Trends in hospital presentations following analytically confirmed synthetic cannabinoid receptor agonist exposure before and after implementation of the 2016 UK Psychoactive Substances Act.

BACKGROUND AND AIMS: The United Kingdom (UK) Psychoactive Substances Act (PSA), implemented on the 26th  May 2016, made the production, supply and sale of all non-exempted psychoactive substances illegal. The aim of this study was to measure trends in hospital presentations for severe toxicity following analytically confirmed synthetic cannabinoid receptor agonist (SCRA) exposure before and after implementation of the PSA. DESIGN: Observational study. SETTING: Thirty-four hospitals across the UK participating in the Identification of Novel Psychoactive Substances (IONA) study. PARTICIPANTS: A total of 627 (79.9% male) consenting individuals who presented to participating hospitals between July 2015 and December 2019 with severe acute toxicity and suspected novel psychoactive substances exposure. MEASUREMENTS: Toxicological analyses of patient samples were conducted using liquid-chromatography tandem mass-spectrometry. Time-series analysis was conducted on the monthly number of patients with and without analytically confirmed SCRA exposure using Poisson segmented regression. FINDINGS: SCRAs were detected in 35.7% (n = 224) of patients. After adjusting for seasonality and the number of active sites, models showed no clear evidence of an upward or downward trend in the number of SCRA exposure cases in the period before (incidence rate ratio [IRR], 1.12; 95% CI, 0.99-1.26; P = 0.068) or after (IRR, 0.97; 95% CI, 0.94-1.01; P = 0.202) the implementation of the PSA. There was also no clear evidence of an upward or downward trend in non-SCRA exposure cases before (IRR, 1.12; 95% CI, 0.98-1.27; P = 0.105) or after (IRR, 1.01; 95% CI, 0.98-1.04; P = 0.478) implementation of the PSA. CONCLUSIONS: There is no clear evidence of an upward or downward trend in the number of patients presenting to UK hospitals with severe acute toxicity following analytically confirmed synthetic cannabinoid receptor agonist exposure since the implementation of the Psychoactive Substances Act.

Learning Automata-based Misinformation Mitigation via Hawkes Processes.

Mitigating misinformation on social media is an unresolved challenge, particularly because of the complexity of information dissemination. To this end, Multivariate Hawkes Processes (MHP) have become a fundamental tool because they model social network dynamics, which facilitates execution and evaluation of mitigation policies. In this paper, we propose a novel light-weight intervention-based misinformation mitigation framework using decentralized Learning Automata (LA) to control the MHP. Each automaton is associated with a single user and learns to what degree that user should be involved in the mitigation strategy by interacting with a corresponding MHP, and performing a joint random walk over the state space. We use three Twitter datasets to evaluate our approach, one of them being a new COVID-19 dataset provided in this paper. Our approach shows fast convergence and increased valid information exposure. These results persisted independently of network structure, including networks with central nodes, where the latter could be the root of misinformation. Further, the LA obtained these results in a decentralized manner, facilitating distributed deployment in real-life scenarios.

Increased breath markers of oxidative stress in normal pregnancy and in preeclampsia.

OBJECTIVES: The purpose of this study was to compare the intensity of oxidative stress in normal pregnancy, preeclampsia, and nonpregnant women using a breath test. STUDY DESIGN: We studied primiparous women in third trimester pregnancy (38 uncomplicated, 26 with preeclampsia) and 60 nonpregnant control subjects. Volatile organic compounds (VOCs) in alveolar breath were analyzed by gas chromatography/mass spectroscopy to construct the breath methylated alkane contour (BMAC), a 3-dimensional display of abundance of C4-C20 alkanes and monomethylated alkanes. RESULTS: The mean volume under curve (VUC) of the BMAC was significantly higher in preeclampsia patients than in normal pregnant women (P < .003) and nonpregnant control subjects (P < .005). A predictive model employing 5 VOCs distinguished preeclampsia from uncomplicated pregnancy (sensitivity = 92.3%, specificity = 89.7%; cross-validated sensitivity = 88.5%, specificity = 79.3%). CONCLUSION: A breath test significantly demonstrated greater oxidative stress in women with preeclampsia than in uncomplicated pregnancy and nonpregnant control subjects. The breath test accurately identified women with established preeclampsia, but further studies are required to determine if this test can predict the onset of disease.