Chemical classification of new psychoactive substances (NPS)

Zapata, Félix; Matey, José Manuel; Montalvo, Gemma; García-Ruiz, Carmen

doi:10.1016/j.microc.2020.105877

Cited by 38 publications

(26 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Less is known about the toxicological effects of NPS. The toxic dose, clinical effects and systemic and organ response to these substances are considered obscure to this moment (Zapata et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

Acute Toxic Effects of AB-CHMINACA on Lung, Heart and Liver: An Experimental Pilot Study

Mousa

Gebri

Masoud

et al. 2021

Ain Shams Journal of Forensic Medicine and Clinical Toxicology

View full text Add to dashboard Cite

Background: Synthetic cannabinoid (SCs) substances are intended for drug addiction while they cannot be easily detected on a regular drug screen. The danger of these substances is not only being undetected, but also their health effects are not well studied and cannot be predicted. This is one of the recent major health problems that threaten populations around the world. Aim of the study: This study is an experimental study to detect the toxic effect of acute exposure to a synthetic cannabinoid substance "AB-CHMINACA' clinically and histopathologically in different organs in adult male albino rats. Material and methods: AB-CHMINACA was tested for dissolution in different solvents to choose the best vehicle. Doses were selected according to "Guidance on dose level selection for regulatory general toxicology studies for pharmaceuticals". Animals were injected intraperitoneal and after 24 hours, animals were sacrificed and the lung, heart, and liver were examined for histopathological changes. Results: AB-CHMINACA dissolves best in organic solvents like ethanol and DMSO. The most suitable vehicle for intraperitoneal injection of animals was ethanol-saline. After injection, animals showed CNS manifestations; depression or excitation followed by depression according to the dose. Histopathological examination of the lung, heart, and liver tissues showed generalized congestion, hemorrhage, inflammatory cell infiltration and degeneration, which increased by increasing the dose. Conclusion: AB-CHMINACA has toxic histopathological effects on the lung, heart, and liver on single-dose exposure even with minimal clinical manifestations. These effects are dose-related.

show abstract

Section: Discussionmentioning

confidence: 99%

Acute Toxic Effects of AB-CHMINACA on Lung, Heart and Liver: An Experimental Pilot Study

Mousa

Gebri

Masoud

et al. 2021

Ain Shams Journal of Forensic Medicine and Clinical Toxicology

View full text Add to dashboard Cite

show abstract

“…A psychoactive drug, also called a psychotropic drug, is a chemical substance that changes a person’s mental state and results in alterations in perception, mood, and/or consciousness. Based on their effects, psychoactive drugs can be classified into the three main categories of stimulants, depressants, and hallucinogens [ 214 , 215 ]. Yet, some drugs may fall under different categories at different times (for example, cannabis is both a depressant drug and a hallucinogen drug).…”

Section: State 5: Under the Influencementioning

confidence: 99%

Survey and Synthesis of State of the Art in Driver Monitoring

Halin

Verly

Droogenbroeck

2021

Sensors

View full text Add to dashboard Cite

Road vehicle accidents are mostly due to human errors, and many such accidents could be avoided by continuously monitoring the driver. Driver monitoring (DM) is a topic of growing interest in the automotive industry, and it will remain relevant for all vehicles that are not fully autonomous, and thus for decades for the average vehicle owner. The present paper focuses on the first step of DM, which consists of characterizing the state of the driver. Since DM will be increasingly linked to driving automation (DA), this paper presents a clear view of the role of DM at each of the six SAE levels of DA. This paper surveys the state of the art of DM, and then synthesizes it, providing a unique, structured, polychotomous view of the many characterization techniques of DM. Informed by the survey, the paper characterizes the driver state along the five main dimensions—called here “(sub)states”—of drowsiness, mental workload, distraction, emotions, and under the influence. The polychotomous view of DM is presented through a pair of interlocked tables that relate these states to their indicators (e.g., the eye-blink rate) and the sensors that can access each of these indicators (e.g., a camera). The tables factor in not only the effects linked directly to the driver, but also those linked to the (driven) vehicle and the (driving) environment. They show, at a glance, to concerned researchers, equipment providers, and vehicle manufacturers (1) most of the options they have to implement various forms of advanced DM systems, and (2) fruitful areas for further research and innovation.

show abstract

“…An area where extensive binding data is of high importance is the field of drug screening. This area has seen a surge of activity in recent years with the "umbrella" of illicit substances being expanded to encompass new chemical architectures beyond classical drugs of abuse [37]. This extended prohibition now covers compounds coined New Psychoactive Substances (NPS), being compounds that are synthetically modified variants of classical compounds that contain a psychoactive pharmacophore with an overall different chemical architecture [38].…”

Section: Dataset Selectionmentioning

confidence: 99%

Identifying Potential Machine Learning Algorithms for the Simulation of Binding Affinities to Molecularly Imprinted Polymers

et al. 2021

View full text Add to dashboard Cite

Molecularly imprinted polymers (MIPs) are synthetic receptors engineered towards the selective binding of a target molecule; however, the manner in which MIPs interact with other molecules is of great importance. Being able to rapidly analyze the binding of potential molecular interferences and determine the selectivity of a MIP can be a long tedious task, being time- and resource-intensive. Identifying computational models capable of reliably predicting and reporting the binding of molecular species is therefore of immense value in both a research and commercial setting. This research therefore sets focus on comparing the use of machine learning algorithms (multitask regressor, graph convolution, weave model, DAG model, and inception) to predict the binding of various molecular species to a MIP designed towards 2-methoxphenidine. To this end, each algorithm was “trained” with an experimental dataset, teaching the algorithms the structures and binding affinities of various molecular species at varying concentrations. A validation experiment was then conducted for each algorithm, comparing experimental values to predicted values and facilitating the assessment of each approach by a direct comparison of the metrics. The research culminates in the construction of binding isotherms for each species, directly comparing experimental vs. predicted values and identifying the approach that best emulates the real-world data.

show abstract

Chemical classification of new psychoactive substances (NPS)

Cited by 38 publications

References 44 publications

Acute Toxic Effects of AB-CHMINACA on Lung, Heart and Liver: An Experimental Pilot Study

Acute Toxic Effects of AB-CHMINACA on Lung, Heart and Liver: An Experimental Pilot Study

Survey and Synthesis of State of the Art in Driver Monitoring

Identifying Potential Machine Learning Algorithms for the Simulation of Binding Affinities to Molecularly Imprinted Polymers

Contact Info

Product

Resources

About