Pharmacokinetics of delta-9-tetrahydrocannabinol following acute cannabis smoke exposure in mice; effects of sex, age, and strain

Increased use of cannabis and cannabinoids for recreational and medical purposes has led to a growth in research on their effects in animal models. The majority of this work has employed cannabinoid injections; however, smoking remains the most common route of cannabis consumption. To better model real-world cannabis use, we exposed mice to cannabis smoke to establish the pharmacokinetics of Δ9THC and its metabolites in plasma and brain. To determine the time course of Δ9THC and two major metabolites [11-hydroxy-delta-9-tetrahydrocannabinol (11-OH-THC) and 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (11-COOH-THC)], male and female C57BL/6J mice were exposed to smoke from sequentially burning 5 cannabis cigarettes. Following smoke exposure, trunk blood and brains were collected at 6 time points (10–240 min). Plasma and brain homogenates were analyzed for Δ9THC and metabolites using a validated ultraperformance liquid chromatography-tandem mass spectrometry method. To assess effects of age, sex, and mouse strain, we exposed mice of four strains (C57BL/6J, FVB, Swiss Webster, and 129S6/SvEv, aged 4–24 months) to cannabis using the same smoke regimen. Samples were collected 10 and 40 min following exposure. Lastly, to assess effects of dose, C57BL/6J mice were exposed to smoke from burning 3 or 5 cannabis cigarettes, with samples collected 40 min following exposure. The pharmacokinetic study revealed that maximum plasma Δ9THC concentrations (Cmax) were achieved at 10 and 40 min for males and females, respectively, while Cmax for brain Δ9THC was observed at 20 and 40 min for males and females, respectively. There were no age or strain differences in plasma Δ9THC concentrations at 10 or 40 min; however, 129S6/SvEv mice had significantly higher brain Δ9THC concentrations than FVB mice. Additionally, 3 cigarettes produced significantly lower plasma 11-COOH-THC concentrations compared to 5 cigarettes, although dose differences were not evident in plasma or brain concentrations of Δ9THC or 11-OH-THC. Across all experiments, females had higher levels of 11-COOH-THC in plasma compared to males. The results reveal robust sex differences in Δ9THC pharmacokinetics, and lay the groundwork for future studies using mice to model the pharmacodynamics of smoked cannabis

Responding to Natural and industrial Disasters: Partnerships and Lessons Learned

OBJECTIVES: The aim of this study was to provide insights learned from disaster research response (DR2) efforts following Hurricane Harvey in 2017 to launch DR2 activities following the Intercontinental Terminals Company (ITC) fire in Deer Park, Texas, in 2019. METHODS: A multidisciplinary group of academic, community, and government partners launched a myriad of DR2 activities. RESULTS: The DR2 response to Hurricane Harvey focused on enhancing environmental health literacy around clean-up efforts, measuring environmental contaminants in soil and water in impacted neighborhoods, and launching studies to evaluate the health impact of the disaster. The lessons learned after Harvey enabled rapid DR2 activities following the ITC fire, including air monitoring and administering surveys and in-depth interviews with affected residents. CONCLUSIONS: Embedding DR2 activities at academic institutions can enable rapid deployment of lessons learned from one disaster to enhance the response to subsequent disasters, even when those disasters are different. Our experience demonstrates the importance of academic institutions working with governmental and community partners to support timely disaster response efforts. Efforts enabled by such experience include providing health and safety training and consistent and reliable messaging, collecting time-sensitive and critical data in the wake of the event, and launching research to understand health impacts and improve resiliency

Prevalence of Alcohol Consumption and Hazardous Drinking, Tobacco and Drug Use in Urban Tanzania, and Their Associated Risk Factors

Evidence suggests substance abuse in Tanzania is a growing public health problem. A random sample of 899 adults aged 15–59 in two urban sites of differing levels of poverty surveyed alcohol, tobacco and illicit substance use. Rates of substance use were 17.2%. 8.7% and 0.8% for alcohol, tobacco and cannabis, respectively. Living in the less affluent area was associated with higher lifetime rates of tobacco and alcohol use. Substance use is less prevalent in Tanzania than in richer countries, but lifetime consumption is higher in poorer areas. The association of substance use with a range of socio-economic factors warrants further research

Modeling Joint Exposures and Health Outcomes for Cumulative Risk Assessment: The Case of Radon and Smoking

Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors

Safety and Efficacy of Dolutegravir in Treatment-Experienced Subjects With Raltegravir-Resistant HIV Type 1 Infection: 24-Week Results of the VIKING Study

Background. Dolutegravir (DTG; S/GSK1349572), a human immunodeficiency virus type 1 (HIV-1) integrase inhibitor, has limited cross-resistance to raltegravir (RAL) and elvitegravir in vitro. This phase IIb study assessed the activity of DTG in HIV-1–infected subjects with genotypic evidence of RAL resistance.Methods. Subjects received DTG 50 mg once daily (cohort I) or 50 mg twice daily (cohort II) while continuing a failing regimen (without RAL) through day 10, after which the background regimen was optimized, when feasible, for cohort I, and at least 1 fully active drug was mandated for cohort II. The primary efficacy end point was the proportion of subjects on day 11 in whom the plasma HIV-1 RNA load decreased by ≥0.7 log10 copies/mL from baseline or was <400 copies/mL.Results. A rapid antiviral response was observed. More subjects achieved the primary end point in cohort II (23 of 24 [96%]), compared with cohort I (21 of 27 [78%]) at day 11. At week 24, 41% and 75% of subjects had an HIV-1 RNA load of <50 copies/mL in cohorts I and II, respectively. Further integrase genotypic evolution was uncommon. Dolutegravir had a good, similar safety profile with each dosing regimen.Conclusion. Dolutegravir 50 mg twice daily with an optimized background provided greater and more durable benefit than the once-daily regimen. These data are the first clinical demonstration of the activity of any integrase inhibitor in subjects with HIV-1 resistant to RAL

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Colliding Worlds: Asteroid research and the legitimization of war in space

Accepted versio

New isotope technologies in environmental physics

As the levels of radionuclides observed at present in the environment are very low, high sensitive analytical systems are required for carrying out environmental investigations. We review recent progress which has been done in low-level counting techniques in both radiometrics and mass spectrometry sectors, with emphasis on underground laboratories, Monte Carlo (GEANT) simulation of background of HPGe detectors operating in various configurations, secondary ionisation mass spectrometry, and accelerator mass spectrometry. Applications of radiometrics and mass spectrometry techniques in radioecology and climate change studies are presented and discussed as well. The review should help readers in better orientation on recent developments in the field of low-level counting and spectrometry, and to advice on construction principles of underground laboratories, as well as on criteria how to choose low or high energy mass spectrometers for environmental investigations

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease