Multiclonal human origin and global expansion of an endemic bacterial pathogen of livestock.

Most new pathogens of humans and animals arise via switching events from distinct host species. However, our understanding of the evolutionary and ecological drivers of successful host adaptation, expansion, and dissemination are limited. Staphylococcus aureus is a major bacterial pathogen of humans and a leading cause of mastitis in dairy cows worldwide. Here we trace the evolutionary history of bovine S. aureus using a global dataset of 10,254 S. aureus genomes including 1,896 bovine isolates from 32 countries in 6 continents. We identified 7 major contemporary endemic clones of S. aureus causing bovine mastitis around the world and traced them back to 4 independent host-jump events from humans that occurred up to 2,500 y ago. Individual clones emerged and underwent clonal expansion from the mid-19th to late 20th century coinciding with the commercialization and industrialization of dairy farming, and older lineages have become globally distributed via established cattle trade links. Importantly, we identified lineage-dependent differences in the frequency of host transmission events between humans and cows in both directions revealing high risk clones threatening veterinary and human health. Finally, pangenome network analysis revealed that some bovine S. aureus lineages contained distinct sets of bovine-associated genes, consistent with multiple trajectories to host adaptation via gene acquisition. Taken together, we have dissected the evolutionary history of a major endemic pathogen of livestock providing a comprehensive temporal, geographic, and gene-level perspective of its remarkable success.

The precision of signals encoding active self-movement.

Everyday actions like moving the head, walking around and grasping objects are typically self-controlled. This presents a problem when studying the signals encoding such actions because active self-movement is difficult to control experimentally. Available techniques demand repeatable trials, but each action is unique, making it difficult to measure fundamental properties like psychophysical thresholds. We present a novel paradigm that recovers both precision and bias of self-movement signals with minimal constraint on the participant. The paradigm relies on linking image motion to previous self-movement, and two experimental phases to extract the signal encoding the latter. The paradigm takes care of a hidden source of external noise not previously accounted for in techniques that link display motion to self-movement in real time (e.g. virtual reality). We use head rotations as an example of self-movement, and show that the precision of the signals encoding head movement depends on whether they are being used to judge visual motion or auditory motion. We find that perceived motion is slowed during head movement in both cases. The 'non-image' signals encoding active head rotation (motor commands, proprioception and vestibular cues) are therefore biased towards lower speeds and/or displacements. In a second experiment, we trained participants to rotate their heads at different rates and found that the imprecision of the head rotation signal rises proportionally with head speed (Weber's Law). We discuss the findings in terms of the different motion cues used by vision and hearing, and the implications they have for Bayesian models of motion perception.

Persistent increased severity of cannabis use disorder symptoms in adolescents compared to adults: a one-year longitudinal study.

Adolescence is a developmental period characterised by increased vulnerability to cannabis use disorder (CUD). However, previous investigations of this vulnerability have relied on cross-sectional comparisons and lack a detailed assessment of cannabis quantity, a potentially important confounding factor. Here, we aimed to investigate the one-year course of CUD in adolescents compared to adults who currently use cannabis, adjusting for a comprehensive measure of cannabis quantity. Data are from a one-year observational longitudinal study (CannTeen) of adolescents and adults who currently used cannabis regularly with five waves of assessment at 3-monthly intervals, based in London, UK. Participants were n = 70 adults (26-29, 45.7% female), who did not regularly use cannabis when they were under age 18, and n = 76 adolescents (16-17, 50.0% female). The exposure was adolescent (compared to adult) frequent cannabis use. The primary outcome was CUD symptoms measured using the cannabis use disorder identification test revised (CUDIT-R) at five time points. Models were adjusted for cannabis quantity using mean weekly standard THC units (one unit = 5 mg THC). Other covariates included gender, and whether each session occurred before or during the COVID-19 pandemic. In models adjusted for pre-registered covariates, adolescents scored 3.7 points higher on the CUDIT-R compared to the adult group across the 5 assessment waves (3.66 95% CIs 1.99, 5.34). There was also evidence of a linear reduction in symptoms over time in both groups (-0.47, 95%CIs -0.67, -0.27). Adolescents had persistently increased CUD symptoms compared to adults across the 12-month period. This association was robust after adjusting for the quantity of cannabis consumed and other covariates.

Applying machine learning to international drug monitoring: classifying cannabis resin collected in Europe using cannabinoid concentrations.

