Drug Abuse Detection Research Articles

Rapid Detection Technology for Cocaine and Methamphetamine Acute Abuse based on EEG

Abstract Multi-domain characterization and a new fast detection method for acute illegal psychostimulants abuse detection based on waking-state EEG of mice is proposed in this paper. To get corftical electroencephalogram (EEG), three groups of mice were injected with cocaine (Coca), methamphetamine (Meth), and saline (Sali) respectively following the experimental paradigm of drug abuse. The EEG features were extracted out by multi-domain views, including time, frequency, complexity, dynamics, and independent domains to obtain acute drug abuse effects on the brain. New strategy combing time domain with frequency domain is developed as multi-domain input and by means of dimension transformation approach preserving temporal information, the performance of drug abuse detection is greatly improved with deep learning models of ResNet50. Results show that comparing to support vector machine (SVM), k nearest neighbor (kNN), random forest (RF), and long short-term memory fully convolutional networks (LSTM-FCN), Res-Net50 based on our proposed multi-domain features has best F1-score of 95.10%. This promising method provides a low-cost, fast, and widely assisted technology for psychostimulants abuse identification.

Capture and analysis of MDMB-4en-PINACA and ADB-4en-PINACA in exhaled breath using functionalized cotton fiber: A novel approach to noninvasive drug abuse detection

Breath analysis has emerged as a promising noninvasive method for detecting drug abuse, offering potential advantages over traditional blood or urine samples. However, the capture and analysis of trace analytes in exhaled breath (EB) remains a challenge for practical applications. In this study, we explore the utilization of poly (methacrylic anhydride-co-ethylene glycol dimethacrylate)-functionalized cotton fiber (poly (MAA-co-EGDMA)-functionalized cotton fiber) for the capture of MDMB-4en-PINACA and ADB-4en-PINACA, two popular synthetic cannabinoids, from exhaled breath. Capture efficiencies of 92 % and 88 % for MDMB-4en-PINACA and ADB-4en-PINACA were achieved demonstrating robust performance across batches and excellent stability. Animal experiments were conducted and exhaled breath samples were collected and analyzed. Shorter half-lives were shown for MDMB-4en-PINACA and ADB-4en-PINACA in EB than in plasma. The detection window for MDMB-4en-PINACA was 210 min, while 150 min for ADB-4en-PINACA. This pilot study presents a novel approach for the capture of MDMB-4en-PINACA and ADB-4en-PINACA in exhaled breath using functionalized cotton fiber. The demonstrated efficacy in capturing MDMB-4en-PINACA and ADB-4en-PINACA highlights the potential of this low-cost and stable platform for noninvasive drug abuse detection. By offering a viable alternative to invasive methods, our findings demonstrate a new noninvasive method of drug abuse detection using exhaled breath holds great promise for enhancing public health efforts to combat drug abuse.

Rapid Screening of New Psychoactive Substances Using pDART-QqQ-MS.

Drug abuse is a severe social problem worldwide. Particularly, the issue of new psychoactive substances (NPSs) have increasingly emerged. NPSs are structural or functional analogs of traditional illicit drugs, such as cocaine, cannabis, and amphetamine; these molecules provide the same or more severe neurological effects. Usually, immunoassays are utilized in the preliminary screening method. However, NPSs have poor detectability in commercially available immunoassay kits. Meanwhile, various chromatography combined with the mass spectrometry platform have been developed to quantify NPSs. Still, a significant amount of time and resources are required during these procedures. Therefore, we established a rapid analytical platform for NPSs employing paper-loaded direct analysis in real time triple quadrupole mass spectrometry (pDART-QqQ-MS). We implemented this platform for the semiquantitative analysis of forensic drug tests in urine. This platform significantly shrinks the analytical time of a single sample within 30 s and requires a low volume of the specimen. The platform can detect 21 NPSs in urine mixtures at a lower limit of qualification of concentration ranging from 20 to 75 nanograms per milliliter (ng mL-1) and is lower than the cutoff value of currently available immune-based devices for detecting multiple drugs (1000 ng mL-1). Urine samples from drug addicts have been collected to verify the platform's effectiveness. By combining efficiency and accuracy, our platform offers a promising solution for addressing the challenges posed by NPSs in drug abuse detection.

