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You have full access to this open access article. MDMA 3,4-methylenedioxymethamphetamine is a psychostimulant popular as a recreational drug because of its effect on mood and social interactions. MDMA is often ingested with caffeine. The aim of the present study was to determine the changes in DA and 5-HT release in the mouse striatum induced by MDMA and caffeine after their chronic administration. Furthermore, the effect of caffeine on MDMA-induced changes in striatal dynorphin and enkephalin and on behavior was assessed. DNA damage was assayed with the alkaline comet assay. The behavioral changes were measured by the open-field OF test and novel object recognition NOR test. Our data provide evidence that long-term caffeine administration has a powerful influence on functions of dopaminergic and serotonergic neurons in the mouse brain and on neurotoxic effects evoked by MDMA. This effect is intensified by inhibition of monoamine oxidase type B MAO-B located in the outer membrane of the mitochondria of serotonergic neurons Leonardi and Azmitia MDMA has been shown to elicit long-lasting neurotoxic effects which vary depending on gender and strain of animals Brodkin et al. Similarly, the damage in serotonergic system was also observed in non-human primates and in the human brain Green et al. Numerous complex mechanisms have been identified as contributors to the neurotoxic effects of MDMA. Oxidative stress and excitotoxicity represent important mechanisms causing neuronal damage by MDMA Cadet et al. MDMA has also been shown to trigger neuroinflammation which seems to be linked with glial activation, in particular microglial activation Costa et al. Other putative mechanisms of MDMA neurotoxicity include hyperthermia, metabolic toxic products, and apoptosis Capela et al. Toxic and inflammatory effects of MDMA are exacerbated by its co-administration with other psychoactive substances Khairnar et al. Caffeine is commonly consumed with MDMA in energy drinks to reduce drowsiness and fatigue, or it is present in illicit drug preparations, e. Molecular mechanism of caffeine action in the brain is based on adenosine receptor antagonism. The targets of caffeine actions include G-protein-coupled adenosine A1 and A2A receptors. It is also suggested that adenosine A1 receptors present on glutamatergic neurons may be involved in striatal DA release Borycz et al. On the other hand, medium-sized spiny neurons projecting to the globus pallidus express D2 receptor Gerfen et al. By contrast, caffeine increases the activity of both types of neurons Johansson et al. Caffeine augmented many effects associated with MDMA use. MDMA-induced hyperthermia and tachycardia but not hyperlocomotion were promoted by caffeine in rats. The results of Khairnar et al. The abovementioned data suggest that caffeine increases MDMA-related neurotoxicity. On the other hand, the results of Ruiz-Medina et al. This raises the question about a long-term caffeine effect on MDMA neurotoxicity. Both drugs were administrated repeatedly in a way mimicking recreational use by young people in dance clubs. In addition, because caffeine could affect behavioral responses, we assessed the effect of chronic caffeine administration on some behavioral parameters associated with MDMA administration. Caffeine and MDMA were dissolved in 0. All injections were done via intraperitoneal ip route, and control animals received their respective vehicles. This cycle of treatments was repeated 3 times as shown on the diagram below. Animals were anesthetized with ketamine 7. After 1 h of the washout period, three basal dialysate samples were collected every 30 min; then, animals were injected with a challenging dose of an appropriate drug as indicated in the figure captions and fraction collection continued for min. At the end of the experiment, the mice were sacrificed and their brains were histologically examined to validate the probe placement. The mobile phase was composed of 0. The flow rate during analysis was set at 0. The chromatographic data were processed by Chromeleon v. Animals were sacrificed by decapitation 3 h after cessation of treatment with drugs. Brains were separated, and several brain regions striatum, frontal cortex were dissected in anatomical borders. Briefly, tissue samples of brain structures were homogenized in ice-cold 0. The mobile phase consisted of 0. The potential of a 3-mm glassy carbon electrode was set at 0. Animals were killed 60 days after termination of drug treatments. The whole cortex was separated in anatomical borders. Next, the brain tissue was minced with surgical scalpel and homogenized in a manual homogenizer with homogenizing solution containing 0. The pellet was resuspended in 0. The nuclei were obtained as a transparent sediment at the bottom. The suspension was mixed with LMA agarose and transferred immediately onto Comet slides. The buffer was drained, and the slides were immersed in alkaline unwinding solution and were left for 45 min in the dark. Next, electrophoresis was run at 21 V for 30 min. The slides were then covered with dye and allowed to dry completely at room temperature in the dark. On the next day, the slides were examined under a fluorescent microscope. DNA damage was presented as an olive tail moment. Olive tail moment is defined as the product of the tail length and the fraction of total DNA in the tail. Tail moment incorporates a measure of both the smallest detectable size of migrating DNA reflected in the comet tail length and the number of damaged pieces represented by the intensity of DNA in the tail. Brains were removed from the skull, and tissue samples including the striatum were collected. The expression of the HPRT1 transcript was quantified at a stable level between the experimental groups to control for variations in cDNA amounts. Cycle threshold values were calculated automatically by iCycler IQ 3. For each mouse, three sections were collected from each of the brain regions analyzed at the following coordinates: from 2. Free-floating sections were rinsed in 0. After completion of incubation with the primary antibody, sections were rinsed three times in 0. After incubation with the secondary antibody, sections were rinsed and immediately mounted onto glass slides coated with gelatin in Mowiol mounting medium. Images of single wavelengths were obtained with an epifluorescence microscope Axio Scope A1, Zeiss, Oberkochen, Germany connected with a digital camera 1. Sections were captured in black and white 8-bit monochrome, and the density of fibers was determined in fixed regions using a threshold level that was kept constant across all images. The pixels were converted into square micrometers by employing a suited calibration, in order to represent the area occupied by a specific immunoreaction product in square micrometers. The final values are expressed as a percentage of the respective vehicle group. No significant differences in the density of immunoreacted fibers were seen between the three coronal sections. For each level of the striatum and mPFC, the obtained value was first normalized with respect to the vehicle, then, values from different levels were averaged. The arena was dimly illuminated with an indirect light of 18 lx. The mice were selected from separate housing cages. Each mouse was diagonally placed in the middle of the box. The behavior of the animals line crossing, center square duration, rearing, stretch attend postures was measured over a 5-min period. The test box was wiped clean between each trial. The laboratory room was dark, and only the center of the open field was illuminated with a W bulb placed 75 cm above the platform. On the first day of the experiment adaptation , mice were placed in the open field for 10 min. On the next day, the animals were placed in the open field for 5 min with two identical objects white tin, 5 cm wide and 14 cm high or green pyramid 5 cm wide and 14 cm high. The time of object interest was measured for each of the two objects separately. Then, 1 h after the first session, the mice were again placed in a free field for 5 min with two different objects, one from the previous session old and the other new white box and green pyramid. The time of object interest was measured for each of the two objects separately sniffing, touching, or climbing. Co-administration of both drugs produced a significantly stronger effect on extracellular DA level than each of the drugs given separately Fig. Time of drug injections is indicated with thick arrows. However, the increase produced by a combination of both drugs was weaker as compared to the effect of MDMA or caffeine given separately Fig. The increase in 5-HT release to ca. The basal extracellular level of 5-HT was decreased from 1. It is clear that the effect of the challenging doses of both psychostimulant drugs on DA release was weaker in groups pretreated chronically with caffeine and MDMA vs. In contrast, the effect of the challenging doses of caffeine and MDMA on 5-HT release was stronger in animals receiving chronic treatment of psychostimulants vs. The increase in DA tissue content was higher in the group treated concomitantly with caffeine and MDMA than in animals receiving these drugs separately Table 2. Caffeine and MDMA given acutely or chronically produced oxidative damage of DNA in nuclei from the mouse cortex as measured 2 months after cessation of treatment Fig. The damage of DNA was stronger after combination of both drugs administered acutely or chronically Fig. The extent of DNA damage was smaller after all treatments when it was measured 24 h after termination of drug administration data not shown. Data represent an olive tail moment. The loss of DNA integrity persisted 60 days after drug administration. Data represent mRNA levels with respect to the control group. Caffeine did not affect those parameters. Bars represent the time of walking and number of crossings a , and time of exploration of novel object b. Our findings indicate that caffeine increased the response of DA neurons to the challenging dose of MDMA while decreasing the response of serotonergic neurons. Furthermore, exploratory and locomotor activities of mice decreased by MDMA were not affected by caffeine, but exploration of novel object in the NOR test was diminished in animals treated with MDMA and caffeine. The pattern of 5-HT release was different showing more stable increase throughout the whole collection time. Moreover, MDMA applied in a single higher dose i. When MDMA was applied chronically 2 days of binge administration per week; this cycle was repeated three times , a weaker response of DA neurons to the challenging dose of MDMA but a stronger response of 5-HT ones was observed. Interestingly, the basal extracellular level of DA in mice receiving MDMA chronically was nearly twofold higher than in control animals, while extracellular 5-HT level was potently decreased. It may be speculated that persistent outflow of DA due to loss of DA uptake capacity may be a cause of increased basal extracellular DA level. Considerable evidence from the literature indicates that internalization of DAT occurs in response to amphetamine treatment Saunders et al. In fact, we observed a decrease in DAT density in the striatum and frontal cortex following chronic exposure to MDMA, which is in line with studies of Saunders et al. This is probably due to compensatory upregulation of 5-HT release machinery resulting from low synaptic 5-HT levels. For instance, Koch and Galloway , Reveron et al. However, some studies report that the activation of 5-HT1A Ichikawa et al. Thus, it may be suggested that long-term exposure to MDMA leads to neuroadaptative changes in sensitivity of serotonin receptors, which may result in differential response of DA and 5-HT neurons, as it is observed in our study. Some data suggest a role of postsynaptic 5-HT2A receptors located on glutamatergic neurons in the neurochemical effects mediated by MDMA. Stimulation of 5-HT2A receptors located on glutamatergic cells in the frontal cortex may elicit an increase in glutamate level leading indirectly to a rise in DA and 5-HT release Alex and Pehek However, it remains unclear how glutamate and GABA release may be involved in upregulation of serotonergic neurons and cause very potent response to the challenging dose of MDMA, as we observed in the present study. However, in contrast to animals pretreated with saline in which caffeine potentiated MDMA-induced increase in 5-HT release, caffeine inhibited the MDMA effect on 5-HT release in animals receiving both psychostimulants repeatedly. It is accepted that the mechanism underlying caffeine influence on neurotransmitter release is related to the blockade of adenosine A1 and A2A receptors. Caffeine may increase DA and glutamate release in the striatum via blockade of inhibitory A1 receptors as was evidenced by a number of studies Borycz et al. The lack of A2A receptors on the striatal monoaminergic neuronal terminals suggests that their role in the control of DA and 5-HT release may be secondary and related to the changes in the activity of striatal output pathways elicited by postsynaptic A2A receptors. These data indicate synergistic interaction between caffeine and MDMA. The difference in results reported by the above-cited studies may be related by way of drug application systemic vs. It may be speculated that persistent blockade of adenosine receptors by caffeine can be responsible for this effect. In the study of Okada et al. However, under A1 receptor blockade by caffeine, the inhibitory effects of A3 receptor were unmasked in addition to the effect of A2 receptor blockade by caffeine Okada et al. Furthermore, it was also demonstrated that 5-HT reuptake activity might be modulated by A3 receptor Okada et al. Thus, the described mechanism of adenosine receptor involvement in the control of 5-HT release and their blockade by caffeine may be responsible for the diminished 5-HT release in response to MDMA and caffeine co-administration. The neurotoxic effect of MDMA in mice seems to be related to dopaminergic and serotonergic systems. The involvement of free radicals in MDMA-induced dopaminergic neurotoxicity in mice was also shown by Peraile et al. Those authors demonstrated that oxidative stress was related with lipid peroxidation and with an increase in superoxide dismutase and decrease in catalase activity. Hydroxyl radical formation together with products of tryptamine oxidation was proposed as the mechanism of MDMA-induced depletion of brain 5-HT by Shankaran et al. Moreover, it was suggested that 5-HT depletion was dependent on 5-HT transporter activity. Barbosa et al. Oxidative damage produced by MDMA may be associated with neuronal cell bodies. Most of the literature has described the striatum as the main target of MDMA neurotoxicity. Here, we provide evidence that other regions are also targets of MDMA neurotoxicity. DNA damage may be a molecular basis for MDMA-induced neuroplasticity with subsequent behavioral and cognitive deficits. At the same time, it slightly but significantly reversed the decrease in striatal DOPAC content and increased DA striatal tissue level. However, it was neuroprotective for DA fibers in the striatum. On the other hand, it potentiated the decrease in cortical SERT fiber density. Thus, caffeine seems to be neuroprotective for striatal dopaminergic fibers, but it seems to increase neurotoxic damage of cortical 5-HT terminals. Moreover, besides damage of cortical 5-HT terminals, caffeine increased MDMA-induced oxidative damage of cortical DNA which suggests degeneration of neuronal cells in this brain region. The neurotoxic effect exerted on cortical neuronal cell bodies may lead to neuroadaptive change of cortical pathways projecting to nigral or raphe nuclei. Thus, overall caffeine effect seems to be partly neuroprotective and partly neurotoxic. This dual action is dependent on doses, the brain region examined, and the schedule of administration as reported by numerous literature. When caffeine was given chronically, it increased activity of antioxidant enzymes superoxide dismutase SOD and catalase CAT in several regions of the rat brain Noschang et al. Aoyama et al. On the other hand, caffeine exhibited prooxidant properties in vitro Azam et al. The neurotoxic potential of caffeine given acutely was evidenced in the mouse brain by enhanced astroglia and microglia reactivities by MDMA Khairnar et al. In contrast, chronic low doses of caffeine exerted anti-inflammatory effects and prevented MDMA-induced neuroinflammatory reaction Ruiz-Medina et al. Study of Frau et al. Thus, caffeine shows differential effects, neuroprotective or neurotoxic, when co-administered with MDMA indicating that the mechanism of action of psychoactive drug combination needs further clarification. This is in line with findings of Benedetto di et al. These data confirm also the role of D1 receptor in MDMA effects, in particular in the development of neurotoxicity after long-term administration Granado et al. The overstimulation of a direct GABAergic pathway with normal functioning of an indirect GABAergic pathway may be responsible for deficit in locomotor activity of mice observed in our study. On the other hand, caffeine co-administered chronically with MDMA decreased the time of exploration of unknown object in the novel object recognition test. It is likely that a combination of both psychostimulants induced deficit in cognitive functions of mice, as also demonstrated by Costa et al. Structural synaptic plasticity of the medial prefrontal cortex was correlated with changes in response to novelty in rats developmentally treated with cocaine Caffino et al. It may be suggested that damage of serotonergic terminals in cortical regions or possible oxidative damage of glutamatergic pathways projecting to the VTA or raphe cell bodies may be responsible for the effect of psychostimulants on cognitive functions. The role of glutamatergic pathway damage by oxidative stress in the hippocampus and cognitive impairment was also shown in mice by Frenzilli et al. Anxiety-like behavior in rats was related to oxidative damage of DNA in the hippocampus by chronic caffeine Noschang et al. The alterations in the brain antioxidant system were suggested to affect the cognitive functions of rats after chronic caffeine ingestion Abreu et al. In conclusion, our data provide evidence that long-term caffeine administration has a powerful influence on dopaminergic and serotonergic neuron functions disturbed by MDMA in the mouse brain and on neurotoxic effects evoked by MDMA. Caffeine potentiates MDMA effect on dopaminergic system and inhibits its effect on serotonergic neurons. Exacerbation of MDMA-evoked oxidative stress may cause damage of serotonergic terminals. Pharmacol Biochem Behav — Pharmacol Ther — Neuroscience — Ann Neurol — J Neurochem — Br J Pharmacol — Neuropsychopharmacology — Article Google Scholar. Ann Med Interne Paris Suppl. Google Scholar. Neurotox Res — Brain Res — NeuroToxicology — J Neurosci — Mov Disord — Psychopharmacology — J Comp Neurol — Trends Pharmacol Sci — Article PubMed Google Scholar. Prog Brain Res — PubMed Google Scholar. Behav Pharmacol — Science — Pharmacol Rep — Pharmacol Rev — Eur J Pharmacol — J Neurol Sci — J Caffeine Res — J Neural Transm — Neuropharmacology — Neurochem Res — J Pharmacol Exp Ther — Neurosci Lett — Eur J Neurosci —9. Academic Press, San Diego. Peacock A, Bruno R, Ferris J, Winstock A Energy drink use frequency among an international sample of people who use drugs: associations with other substance use and well-being. Drug Alcohol Depend — Reveron ME, Maier EY, Duvauchelle CL Behavioral, thermal and neurochemical effects of acute and chronic 3,4-methylenedioxymethamphetamine ecstasy self-administration. Behav Brain Res — JAMA — Biol Psychol — Synapse — Eur J Neurosci — Proc Natl Acad Sci — Shankaran M, Yamamoto BK, Gudelsky GA Involvement of the serotonin transporter in the formation of hydroxyl radicals induced by 3,4-methylenedioxymethamphetamine. Prog Neurobiol — Aust J Pharm — Brit Aust J Pharm — Download references. You can also search for this author in PubMed Google Scholar. Reprints and permissions. Neurotox Res 33 , — Download citation. Received : 04 August Revised : 04 October Accepted : 18 October Published : 13 November Issue Date : April Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative. Neurotoxicity Research Aims and scope Submit manuscript. Download PDF. Abstract MDMA 3,4-methylenedioxymethamphetamine is a psychostimulant popular as a recreational drug because of its effect on mood and social interactions. Molecular changes in the nucleus accumbens and prefrontal cortex associated with the locomotor sensitization induced by coca paste seized samples Article 07 February Long-term disruption of tissue levels of glutamate and glutamatergic neurotransmission neuromodulators, taurine and kynurenic acid induced by amphetamine Article 14 March Use our pre-submission checklist Avoid common mistakes on your manuscript. Brain Microdialysis Animals were anesthetized with ketamine 7. Comet Assay Preparation of Nuclear Suspension Animals were killed 60 days after termination of drug treatments. Reaction Protocols Free-floating sections were rinsed in 0. Image Analysis Images of single wavelengths were obtained with an epifluorescence microscope Axio Scope A1, Zeiss, Oberkochen, Germany connected with a digital camera 1. Full size image. Table 3 The density of dopamine transporter DAT and serotonin transporter SERT in the mouse striatum and frontal cortex measured after cessation of treatment with the drugs Full size table. Conclusions In conclusion, our data provide evidence that long-term caffeine administration has a powerful influence on dopaminergic and serotonergic neuron functions disturbed by MDMA in the mouse brain and on neurotoxic effects evoked by MDMA. View author publications. About this article. Copy to clipboard. Search Search by keyword or author Search. 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Official websites use. Share sensitive information only on official, secure websites. The aim of this study was to determine the monthly DTR mass load of amphetamine-type compounds in Poland as well as an investigation of cyclical behaviour by using time series analysis and especially trends analysis. Back-calculations used in the sewage epidemiology approach were applied to estimate the DTR mass load level of the drugs analyzed. Trends analysis was performed by fitting the data to a simple linear regression and then by using smoothing by means of a moving average Mat lab a. Trend analysis displays a steady tendency of increase or decrease throughout time series. When we plot the observation against time, we may notice that a straight line can describe the increase or decrease in the series as time goes on. Simple linear regression and method of last squares to estimate parameters of a straight-line model were used. Additionally, a lagged plot autocorrelation plot was used to investigate an appearance of correlation between amphetamines throughout time. Trends analysis showed the slight increase in consumption of amphetamine and decreasing trend in case of ecstasy and methamphetamine within the investigated period. There is also visible, strong correlation between ecstasy and methamphetamine consumption which cannot be stated in case of amphetamine. Trends analysis is a very useful tool to analyse the increasing or decreasing tendency in consumption of illicit drugs based on the DTR mass load data. This method proposed by Daughton and Thernes 1 was first implemented by the Zucatto research group 2 — 4 to estimate the DTR mass load level of cocaine in some Italian cities, based on the analysis of surface and wastewater samples. Such investigations have been conducted in the last few years in other European countries, such as Belgium 5 — 7 , United Kingdom 8 , Italy - Florence 9 , Spain 10 — 14 , Croatia 15 , Switzerland 16 and also in Canada 17 and the United States of America The application of wastewater analysis to the investigation of illicit drug use represents an innovative approach to the monitoring of the illicit drug problem. This method is most useful for drug surveillance at the community level. It could be used as a drug surveillance tool to assist public health and law enforcement officials in identifying patterns of drug use across municipalities of all sizes. Furthermore, because wastewater sampling and analysis can be conducted on a daily, weekly or monthly basis, the data can be used to give a real-time measure that provides communities with more opportunities 19 for monitoring the impact and effectiveness of prevention and intervention activities. The analysis of wastewater is based upon samples drawn from the total liquid waste produced by a population. The mass flow of analytes contains information about the overall DTR mass load. The results do not provide specific information about who has consumed which drugs, or what specific doses of drugs may have been taken. It is not possible to determine directly whether an observed variation in wastewater samples reflects changes in the number of active users prevalence , or whether it relates to changes in levels of use patterns of use, dosage among users Undoubtedly, there are difficulties in using wastewater measurements of drugs to make inferences about the prevalence of users. The approach may, for example, be subject to limitations in the accuracy of estimates regarding collective DTR mass load parameters, and these levels of uncertainty might be further increased by potential sources of error and variability related to the assumptions that are required for the calculations. Uncertainties surrounding the analysis of wastewater samples may include, for example, issues concerning epidemiological questions, such as the phenotypes of users or behavioural variations in patterns of drug taking. Uncertainties may be related to individual differences in drug metabolism, such as the levels of drug metabolites in the blood. Information on human excretion rates for different substances is important for calculating the original amount of drugs consumed, but the data that is available on this topic is very limited because these values have generally been obtained from rather small samples of healthy volunteers, and they may not be representative of the metabolic responses of chronic drug users Additionally, closed water systems may serve transient human populations, and as a result, it may be difficult to characterize the population served by a given wastewater treatment system because of various sorts of changes that may occur in the resident populations of a given area for instance, due to people congregating at inner-city venues during weekends. This may lead to problems in determining whether an apparent rise in observed drug use measurements is due to an increase in DTR mass load by the resident population, or to an increase in the number of consumers because of changes in the resident population Moreover, the samples obtained from a wastewater system will be affected by leakage or heavy rainfalls. The greatest loss of drug residues is likely to occur during storms. The analysis of wastewater samples may also be confounded by the sudden or unexpected introduction of high concentrations of chemical agents. Finally, information is required about substance transport or degradation in wastewater systems. The physical, chemical and biological transformation processes of solutes may have an important effect upon the ability to make meaningful estimates, and knowledge about such processes is incomplete, even for conventional pollutants 3 , 4 , A number of complex chemical and biological interactions occur within sewer systems. Very little is known about how drugs and their metabolites in wastewater systems may be affected by biotransformation or sorption in sewer biofilms and sediments. Drug loads may also be affected by natural processes such as changes in wastewater temperature 3 , There are many advantages of the sewage methodology but it also requires further optimisation and standardization various important param-eters like sample collection and back-calculation 23 , Because there are still many areas of uncertainty, the aim of this research was to identify trends that allowed the monitoring of changes in patterns than calculating levels of DTR mass load or the numbers of illicit drug consumers. This approach makes estimation easier because the aforementioned factors do not have such significance as conducting repeated measures and sampling under the same conditions over time with a constant time interval In the present study a near-two sampling campaign was conducted at a single Wastewater Treatment Plant WWTP in Poznan, which served almost the whole city of Poznan at the time of our study. Sewage epidemiology was applied for amphetamine-like stimulants. Back-calculations from concentrations in influent wastewater to the amount of DTR mass load of illicit drug were conducted based on correction factors, flow rates, and the number of inhabitants. The samples were collected from the central wastewater treatment plant, which at that time served almost the whole city and its suburbs, a total of approximately people. Two wastewater samples 10 L each were collected twice a week, on Monday and on Wednesday, from June to December Analysis of the samples was performed on the same day, just after collection. All other reagents were acquired from J. Beker USA. Solid-phase extraction of the substances to be analyzed was performed using Bakerbond Narc-2 mixed mode cartridges, which were conditioned with methanol 2 mL , followed by deionized water 2 mL and then a phosphate buffer 2 mL, 0. When the sample was eluted under gravity, the column was washed with deionized water 2 mL , followed by hydrochloric acid 0. A vacuum was applied and the cartridges were dried for min. The analytes were eluted into a vial with a mixture of chloroform: isopropanol: ammonium hydroxide , 2 mL. The eluates of two samples each 10L were pooled and dried under a nitrogen stream. The capillary voltage was V and the temperature was 0 C, while the auxiliary and collision gas was N 2. The collision energy and tube lens were optimized for each analyte and standards separately. Identification and quantification were performed using two characteristic transitions in multiple reaction monitoring MRM mode for the fragmentation products of the protonated or deprotonated pseudomolecular ions of each substance and each deutered analogue. An 8-point calibration curve was built at 4, 8, 12, 16, 20, 24, 28, 32 ng for amphetamine, metham-phetamine, MDA and MDMA and the solutions were spiked with 30 ng of all internal standards. Validation was carried out according to Funk methodology 27 , including testing homogeneity, linearity, homogeneity of variances precision , outliers and securing the lower range limit. The matrix effect was determined by analyzing 50 mL of wastewater samples spiked with internal standards. The recoveries for the whole process of sample preparation, filtration and extraction were set within the range 0. Estimation of community drug use was done according to the method described by 2. In the case of amphetamines, the substances which are used as drug target residues DTR are the parent drugs, because all are excreted mainly as unchanged compounds. The concentrations of these substances were very low and therefore the dried residues of two untreated wastewater samples each 10L after filtration and SPE extraction were pooled and combined by re-dissolving them in the mobile phase to perform HPLC-MS-MS analysis. This value was then divided by the number of people served by WWTP to estimate the grams of DTR excreted in wastewater per person per month and finally normalized to a value of grams per month per people. Cocaine DTR mass load was originally estimated by Zuccato from the data for its major metabolite, benzylececgonine BE , so the molar ratio of 1. In the case of amphetamines, the parent drug is determined and therefore the molar ratio is 1, so the correction factor for the estimation takes into consideration only the percentage of the drug dose excreted as DTR for amphetamine this is 30, for methamphetamine 43 and for MDMA Correction factors the fraction of the consumed parent drug extracted as DTR in urine and the parent drug-to-DTR molar mass ratio were 3. Finally, the amount of illicit drugs consumed monthly by people was estimated. Time series were analyzed in order to understand the underlying structure and function that produced the observations. Understanding the mechanisms of a time series allows a mathematical model to be developed that explains the data in such a way that prediction, monitoring, or control can occur. It is assumed that a time series data set has at least one systematic pattern. The most common patterns are trends and seasonality. Trends are generally linear or quadratic. To find trends moving averages or regression analysis are often used. Seasonality is a trend that repeats itself systematically over time. A second assumption is that the data exhibits enough of a random process so that it is hard to identify the systematic patterns within the data. Time series analysis techniques often employ some type of filter to the data in order to dampen the error. Other potential patterns got to do with lingering effects of earlier observations or earlier random errors A Time Series was constructed and trend analysis was carried out to indicate any in crease or decrease tendencies. Trend analysis was performed by fitting the data to a simple linear regression and then by using smoothing in meaning of a moving average. Analysis of the correlation was performed using plots of cross-correlation. Autocorrelation refers to the correlation of a time series with its own past and future values. Time series are very complex because each observation is somewhat depending on a previous observation and often is influenced by more than one previous observation. Random errors are also influential from one observation to another. These influences are called autocorrelation— dependent relationships between successive observations of the same variable. The challenge of time series analysis is to extract the autocorrelation elements of the data, either to understand the trend itself or to model the underlying mechanisms. Time series reflect the stochastic nature of most measurements over time. Thus, data may be skewed, with meaning and variation not constant, abnormally distributed, and not randomly sampled or independent. Another abnormal aspect of time series observations is that they are often not evenly spaced in time due to instrument failure, or simply due to variation in the number of days in a month. Autocorrelation can be exploited for predictions: an auto correlated time series is predictable, probabilistically, because future values depend on current and past values. Finally, simple indices were calculated to demonstrate how the DTR mass load data may be presented in a comparative form. In order to check trends that occurred during the near-two-year monitoring of amphetamine-like substances in wastewater in Poznan. Trends analysis was performed. A time series is a set of measurements of a variable that are ordered over time. One of the aims of time series analysis is to look for a steady tendency of increase or decrease over time. Such a tendency is called a trend. The tendency may take the form of seasonality or cyclical behaviour. In Fig. It can be seen that two cyclical peaks occurred together for amphetamine, methamphet-amine and ecstasy December and March to July This is proof of the seasonality of the illicit drug DTR mass load in Poznan. It is impossible to state cyclical behaviour in a two-year study and therefore the authors omitted this subject. Figure 1 presents a fitted line with parameters of regression to each time series. We cannot give much credence to regression results but the position and regression parameters clearly indicate that the ecstasy and methamphetamine DTR mass load decreased during the period of investigation slope value In the case of amphetamine, a slight increase slope 0. Notice that the plots showed a cyclical increase and in the case of meth-amphetamine and ecstasy there was an increase in DTR mass load from October to May There are as many as five peaks a sharp increase in consumption December , March , May , September and November in the case of ecstasy, three for methamphetamine December , March , September and only two for amphetamine December , May It is important to bear in mind that the analysis did not concern values but only trends. All three amphetamine-type stimulants showed only one common peak, in December Furthermore, there were two common peaks for ecstasy and methamphetamine, in December and March , and two for amphetamine and ecstasy December and May At this point it is important to realize that linear or polynomial regression fitting is generally used for prognosis or forecasting time series. In our case it was only used for detecting a trend. There is no sense in presenting a coefficient of determination or errors for these regression lines because errors of regression models for time series may not be independent of one another and the coefficient of determination is not a reliable measure of fitting. Trend analysis does not enjoy the theoretical strengths that regression analysis does in a non-time series context. The main advantage of trend analysis is that when the model is appropriate and the data exhibit a clear trend, simple analysis may be carried out. The correlation function is an important diagnostic tool for analyzing time series in the time domain. We use an autocorrelation plot, or correlogram, to better understand the evolution of a process through time by the probability of a relationship between data values separated by a specific number of time steps. A correlogram plots correlation coefficients on the vertical axis, and lag values on the horizontal. Cross-correlation is a measure of the degree of the linear relationship between two time series. A high correlation between time series at a specific lag might indicate a time delay. The plots on the diagonal are a collerogram and off-diagonal elements are cross-correlation. We focused on cross correlation because a correlogram is not useful when the data contains a trend; index data at all lags will appear to be correlated because a data value on one side of the mean tends to be followed by a large number of values on the same side of the mean. A strong correlation was indicated between ecstasy and methamphetamine, especially in a lag interval from -5 to 5, which corresponds to the December -May time period. This is proof that DTR mass load ecstasy and methamphetamine is more correlated than amphetamine with ecstasy or amphetamine with metham-phetamine. Estimation of DTR mass load or the number of doses consumed per day per by wastewater analysis is quite a promising method for gathering data about the problem of illicit drugs. Analysis of illicit drugs in wastewater becomes a great tool to assist public health and law enforcement officials in identifying patterns of drug use and to reduce the harmful consequences associated with drug use. The methods used for this kind of estimation although improving, are still inaccurate. There are no proved models which could be used for comparison and calculation purposes. If such a model exists, it would be useful in the system where it was created. According to those facts, the authors put emphasis on trends that occurred during the near-two-year monitoring of amphetamine-like substances in wastewater in Poznan. In case of amphetamine a slight increase can be observed but ecstasy and methamphetamine have a decreasing tendency during the investigated period. The autocorrelation of a time series indicates that there is a correlation between ecstasy and methamphetamine consumption. We are not able to compare these results with the results of other authors cited in this paper, because trends analysis has not been done by them 1 , 5 — We can compare only the DTR mass loads of analyzed illicit drugs what is presented in Table 2 It is very difficult to compare the results because of the differences within the whole methodology itself sampling for instance or back- calculation the data of the population. Amphetamines-group substances consumption. Comparison with previously all published data for Europe. Based on the trends analysis we can also observe the sharp increase in some months, like December or May which could be caused by end-of-term exams at Poznan universities. If we want to describe the relative change of DTR mass load, we can construct a simple index of DTR mass load, that is, a number that measures the changes in a set of measurements over time. The index for any month during monitoring period is defined as follows:. It is very important to understand that a change in the index from period to period may not be interpreted as a percentage except when one of the two periods is the base period. Table 1 shows the months, the values of DTR mass load and DTR mass load index for amphetamine, methamphetamine and ecstasy from June to December Using indexes makes it possible to compare the DTR mass load of amphetamines with various correction coefficients resulting from a different molar ratio and pharma-cokinetics. It can be seen that the indexes of methamphetamine and ecstasy smoothly decrease; the index of amphetamine shows more variation than the others but seems not to change or increase smoothly. Looking at Table1, it is clear that in December and May the value of the DTR mass load index for amphetamine stood at over compared with June The indexes were made on the basis of the first June period. As time passes, the relevance of any base period in the past decreases in terms of comparison with values in the present. Therefore, it is sometimes useful to change the base period and move it closer to the present. There is a simple way of changing the base period of an index. We need to change the index number of the new base period so that it will equal and change all other numbers using the same operation. Thus we divide all numbers in the index by the index value of the proposed new base period and multiply by Using indices of DTR mass load instead of values of DTR mass load makes data more comparable and much clearer to interpret. The form of index seems to be a more comfortable tool to assist public health and law enforcement officials in identifying patterns of drug use across municipalities of all size. The application of wastewater analysis to the investigation of illicit drug use represents an innovative approach to the monitoring of this problem. Many scientific works about wastewater analysis have been published in journals over last ten years. Many of them focused on estimating the DTR mass load or number of illicit drug users. Maximum effort is put into accuracy and effective estimation, and each year, this estimation becomes more and more reliable. In this work, the authors placed greater emphasis on trends occurring during the near-two-year monitoring of wastewater. Looking for trends in DTR mass load figures is probably devoid of uncertainties that occur during estimation data, such as DTR mass load per day month, number of consumers etc. Carrying out a trend analysis requires these to be estimated, but in fact the most important task is to maintain the invariable and repeatable condition of sampling and analysis. Monitoring amphetamine-like substances in wastewater at the Poznan Wastewater Treatment Plant indicated a decrease in the DTR mass load of ecstasy and methamphetamine and a slight increase in amphetamine DTR mass load. Cross-correlation analysis showed a correlation between methamphetamine and ecstasy and a lack of correlation between amphetamine and others. Data filtered by a moving average revealed that from June to September the DTR mass load had increased to a great extent in terms of ecstasy and methamphetamine and less in the case of amphetamine. It followed a decrease after the plateau phase from September to March in the case of methamphetamine and July in the case of ecstasy. Although it would be very valuable, it is not possible to compare these results with previous research 1 - 5 , 13 because they carried out a daily quantification in the short term, while our research was focused on monthly DTR mass load in a long time period, which was required by the authorities given in the acknowledgements. The authors declare that there is no conflict of interests. As a library, NLM provides access to scientific literature. Iran J Public Health. Received Nov 26; Accepted Jan 9. Open in a new tab. Similar articles. Add to Collections. Create a new collection. Add to an existing collection. Choose a collection Unable to load your collection due to an error Please try again. Add Cancel.
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Trends of Amphetamine Type Stimulants DTR Mass Load in Poznan Based on Wastewater Analysis
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Trends of Amphetamine Type Stimulants DTR Mass Load in Poznan Based on Wastewater Analysis
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