In Europe, concentrations of ∆9-tetrahydrocannabinol (THC) in cannabis resin (also known as hash) have risen markedly in the past decade, potentially increasing risks of mental health disorders. Current approaches to international drug monitoring cannot distinguish between different types of cannabis resin which may have contrasting health effects due to THC and cannabidiol (CBD) content. Here, we compared concentrations of THC and CBD in different types of cannabis resin collected in Europe (either Moroccan-type, or Dutch-type). We then tested the ability of machine learning algorithms to classify the type of cannabis resin (either Moroccan-type, or Dutch-type) using routinely collected monitoring data on THC and CBD. Finally, we applied the optimal algorithm to new samples collected in countries where the type of cannabis resin was unknown, the UK and Denmark. Results showed that overall, Dutch-type samples had higher THC (Hedges' g = 2.39) and lower CBD (Hedges' g = 0.81) than Moroccan-type samples. A Support Vector Machine algorithm achieved classification accuracy exceeding 95%, with little variation in this estimate, good interpretability, and plausibility. It made contrasting predictions about the type of cannabis resin collected in the UK (94% Moroccan-type; 6% Dutch-type) and Denmark (36% Moroccan-type; 64% Dutch-type). In conclusion, we provide proof-of-concept evidence for the potential of machine learning to inform international drug monitoring. Our findings should not be interpreted as objective confirmatory evidence but suggest that Dutch-type cannabis resin has higher THC concentrations than Moroccan-type cannabis resin, which may contribute to variation in drug markets and health outcomes for people who use cannabis in Europe.

A phase III multisite randomised controlled trial to compare the efficacy of cannabidiol to placebo in the treatment of cannabis use disorder: the CBD-CUD study protocol.

BACKGROUND: Cannabis use disorder (CUD) is increasingly common and contributes to a range of health and social problems. Cannabidiol (CBD) is a non-intoxicating cannabinoid recognised for its anticonvulsant, anxiolytic and antipsychotic effects with no habit-forming qualities. Results from a Phase IIa randomised clinical trial suggest that treatment with CBD for four weeks reduced non-prescribed cannabis use in people with CUD. This study examines the efficacy, safety and quality of life of longer-term CBD treatment for patients with moderate-to-severe CUD. METHODS/DESIGN: A phase III multi-site, randomised, double-blinded, placebo controlled parallel design of a 12-week course of CBD to placebo, with follow-up at 24 weeks after enrolment. Two hundred and fifty adults with moderate-to-severe CUD (target 20% Aboriginal), with no significant medical, psychiatric or other substance use disorders from seven drug and alcohol clinics across NSW and VIC, Australia will be enrolled. Participants will be administered a daily dose of either 4 mL (100 mg/mL) of CBD or a placebo dispensed every 3-weeks. All participants will receive four-sessions of Cognitive Behavioural Therapy (CBT) based counselling. Primary endpoints are self-reported cannabis use days and analysis of cannabis metabolites in urine. Secondary endpoints include severity of CUD, withdrawal severity, cravings, quantity of use, motivation to stop and abstinence, medication safety, quality of life, physical/mental health, cognitive functioning, and patient treatment satisfaction. Qualitative research interviews will be conducted with Aboriginal participants to explore their perspectives on treatment. DISCUSSION: Current psychosocial and behavioural treatments for CUD indicate that over 80% of patients relapse within 1-6 months of treatment. Pharmacological treatments are highly effective with other substance use disorders but there are no approved pharmacological treatments for CUD. CBD is a promising candidate for CUD treatment due to its potential efficacy for this indication and excellent safety profile. The anxiolytic, antipsychotic and neuroprotective effects of CBD may have added benefits by reducing many of the mental health and cognitive impairments reported in people with regular cannabis use. TRIAL REGISTRATION: Australian and New Zealand Clinical Trial Registry: ACTRN12623000526673 (Registered 19 May 2023).

Polydrug Use Typologies of Regular Ecstasy Users Visiting Electronic Dance Music Events: A Latent Class Analysis.

