were analyzed using solid-phase extraction followed by liquid chromatography-tandem mass spectrometry to determine loadings of alprazolam, clonazepam, diazepam, ketamine, lorazepam, nordiazepam, temazepam, zolpidem, and zaleplon in raw wastewater. Simultaneously, prescription data of the aforementioned drugs were extracted from the Medicaid database from 2019 to 2021. Results showed high detection frequencies of ketamine (90 %), lorazepam (87 %), clonazepam (76 %) and temazepam (73 %) across both Mexico and United States and comparatively lower detection frequencies for zaleplon (22 %), zolpidem (9 %), nordiazepam (<1 %), diazepam (<1 %), and alprazolam (<1 %) during the pandemic. Average mass consumption rates, estimated using WBE and reported in units of mg/day/1000 persons, ranged between 62 (temazepam) and 1100 (clonazepam) in the United States. Results obtained from the Medicaid database also showed a significant change (p < 0.05) in the prescription volume between the first quarter of 2019 (before the pandemic) and the first quarter of 2021 (pandemic event) for alprazolam, clonazepam and lorazepam. Study results include the first detections of zaleplon and zolpidem in wastewater from North America.

A miniaturized passive sampling-based workflow for monitoring chemicals of emerging concern in water.

The miniaturization of a full workflow for identification and monitoring of contaminants of emerging concern (CECs) is presented. Firstly, successful development of a low-cost small 3D-printed passive sampler device (3D-PSD), based on a two-piece methacrylate housing that held up to five separate 9 mm disk sorbents, is discussed. Secondly, a highly sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method reduced the need for large scale in-laboratory apparatus, solvent, reagents and reference material quantities for in-laboratory passive sampler device (PSD) calibration and extraction. Using hydrophilic-lipophilic balanced sorbents, sampling rates (Rs) were determined after a low 50 ng L-1 exposure over seven days for 39 pesticides, pharmaceuticals, drug metabolites and illicit drugs over the range 0.3 to 12.3 mL day-1. The high sensitivity LC-MS/MS method enabled rapid analysis of river water using only 10 µL of directly injected sample filtrate to measure occurrence of 164 CECs and sources along 19 sites on the River Wandle, (London, UK). The new 3D-PSD was then field-tested over seven days at the site with the highest number and concentration of CECs, which was down-river from a wastewater treatment plant. Almost double the number of CECs were identified in 3D-PSD extracts across sites in comparison to water samples (80 versus 42 CECs, respectively). Time-weighted average CEC concentrations ranged from 8.2 to 845 ng L-1, which were generally comparable to measured concentrations in grab samples. Lastly, high resolution mass spectrometry-based suspect screening of 3D-PSD extracts enabled 113 additional compounds to be tentatively identified via library matching, many of which are currently or are under consideration for the EU Watch List. This miniaturized workflow represents a new, cost-effective, and more practically efficient means to perform passive sampling chemical monitoring at a large scale. SYNOPSIS: Miniaturized, low cost, multi-disk passive samplers enabled more efficient multi-residue chemical contaminant characterization, potentially for large-scale monitoring programs.

Quantitative Determination and Environmental Risk Assessment of 102 Chemicals of Emerging Concern in Wastewater-Impacted Rivers Using Rapid Direct-Injection Liquid Chromatography-Tandem Mass Spectrometry.

The rapid source identification and environmental risk assessment (ERA) of hundreds of chemicals of emerging concern (CECs) in river water represent a significant analytical challenge. Herein, a potential solution involving a rapid direct-injection liquid chromatography-tandem mass spectrometry method for the quantitative determination of 102 CECs (151 qualitatively) in river water is presented and applied across six rivers in Germany and Switzerland at high spatial resolution. The method required an injection volume of only 10 µL of filtered sample, with a runtime of 5.5 min including re-equilibration with >10 datapoints per peak per transition (mostly 2 per compound), and 36 stable isotope-labelled standards. Performance was excellent from the low ng/L to µg/L concentration level, with 260 injections possible in any 24 h period. The method was applied in three separate campaigns focusing on the ERA of rivers impacted by wastewater effluent discharges (1 urban area in the Basel city region with 4 rivers, as well as 1 semi-rural and 1 rural area, each focusing on 1 river). Between 25 and 40 compounds were quantified directly in each campaign, and in all cases small tributary rivers showed higher CEC concentrations (e.g., up to ~4000 ng/L in total in the R. Schwarzach, Bavaria, Germany). The source of selected CECs could also be identified and differentiated from other sources at pre- and post- wastewater treatment plant effluent discharge points, as well as the effect of dilution downstream, which occurred over very short distances in all cases. Lastly, ERA for 41 CECs was performed at specific impacted sites, with risk quotients (RQs) at 1 or more sites estimated as high risk (RQ > 10) for 1 pharmaceutical (diclofenac), medium risk (RQ of 1-10) for 3 CECs (carbamazepine, venlafaxine, and sulfamethoxazole), and low risk (RQ = 0.1-1.0) for 7 CECs (i.e., RQ > 0.1 for 11 CECs in total). The application of high-throughput methods like this could enable a better understanding of the risks of CECs, especially in low flow/volume tributary rivers at scale and with high resolution.

