Simultaneous determination of 137 drugs of abuse, new psychoactive substances, and novel synthetic opioids in meconium by UHPLC-QTOF

New psychoactive substances (NPS) have been introduced into the market in recent years, with new analytes reported every year. The use of these substances in women can occur at any stage of life, even in the childbearing age. Drug use during pregnancy presents significant risks for the mother and the fetus, so it is important to have tools that allow to detect prenatal exposure to these substances of abuse. Therefore, an analytical method for the determination of 137 NPS and other drugs of abuse in meconium by UHPLC-QTOF was developed and validated for semi-quantitative purpose. Linearity range, limit of detection (LOD), precision, matrix effect, selectivity, and specificity were evaluated. For all analytes, the calibration curves were studied in the ranges between 2, 10, or 50 ng/g and 750 or 1000 ng/g, (depending on the analyte) and the LOD ranged between 0.04 and 2.4 ng/g. The method was applied to 30 meconium specimens from cases in which fentanyl had been administered as epidural anesthesia at the time of delivery or cases in which the maternal hair was positive to other drug of abuse. Four meconium samples tested positive for fentanyl (range concentration = 440-750 ng/g) and two samples tested positive to acetylfentanyl (range concentration = 190-1400 ng/g).

Seizures of New Psychoactive Substances on the Italian territory during the COVID-19 pandemic

In recent years, the availability and the consequent consumption of New Psychoactive Substances (NPS) have proliferated at an unprecedented rate, posing a significant risk to the public health and challenging the law enforcement efforts to tackle the black market. In particular, large availability on Internet and unmonitored shipping have facilitated the diffusion of NPS on national territories. In this scenario, the forensic activity based on the process of drug detection, including investigation, seizure, recognition and analytical identification is crucial to get insights into the drug black market transformation. In this study, we describe the results obtained from the analysis of hundreds of packages seized during the months of year 2020, and suspected to contain NPS because not reacting with standard field test kits. We focused on the analysis by GC-MS and HPLC-HRMS, and NPS in particular, trying to underline the most common molecules present on the Italian territory during the COVID-19 pandemic. NPS were identified in 92.6% of the samples. The most prevalent compounds were synthetic cathinones, and 3-MMC in particular, which alone accounted for 18.6% of the total cases. Other prevalent molecules were 5F-MDMB-PICA, 2-FDCK, 1cp-LSD and 1P-LSD. Fentanyl was never detected. The information obtained from drug seizures is crucial to publish national alerts, which are in turn important to assist the legislative effort to ban new compounds and the update of toxicological and analytical methods.

Patterns of Routes of Administration and Drug Tampering for Nonmedical Opioid Consumption: Data Mining and Content Analysis of Reddit Discussions

Background

The complex unfolding of the US opioid epidemic in the last 20 years has been the subject of a large body of medical and pharmacological research, and it has sparked a multidisciplinary discussion on how to implement interventions and policies to effectively control its impact on public health.

Objective

This study leverages Reddit, a social media platform, as the primary data source to investigate the opioid crisis. We aimed to find a large cohort of Reddit users interested in discussing the use of opioids, trace the temporal evolution of their interest, and extensively characterize patterns of the nonmedical consumption of opioids, with a focus on routes of administration and drug tampering.

Methods

We used a semiautomatic information retrieval algorithm to identify subreddits discussing nonmedical opioid consumption and developed a methodology based on word embedding to find alternative colloquial and nonmedical terms referring to opioid substances, routes of administration, and drug-tampering methods. We modeled the preferences of adoption of substances and routes of administration, estimating their prevalence and temporal unfolding. Ultimately, through the evaluation of odds ratios based on co-mentions, we measured the strength of association between opioid substances, routes of administration, and drug tampering.

Results

We identified 32 subreddits discussing nonmedical opioid usage from 2014 to 2018 and observed the evolution of interest among over 86,000 Reddit users potentially involved in firsthand opioid usage. We learned the language model of opioid consumption and provided alternative vocabularies for opioid substances, routes of administration, and drug tampering. A data-driven taxonomy of nonmedical routes of administration was proposed. We modeled the temporal evolution of interest in opioid consumption by ranking the popularity of the adoption of opioid substances and routes of administration, observing relevant trends, such as the surge in synthetic opioids like fentanyl and an increasing interest in rectal administration. In addition, we measured the strength of association between drug tampering, routes of administration, and substance consumption, finding evidence of understudied abusive behaviors, like chewing fentanyl patches and dissolving buprenorphine sublingually.