INTRODUCTION: Polydrug use patterns among young adults using ecstasy vary, as well as their willingness to change them. Polydrug use patterns are likely associated with different adverse health outcomes. It is unknown whether polydrug use patterns of young adults who use ecstasy are similar in different countries. This study aims to identify and compare polydrug use patterns and willingness to change them of young adults that use ecstasy in the United Kingdom (UK) and the Netherlands (NL), two countries with a high prevalence of ecstasy use and a large electronic dance music (EDM) scene. METHODS: The data from the online cross-sectional Electronic Music Scene Survey were used in a latent class analysis. The binary indicators used in the estimation were past-year substance use of 21 different substances. The sample consisted of young adult ecstasy users that regularly visit EDM events (age 18-34). RESULTS: A total of 1,077 respondents from the UK (age M = 23.1) and 1,178 from the NL (age M = 23.7) that regularly visit EDM events were included in the analyses. In both countries, three polydrug use patterns of ecstasy users were identified based on Bayesian Information Criterion fit indices: a traditional polydrug use class (UK: 28%; NL: 40%), a stimulant and ketamine polydrug use class (UK: 48%; NL: 52%), and an extensive polydrug use class (UK: 24%; NL: 8%) characterized by substantial use of stimulants, depressant, and psychedelic substances. Overall, young adults that used ecstasy in the UK consumed 3,4-methylenedioxymeth-amphetamine (MDMA) more often as powder/crystalline and at higher dosages compared to young adults in the NL who preferred MDMA tablets. Regardless of polydrug class or country, most respondents indicated that they had the intention to reduce but not quit their use. CONCLUSION: In both countries, structurally similar polydrug use patterns among young adults that use ecstasy were found, while the use frequencies of individual substances and preferred MDMA form varied between the countries.

Instant Detection of Synthetic Cannabinoids on Physical Matrices, Implemented on a Low-Cost, Ultraportable Device.

Synthetic cannabinoids (SCs) make up a class of novel psychoactive substances (NPS), used predominantly in prisons and homeless communities in the U.K. SCs can have severe side effects, including psychosis, stroke, and seizures, with numerous reported deaths associated with their use. The chemical diversity of SCs presents the major challenge to their detection since approaches relying on specific molecular recognition become outdated almost immediately. Ideally one would have a generic approach to detecting SCs in portable settings. The problem of SC detection is more challenging still because the majority of SCs enter the prison estate adsorbed onto physical matrices such as paper, fabric, or herb materials. That is, regardless of the detection modality used, the necessary extraction step reduces the effectiveness and ability to rapidly screen materials on-site. Herein, we demonstrate a truly instant generic test for SCs, tested against real-world drug seizures. The test is based on two advances. First, we identify a spectrally silent region in the emission spectrum of most physical matrices. Second, the finding that background signals (including from autofluorescence) can be accurately predicted is based on tracking the fraction of absorbed light from the irradiation source. Finally, we demonstrate that the intrinsic fluorescence of a large range of physical substrates can be leveraged to track the presence of other drugs of interest, including the most recent iterations of benzodiazepines and opioids. We demonstrate the implementation of our presumptive test in a portable, pocket-sized device that will find immediate utility in prisons and law enforcement agencies around the world.

Photochemical Fingerprinting Is a Sensitive Probe for the Detection of Synthetic Cannabinoid Receptor Agonists; toward Robust Point-of-Care Detection.

With synthetic cannabinoid receptor agonist (SCRA) use still prevalent across Europe and structurally advanced generations emerging, it is imperative that drug detection methods advance in parallel. SCRAs are a chemically diverse and evolving group, which makes rapid detection challenging. We have previously shown that fluorescence spectral fingerprinting (FSF) has the potential to provide rapid assessment of SCRA presence directly from street material with minimal processing and in saliva. Enhancing the sensitivity and discriminatory ability of this approach has high potential to accelerate the delivery of a point-of-care technology that can be used confidently by a range of stakeholders, from medical to prison staff. We demonstrate that a range of structurally distinct SCRAs are photochemically active and give rise to distinct FSFs after irradiation. To explore this in detail, we have synthesized a model series of compounds which mimic specific structural features of AM-694. Our data show that FSFs are sensitive to chemically conservative changes, with evidence that this relates to shifts in the electronic structure and cross-conjugation. Crucially, we find that the photochemical degradation rate is sensitive to individual structures and gives rise to a specific major product, the mechanism and identification of which we elucidate through density-functional theory (DFT) and time-dependent DFT. We test the potential of our hybrid "photochemical fingerprinting" approach to discriminate SCRAs by demonstrating SCRA detection from a simulated smoking apparatus in saliva. Our study shows the potential of tracking photochemical reactivity via FSFs for enhanced discrimination of SCRAs, with successful integration into a portable device.