The transportation, transformation and (bio)accumulation of pharmaceuticals in the terrestrial ecosystem.

Soil dwelling organisms, plants and many primary consumers in food webs face the challenge of exposure to contaminants of emerging concern (CECs) present in terrestrial systems, including thousands of substances derived from pharmaceutical and personal care products (PPCPs). The recent increase in the consumption of modern human or veterinary drugs has resulted in a surge of anthropogenic pharmaceuticals, frequently introduced into terrestrial environments via untreated/treated wastewater. Pharmaceuticals display diverse degradation and accumulation behaviours in receiving bodies, however their impact on soils has, at large, been overlooked. Details about adsorption, absorption, degradation and uptake behaviours, as well as the fate and actual environmental impact of pharmaceuticals are a prerequisite before the traditional transportation prediction models originally designed for the aquatic environment can be extrapolated to terrestrial systems. Without this knowledge, our ability for informed risk assessments and the resultant implementation of contamination management strategies of soils will remain limited. This review discusses the current knowledgebase pertaining the introduction of pharmaceuticals to soils via wastewater irrigation or the application of biosolids. The focus on the transportation, transformation and accumulation of pharmaceuticals through the food chain highlights the urgent need to strengthen our capabilities concerning their detection and characterization in the terrestrial ecosystem.

Rapid direct analysis of river water and machine learning assisted suspect screening of emerging contaminants in passive sampler extracts.

A novel and rapid approach to characterise the occurrence of contaminants of emerging concern (CECs) in river water is presented using multi-residue targeted analysis and machine learning-assisted in silico suspect screening of passive sampler extracts. Passive samplers (Chemcatcher®) configured with hydrophilic-lipophilic balanced (HLB) sorbents were deployed in the Central London region of the tidal River Thames (UK) catchment in winter and summer campaigns in 2018 and 2019. Extracts were analysed by; (a) a rapid 5.5 min direct injection targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for 164 CECs and (b) a full-scan LC coupled to quadrupole time of flight mass spectrometry (QTOF-MS) method using data-independent acquisition over 15 min. From targeted analysis of grab water samples, a total of 33 pharmaceuticals, illicit drugs, drug metabolites, personal care products and pesticides (including several EU Watch-List chemicals) were identified, and mean concentrations determined at 40 ± 37 ng L-1. For targeted analysis of passive sampler extracts, 65 unique compounds were detected with differences observed between summer and winter campaigns. For suspect screening, 59 additional compounds were shortlisted based on mass spectral database matching, followed by machine learning-assisted retention time prediction. Many of these included additional pharmaceuticals and pesticides, but also new metabolites and industrial chemicals. The novelty in this approach lies in the convenience of using passive samplers together with machine learning-assisted chemical analysis methods for rapid, time-integrated catchment monitoring of CECs.

Perchlorate detection via an invertebrate biosensor.

Improvised explosive devices (IEDs) are constructed from easily obtainable ingredients that are often unregulated and difficult to trace. Salts of the oxyhalide perchlorate are frequently used as oxidisers in IEDs and in commercially available munitions, thus a reliable detection is needed to aid forensic investigations and the tracing of environmental ground or surface water contamination. We introduce the nematode Caenorhabditis elegans as a biosensor for the presence of perchlorate, a promising alternative to the costly, technically challenging and time-consuming current perchlorate detection methods. Perchlorate uptake dynamics in C. elegans were first validated using ion exchange chromatography followed by assessing the effects of perchlorate on key life-point indices to verify the suitability of the nematodes as a forensic biosensor. Whole genome microarrays and qPCR analyses established that a set of immune and stress response genes were enriched during perchlorate exposure. A nematode strain (agIs219) containing an integrated copy of the significantly overexpressed t24b8.5 gene promoter followed by a GFP reporter gene was shown to fluoresce in a perchlorate dose dependent manner with a limit of detection (LOD) of 0.5 mg mL-1. Whilst chemicals commonly used in the construction of IEDs did not induce fluorescence, exposure to other oxyhalides did, highlighting the presence of possible shared stress response pathways. Burnt wire sparklers containing potassium perchlorate elicited fluorescence while other non-perchlorate containing post-blast explosion matrices did not. This demonstrates how C. elegans can be used to screen for perchlorate at environmental hotspots, an optimization, possibly with other target transgenes, is required to enable the detection of perchlorate at concentrations below 0.5 mg mL-1.