Conclusions

This work investigated some important consumption-related aspects of the opioid epidemic using Reddit data. We believe that our approach may provide a novel perspective for a more comprehensive understanding of nonmedical abuse of opioids substances and inform the prevention, treatment, and control of the public health effects.

The Impact of COVID-19 Pandemic and Lockdown on Alcohol Consumption: A Perspective From Hair Analysis

Introduction and Aims: The increase in stress levels, social confinement, and addiction's physical consequences play an essential role in the proliferation of drug abuse. In this context, the Covid-19 pandemic produced remarkable effects on those individuals prone to addictions, especially to alcohol. Alcohol is linked to multiple dangerous conditions such as social issues, severe medical conditions, and road accidents. The determination of ethylglucuronide (EtG) in hair is frequently performed to test and monitor chronic excessive alcohol intake conditions, as it allows differentiation among low-risk/moderate drinkers, and excessive/chronic drinkers. Our study aimed to explore hair EtG levels in a controlled population to assess the impact of Covid-19 lockdown on alcohol intake along March-May 2020. Materials and Methods: EtG levels were measured in all hair samples collected in the months following April 2020 to evaluate the behaviors related to alcohol intake along with the time frame from March to May 2020. The measured concentration distributions for each month were compared with those reported in the same month during the previous 4 years (2016-2019). The dataset was built to highlight possible differences between genders, and the different categories of alcohol consumption, separately. Results: The samples collected from April to August 2020 (500 < N <1,100 per month) showed an increase in the percentage of subjects classified as abstinent/low-risk drinkers (from 60 up to 79%) and a decrease of subjects classified as moderate and chronic drinkers (-12 and -7%, respectively) when compared to the previous 4 years. A decrease in the overall mean value of EtG in the period April-June 2020 was observed, while the EtG levels of both June and July 2020 provided an increasing trend for chronic/excessive consumers (+27 and +19% for June and July 2020, respectively). A peculiar rise in the EtG levels of moderate and chronic/excessive female consumers was observed along April-June 2020, too. Discussion and Conclusions: Behavioral and social studies generally report a decrease in alcohol consumption during the Covid-19 lockdown. However, people already suffering from drug or alcohol addictions before Covid-19 pandemic seemingly enhance their harmful behavior. Our data from April to August 2020 are consistent with both suppositions. Our observations confirm once again the utility of EtG to investigate the patterns of alcohol consumption in the population.

Determination of cannabinoids in urine, oral fluid and hair samples after repeated intake of CBD-rich cannabis by smoking

Cannabidiol prevalent (CBD-rich) cannabis derivatives are increasingly popular and widely available on the market as replacement of THC, tobacco substitutes or therapeutics for various health conditions. In this paper, we evaluate the impact of a repeated CBD-rich cannabis intake on levels of cannabinoids in biological samples. Urine, oral fluid and hair (pubic and head) samples were obtained from a naive user during a 26-day smoking period of one 250-mg CBD-rich cannabis joint/day containing 6.0% cannabidiol (CBD; 15mg) and 0.2% delta-9-tetrahydrocannabinol (THC; 0.5mg). In total, 35 urine, 8 oral fluid and 4hair sample were collected. Cannabinoids concentrations were quantified by a UHPLC/MSⁿ technique. The results suggested that the repeated exposure to CBD-rich cannabis (containing small amounts of THC) can generate positive results in biological samples. Urinary concentrations of 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH) were quantitatively detected after 8 days from the smoking start and exceeded the 15ng/mL cut-off limit on day-15 even in the urine sample collected 12h after the last intake. In the oral fluid collected on day-26, no cannabinoids were found before the cannabis intake, thus excluding accumulation, while THC was detectable up to 3h after the cannabis intake, at concentrations progressively decreasing from about 18 to 6ng/mL. Hair samples collected one week after the end of the study turned out negative for THC and THC-COOH, suggesting that this matrix is suitable to discriminate the chronic consumption of CBD-rich cannabis from THC-prevalent products. The obtained findings are relevant for the interpretations of cannabinoids levels in biological fluids, also in light of the legal implications of a positive result.