Setting the basis of best practices and standards for curation and annotation of logical models in biology-highlights of the [BC]2 2019 CoLoMoTo/SysMod Workshop.

The fast accumulation of biological data calls for their integration, analysis and exploitation through more systematic approaches. The generation of novel, relevant hypotheses from this enormous quantity of data remains challenging. Logical models have long been used to answer a variety of questions regarding the dynamical behaviours of regulatory networks. As the number of published logical models increases, there is a pressing need for systematic model annotation, referencing and curation in community-supported and standardised formats. This article summarises the key topics and future directions of a meeting entitled 'Annotation and curation of computational models in biology', organised as part of the 2019 [BC]2 conference. The purpose of the meeting was to develop and drive forward a plan towards the standardised annotation of logical models, review and connect various ongoing projects of experts from different communities involved in the modelling and annotation of molecular biological entities, interactions, pathways and models. This article defines a roadmap towards the annotation and curation of logical models, including milestones for best practices and minimum standard requirements.

Anhedonia, Apathy, Pleasure, and Effort-Based Decision-Making in Adult and Adolescent Cannabis Users and Controls.

BACKGROUND: Cannabis use may be linked with anhedonia and apathy. However, previous studies have shown mixed results, and few have examined the association between cannabis use and specific reward sub-processes. Adolescents may be more vulnerable than adults to harmful effects of cannabis. This study investigated (1) the association between non-acute cannabis use and apathy, anhedonia, pleasure, and effort-based decision-making for reward; and (2) whether these relationships were moderated by age group. METHODS: We used data from the "CannTeen" study. Participants were 274 adult (26-29 years) and adolescent (16-17 years) cannabis users (1-7 d/wk use in the past 3 months) and gender- and age-matched controls. Anhedonia was measured with the Snaith-Hamilton Pleasure Scale (n = 274), and apathy was measured with the Apathy Evaluation Scale (n = 215). Effort-based decision-making for reward was measured with the Physical Effort task (n = 139), and subjective wanting and liking of rewards was measured with the novel Real Reward Pleasure task (n = 137). RESULTS: Controls had higher levels of anhedonia than cannabis users (F1,258 = 5.35, P = .02, η p2 = .02). There were no other significant effects of user-group and no significant user-group*age-group interactions. Null findings were supported by post hoc Bayesian analyses. CONCLUSION: Our results suggest that cannabis use at a frequency of 3 to 4 d/wk is not associated with apathy, effort-based decision-making for reward, reward wanting, or reward liking in adults or adolescents. Cannabis users had lower anhedonia than controls, albeit at a small effect size. These findings are not consistent with the hypothesis that non-acute cannabis use is associated with amotivation.

Cannabis use as a potential mediator between childhood adversity and first-episode psychosis: results from the EU-GEI case-control study.

BACKGROUND: Childhood adversity and cannabis use are considered independent risk factors for psychosis, but whether different patterns of cannabis use may be acting as mediator between adversity and psychotic disorders has not yet been explored. The aim of this study is to examine whether cannabis use mediates the relationship between childhood adversity and psychosis. METHODS: Data were utilised on 881 first-episode psychosis patients and 1231 controls from the European network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study. Detailed history of cannabis use was collected with the Cannabis Experience Questionnaire. The Childhood Experience of Care and Abuse Questionnaire was used to assess exposure to household discord, sexual, physical or emotional abuse and bullying in two periods: early (0-11 years), and late (12-17 years). A path decomposition method was used to analyse whether the association between childhood adversity and psychosis was mediated by (1) lifetime cannabis use, (2) cannabis potency and (3) frequency of use. RESULTS: The association between household discord and psychosis was partially mediated by lifetime use of cannabis (indirect effect coef. 0.078, s.e. 0.022, 17%), its potency (indirect effect coef. 0.059, s.e. 0.018, 14%) and by frequency (indirect effect coef. 0.117, s.e. 0.038, 29%). Similar findings were obtained when analyses were restricted to early exposure to household discord. CONCLUSIONS: Harmful patterns of cannabis use mediated the association between specific childhood adversities, like household discord, with later psychosis. Children exposed to particularly challenging environments in their household could benefit from psychosocial interventions aimed at preventing cannabis misuse.

The association between reasons for first using cannabis, later pattern of use, and risk of first-episode psychosis: the EU-GEI case-control study.

