Longitudinal visibility of MRI findings in living victims of strangulation.

Initial experiences with magnetic resonance imaging (MRI) of living strangulation victims demonstrated additional findings of internal injuries compared to the standard clinical forensic examination. However, existing studies on the use of MRI for this purpose mostly focused on the first 48 h after the incident. The aims of this study were (a) to evaluate the longitudinal visibility of MRI findings after violence against the neck by performing two MRI examinations within 12 days and a minimum of four days between both MRI scans and (b) to assess which MRI sequences were most helpful for the detection of injuries.

Effect of vaporizing cannabis rich in cannabidiol on cannabinoid levels in blood and on driving ability - a randomized clinical trial.

The aim of this prospective, placebo-controlled, double-blind, randomized, cross-over study was to determine cannabinoid levels in blood and driving-related ability after single (S1) and repetitive (S2) vaporization of cannabis rich in cannabidiol (CBD) containing < 1% Δ-etrahydrocannabinol (THC). Healthy adult volunteers (N = 27, N = 20) with experience in smoking vapor-inhaled two low-THC/CBD-rich cannabis products both with < 1% THC (product 1: 38 mg CBD, 1.8 mg THC; product 2: 39 mg CBD, 0.

Clinical, Brain, and Multilevel Clustering in Early Psychosis and Affective Stages.

Importance: Approaches are needed to stratify individuals in early psychosis stages beyond positive symptom severity to investigate specificity related to affective and normative variation and to validate solutions with premorbid, longitudinal, and genetic risk measures.

Objective: To use machine learning techniques to cluster, compare, and combine subgroup solutions using clinical and brain structural imaging data from early psychosis and depression stages.

Design, Setting, And Participants: A multisite, naturalistic, longitudinal cohort study (10 sites in 5 European countries; including major follow-up intervals at 9 and 18 months) with a referred patient sample of those with clinical high risk for psychosis (CHR-P), recent-onset psychosis (ROP), recent-onset depression (ROD), and healthy controls were recruited between February 1, 2014, to July 1, 2019.

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

Importance: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improved by efficiently combining clinical and biological models and by broadening the risk spectrum to young patients with depressive syndromes remains unclear.

Objectives: To evaluate whether psychosis transition can be predicted in patients with CHR or recent-onset depression (ROD) using multimodal machine learning that optimally integrates clinical and neurocognitive data, structural magnetic resonance imaging (sMRI), and polygenic risk scores (PRS) for schizophrenia; to assess models' geographic generalizability; to test and integrate clinicians' predictions; and to maximize clinical utility by building a sequential prognostic system.

Clinical and functional ultra-long-term outcome of patients with a clinical high risk (CHR) for psychosis.

Background: Few studies have followed up patients with a clinical high risk (CHR) for psychosis for more than 2-3 years. We aimed to investigate the rates and baseline predictors for remission from CHR and transition to psychosis over a follow-up period of up to 16 years. Additionally, we examined the clinical and functional long-term outcome of CHR patients who did not transition.