Long-term benefits of hematopoietic stem cell-based macrophage/microglia delivery of GDNF to the CNS in a mouse model of Parkinson's disease.

Glial cell line-derived neurotrophic factor (GDNF) protects dopaminergic neurons in various models of Parkinson's disease (PD). Cell-based GDNF gene delivery mitigates neurodegeneration and improves both motor and non-motor functions in PD mice. As PD is a chronic condition, this study aims to investigate the long-lasting benefits of hematopoietic stem cell (HSC)-based macrophage/microglia-mediated CNS GDNF (MMC-GDNF) delivery in an MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine) mouse model. The results indicate that GDNF treatment effectively ameliorated MPTP-induced motor deficits for up to 12 months, which coincided with the protection of nigral dopaminergic neurons and their striatal terminals. Also, the HSC-derived macrophages/microglia were recruited selectively to the neurodegenerative areas of the substantia nigra. The therapeutic benefits appear to involve two mechanisms: (1) macrophage/microglia release of GDNF-containing exosomes, which are transferred to target neurons, and (2) direct release of GDNF by macrophage/microglia, which diffuses to target neurons. Furthermore, the study found that plasma GDNF levels were significantly increased from baseline and remained stable over time, potentially serving as a convenient biomarker for future clinical trials. Notably, no weight loss, altered food intake, cerebellar pathology, or other adverse effects were observed. Overall, this study provides compelling evidence for the long-term therapeutic efficacy and safety of HSC-based MMC-GDNF delivery in the treatment of PD.

Personalized neoantigen vaccine and pembrolizumab in advanced hepatocellular carcinoma: a phase 1/2 trial.

Programmed cell death protein 1 (PD-1) inhibitors have modest efficacy as a monotherapy in hepatocellular carcinoma (HCC). A personalized therapeutic cancer vaccine (PTCV) may enhance responses to PD-1 inhibitors through the induction of tumor-specific immunity. We present results from a single-arm, open-label, phase 1/2 study of a DNA plasmid PTCV (GNOS-PV02) encoding up to 40 neoantigens coadministered with plasmid-encoded interleukin-12 plus pembrolizumab in patients with advanced HCC previously treated with a multityrosine kinase inhibitor. Safety and immunogenicity were assessed as primary endpoints, and treatment efficacy and feasibility were evaluated as secondary endpoints. The most common treatment-related adverse events were injection-site reactions, observed in 15 of 36 (41.6%) patients. No dose-limiting toxicities or treatment-related grade ≥3 events were observed. The objective response rate (modified intention-to-treat) per Response Evaluation Criteria in Solid Tumors 1.1 was 30.6% (11 of 36 patients), with 8.3% (3 of 36) of patients achieving a complete response. Clinical responses were associated with the number of neoantigens encoded in the vaccine. Neoantigen-specific T cell responses were confirmed in 19 of 22 (86.4%) evaluable patients by enzyme-linked immunosorbent spot assays. Multiparametric cellular profiling revealed active, proliferative and cytolytic vaccine-specific CD4+ and CD8+ effector T cells. T cell receptor ß-chain (TCRß) bulk sequencing results demonstrated vaccination-enriched T cell clone expansion and tumor infiltration. Single-cell analysis revealed posttreatment T cell clonal expansion of cytotoxic T cell phenotypes. TCR complementarity-determining region cloning of expanded T cell clones in the tumors following vaccination confirmed reactivity against vaccine-encoded neoantigens. Our results support the PTCV's mechanism of action based on the induction of antitumor T cells and show that a PTCV plus pembrolizumab has clinical activity in advanced HCC. ClinicalTrials.gov identifier: NCT04251117 .

Participation in Australian drug treatment programs for individuals engaging in high-risk substance use: Data from a nationally representative sample.