Development of an analytical system for dried blood spots for forensic toxicology: a case study of five common drugs and poisons

Dried blood spot (DBS) technology is a simple and convenient method for collecting, transporting, and storing blood samples on filter paper, and has numerous applications in the clinical, research, and public health settings. This technique is gaining popularity in the field of forensic science because it facilitates the rapid analysis of prohibited drugs in blood samples and offers significant advantages in toxicology scenarios such as drinking-driving screening, drug abuse detection, and doping detection. However, the lack of a standardized system and the fact that its stability and reliability have not been thoroughly researched and demonstrated limit its application in judicial practice in China. DBS samples can be prepared, stored, and analyzed in various ways, all of which may significantly affect the results. In this study, we developed a method based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) that focuses on the preparation, pretreatment, analysis, and storage of DBS samples. A thorough investigation was conducted to examine the optimal preparation conditions, including the blood spot matrix, drying technique, and preprocessing parameters, such as the solvent and extraction method. Moreover, the analytical conditions, such as the mobile phase system and elution gradient, were established to facilitate the quantitative detection of methamphetamine, lidocaine, ketamine, fentanyl, and diazepam in both DBS and whole-blood samples. The impact of storage conditions, such as the temperature, humidity, and sealing, on the analytical results of the DBS and whole-blood samples was also examined. The results showed a strong linear relationship for lidocaine and fentanyl within the range of 0.5-100 ng/mL. Similarly, methamphetamine, ketamine, and diazepam exhibited good linearity within the range of 2-100 ng/mL. The coefficients of determination (r2) ranged from 0.9983 to 0.9997, and the limits of detection ranged from 0.2 to 0.5 ng/mL, indicating a high degree of correlation and sensitivity. Stability tests demonstrated that the five target substances remained stable in the DBS for 60 days, with the measured contents deviating from the nominal values by 15%. Moreover, the measurement results of the DBS samples were highly similar to those of the whole-blood samples, with mean percentage differences of 4.44%, 3.50%, 7.66%, 5.10%, and 5.25% for fentanyl, diazepam, ketamine, lidocaine, and methamphetamine, respectively. Throughout the 60-day storage period, the maintenance of temperatures of -20 and 4 ℃, as well as sealing and dry storage, was not necessary. Room temperature was the most practical storage environment for the DBS samples. The results for each target showed very small concentration differences between the whole-blood and DBS samples, indicating that the DBS samples were suitable for drug and poison analysis in blood. Furthermore, the DBSs exhibited high quantitative consistency with the whole-blood samples, rendering them suitable matrices for preserving blood samples. Because DBS samples are easy to handle and store, they can realize the lightweight preservation of blood samples and provide a novel solution for the analysis and preservation of blood samples in public security practice. We recommend conducting comprehensive validations before utilizing DBS for analysis, particularly in terms of quantification, to ensure the judicial reliability of the results.

Sensors in the Detection of Abused Substances in Forensic Contexts: A Comprehensive Review.

Forensic toxicology plays a pivotal role in elucidating the presence of drugs of abuse in both biological and solid samples, thereby aiding criminal investigations and public health initiatives. This review article explores the significance of sensor technologies in this field, focusing on diverse applications and their impact on the determination of drug abuse markers. This manuscript intends to review the transformative role of portable sensor technologies in detecting drugs of abuse in various samples. They offer precise, efficient, and real-time detection capabilities in both biological samples and solid substances. These sensors have become indispensable tools, with particular applications in various scenarios, including traffic stops, crime scenes, and workplace drug testing. The integration of portable sensor technologies in forensic toxicology is a remarkable advancement in the field. It has not only improved the speed and accuracy of drug abuse detection but has also extended the reach of forensic toxicology, making it more accessible and versatile. These advancements continue to shape forensic toxicology, ensuring swift, precise, and reliable results in criminal investigations and public health endeavours.

The Effect of Some Adulterants on Drug Abuse Detection by Immunoassay Test Strips

The Effect of Some Adulterants on Drug Abuse Detection by Immunoassay Test Strips

Determination of Nine Fentanyl Drugs in Hair Samples by GC-MS/MS and LC-MS/MS.

We established GC-MS/MS and LC-MS/MS analysis methods for nine fentanyl drugs in hair samples. Human hairs were prepared by soaking in a solution of water-dimethyl sulfoxide with target analytes. The drugs were norfentanyl, acetyl fentanyl, para-fluorofentanyl, isobutyryl fentanyl, fentanyl, thiofentanyl, 4-fluoroisobutyr fentanyl, ocfentanil, and tetrahydrofuran fentanyl. For a single-factor experiment, a Box–Behnken design-response surface was used to optimize the pretreatment conditions of samples. The prepared samples were quantitatively analyzed by GC-MS/MS and LC-MS/MS. The working curve method was used for quantitative analysis with fentanyl-D5 as the internal standard. The concentrations of the nine fentanyl drugs in the samples were 1.488–6.494 ng mg–1, RSDs < 5.0%. For GC-MS/MS, the linear range of the nine fentanyl drugs was 0.5–5.0 ng mg–1, r2 > 0.999. The detection limits were 0.02–0.05 ng mg–1, and the recovery rates were >86%. For LC-MS/MS, the nine fentanyl drugs had an excellent linear relationship within the concentration range of 3.0–220.0 pg mg–1, r2 > 0.999. The detection limits were 0.05 pg mg–1 and the recovery rates were >84%. The established methods were used for the detection of fentanyl drugs in human hairs, with high sensitivity, accuracy, and specificity. These two methods can be used for the certification of fentanyl certified reference substances (CRMs). In the experiment, the developed hair CRMs, which will continue to be studied in the future, are expected to be used in forensic drug abuse detection.

An Ensemble Deep Learning Model for Drug Abuse Detection in Sparse Twitter-Sphere.

As the problem of drug abuse intensifies in the U.S., many studies that primarily utilize social media data, such as postings on Twitter, to study drug abuse-related activities use machine learning as a powerful tool for text classification and filtering. However, given the wide range of topics of Twitter users, tweets related to drug abuse are rare in most of the datasets. This imbalanced data remains a major issue in building effective tweet classifiers, and is especially obvious for studies that include abuse-related slang terms. In this study, we approach this problem by designing an ensemble deep learning model that leverages both word-level and character-level features to classify abuse-related tweets. Experiments are reported on a Twitter dataset, where we can configure the percentages of the two classes (abuse vs. non abuse) to simulate the data imbalance with different amplitudes. Results show that our ensemble deep learning models exhibit better performance than ensembles of traditional machine learning models, especially on heavily imbalanced datasets.

Тестирование системы образования на наркотики: проблемное поле

The article focuses on the role of the education system in monitoring the health of the younger generation, and in particular, on the methodological issues of studying the psychological well-being and drug use among students. The subject of detecting and preventing drug use in the education system has traditionally attracted the attention of the professional community. The Herzen State Pedagogical University of Russia participated in the approbation procedures for the new method of the National Socio-Psychological Screening, recommended by the State Policy Department of Higher Education and Youth Policy of the Ministry of Education and Science of the Russian Federation in 2018. In addition, the University has conducted an annual internal screening in order to assess the students’ psychological well-being, which included scales for drug use assessment. The outcomes of the screenings made it possible to formulate a number of recommendations for the development of a program for detecting drug use in the education system. This paper presents these recommendations. The issues discussed in the article concern legal regulations in the sphere of control over teenage deviance in the education system, the principles of organising a system of drug abuse detection, and the conceptual issues of drug abuse prevention. The paper quotes the results of the student screening that prove the necessity to develop a system of measures to protect students’ psychological well-being which should provide the foundation for solving the problem of drug use. The authors also assess of the organisational costs and time expenditure required for an educational institution to conduct a comprehensive mandatory screening, as provided for by the common methodology of the National Socio-Psychological Screening.

Wearable Fluid Capture Devices for Electrochemical Sensing of Sweat.

Wearable sensing technologies are vital for realizing personalized health monitoring. Noninvasive human sweat sampling is essential for monitoring an individual's physical state using rich physiological data. However, existing wearable sensing technologies lack the controlled capture of body sweat and in performing on-device measurement without inflammatory contact. Herein, we report the development of a wearable sweat-capture device using patterned graphene arrays with controlled superwettability and electrical conductivity for simultaneously capturing and electrochemically measuring sweat droplets. The sweat droplets exhibited strong attachment on the superhydrophilic graphene patterns, even during moderate exercising. The captured sweat droplets present strong electrochemical signals using graphene films as the working electrode and metal pins as the counter electrode arrays assembled on 3D printed holders, at the detection limit of 6 μM for H2O2 sensing. This research enables full-body spatiotemporal mapping of sweat, which is beneficial for a broad range of personalized monitoring applications, such as drug abuse detection, athletics performance optimization, and physiological wellness tracking.

Wearables technology for drug abuse detection: A survey of recent advancement

Abstract Wearable sensors have gathered tremendous interest for a plethora of applications, yet there is a void of robust and accurate wearable systems for reliable drug monitoring. Wearables can be found in many different form factors and physiologic monitoring capabilities. Due to their compact size, wearables can easily adjust to various computer and accessibility requirements for a wide range of applications. Recent work has demonstrated the feasibility wearable sensors to non-invasively detect drugs, specifically drugs of abuse. This review highlights the recent development of wearables for continuous drug monitoring. The article presents a comprehensive survey and classification of different methods, research prototypes and commercially available devices. For each method we review the pros and cons, characteristics that promote flexibility, scalability, real-time applications, and eventually autonomous system architecture.