BACKGROUND: While cannabis use is a well-established risk factor for psychosis, little is known about any association between reasons for first using cannabis (RFUC) and later patterns of use and risk of psychosis. METHODS: We used data from 11 sites of the multicentre European Gene-Environment Interaction (EU-GEI) case-control study. 558 first-episode psychosis patients (FEPp) and 567 population controls who had used cannabis and reported their RFUC.We ran logistic regressions to examine whether RFUC were associated with first-episode psychosis (FEP) case-control status. Path analysis then examined the relationship between RFUC, subsequent patterns of cannabis use, and case-control status. RESULTS: Controls (86.1%) and FEPp (75.63%) were most likely to report 'because of friends' as their most common RFUC. However, 20.1% of FEPp compared to 5.8% of controls reported: 'to feel better' as their RFUC (χ2 = 50.97; p < 0.001). RFUC 'to feel better' was associated with being a FEPp (OR 1.74; 95% CI 1.03-2.95) while RFUC 'with friends' was associated with being a control (OR 0.56; 95% CI 0.37-0.83). The path model indicated an association between RFUC 'to feel better' with heavy cannabis use and with FEPp-control status. CONCLUSIONS: Both FEPp and controls usually started using cannabis with their friends, but more patients than controls had begun to use 'to feel better'. People who reported their reason for first using cannabis to 'feel better' were more likely to progress to heavy use and develop a psychotic disorder than those reporting 'because of friends'.

Transcriptome-based network analysis reveals a spectrum model of human macrophage activation.

Macrophage activation is associated with profound transcriptional reprogramming. Although much progress has been made in the understanding of macrophage activation, polarization, and function, the transcriptional programs regulating these processes remain poorly characterized. We stimulated human macrophages with diverse activation signals, acquiring a data set of 299 macrophage transcriptomes. Analysis of this data set revealed a spectrum of macrophage activation states extending the current M1 versus M2-polarization model. Network analyses identified central transcriptional regulators associated with all macrophage activation complemented by regulators related to stimulus-specific programs. Applying these transcriptional programs to human alveolar macrophages from smokers and patients with chronic obstructive pulmonary disease (COPD) revealed an unexpected loss of inflammatory signatures in COPD patients. Finally, by integrating murine data from the ImmGen project we propose a refined, activation-independent core signature for human and murine macrophages. This resource serves as a framework for future research into regulation of macrophage activation in health and disease.

Graphia: A platform for the graph-based visualisation and analysis of high dimensional data.

Graphia is an open-source platform created for the graph-based analysis of the huge amounts of quantitative and qualitative data currently being generated from the study of genomes, genes, proteins metabolites and cells. Core to Graphia's functionality is support for the calculation of correlation matrices from any tabular matrix of continuous or discrete values, whereupon the software is designed to rapidly visualise the often very large graphs that result in 2D or 3D space. Following graph construction, an extensive range of measurement algorithms, routines for graph transformation, and options for the visualisation of node and edge attributes are available, for graph exploration and analysis. Combined, these provide a powerful solution for the interpretation of high-dimensional data from many sources, or data already in the form of a network or equivalent adjacency matrix. Several use cases of Graphia are described, to showcase its wide range of applications in the analysis biological data. Graphia runs on all major desktop operating systems, is extensible through the deployment of plugins and is freely available to download from https://graphia.app/.

Acceptability of integrating smoking cessation treatment into routine care for people with mental illness: A qualitative study.