INTRODUCTION: Substance use, including drugs, alcohol and smoking have a significant health, social and economic impact. We aim to assess the rate and factors associated with treatment access among individuals with high-risk substance use. METHOD: This study is a cross-sectional analysis of the 2019 Australian National Drug Strategy Household Survey (N = 22,015). Participants were persons with high-risk substance use based on the Alcohol, Smoking and Substance Involvement Screening Test-Lite (ASSIST-Lite) and current smokers. We measured self-reports of past 12-month engagement in a tobacco, alcohol or other drugs treatment program. RESULTS: Overall, 0.4% had high-risk drug use (0.3% cannabis, 0.1% meth/amphetamine or 0.1% opioids), 7.4% had high-risk alcohol use, and 14.0% currently smoked. Among high-risk users, past 12-month treatment access rates were 50.6% [22.3-78.9%] for opioids, 27.1% [8.1-46.1%] for meth/amphetamine, 14.5% [4.3-24.7%] for cannabis, 9.6% [8.1-11.0%] for alcohol and 11.7% [10.6-12.9%] for current smoking. The primary source of treatment support was information and education (12.7% drugs, 4.6% alcohol, 4.0% smoking), followed by counselling (6.7% drugs, 4.5% alcohol, 3.0% smoking). Online or internet support was accessed by 5.9% (drug) and 1.6% (alcohol) people with high-risk use. Psychological distress was associated with treatment access (drugs: odds ratio 3.03 [0.77-11.95], p = 0.111; alcohol: odds ratio 3.16 [2.20-4.56], p ≤ 0.001; smoking: odds ratio 1.95 [1.52-2.49], p ≤ 0.001). DISCUSSION AND CONCLUSIONS: The proportion of people engaging in risky substance use who had used treatment programs remains low, especially for alcohol. Public health strategies to scale up treatment access are warranted.

Viral Vaping: A systematic review and meta analysis of e-cigarette and Tobacco-Related social media content and its influence on youth behaviours and attitudes.

AIMS: E-cigarette and tobacco-related content on social media continues to rise from lax restrictions on both personal and promotional posts. This content has been linked to various mechanisms of increased e-cigarette and tobacco use (i.e., lower risk perceptions and increased susceptibility). This study aimed to synthesis the association between exposure to e-cigarette and tobacco-related content and youth behaviours and attitudes. METHODS: A comprehensive search was conducted on PubMed, Scopus, PsycINFO and Web of Science. Studies published post-2004 reporting effect estimates for exposure or engagement with e-cigarette or tobacco content on social media and behaviour or attitude outcomes were included. RESULTS: Thirty-two studies (N = 274,283, aged 9 to 25 years) were included for synthesis. Meta-analyses revealed significant associations between engagement with tobacco content and use (OR 2.21; 95% CI = 1.27-3.82, p =.005; I2 = 96.4%), exposure to tobacco content and never users' lower risk perceptions (OR 0.68; 95% CI = 0.49-0.91; p =.011; I2 = 78.2%), and exposure to e-cigarette content and use (OR 1.37; 95% CI = 0.99-1.88; p = 0.058; I2 = 64.4%). There was no observed relationship between exposure to tobacco content and ever users' risk perceptions (OR 0.83; 95% CI = 0.61-1.13; p =.231; I2 = 83.5%). Qualitative synthesis found significant associations between tobacco exposure and increased current use and pro-tobacco attitudes; e-cigarette exposure and increased susceptibility and lower risk perceptions; tobacco engagement and increased susceptibility; e-cigarette engagement and increased use; dual exposure and increased susceptibility; and dual engagement and increased dual use. Mixed findings were identified for the influence of e-cigarette exposure on attitudes, tobacco exposure on susceptibility, dual exposure on dual use behaviours, and dual engagement on dual susceptibility. CONCLUSIONS: Findings suggest an association between exposure and engagement to e-cigarette or tobacco products on social media and use or pro-use attitudes among youth. Further substantive research in the area of youth-specific use and attitudes following exposure and engagement with e-cigarette and tobacco content is needed to quantify this association.

Longitudinal association between exposure to e-cigarette advertising and youth e-cigarette use in the United States.

BACKGROUND AND AIM: E-cigarette marketing strategies are targeting and appealing to youth, particularly through social media. This study examined the longitudinal relationship between recalled exposure to e-cigarette advertisements on social media and across five traditional advertising mediums, and e-cigarette use, a year later. DESIGN: Weighted regression analyses of waves 4 (W4; 2017), 4.5 (W4.5; 2018) and 5 (W5; 2019) from the Population Assessment of Tobacco and Health Study. SETTING: United States. PARTICIPANTS: Youth aged 12-17 years at W4 or W4.5 (N = 16,671). MEASUREMENTS: We examined the association between past 30-day recalled exposure to six different e-cigarette advertisement mediums (gas stations/convenience stores, social media/websites, newspaper/magazines, radio, billboard, TV) in W4.5 and past 30-day and past 12-month e-cigarette use in W5, while controlling for W4 e-cigarette use and covariates such as sociodemographic variables, academic performance, peer cigarette/e-cigarette use and other substance use. Associations between recalled exposure (W4.5) and lifetime use (W5) among e-cigarette naïve youth at W4.5 (N = 8,914) were also assessed. FINDINGS: Past 12-month and past 30-day e-cigarette use was significantly associated with recalled exposure to e-cigarette advertisement on social media/websites (aOR = 1.65 [99.17 %CI = 1.36,1.99; aOR = 1.49 [99.17 %CI = 1.13, 1.97]) and gas stations/convenience stores (aOR = 1.33; [99.17 %CI = 1.11,1.58]; aOR = 1.27 [99.17 %CI = 1.03,1.58]). Exposure to e-cigarette advertisement on social media/websites (aOR = 1.35 [99.17 %CI = 1.04,1.74]) and gas stations/convenience stores (aOR = 1.67 [99.17 %CI = 1.31,2.13]) was significantly associated with lifetime e-cigarette use among baseline youth who were e-cigarette naïve. CONCLUSIONS: Exposure to e-cigarette advertisement on social media/websites and gas stations/convenience stores was associated with youth e-cigarette use a year later. Stricter restrictions on marketing in these mediums is needed to limit youth exposure to e-cigarette marketing messages if we are to reduce e-cigarette use.