Development of new method of drug abuse detection based brain computer interface

A methods of drugs abuse detection is urgently needed. Currently a conventional method such as urine test, hair test, Functional Magnetic Resonance Imaging, Positron Emission Tomography, and others are used. Those methods, instead of expensive and complicated, it is require a medical experts. Furthermore, this tool cannot be used to detect new variations of drug. In this study, a new method of drugs abuse detection based brain computer interface (BCI) which recorded with an electroencephalogram is developed. In principle, as long as the subject is still be able to remember, then the tool will be able to detect whether ever use a drug or not. In the experiment 15 subjects are tested. In the signal processing, the EEG signal is filtered with baseline correction and band-pass filter and extracted using wavelet symlet method. The brain maps of damaged brains are in sharp contrast to those of brains which have not been subjected to drug abuse. This studies could be used to identify drug abusers and alternative tool for rehabilitation.

Bioanalytical devices: Technological leap for sweat sensing.

Sweat analysis is an ideal method for continuously tracking a person's physiological state, but developing devices for this is difficult. A wearable sweat monitor that measures several biomarkers is a breakthrough. See Letter p.509 Human sweat is attracting attention as a carrier of biomarkers of potential diagnostic importance, as well as in drug abuse detection and athletic performance optimization. In particular, sweat is much more tractable than other body fluids for continuous bio-monitoring. This paper presents a fully integrated flexible sensor platform for sweat analysis, based on existing technologies. Ali Javey and colleagues successfully connect plastic-based skin sensors to conventional silicon integrated circuitry to achieve multiple simultaneous measurement of sweat metabolites (glucose and lactate) and electrolytes (sodium and potassium). Skin temperature was measured to provide in situ calibration of the sensors. A small cohort human subject validation was performed to demonstrate the practical value of the platform — and a specially designed Android app created — for real-time assessment of physiological status, either as a wristband or forehead patch.

Effects of morphine on pupillary light reflex in monkeys

The pupil size of both human and other animals can be affected by light. Many kinds of psychiatrical and psychological disorders, such as drug abuse, associate with abnormal properties of pupillary light reflex. Thus, the properties of pupillary light reflex could serve as an indicator for drug abuse detection. However, the effect of drug abuse on pupillary light reflex is till unclear. To assess the effects of addictive drugs on pupillary light reflex quantificationally, in the present study, we examined the effects of morphine on pupil diameter and pupillary light reflex in rhesus monkeys. By measuring the pupil diameter at different timing points before and after the administration of morphine, we found that morphine administration reduced the diameter of pupil and decreased the constriction rate. Our present results provide an experimental support for applying the properties of pupillary light reflex as a reference in addicts' detection.

Hair Analysis as Method for Determination of Level of Drugs and Pharmaceutical in Human Body: Review of Chromatographic Procedures

Interest in hair analysis as an alternativ or complementary approach to urinalysis for drug abuse detection has grown in recent years. Hair analysis can be particularly advantageous for drugs and their enantiomers. More than hundred pharmaceuticals, drugs of abuse agents are reported to be detectable in human and animal hair. This article reviews the aalysis of drugs and drug metabolites by chromatographic procedures, incuding the pretreatment steps, and the xtraction methods. Tihe eneral tendency in the last years, to highly sophisticated techiques gas chromatography–mass spectrometry (GC–MS–NCI), high pressure liquid chromatography–mass spectrometry (HPLC–MS), gas chromatography–mass spectrometry–mass spectrometry (GC–MS–MS) well illustrates this constant fight for sensitivity.

Liquid chromatographic method for the determination of enantiomeric composition of amphetamine and methamphetamine in hair samples

Interest in hair analysis as an alternative or complementary approach to urinalysis for drug abuse detection has grown in recent years. Hair analysis can be particularly advantageous for drugs such as amphetamine and methamphetamine that are rapidly excreted. Confirmation of abuse of these stimulants is complicated by the fact that some forms are found in legitimate medications. Examination of the enantiomeric composition of amphetamine and methamphetamine in hair samples can provide valuable assistance in interpreting drug testing results. In this work, we developed a liquid chromatographic method for the separation of amphetamine and methamphetamine enantiomers isolated from human hair samples. The drug enantiomers were separated on a chiral stationary phase after derivatization with an achiral fluorescent agent. The methodology was evaluated with a Standard Reference Material that contained several drugs of abuse including amphetamine and methamphetamine.