Quantitative Assessment of Dietary (Poly)phenol Intake: A High-Throughput Targeted Metabolomics Method for Blood and Urine Samples.

Many studies have associated the consumption of (poly)phenol-rich diets with health benefits. However, accurate high-throughput quantitative methods for estimating exposure covering a broad spectrum of (poly)phenols are lacking. We have developed and validated a high-throughput method for the simultaneous quantification of 119 (poly)phenol metabolites in plasma and urine using ultra high-performance liquid chromatography coupled with triple quadrupole mass spectrometry, with a very fast sample treatment and a single run time of 16 min. This method is highly sensitive, precise, accurate, and shows good linearity for all compounds (R2 > 0.992). This novel method will allow a quantitative assessment of habitual (poly)phenol intake in large epidemiological studies as well as clinical studies investigating the health benefits of dietary (poly)phenols.

Multicompartment and cross-species monitoring of contaminants of emerging concern in an estuarine habitat.

The fate of many chemicals in the environment, particularly contaminants of emerging concern (CEC), have been characterised to a limited extent with a major focus on occurrence in water. This study presents the characterisation, distribution and fate of multiple chemicals including pharmaceuticals, recreational drugs and pesticides in surface water, sediment and fauna representing different food web endpoints in a typical UK estuary (River Colne, Essex, UK). A comparison of contaminant occurrence across different benthic macroinvertebrates was made at three sites and included two amphipods (Gammarus pulex &Crangon crangon), a polychaete worm (Hediste diversicolor) and a gastropod (Peringia ulvae). Overall, multiple contaminants were determined in all compartments and ranged from;

Trace multi-class organic explosives analysis in complex matrices enabled using LEGO®-inspired clickable 3D-printed solid phase extraction block arrays.

The development of a new, lower cost method for trace explosives recovery from complex samples is presented using miniaturised, click-together and leak-free 3D-printed solid phase extraction (SPE) blocks. For the first time, a large selection of ten commercially available 3D printing materials were comprehensively evaluated for practical, flexible and multiplexed SPE using stereolithography (SLA), PolyJet and fused deposition modelling (FDM) technologies. Miniaturised single-piece, connectable and leak-free block housings inspired by Lego® were 3D-printed in a methacrylate-based resin, which was found to be most stable under different aqueous/organic solvent and pH conditions, using a cost-effective benchtop SLA printer. Using a tapered SPE bed format, frit-free packing of multiple different commercially available sorbent particles was also possible. Coupled SPE blocks were then shown to offer efficient analyte enrichment and a potentially new approach to improve the stability of recovered analytes in the field when stored on the sorbent, rather than in wet swabs. Performance was measured using liquid chromatography-high resolution mass spectrometry and was better, or similar, to commercially available coupled SPE cartridges, with respect to recovery, precision, matrix effects, linearity and range, for a selection of 13 peroxides, nitramines, nitrate esters and nitroaromatics. Mean % recoveries from dried blood, oil residue and soil matrices were 79 ± 24%, 71 ± 16% and 76 ± 24%, respectively. Excellent detection limits between 60 fg for 3,5-dinitroaniline to 154 pg for nitroglycerin were also achieved across all matrices. To our knowledge, this represents the first application of 3D printing to SPE of so many organic compounds in complex samples. Its introduction into this forensic method offered a low-cost, 'on-demand' solution for selective extraction of explosives, enhanced flexibility for multiplexing/design alteration and potential application at-scene.

Untargeted metabolomics changes on Gammarus pulex induced by propranolol, triclosan, and nimesulide pharmaceutical drugs.

The presence of pharmaceuticals and personal care products (PPCPs) in natural water resources due to incomplete removal in Wastewater Treatment Plants (WWTPs) is a serious environmental concern at present. In this work, the effects of three pharmaceuticals (propranolol, triclosan, and nimesulide) on Gammarus pulex metabolic profiles at different doses and times of exposure have been investigated by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). The complex data sets generated in the different exposure experiments were analyzed with the ROIMCR procedure, based on the selection of the MS regions of interest (ROI) data and on their analysis by the Multivariate Curve-Resolution Alternating Least Squares (MCR-ALS) chemometrics method. This approach, allowed the resolution and identification of the metabolites present in the analyzed samples, as well as the estimation of their concentration changes due to the exposure experiments. ANOVA Simultaneous Component Analysis (ASCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were then conducted to assess the changes in the concentration of the metabolites for the three pharmaceuticals at the different conditions of exposure. The three tested pharmaceuticals changed the concentrations of metabolites, which were related to different KEGG functional classes. These changes summarize the biochemical response of Gammarus pulex to the exposure by the three investigated pharmaceuticals. Possible pathway alterations related to protein synthesis and oxidative stress were observed in the concentration of identified metabolites.