INTRODUCTION: Improving Access to Psychological Therapies (IAPTs) Services could offer smoking cessation treatment to improve physical and psychological outcomes for service users, but it currently does not. This study aimed to understand participants' views and experiences of receiving a novel smoking cessation intervention as part of the ESCAPE trial (intEgrating Smoking Cessation treatment As part of usual Psychological care for dEpression and anxiety). We used the Capability, Opportunity and Motivation Model of Behaviour (COM-B) to understand the (i) acceptability of the integrated smoking cessation treatment, (ii) views of psychological well-being practitioners' (PWPs) ability to deliver the smoking cessation treatment and (iii) positive and negative impacts of smoking cessation treatment. METHODS: This was a qualitative study embedded within a feasibility randomized-controlled trial (ESCAPE) in primary care services in the United Kingdom (IAPT). Thirty-six participants (53% female) from both usual care and intervention arms of the ESCAPE trial, including both quitters and nonquitters, were interviewed using semi-structured interviews. Data were analysed using a framework approach to thematic analysis, using the COM-B as a theoretical frame. RESULTS: Psychological Capability: Integrated smoking cessation treatment was acceptable and encouraged participants to reflect on their mental health. Some participants found it difficult to understand nicotine withdrawal symptoms. MOTIVATION: Participants were open to change during the event of presenting to IAPT. Some described being motivated to take part in the intervention by curiosity, to see whether quitting smoking would help their mental health. Physical Opportunity: IAPT has a natural infrastructure for supporting integrated treatment, but there were some barriers such as session duration and interventions feeling segmented. Social Opportunity: Participants viewed PWPs as having good interpersonal skills to deliver a smoking cessation intervention. CONCLUSION: People with common mental illness generally accepted integrated smoking cessation and mental health treatment. Smoking cessation treatment fits well within IAPT's structure; however, there are barriers to implementation. PATIENT OR PUBLIC CONTRIBUTION: Before data collection, we consulted with people with lived experience of smoking and/or mental illness and lay public members regarding the aims, design and interview schedules. After analysis, two people with lived experience of smoking and mental illness individually gave feedback on the final themes and quotes.

Legal sourcing of ten cannabis products in the Canadian cannabis market, 2019-2021: a repeat cross-sectional study.

BACKGROUND: One of the objectives of cannabis legalization in Canada is to transition consumers from the illegal to the legal market. Little is known about how legal sourcing varies across different cannabis product types, provinces, and frequency of cannabis use. METHODS: Data were analyzed from Canadian respondents in the International Cannabis Policy Study, a repeat cross-sectional survey conducted annually from 2019 to 2021. Respondents were 15,311 past 12-month cannabis consumers of legal age to purchase cannabis. Weighted logistic regression models estimated the association between legal sourcing ("all"/ "some"/ "none") of ten cannabis product types, province, and frequency of cannabis use over time. RESULTS: The percentage of consumers who sourced "all" their cannabis products from legal sources in the past 12 months varied by product type, ranging from 49% of solid concentrate consumers to 82% of cannabis drink consumers in 2021. The percentage of consumers sourcing "all" their respective products legally was greater in 2021 than 2020 across all products. Legal sourcing varied by frequency of use: weekly or more frequent consumers were more likely to source "some" (versus "none") of their products legally versus less frequent consumers. Legal sourcing also varied by province, with a lower likelihood of legal sourcing in Québec of products whose legal sale was restricted (e.g., edibles). CONCLUSION: Legal sourcing increased over time, demonstrating progress in the transition to the legal market for all products in the first three years of legalization in Canada. Legal sourcing was highest for drinks and oils and lowest for solid concentrates and hash.

A graph-based approach for the visualisation and analysis of bacterial pangenomes.

BACKGROUND: The advent of low cost, high throughput DNA sequencing has led to the availability of thousands of complete genome sequences for a wide variety of bacterial species. Examining and interpreting genetic variation on this scale represents a significant challenge to existing methods of data analysis and visualisation. RESULTS: Starting with the output of standard pangenome analysis tools, we describe the generation and analysis of interactive, 3D network graphs to explore the structure of bacterial populations, the distribution of genes across a population, and the syntenic order in which those genes occur, in the new open-source network analysis platform, Graphia. Both the analysis and the visualisation are scalable to datasets of thousands of genome sequences. CONCLUSIONS: We anticipate that the approaches presented here will be of great utility to the microbial research community, allowing faster, more intuitive, and flexible interaction with pangenome datasets, thereby enhancing interpretation of these complex data.

The Effect of Conflicting Public Health Guidance on Smokers' and Vapers' E-cigarette Harm Perceptions.

