New Psychoactive Substances - A Review and Updates

New psychoactive substances (NPS) are a heterogeneous group of substances. They are associated with a number of health and social harms on an individual and societal level. NPS toxicity and dependence syndromes are recognised in primary care, emergency departments, psychiatric inpatient and community care settings. One pragmatic classification system is to divide NPS into one of four groups: synthetic stimulants, synthetic cannabinoids, synthetic hallucinogens and synthetic depressants (which include synthetic opioids and benzodiazepines). We review these four classes of NPS, including their chemical structures, mechanism of action, modes of use, intended intoxicant effects, and their associated physical and mental health harms. The current challenges faced by laboratory testing for NPS are also explored, in the context of the diverse range of NPS currently available, rate of production and emergence of new substances, the different formulations, and methods of acquisition and distribution

First demonstration of in vivo mapping for regional brain monoacylglycerol lipase using PET with [11C]SAR127303

Monoacylglycerol lipase (MAGL) is a main regulator of the endocannabinoid system within the central nervous system (CNS). Recently, [11C]SAR127303 was developed as a promising radioligand for MAGL imaging. In this study, we aimed to quantify regional MAGL concentrations in the rat brain using positron emission tomography (PET) with [11C]SAR127303. An irreversible two-tissue compartment model (2-TCMi, k4 = 0) analysis was conducted to estimate quantitative parameters (k3, Ki2-TCMi, and λk3). These parameters were successfully obtained with high identifiability ( striatum > hippocampus > thalamus > cerebellum > hypothalamus ≈ pons. In vitro autoradiographs using [11C]SAR127303 showed a heterogeneous distribution of radioactivity, as seen in the PET images. The Ki2-TCMi and λk3 values correlated relatively highly with in vitro binding (r > 0.4, P < 0.005). The Ki2-TCMi values showed high correlation and low underestimation (<10%) compared with the slope of a Patlak plot analysis with linear regression (KiPatlak). In conclusion, we successfully estimated regional net uptake value of [11C]SAR127303 reflecting MAGL concentrations in rat brain regions for the first time