Predicting the long-term effects of electronic cigarette use on population health: a systematic review of modelling studies.

OBJECTIVE: To systematically review and synthesise the findings of modelling studies on the population impacts of e-cigarette use and to identify potential gaps requiring future investigation. DATA SOURCE AND STUDY SELECTION: Four databases were searched for modelling studies of e-cigarette use on population health published between 2010 and 2023. A total of 32 studies were included. DATA EXTRACTION: Data on study characteristics, model attributes and estimates of population impacts including health outcomes and smoking prevalence were extracted from each article. The findings were synthesised narratively. DATA SYNTHESIS: The introduction of e-cigarettes was predicted to lead to decreased smoking-related mortality, increased quality-adjusted life-years and reduced health system costs in 29 studies. Seventeen studies predicted a lower prevalence of cigarette smoking. Models that predicted negative population impacts assumed very high e-cigarette initiation rates among non-smokers and that e-cigarette use would discourage smoking cessation by a large margin. The majority of the studies were based on US population data and few studies included factors other than smoking status, such as jurisdictional tobacco control policies or social influence. CONCLUSIONS: A population increase in e-cigarette use may result in lower smoking prevalence and reduced burden of disease in the long run, especially if their use can be restricted to assisting smoking cessation. Given the assumption-dependent nature of modelling outcomes, future modelling studies should consider incorporating different policy options in their projection exercises, using shorter time horizons and expanding their modelling to low-income and middle-income countries where smoking rates remain relatively high.

Seeking order in patterns of polysubstance use.

PURPOSE OF REVIEW: This review provides an overview of recent developments in understanding polysubstance use patterns across the lifespan, and advances made in the prevention and treatment of harm arising from polysubstance use. RECENT FINDINGS: A comprehensive understanding of the patterns of polysubstance use is hampered by heterogeneity across study methods and types of drugs measured. Use of statistical techniques such as latent class analysis has aided in overcoming this limitation, identifying common patterns or classes of polysubstance use. These typically include, with decreasing prevalence, (1) Alcohol use only; (2) Alcohol and Tobacco; (3) Alcohol, Tobacco, and Cannabis; and finally (4) a low prevalence, Extended Range cluster that includes other illicit drugs, New Psychoactive Substances (NPS), and nonmedical prescription medications. SUMMARY: Across studies, there are commonalities present in clusters of substances used. Future work that integrates novel measures of polysubstance use and leverages advances in drug monitoring, statistical analysis and neuroimaging will improve our understanding of how and why drugs are combined, and more rapidly identify emerging trends in multiple substance use. Polysubstance use is prevalent but there is a paucity of research exploring effective treatments and interventions.

Common adverse events of electronic cigarettes compared with traditional nicotine replacement therapies: A systematic review and meta-analysis.

ISSUES: Established literature suggests that electronic cigarettes (EC) are more effective than traditional nicotine replacement therapies (NRT) as a smoking cessation aid, but the factors that mediate this difference remain poorly understood. We examine how adverse events (AE) associated with EC use relative to NRTs differ, with the view that differences in AEs experienced may drive differences in use and compliance. APPROACH: Papers for inclusion were identified via a three-tiered search strategy. Eligible articles involved healthy participants and compared nicotine ECs to non-nicotine ECs or NRTs and reported frequency of AE as an outcome. Random-effects meta-analyses were conducted to compare the likelihood for each of the AEs between nicotine ECs, non-nicotine placebo ECs and NRTs. KEY FINDINGS: A total of 3756 papers were identified, of which 18 were meta-analysed (10 cross-sectional and 8 randomised controlled trials). Meta-analytic results found no significant difference in the rates of reported AEs (i.e., cough, oral irritation, nausea) between nicotine ECs and NRTs, and between nicotine and non-nicotine placebo ECs. IMPLICATIONS: The variation in the incidence of AEs likely does not explain user preferences of ECs to NRTs. Incidence of common AEs reported because of EC and NRT use did not differ significantly. Future work will need to quantify both the adverse and favourable effects of ECs to understand the experiential mechanisms that drive the high uptake of nicotine ECs relative to established NRTs. CONCLUSIONS: There is inconclusive evidence on the incidence of AEs experience when using ECs compared to NRTs, possibly given the small sample size of studies.

