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Wastewater-based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study were to: (i) assess spatial and temporal trends of population-normalized mass loads of benzoylecgonine, amphetamine, methamphetamine and 3,4-methylenedioxymethamphetamine (MDMA) in raw wastewater over 7 years (2011-17); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city; and (iii) compare these with existing prevalence and seizure data.Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017.Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries.Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of ΔBenzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA and methamphetamine in East and North-Central Europe. In other continents, methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. During the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge.The analysis of wastewater to quantify drug loads provides near real-time drug use estimates that globally correspond to prevalence and seizure data.

Background and aims Wastewater‐based epidemiology is an additional indicator of drug use that is gaining reliability to complement the current established panel of indicators. The aims of this study were to: (i) assess spatial and temporal trends of population‐normalized mass loads of benzoylecgonine, amphetamine, methamphetamine and 3,4‐methylenedioxymethamphetamine (MDMA) in raw wastewater over 7 years (2011–17); (ii) address overall drug use by estimating the average number of combined doses consumed per day in each city; and (iii) compare these with existing prevalence and seizure data. Design Analysis of daily raw wastewater composite samples collected over 1 week per year from 2011 to 2017. Setting and Participants Catchment areas of 143 wastewater treatment plants in 120 cities in 37 countries. Measurements Parent substances (amphetamine, methamphetamine and MDMA) and the metabolites of cocaine (benzoylecgonine) and of Δ9‐tetrahydrocannabinol (11‐nor‐9‐carboxy‐Δ9‐tetrahydrocannabinol) were measured in wastewater using liquid chromatography–tandem mass spectrometry. Daily mass loads (mg/day) were normalized to catchment population (mg/1000 people/day) and converted to the number of combined doses consumed per day. Spatial differences were assessed world‐wide, and temporal trends were discerned at European level by comparing 2011–13 drug loads versus 2014–17 loads. Findings Benzoylecgonine was the stimulant metabolite detected at higher loads in southern and western Europe, and amphetamine, MDMA and methamphetamine in East and North–Central Europe. In other continents, methamphetamine showed the highest levels in the United States and Australia and benzoylecgonine in South America. During the reporting period, benzoylecgonine loads increased in general across Europe, amphetamine and methamphetamine levels fluctuated and MDMA underwent an intermittent upsurge. Conclusions The analysis of wastewater to quantify drug loads provides near real‐time drug use estimates that globally correspond to prevalence and seizure data., This study was supported by the following countries, institutions and projects Australia: Thyne Reid foundation; Canada: Natural Sciences and Engineering Research Council of Canada (NSERC); Iceland: The Icelandic Research Fund (Grant number 163049–051); Slovenia: Slovene Research Agency (funding Project L1–9191); Spain: MINECO/AEI projects (CTM2014–56628‐C3–2‐R, CTQ2015–65603‐P, CTM2016–81935‐REDT, CTM2017–84763‐C3–2‐R), Galician Council of Culture, Education and Universities (ED481D 2017/003); UK: Environmental Sustainability Knowledge Transfer Network, Engineering and Physical Sciences Research Council and Thermo Fisher Scientific (CASE industrial scholarship for K. Munro, Ref.: EP/J502029/1). European Monitoring Centre for Drugs and Drug Addiction (EMCDDA); EU International Training Network SEWPROF (Marie Curie‐FP7‐PEOPLE, grant number 317205); COST Action ES1307 supported by COST (European Cooperation in Science and Technology); WATCH (Wastewater Analysis of Traces of illicit drug‐related Chemicals for law enforcement and public Health DG migration and Home affairs ‐ HOME/2015/ISFP/PR/DRUG/0062). Sampling support and provision of catchment information Austria: Klemens Geiger and Michael Schlapp; Belgium: Jonathan Phariseau, Bart Coene, Luc Van Os, Peter Nys, Dieter Lemaire, Jean‐François Mougel, Patrick Vantroyen and Karel Claes; Croatia: Marin Ganjto; Czech Republic: Jiri Stara and Robert Hrich Brněnské; France: Véronique Bremont; Italy: Roberto Mazzini and Francesca Pizza (Milan), Francesco Avolio (Bologna), Fabrizio Moratto and Sergio Ghezzi (Gorizia), Rosanna Brienza and Simona Panariello (Potenza), Pier Paolo Abis and Antonia Attanasio (Bari), Antonella Cicala (Palermo); Norway: Pia Ryrfors; Portugal: João Goulão, José Martins, Pedro Alvaro and Fátima Paixão; Slovakia: Silvia Antalová and Jozef Tichy; Spain: Begoña Martínez López, Cristian Mesa, Santiago Querol Rodriguez, Fernando Llavador, Enrique Albors and Gloria Fayos; the Netherlands: Alex Veltman, Peter Theijssen, Peter van Dijk, Stefan Wijers, Mark Stevens, Ferry de Wilde. Analytical support Australia: Maulik Ghetia; Cyprus: Popi Karaolia; Greece: Nikoilaos Raikos; Spain: Ana Maria Botero‐Coy, Clara Boix, Alberto Celma, Jorge Pitarch, Inés Racamonde and Eddie Fonseca; Italy: Emma Gracia‐Lor, Nikolaos I. Rousis and Noelia Salgueiro‐Gonzalez. Data repository and data screening Eawag: Harald von Waldow; EMCDDA: Renate Hochwieser, Liesbeth Vandam, João Matias and Federica Mathis.

The occurrence of pharmaceutical and illicit drug residues potentially arising from combined sewer overflows (CSOs) in the Central London portion of the Thames Estuary is presented. Approximately 39 million tonnes of untreated sewage enter the River Thames at 57 CSO points annually. Differential analysis of influents and effluents in a major wastewater treatment plant identified seven potential drug-related CSO markers based on removal rates. Three were present in influent at concentrations1 μg L

Sleep is a dynamic process in most animals, involving distinct stages that probably perform multiple functions for the brain. Before sleep functions can be initiated, it is likely that behavioral responsiveness to the outside world needs to be reduced, even while the animal is still awake. Recent work in Drosophila has uncovered a sleep switch in the dorsal fan-shaped body (dFB) of the fly’s central brain, but it is not known whether these sleep-promoting neurons also govern the acute need to ignore salient stimuli in the environment during sleep transitions. We found that optogenetic activation of the sleep switch suppressed behavioral responsiveness to mechanical stimuli, even in awake flies, indicating a broader role for these neurons in regulating arousal. The dFB-mediated suppression mechanism and its associated neural correlates requires innexin6 expression, suggesting that the acute need to reduce sensory perception when flies fall asleep is mediated in part by electrical synapses.

Quantitative measurement of drug consumption biomarkers in wastewater can provide objective information on community drug use patterns and trends. This study presents the measurement of alcohol consumption in 20 cities across 11 countries through the use of wastewater-based epidemiology (WBE), and reports the application of these data for the risk assessment of alcohol on a population scale using the margin of exposure (MOE) approach. Raw 24-h composite wastewater samples were collected over a one-week period from 20 cities following a common protocol. For each sample a specific and stable alcohol consumption biomarker, ethyl sulfate (EtS) was determined by liquid chromatography coupled to tandem mass spectrometry. The EtS concentrations were used for estimation of per capita alcohol consumption in each city, which was further compared with international reports and applied for risk assessment by MOE. The average per capita consumption in 20 cities ranged between 6.4 and 44.3L/day/1000 inhabitants. An increase in alcohol consumption during the weekend occurred in all cities, however the level of this increase was found to differ. In contrast to conventional data (sales statistics and interviews), WBE revealed geographical differences in the level and pattern of actual alcohol consumption at an inter-city level. All the sampled cities were in the "high risk" category (MOE10) and the average MOE for the whole population studied was 2.5. These results allowed direct comparisons of alcohol consumption levels, patterns and risks among the cities. This study shows that WBE can provide timely and complementary information on alcohol use and alcohol associated risks in terms of exposure at the community level.

The modelling and prediction of reversed-phase chromatographic retention time (tR) under gradient elution conditions for 166 pharmaceuticals in wastewater extracts is presented using artificial neural networks for the first time. Radial basis function, multilayer perceptron and generalised regression neural networks were investigated and a comparison of their predictive ability for model solutions discussed. For real world application, the effect of matrix complexity on tR measurements is presented. Measured tR for some compounds in influent wastewater varied by >1min in comparison to tR in model solutions. Similarly, matrix impact on artificial neural network predictive ability was addressed towards developing a more robust approach for routine screening applications. Overall, the best neural network had a predictive accuracy of R data in wastewater samples (2=0.92. Finally, the model was evaluated for application to the semi-targeted identification of pharmaceutical residues during a weeklong wastewater sampling campaign. The model successfully identified native compounds at a rate of 83±4% and 73±5% in influent and effluent extracts, respectively. The use of an HRMS database and the optimised ANN model was also applied to shortlisting of 37 additional compounds in wastewater. Ultimately, this research will potentially enable faster identification of emerging contaminants in the environment through more efficient post-acquisition data mining.