BACKGROUND: E-cigarettes are increasingly being viewed, incorrectly, as more harmful than cigarettes. This may discourage smokers from switching to e-cigarettes. One potential explanation for these increasingly harmful attitudes is conflicting information presented in the media and online, and from public health bodies. AIMS AND METHODS: In this prospectively registered online study, we aimed to examine the impact of conflicting public health information on smokers' and vapers' e-cigarette harm perceptions. Daily UK smokers who do not vape (n = 334) and daily UK vapers (n = 368) were randomized to receive either: (1) a consistent harm reduction statement from two different public health bodies (Harm Reduction), (2) a consistent negative statement about e-cigarette harms from two different public health bodies (Negative), (3) a harm reduction statement from one public health body and a negative statement from another (Conflict), and (4) a statement of the risks of smoking followed by a harm reduction statement from one public health body and a negative statement from another (Smoking Risk + Conflict). Participants then answered questions regarding their perceptions of e-cigarette harm. RESULTS: The Negative condition had the highest e-cigarette harm perceptions, significantly higher than the Smoking Risk + Conflict condition (MD = 5.4, SE = 1.8, p < .016, d = 0.3 [CI 0.73 to 10.04]), which did not differ from the Conflict condition (MD = 1.5, SE = 1.8, p = .836, d = 0.1 [CI -3.14 to 6.17]). The Conflict condition differed from the Harm Reduction condition, where harm perceptions were lowest (MD = 5.4, SE = 1.8, p = .016, d = 0.3 [CI 0.74 to 10.07]). CONCLUSIONS: These findings are the first to demonstrate that, compared to harm reduction information, conflicting information increases e-cigarette harm perceptions amongst vapers, and smokers who do not vape. IMPLICATIONS: This research provides the first empirical evidence that conflicting information increases smokers' and vapers' e-cigarette harm perceptions, compared to harm reduction information. This may have a meaningful impact on public health as e-cigarette harm perceptions can influence subsequent smoking and vaping behavior. Conflicting information may dissuade smokers, who have the most to gain from accurate e-cigarette harm perceptions, from switching to e-cigarettes. These findings indicate that public health communications that are consensus-based can lower harm perceptions of e-cigarettes, and have the potential to reduce morbidity and mortality attributable to tobacco smoking.

Drug Use Changes at the Individual Level: Results from a Longitudinal, Multisite Survey in Young Europeans Frequenting the Nightlife Scene.

BACKGROUND: Monitoring emerging trends in the increasingly dynamic European drug market is vital; however, information on change at the individual level is scarce. In the current study, we investigated changes in drug use over 12 months in European nightlife attendees. METHOD: In this longitudinal online survey, changes in substances used, use frequency in continued users, and relative initiation of use at follow-up were assessed for 20 different substances. To take part, participants had to be aged 18-34 years; be from Belgium, Italy, the Netherlands, Sweden, or the UK; and have attended at least 6 electronic music events in the past 12 months at baseline. Of 8,045 volunteers at baseline, 2,897 completed the survey at both time points (36% follow-up rate), in 2017 and 2018. RESULTS: The number of people using ketamine increased by 21% (p < 0.001), and logarithmized frequency of use in those continuing use increased by 15% (p < 0.001; 95% CI: 0.07-0.23). 4-Fluoroamphetamine use decreased by 27% (p < 0.001), and logarithmized frequency of use in continuing users decreased by 15% (p < 0.001, 95% CI: -0.48 to -0.23). The drugs with the greatest proportion of relative initiation at follow-up were synthetic cannabinoids (73%, N = 30), mephedrone (44%, N = 18), alkyl nitrites (42%, N = 147), synthetic dissociatives (41%, N = 15), and prescription opioids (40%, N = 48). CONCLUSIONS: In this European nightlife sample, ketamine was found to have the biggest increase in the past 12 months, which occurred alongside an increase in frequency of use in continuing users. The patterns of uptake and discontinuation of alkyl nitrates, novel psychoactive substances, and prescription opioids provide new information that has not been captured by existing cross-sectional surveys. These findings demonstrate the importance of longitudinal assessments of drug use and highlight the dynamic nature of the European drug landscape.

The pinna enhances angular discrimination in the frontal hemifield.

Human sound localization in the horizontal dimension is thought to be dominated by binaural cues, particularly interaural time delays, because monaural localization in this dimension is relatively poor. Remaining ambiguities of front versus back and up versus down are distinguished by high-frequency spectral cues generated by the pinna. The experiments in this study show that this account is incomplete. Using binaural listening throughout, the pinna substantially enhanced horizontal discrimination in the frontal hemifield, making discrimination in front better than discrimination at the rear, particularly for directions away from the median plane. Eliminating acoustic effects of the pinna by acoustically bypassing them or low-pass filtering abolished the advantage at the front without affecting the rear. Acoustic measurements revealed a pinna-induced spectral prominence that shifts smoothly in frequency as sounds move from 0° to 90° azimuth. The improved performance is discussed in terms of the monaural and binaural changes induced by the pinna.