Targeted and untargeted detection of fentanyl analogues and their metabolites in hair by means of UHPLC-QTOF-HRMS

Detection of new psychoactive substances and synthetic opioids is generally performed by means of targeted methods in mass spectrometry, as they generally provide adequate sensitivity and specificity. Unfortunately, new and unexpected compounds are continuously introduced in the illegal market of abused drugs, preventing timely updating of the analytical procedures. Moreover, the investigation of biological matrices is influenced by metabolism and excretion, in turn affecting the chance of past intake detectability. In this scenario, new opportunities are offered by both the non-targeted approaches allowed by modern UHPLC-HRMS instrumentation and the investigation of hair as the matrix of choice to detect long-term exposure to toxicologically relevant substances. In this study, we present a comprehensive and validated workflow that combines the use of UHPLC-QTOF-HRMS instrumentation with a simple hair sample extraction procedure for the detection of a variety of fentanyl analogues and metabolites. A simultaneous targeted and untargeted analysis was applied to 100 real samples taken from opiates users. MS and MS/MS data were collected for each sample. Data acquisition included a TOF-MS high-resolution scan combined with TOF-MS/MS acquisition demonstrating considerable capability to detect expected and unexpected substances even at low concentration levels. The predominant diffusion of fentanyl was confirmed by its detection in 68 hair samples. Other prevalent analogues were furanylfentanyl (28 positive samples) and acetylfentanyl (14 positive samples). Carfentanil, methylfentanyl, and ocfentanil were not found in any of the analyzed samples. Furthermore, the retrospective data analysis based on untargeted acquisition allowed the identification of two fentanyl analogues, namely β-hydroxyfentanyl and methoxyacetylfentanyl, which were not originally included in the panel of targeted analytes.

Cannabis knowledge and implications for health: Considerations regarding the legalization of non-medical cannabis

Cannabis contains over a hundred of different cannabinoids, of which Δ⁹-tetrahydrocannabinol (THC) and cannabidiol (CBD) are the most well studied. The use of high-potency cannabis, containing high concentrations of THC and low concentrations of CBD, has been linked to adverse health outcomes, particularly for adolescents and young adults. Recently, an increase in cannabis potency has been observed in jurisdictions that legalized the sale of cannabis for non-medical purposes. Moreover, an increase of cannabis use and cannabis-related emergency treatment have also been observed in these jurisdictions. At the same time, risk perception regarding cannabis use has decreased in these populations. Trivializing language and an increased appearance of commercial cannabis in the public space may lead to a generalized underestimation of the risks of cannabis use. New regulation models principally focus on the creation of a legal cannabis market economy, the diversion of profits from illegal markets, and the reduction of costs associated with prohibition. However, an approach that specifically focuses on the rights to the health and safety of the individual should be considered in order to reduce the risks associated with cannabis legalization. Such an approach should promote and protect individual and social health and safety, establish a strict quality control of legal cannabis products regulated according to THC and CBD content, and eliminate all sorts of incentives to use, thus providing a more consistent, sustainable, and ethical framework for the legalization of non-medical cannabis use.

Toward the Interpretation of Positive Testing for Fentanyl and Its Analogs in Real Hair Samples: Preliminary Considerations

The detection of new psychoactive substances (NPS) in hair has become extensively researched in recent years. Although most NPS fall into the classes of synthetic cannabinoids and designer cathinones, novel synthetic opioids (NSO) have appeared with increasing frequency in the illicit drug supply. While the detection of NSO in hair is now well documented, interpretation of results presents several controversial issues, as is quite common in hair analysis. In this study, an ultra-high-performance liquid chromatography-tandem mass spectrometry method able to detect 13 synthetic opioids (including fentanyl analogs) and metabolites in hair was applied to 293 real samples. Samples were collected in the USA between November 2016 and August 2018 from subjects who had reported heroin use in the past year or had already tested positive to hair testing for common opiates. The range, mean and median concentrations were calculated for each analyte, in order to draw a preliminary direction for a possible cut-off to discriminate between exposure to either low or high quantities of the drug. Over two-thirds (68%) of samples tested positive for fentanyl at concentrations between LOQ and 8600 pg/mg. The mean value was 382 pg/mg and the median was 95 pg/mg. The metabolites norfentanyl and 4-ANPP were also quantified and were found between LOQ and 320 pg/mg and between LOQ and 1400 pg/mg, respectively. The concentration ratios norfentanyl/fentanyl, 4-ANPP/fentanyl and norfentanyl/4-ANPP were also tested as potential markers of active use and to discriminate the intake of fentanyl from other analogs. The common occurrence of samples positive for multiple drugs may suggest that use is equally prevalent among consumers, which is not the case, as correlations based on quantitative results demonstrated. We believe this set of experimental observations provides a useful starting point for a wide discussion aimed to better understand positive hair testing for fentanyl and its analogs in hair samples.