Global prevalence of heated tobacco product use, 2015-22: A systematic review and meta-analysis.

BACKGROUND AND AIMS: Heated tobacco products (HTPs) are electronic devices that heat process tobacco to release an aerosol containing nicotine and other chemicals. Limited data exist on world-wide HTP use prevalence. This meta-analytic review estimated the prevalence of HTP use by country, World Health Organization (WHO) region, year, sex/gender and age. METHODS: Five databases (Web of Science, Scopus, Embase, PubMed and PsycINFO) were searched between January 2015 and May 2022. Included studies reported the prevalence of HTP use in nationally representative samples post-modern HTP device market entry (2015). A random-effects meta-analysis was used to estimate overall prevalence for life-time, current and daily HTP use. RESULTS: Forty-five studies (n = 1 096 076) from 42 countries/areas from the European Region (EUR), Western Pacific Region (WPR), Region of the Americas (AMR) and African Region (AFR) met inclusion criteria. Estimated pooled prevalence for life-time, current and daily HTP use was 4.87% [95% confidence interval (CI) = 4.16, 5.63], 1.53% (95% CI = 1.22, 1.87) and 0.79% (95% CI = 0.48, 1.18), respectively, across all years (2015-22). Life-time HTP use prevalence significantly increased by 3.39% for WPR [0.52% (95% CI = 0.25, 0.88) in 2015 to 3.91% (95% CI = 2.30, 5.92) in 2019] and 5.58% for EUR [1.13% (95% CI = 0.59, 1.97) in 2016 to 6.98% (95% CI = 5.69, 8.39) in 2020]. Current HTP use increased by 10.45% for WPR [0.12% (95% CI = 0, 0.37) in 2015 to 10.57% (95% CI = 5.59, 16.88) in 2020] and 1.15% for EUR [0% (95% CI = 0, 0.35) in 2016 to 1.15% (95% CI = 0.87, 1.47) in 2020]. Meta-regression revealed higher current HTP use in WPR [3.80% (95% CI = 2.88, 4.98)] compared with EUR [1.40% (95% CI = 1.09, 1.74)] and AMR [0.81% (95% CI = 0.46, 1.26)] and for males [3.45% (95% CI = 2.56, 4.47)] compared with females [1.82% (95% CI = 1.39, 2.29)]. Adolescents had higher life-time HTP use prevalence [5.25% (95% CI = 4.36, 6.21) than adults [2.45% (95% CI = 0.79, 4.97)]. Most studies scored a low risk of sampling bias due to their nationally representative sampling. CONCLUSION: The prevalence of HTPs use increased in the EUR and WPR between 2015 and 2020, with nearly 5% of the included populations having ever tried HTP and 1.5% identifying as current users during the study period.

A latent class analysis of patterns of tobacco and cannabis use in Australia and their health-related correlates.

INTRODUCTION: The shifting landscape in Australia's tobacco and cannabis policies and emerging new products and modes of administration may increase experimentation and the risks of addiction to these drugs. METHODS: We analysed cross-sectional data from the 2019 National Drug Strategy and Household Survey (n = 22,015) of Australians aged 14 and above. Latent class analysis was used to identify distinct groups based on types of tobacco and cannabis products used. The socio-demographic, health-rated correlates and past-year substance use of each latent class was examined. RESULTS: A four-class solution was identified: co-use of tobacco and cannabis (2.4%), cannabis-only (5.5%), tobacco-only (8.0%) and non-user (84.0%). Males (odds ratio [OR] range 1.5-2.9), younger age (OR range 2.4-8.4), moderate to high psychological distress (OR range 1.3-3.0), using illicit substances in the last year (OR range 1.41-22.87) and high risk of alcohol use disorder (OR range 2.0-21.7) were more likely to be in the tobacco/cannabis use classes than non-users. Within the co-use class, 78.4% mixed tobacco with cannabis and 89.4% had used alcohol with cannabis at least once. DISCUSSION AND CONCLUSIONS: Approximately 16% of respondents used tobacco or cannabis, or both substances, and no major distinct subgroups were identified by the use of different product types. Mental health issues and the poly-substance use were more common in the class who were co-users of cannabis and tobacco. Existing policies need to minimise cannabis and tobacco-related harms to reduce the societal burden associated with both substances.