Shifts in Unintentional Exposure to Drugs Among People Who Use Ecstasy in the Electronic Dance Music Scene, 2016-2019

BACKGROUND AND OBJECTIVES

Electronic dance music (EDM) party attendees who use ecstasy (3,4-methylenedioxymethamphetamine [MDMA], Molly) are at high risk for ingesting adulterant drugs, but little is known regarding trends in exposure. We sought to determine whether adulteration has shifted in recent years.

METHODS

Adults entering EDM events at nightclubs and dance festivals in NYC were surveyed in 2016 and 2019. We tested hair samples from a subsample of those reporting past-year ecstasy use using ultra-high performance liquid chromatography-tandem mass spectrometry. Differences in unreported drug exposure and suspected adulteration were compared between 2016 (n = 90) and 2019 (n = 72).

RESULTS

MDMA detection was stable at 72-74%. We detected decreases in unreported use of methamphetamine (from 22.2% to 5.6% [P = .003], an 74.8% decrease), new psychoactive substances (from 31.1% to 2.8% [P < .001], a 91.0% decrease), and synthetic cathinones in particular (from 27.8% to 2.8% (P < .001, an 89.9% decrease). Unreported ketamine exposure increased from 18.9% to 34.7% (P = .022, an 83.6% increase). We also detected decreases in participants' suspicion of their ecstasy being adulterated with methamphetamine (from 20.0% to 5.6% [P = .010], an 72.0% decrease) and "bath salts" (synthetic cathinones, from 8.9% to 1.4% [P = .044], an 84.3% decrease).

DISCUSSION AND CONCLUSIONS

Unknown exposure to adulterants among people who use ecstasy in the EDM scene is shifting. Monitoring of exposure to adulterants is needed to inform harm reduction.

SCIENTIFIC SIGNIFICANCE

This was among the first studies to examine unintentional exposure to drugs over time in this population and unintentional exposure to synthetic cathinones in particular appears to be declining. (Am J Addict 2021;30:49-54).

Optimization and validation of a GC-MS quantitative method for the determination of an extended estrogenic profile in human urine: Variability intervals in a population of healthy women

An analytical method based on GC-MS was developed for the determination of a wide panel of urinary estrogens, together with their principal metabolites. Because of the low concentration of estrogens in urine, an efficient sample pre-treatment was optimized by a design of experiment (DoE) procedure to achieve satisfactory sensitivity. A second DoE was built for the optimization of the chromatographic run, with the purpose of reaching the most efficient separation of analytes with potentially interfering ions and similar chromatographic properties. The method was fully validated using a rigorous calibration strategy: from several replicate analyses of blank urine samples spiked with the analytes, calibration models were built with particular attention to the study of heteroscedasticity and quadraticity. Other validation parameters, including the limit of detection, intra-assay precision and accuracy, repeatability, selectivity, specificity, and carry-over, were obtained using the same set of data. Further experiments were performed to evaluate matrix effect and extraction recovery. Then the urinary estrogen profiles of 138 post-menopausal healthy women were determined. These profiles provide a representation of physiological concentration ranges, which, in forthcoming studies, will be matched on the base of multivariate statistics with the urinary estrogenic profile of women with breast or ovarian cancer.

Underreporting of drug use among electronic dance music party attendees

BACKGROUND AND OBJECTIVES

Electronic dance music (EDM) party attendees are at high risk for drug use. However, little is known regarding the extent of underreporting of drug use in this population, in part, because use of synthetic drugs is often associated with unknown exposure to adulterant drugs. We estimated the extent of underreported drug use in this population by comparing self-reported use to hair toxicology results.

METHODS

Time-space sampling was used to survey adults entering EDM events at nightclubs and dance festivals in New York City from January through August of 2019. Seven hundred ninety-four adults were surveyed and 141 provided analyzable hair samples. We queried past-year use of >90 drugs and tested hair samples using ultra-high performance liquid chromatography-tandem mass spectrometry. We compared hair test results to past-year self-reported use and adjusted prevalence estimates by defining use as reporting use or testing positive. Correlates of discordant reporting, defined as testing positive after not reporting use, were estimated.

RESULTS

Prevalence of drug use increased when considering positive hair tests in estimates, with 43.8% of participants testing positive for at least one drug after not reporting use. For example, based on self-report, cocaine use prevalence was 51.1%, and increased by a factor of 1.6 to a prevalence of 80.0% when adding hair test results to self-report. Younger adults (ages 18-25), black and other/mixed race participants, those reporting "other" sexuality, and those with a college degree were at significantly higher risk for testing positive for drugs not reportedly used. Those who self-reported using more types of drugs were less likely to test positive after not reporting use (adjusted prevalence ratio = 0.53, 95% confidence interval = 0.41-0.68).

CONCLUSIONS

We detected underreporting of drug use, particularly cocaine and ketamine. More research is needed to determine whether this is driven by intentional underreporting or unknown exposure through adulterants.

Experimental and statistical protocol for the effective validation of chromatographic analytical methods

The validation of analytical methods is of crucial importance in several fields of application. A new protocol for the validation of chromatographic methods has been proposed. The overall protocol is described in a parallel paper, where the case of a multi-targeted gas chromatography – mass spectrometry (GC–MS) method for the determination of androgens in human urine is in-depth discussed. The purpose of this paper is to report the details about the GC–MS separation and detection of the target analytes, and to provide the mathematical formulas needed to perform the validation of the principal parameters. Briefly, the validation protocol foresees the repetition of three calibration curves in three different days, providing a total amount of nine replicates. Such a structured design allows to use the same experiments to•

perform a rigorous calibration study, by the evaluation of heteroscedasticity, comparison of several weights and linear/quadratic calibration curves.

•

determine several parameters which are traditionally computed from dedicated experiments, namely intra- and inter-day accuracy and precision, limit of detection, specificity, selectivity, ion abundance repeatability, and carry over.

•

Finally, few further experiments are necessary to evaluate the retention time repeatability, matrix effect and extraction recovery.

Spatial heterogeneity and socioeconomic determinants of opioid prescribing in England between 2015 and 2018

BACKGROUND

Opioid overdoses have had a serious impact on the public health systems and socioeconomic welfare of several countries. Within this broader context, we focus our study on primary care opioid prescribing in England from 2015 to 2018, particularly the patterns of spatial variations at the community level and the socioeconomic and environmental factors that drive consumption.

METHODS

Leveraging open data sources, we combine prescription records with aggregated data on patient provenance and build highly granular maps of Oral Morphine Equivalent (OME) prescribing rates for Lower Layer Super Output Areas (LSOA). We quantify the strength of spatial associations by means of the Empirical Bayes Index (EBI) that accounts for geographical variations in population density. We explore the interplay between socioeconomic and environmental determinants and prescribing rates by implementing a multivariate logistic regression model across different temporal snapshots and spatial scales.

RESULTS

We observe, across time and geographical resolutions, a significant spatial association with the presence of localized hot and cold spots that group neighboring areas with homogeneous prescribing rates (e.g., EBI = 0.727 at LSOA level for 2018). Accounting for spatial dependency effects, we find that LSOA with both higher employment deprivation (OR = 62.6, CI 52.8-74.3) and a higher percentage of ethnically white (OR = 30.1, CI 25.4-35.7) inhabitants correspond to higher prescribing rates. Looking at educational attainment, we find LSOA with the prevalent degree of education being apprenticeship (OR = 2.33, CI 1.96-2.76) a risk factor and those with level 4+ (OR = 0.41, CI 0.35-0.48) a protective factor. Focusing on environmental determinants, housing (OR = 0.18, CI 0.15-0.21) and outdoor environment deprivation (OR = 0.62, CI 0.53-0.72) indices capture the bi-modal behavior observed in the literature concerning rural/urban areas. The results are consistent across time and spatial aggregations.

CONCLUSIONS

Failing to account for local variations in opioid prescribing rates smooths out spatial dependency effects that result in underestimating/overestimating the impact on public health policies at the community level. Our study suggests a novel approach to inform more targeted interventions toward the most vulnerable population strata.

Prospective evaluation of urinary steroids and prostate carcinoma-induced deviation: preliminary results

BACKGROUND

The serum prostate-specific antigen is the most widespread biomarker for prostate disease. Its low specificity for prostatic malignancies is a matter of concern and the reason why new biomarkers for screening purposes are needed. The correlation between altered production of the main steroids and prostate carcinoma (PCa) occurrence is historically known. The purpose of this study is to evaluate the modifications of a comprehensive urinary endogenous steroidal profile (USP) induced by PCa, by multivariate statistical methods.

METHODS

A total of 283 Italian subjects were included in the study, 139 controls and 144 PCa-affected patients. The USP, including 17 steroids and five urinary steroidal ratios, was quantitatively evaluated using gas chromatography coupled with single quadrupole mass spectrometry (GC-MS). The data were interpreted using a chemometric, multivariate approach (intrinsically more sensible to alterations with respect to traditional statistics) and a model for the discrimination of cancer-affected profiles was built.

RESULTS

Two multivariate classification models were calculated, the former including three steroids with the highest statistical significance (e.g. testosterone, etiocholanolone and 7β-OH-DHEA) and PSA values, the latter considering the three steroids' levels only. Both models yielded high sensitivity and specificity scores near to 70%, resulting significantly higher than PSA alone.

CONCLUSIONS

Three USP steroids resulted significantly altered in our PCa population. These preliminary results, combined with the simplicity and low-cost of the analysis, open to further investigation of the potential role of this restricted USP in PCa diagnosis.

Individual and cyclic estrogenic profile in women: Structure and variability of the data

The concentration of estrogens in the body fluids of women is highly variable, due to the menstrual cycle, circadian oscillations, and other physiological and pathological causes. To date, only the cyclic fluctuations of the principal estrogens (estradiol and estrone) have been studied, with limited outcome of general significance. Aim of the present study was to examine in detail the cyclic variability of a wide estrogens' panel and to interpret it by multivariate statistics. Four estrogens (17α-estradiol, 17β-estradiol, estrone, estriol) and eleven of their metabolites (4-methoxyestrone, 2-methoxyestrone, 16α-hydroxyestrone, 4-hydroxyestrone, 2-hydroxyestrone, 4-methoxyestradiol, 2-methoxyestradiol, 4-hydroxyestradiol, 2-hydroxyestradiol, estriol, 16-epiestriol, and 17-epiestriol) were determined in urine by a gas chromatography - mass spectrometry method, which was developed by design of experiments and fully validated according to ISO 17025 requirements. Then, urine samples collected every morning for a complete menstrual cycle from 9 female volunteers aged 24-35 years (1 parous) were analysed. The resulting three-dimensional data (subjects × days × estrogens) were interpreted using several statistical tools. Parallel Factor Analysis compared the estrogen profiles in order to explore the cyclic and inter-individual variability of each analyte. Principal Component Analysis (PCA) provided clear separation of the sampling days along the cycle, allowing discrimination among the luteal, ovulation, and follicular phases. The scores obtained from PCA were used to build a Linear Discriminant Analysis classification model which enhanced the recognition of the three cycle's phases, yielding an overall classification non-error rate equal to 90%. These statistical models may find prospective application in fertility studies and the investigation of endocrinology disorders and other hormone-dependent diseases.

Multivariate interpretation of the urinary steroid profile and training-induced modifications. The case study of a Marathon runner

The steroidal module of the athlete biological passport (ABP) introduced by the World Anti-Doping Agency (WADA) in 2014 includes six endogenous androgenic steroids and five of their concentration ratios, monitored in urine samples collected repeatedly from the same athlete, whose values are interpreted by a Bayesian model on the basis of intra-individual variability. The same steroid profile, plus dihydrotestosterone (DHT) and DHEA, was determined in 198 urine samples collected from an amateur marathon runner monitored over three months preceding an international competition. Two to three samples were collected each day and subsequently analyzed by a fully validated gas chromatography-mass spectrometry protocol. The objective of the study was to identify the potential effects of physical activity at different intensity levels on the physiological steroid profile of the athlete. The results were interpreted using principal component analysis and Hotelling's T² vs Q residuals plots, and were compared with a profile model based on the samples collected after rest. The urine samples collected after activity of moderate or high intensity, in terms of cardiac frequency and/or distance run, proved to modify the basal steroid profile, with particular enhancement of testosterone, epitestosterone, and 5α-androstane-3α,17β-diol. In contrast, all steroid concentration ratios were apparently not modified by intense exercise. The alteration of steroid profiles seemingly lasted for few hours, as most of the samples collected 6 or more hours after training showed profiles compatible with the "after rest" model. These observations issue a warning about the ABP results obtained immediately post-competition.

Detection of Fentanyl Analogs and Synthetic Opioids in Real Hair Samples

Novel synthetic opioids include various analogs of fentanyl and emerging non-fentanyl compounds with different chemical structures, such as AH-7921, MT-45 and U-47700. In recent years, these drugs have rapidly emerged on the drug market, and their abuse has been increasing worldwide. The motivations for use of these new compounds include their legal status, ready availability, low cost, users' curiosity or preference for their particular pharmacological properties and the intention to avoid detection. Furthermore, more common drugs like heroin are now increasingly being replaced or cut with fentanyl or new designer opioids; thus, many drug users are unintentionally or unknowingly using synthetic fentanyl analogs. In this scenario, the detection of new psychoactive substances in hair can provide insight into their current diffusion among the population and social characteristics of these synthetic drug users. In this manuscript, we describe a simple, fast, specific and sensitive UHPLC-MS-MS method able to detect 13 synthetic opioids (including fentanyl analogs) and metabolites in hair samples. Furthermore, the method includes the detection of 4-anilino-N-phenethyl-piperidine (4-ANPP), which is considered both a precursor and a metabolite of several fentanyl analogs. The method was applied to 34 real hair samples collected in New York City from subjects who had reported past-year non-medical opioid and/or heroin use. In total, 17 samples tested positive for at least one target analyte, with oxycodone (nine samples) and tramadol (eight samples) being the most common. Among these, the method was able to quantify furanyl-fentanyl and fentanyl in the pg/mg range in two samples. Simultaneously, also 4-ANPP was detected, giving evidence for the first time that this compound can be selected as a marker of fentanyl analogs use via hair testing. In conclusion, this study confirmed the increasing diffusion of new synthetic opioids and "fentalogs" with high potency among non-medical opioid users.

Synthetic cathinone adulteration of illegal drugs

RATIONALE

Current prevalence estimates of synthetic cathinone ("bath salt") use may be underestimates given that traditional metrics (e.g., surveys, urinalysis) often fail to capture the emergent issue of synthetic cathinone adulteration of more common illegal drugs, such as ecstasy (3,4-methylenedioxymethamphetamine).

OBJECTIVES

This review examines the evolution of synthetic cathinones and prevalence of use over the past decade in the United States. We also review methods of self-report and biological testing of these compounds as well as adverse outcomes associated with adulterated drug use.

RESULTS

Synthetic cathinone use emerged in the United States by 2009 with use associated with tens of thousands of poisonings. Reported poisonings and self-reported use have substantially decreased over the past five years. However, our review suggests that current estimates of use are underestimates due to underreporting stemming primarily from unknown or unintentional use of adulterated formulations of relatively popular illegal drugs, such as ecstasy.

CONCLUSIONS

While intentional synthetic cathinone use has decreased in recent years, evidence suggests that prevalence of use is underestimated. Testing of drugs and/or biological specimens can improve the accuracy of synthetic cathinone use estimates. Furthermore, we advocate that researchers and clinicians should become better aware that exposure to these potent compounds (e.g., as adulterants) often occurs unknowingly or unintentionally. To improve our understanding of synthetic cathinone adulteration, research utilizing a combinatorial approach (survey and biological testing) will help more accurately estimate the prevalence and impact of this public health issue.