Vaping on TikTok: a systematic thematic analysis.

INTRODUCTION: The rising popularity of TikTok among adolescents may influence their awareness and perceptions of e-cigarette use via user-generated content. This study aimed to examine how e-cigarette/vaping-related videos are portrayed on TikTok. METHODS: The nine most viewed hashtag based keywords were used to identify popular e-cigarette/vaping-related videos on TikTok (n=1000) from its inception (earliest upload date: January 2019) to November 2020. Five researchers independently coded the number of views, likes, user category and theme. RESULTS: A final sample of 808 e-cigarette/vaping-related videos that met study criteria were included. Collectively, these videos were viewed over 1.5 billion times, with a median view count of 1 000 000 (range 112 900-78 600 000) and a median 'likes' count of 143 000 (range 10 000-1 000 000). A majority of the videos portrayed e-cigarette use positively (63%; collectively viewed over 1.1 billion times). Neutral depictions of e-cigarette use were viewed a total of 290 million times (24%) and negative depictions of e-cigarettes were viewed a total of 193 million times (13%). The video themes included (not mutually exclusively): 'comedy and joke' (52%; total of 618 million views), 'lifestyle and acceptability' (35%; 459 million), 'marketing' (29%; 392 million), 'vaping tricks' (20%; 487 million), 'nicotine and addiction' (20%; 194 million), 'creativity' (16%; 322 million) and 'warning' (11%; 131 million). CONCLUSION: Our findings illustrated that positively framed e-cigarette and vaping-related postings available without age restrictions on TikTok-a rising video-sharing platform that is popular among adolescents-have been viewed many times. Effective age restrictions are needed to reduce adolescents' potential exposure to videos that portray vaping positively.

Trends and Socio-Demographic Differences of Cannabis Vaping in the USA and Canada.

Given the rise in cannabis vaping, it is important to highlight the heterogeneity in vaping different cannabis product because of the potential differences in their health risks. This study aims to estimate the trends and socio-demographic correlates of the use of various cannabis vaping products across jurisdiction with different legal status. Data from the 2018 (n = 27,169) and 2019 (n = 47,747) waves of the International Cannabis Policy Study (ICPS) were used. Respondents aged 16-65 completed web-based surveys. In 2019, proportions of past year vaping of cannabis oil, dried flower and concentrates in the overall sample were highest in U.S. jurisdictions where cannabis was legalized for non-medical use (17.4%, 6.0%, 4.9%), followed by U.S. jurisdiction where non-medical cannabis use is illegal (13.7%, 5.8%, 2.9%), and lowest in Canada (8.1%, 4.4%, 2.1%). Vaping dried flower decreased from 2019 to 2018 in U.S. legal jurisdictions and Canada, while vaping cannabis oil and concentrates increased in all jurisdictions (p < 0.001). The odds of vaping all forms of products were higher among younger respondents (16-55 years), males, respondents with some college education, and persons with low-risk perceptions on daily cannabis vaping. In both ICPS surveys (2018 and 2019), cannabis oil was the most frequently vaped products, followed by dried flower, and concentrates. Detailed measures of product forms for cannabis vaping should be considered in future surveys.

Improving assessment and progress monitoring in alcohol use disorder: An implementation evaluation of the instant assessment and personalised feedback system (iAx).

BACKGROUND: When treating patients with alcohol use disorder (AUD), best practice guidelines recommend the use of standardised assessment instruments to obtain reliable information about psychological symptoms and functioning to inform treatment. Due to time constraints and administrative burden, many mental health practitioners do not routinely use standardised assessments. To overcome these barriers, an instant assessment and feedback system (iAx) was developed that electronically administers standardised instruments. Responses are instantly scored and benchmarked against clinical norms for immediate interpretation. This allows for timely assessment and feedback. The aim of this study was to evaluate the implementation of the iAx system at a specialist alcohol and drug outpatient unit in a public hospital. METHODS: Baseline (pre-iAx implementation; paper-and-pencil assessments) and follow-up (post-iAx implementation) clinical audits collated records from 313 patients with AUD across 2,616 treatment sessions. Multilevel modelling was used to determine if use of standardised instruments increased post-iAx implementation. RESULTS: Post-iAx implementation, there was a significant increase in the probability of using standardised assessments during the initial assessment and throughout treatment (ps < 0.001). Specifically, the use of standardised assessments to inform initial assessment of patients increased from 51% to 89%, and progress monitoring of symptoms increased from 28% to 84%. A significant increase in treatment completion rates was also observed post-iAx implementation (from 15.6% to 32.4%). Psychologists and patients also provided feedback on iAx acceptability, appropriateness and feasibility. CONCLUSIONS: This study found support for the successful implementation of an electronic, theory-driven iAx system to improve assessment practices with patients with AUD in routine clinical settings.

Changes in patterns of youth multiple tobacco and/or e-cigarette product use in the US between 2014 and 2020: a multiple-group latent class analysis.

BACKGROUND: Multiple tobacco and e-cigarette product (MTEP) use, the concurrent use of two or more different types of tobacco and/or e-cigarettes products, is common among young people in the US. Changes in patterns of MTEP use among US youth between 2014 and 2020 were identified and the determinants of MTEP use were examined. METHODS: Four years of repeated cross-sectional data from the US National Youth Tobacco Survey of middle and high school students from grade 6 to 12 (Ntotal=77 402). Multigroup latent class analysis (LCA) was applied to the data series to allow for simultaneous identification of MTEP use patterns between 2014 and 2020. Logistic regression was used to predict class membership on demographic and tobacco-related variables. FINDINGS: Over the 7-year period, LCA identified three patterns: minimal/non-users (MNU: ~89.8%), mostly occasional e-cigarette and cigarette users (MOEC: ~9%) and polytobacco users (POLY: ~1.2%). From 2014 to 2020, MNU increased from 86.4% to 92% (p<0.05), while MOEC and POLY decreased from 11.2% to 7.9% and from 2.4% to 0.1%, respectively. The probability of regular e-cigarette use increased from 0 to 2.3% among MNU, 6% to 31.9% among MOEC and 29.6% to 67.6% among POLY (p<0.05). In binomial logistic regression, being male, in high school, non-heterosexual, living with someone who uses tobacco at home, having cognitive difficulties, having lower perceptions of tobacco's danger and exposure to tobacco marketing were associated with greater odds of MOEC and POLY than MNU. CONCLUSIONS: There was an increase in regular e-cigarette use in all three classes, but a corresponding decrease in the proportion of MTEP use. Public health interventions to discourage uptake of e-cigarettes, such as tighter restrictions on marketing to minors, are warranted and there is a need to consider disparities in the determinants of MTEP use.

Kynurenine Metabolism as a Mechanism to Improve Fatigue and Physical Function in Postmenopausal Breast Cancer Survivors Following Resistance Training.

This pilot examines whether resistance training (RT) can induce changes in kynurenine (KYN) metabolism, which may contribute to improved physical function in breast cancer survivors (BCSs). Thirty-six BCSs (63.2 ± 1.1 years) underwent assessments of physical function and visual analog scale (100 cm) fatigue and quality of life before and after 12 weeks of RT (N = 22) or non-exercise control (CBCT©: Cognitively Based Compassion Training, N = 10). Blood was collected before and after interventions for assessment of KYN, kynurenic acid (KYNA), and peroxisome proliferator-activated receptor γ co-activator 1α (PGC-1α). At baseline, the women were moderately fatigued (mean score: 46 cm) and at risk of poor functional mobility. A group*time interaction was observed for all measures of strength with improvements (~25−35%) following RT (p's < 0.01), but not CBCT. Time effects were observed for fatigue (−36%) and quality of life (5%) (p's < 0.01), where both groups improved in a similar manner. A group*time interaction was observed for KYN (p = 0.02) and PGC-1α (p < 0.05), with KYN decreasing and PGC-1α increasing following RT and the opposite following CBCT. These changes resulted in KYN/KYNA decreasing 34% post-RT, but increasing 21% following CBCT. These data support RT as a therapeutic intervention to counteract the long-term side effect of fatigue and physical dysfunction in BCSs. Additionally, the results suggest that this effect may be mediated through the activation of PGC-1α leading to alterations in KYN metabolism.

Association between the implementation of tobacco control policies and adolescent vaping in 44 lower-middle, upper-middle, and high-income countries.

AIM: To (i) estimate the prevalence of adolescent vaping in 47 lower-middle, upper-middle and high-income countries, and (ii) test the association between implementation of World Health Organisation (WHO) tobacco control policies and adolescent e-cigarette use (also known as vaping) in 44 countries where implementation data were available. DESIGN: Cross-sectional surveys. SETTINGS: A total of 47 lower-middle, upper-middle and high-income countries. PARTICIPANTS: A total of 151 960 adolescents (typically ages 13-15) who participated in WHO's Global Youth Tobacco Survey between 2015 and 2018. MEASUREMENTS: Prevalence of past-30-day vaping and past 30-day frequent vaping (≥10 days) were estimated from the surveys. Data on the implementation of six tobacco control measures including monitoring, smoke-free policies, cessation programs, warning about the dangers of tobacco, advertising bans and taxation were taken from WHO's report on global tobacco epidemic. FINDINGS: The overall weighted prevalence of adolescent vaping and frequent vaping in the past 30 days was 8.6% (95% CI, 8.3-8.9) and 1.7% (95% CI, 1.6-1.8), respectively. For five of WHO's policies (monitoring, smoking-free environment, cessation programs, health warning and advertising bans), their association with adolescent vaping was inconclusive because of large variation of their effects across countries. Higher tax on combustible tobacco products was associated with higher adolescent vaping (> = 75% tax vs < 25% tax; odds ratio = 2.58; 95% CI, 1.25-5.21). CONCLUSION: In 47 lower-middle, upper-middle and high-income countries from 2015 to 2018, ~1 in 12 (8.6%) adolescents reported vaping in the past 30 days, but prevalence of frequent vaping was low (1 in 60; 1.7%). A higher tobacco tax was associated with higher adolescent vaping.

Assessment of a Plasma Amyloid Probability Score to Estimate Amyloid Positron Emission Tomography Findings Among Adults With Cognitive Impairment.

Importance: The diagnostic evaluation for Alzheimer disease may be improved by a blood-based diagnostic test identifying presence of brain amyloid plaque pathology. Objective: To determine the clinical performance associated with a diagnostic algorithm incorporating plasma amyloid-ß (Aß) 42:40 ratio, patient age, and apoE proteotype to identify brain amyloid status. Design, Setting, and Participants: This cohort study includes analysis from 2 independent cross-sectional cohort studies: the discovery cohort of the Plasma Test for Amyloidosis Risk Screening (PARIS) study, a prospective add-on to the Imaging Dementia-Evidence for Amyloid Scanning study, including 249 patients from 2018 to 2019, and MissionAD, a dataset of 437 biobanked patient samples obtained at screenings during 2016 to 2019. Data were analyzed from May to November 2020. Exposures: Amyloid detected in blood and by positron emission tomography (PET) imaging. Main Outcomes and Measures: The main outcome was the diagnostic performance of plasma Aß42:40 ratio, together with apoE proteotype and age, for identifying amyloid PET status, assessed by accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results: All 686 participants (mean [SD] age 73.2 [6.3] years; 368 [53.6%] men; 378 participants [55.1%] with amyloid PET findings) had symptoms of mild cognitive impairment or mild dementia. The AUC of plasma Aß42:40 ratio for PARIS was 0.79 (95% CI, 0.73-0.85) and 0.86 (95% CI, 0.82-0.89) for MissionAD. Ratio cutoffs for Aß42:40 based on the Youden index were similar between cohorts (PARIS: 0.089; MissionAD: 0.092). A logistic regression model (LRM) incorporating Aß42:40 ratio, apoE proteotype, and age improved diagnostic performance within each cohort (PARIS: AUC, 0.86 [95% CI, 0.81-0.91]; MissionAD: AUC, 0.89 [95% CI, 0.86-0.92]), and overall accuracy was 78% (95% CI, 72%-83%) for PARIS and 83% (95% CI, 79%-86%) for MissionAD. The model developed on the prospectively collected samples from PARIS performed well on the MissionAD samples (AUC, 0.88 [95% CI, 0.84-0.91]; accuracy, 78% [95% CI, 74%-82%]). Training the LRM on combined cohorts yielded an AUC of 0.88 (95% CI, 0.85-0.91) and accuracy of 81% (95% CI, 78%-84%). The output of this LRM is the Amyloid Probability Score (APS). For clinical use, 2 APS cutoff values were established yielding 3 categories, with low, intermediate, and high likelihood of brain amyloid plaque pathology. Conclusions and Relevance: These findings suggest that this blood biomarker test could allow for distinguishing individuals with brain amyloid-positive PET findings from individuals with amyloid-negative PET findings and serve as an aid for Alzheimer disease diagnosis.

Changes in Viewer Engagement and Accessibility of Popular Vaping Videos on TikTok: A 12-Month Prospective Study.

AIM: There are concerns regarding what young people are exposed to on TikTok due to trending content promoting e-cigarette use through humour, marketing and lifestyle acceptability. Using baseline data from November 2020, we aimed to examine how much content from a sample of popular vaping videos remained accessible at 9- and 12-month follow-ups. We aimed to monitor changes in viewer engagement (using metadata) before and after the U.S. Congressional Hearing on youth protection measures on social media in October 2021. METHODS: Hashtag-based keywords were used to collect the most viewed publicly available e-cigarette related videos on TikTok (N = 802) from inception to November 2020 to form a baseline. Researchers conducted a longitudinal descriptive study using this data, with 9- and 12-month follow-ups to measure changes in viewer engagement (using metadata) and content availability. FINDINGS: Of the 802 videos from the baseline, 562 remained at the 9-month follow-up and 511 remained at the 12-month follow-up. At the 12-month follow-up, the majority of vaping-related hashtags were removed by TikTok after the Congressional Hearing. Between the baseline and 9-month follow up, views increased by 1.4% and likes increased by 4.4%. At 12-month follow-up, views had increased by 1.7% and likes by 4.2% compared to baseline data. Whilst 291 videos were no longer publicly accessible at 12-month follow-up, 39 of these were made inaccessible by the content creators. The most viewed and most liked vaping videos at baseline were still publicly available. CONCLUSIONS: Whilst the depiction type and thematic distribution of removed videos suggest that TikTok may be removing a small proportion of content that promotes the use of e-cigarettes, metadata of remaining videos indicate an increase in viewer engagement. TikTok's removal of explicit substance-related hashtags from the platform could be a step towards preventing adolescents from being exposed to harmful behaviours and substances online. However, the platform should consider enforcing effective age restrictions on content that promotes substance use in a positive light.

Non-medical use of pharmaceutical opioids with and without other illicit substance use: Trends from two repeated nationally representative Australian surveys.

Background: Due to concerns over the public health impact of increasing opioid use, Australia up-scheduled codeine in 2018, requiring codeine-containing pharmaceuticals to be prescription-only. We examined pre-post changes in the prevalence and correlates of non-medical use of pharmaceutical opioids (NMUPO) and other illicit substance use (ISU). Methods: We conducted a cross-sectional analysis of 45,463 participants aged 14 or above in the Australian National Drug Strategy Household Surveys (NDSHS) 2016 and 2019. Participants were categorized based on their past 12 months NMUPO and ISU patterns. Correlates examined included socio-demographic, psychological (Kessler 10), health and behavioral variables. Results: The overall prevalence of any NMUPO decreased from 3.56% in 2016 to 2.65% in 2019, and the prevalence of codeine use from 2.98% to 1.49%. No significant changes were observed in the use of other types of painkillers (e.g. oxycodone and fentanyl) between 2016 and 2019. The overall decrease in NMUPO primarily occurred among people who used NMUPO only and did not use other illicit drugs. Older adults were more likely to report NMUPO only. Younger age, higher psychological distress, risky alcohol use, and daily smoking were associated with both NMUPO and illicit drug use. Conclusions: A comparison of cross-sectional data from two time-points showed that the prevalence of NMUPO use among people who used NMUPO exclusively was lower post-up-scheduling of codeine in Australia. However, NMUPO use did not reduce among people who used both NMUPO and other illicit drugs. Public health interventions are needed to reduce opioid-related harm in those who also used other illicit drugs.

Is smoking reduction and cessation associated with increased e-cigarette use? Findings from a nationally representative sample of adult smokers in Australia.

AIMS: E-cigarettes may benefit public health if they are effective for smoking cessation. Evidence suggests that the frequency of e-cigarette use is likely an important predicator of smoking cessation success, so we examined the associations between frequency of e-cigarette use and smoking reduction and cessation in an Australian population sample of past year adult smokers. METHODS: Data from the 2019 National Drug Strategy Household Survey were used (N = 22,015). The sample was restricted to 3868 adults who had smoked within the past year. The outcome was self-reported smoking status and smoking reduction, adjusted for key potential confounders. RESULTS: Compared with no current e-cigarette use, daily e-cigarette users reported an increased likelihood for smoking reduction among current daily smokers (RRR = 2.83; 95% CI = 1.53, 5.22) and were more likely to report quitting smoking among past year smokers (RRR = 2.16; 95% CI = 1.30, 3.58). Smoking reduction and cessation for occasional e-cigarette use were not significantly different from no e-cigarette use. CONCLUSIONS: Daily, but not occasional, e-cigarette users were more likely to quit or reduce smoking cigarettes than Australian smokers who did not use e-cigarettes.