In multivariate analysis, only DM (P = 0.008) was found to be independent risk factors for RP. According to RPA, the risk of developing RP was highest in patients with DM. Conclusions In our study, besides the known dosimetric factors, DM was found to be the most important risk factor causing RP development in multivariate analysis and RPA. The risk is tripled compared to patients without DM.On November 2015, Samarco tailings dam in Mariana MG, Brazil, collapsed, releasing 62 million tons of tailings that advanced through 668 km of the Doce River and adjacent floodplain. Although being the worst environmental disaster in Brazil, little is known about consequences to aquatic biota. Here we evaluate the effects of the tailings mudflow on metal and arsenic concentration in fish and how concentration correlates with water and fish characteristics. We quantified semitotal amounts of Ag, Al, As, Cd, Cr, Cu, Fe, Hg, Mn, Ni, Pb and Zn in fish muscle tissue using ICP-MS in 255 individuals (34 species) sampled in unaffected and affected along the Doce River basin. Arsenic and Hg were higher in fish from affected sites, likely due to turbulent mixing of previously sedimented material by the giant tailings wave. Silver and Zn concentrations were higher in unaffected sites. Arsenic concentration in Geophagus brasiliensis decreased with increasing fish weight. Copper and Zn decreased with increasing fish weight considering the whole assembly of fish. The tailings mudflow increased water conductivity and conductivity increased Al concentration in fish, so we expected a larger Al concentration in fishes from affected sites. However, the observed Al concentration in fishes from affected sites was lower than expected by water conductivity. Thus, the tailings mudflow reduced Al uptake or accumulation in fishes. Mercury decreased with increasing water conductivity in both unaffected and affected sites considering all species and in G. brasiliensis alone. Despite the relatively low concentration range of metals and As found in fish, fishes from sites affected by the iron ore tailings mudflow showed higher As and Hg concentration, compared to fishes from unaffected sites. The higher As and Hg in affected sites require further detailed monitoring to ensure safeguards of human health by fishing activity along the Doce River. This article is protected by copyright. All rights reserved.Aims The impact of ageing on antiretroviral pharmacokinetics remains uncertain, leading to missing dosing recommendations for elderly people living with human immunodeficiency virus (HIV PLWH). The objective of this study was to investigate whether ageing leads to clinically relevant pharmacokinetic changes of antiretrovirals that would support a dose adjustment based on the age of the treated PLWH. Methods Plasma concentrations for 10 first-line antiretrovirals were obtained in PLWH ≥55 years, participating in the Swiss HIV Cohort Study, and used to proof the predictive performance of our physiologically based pharmacokinetic (PBPK) model. The verified PBPK model predicted the continuous effect of ageing on HIV drug pharmacokinetics across adulthood (20-99 years). The impact of ethnicity on age-related pharmacokinetic changes between whites and other races was statistically analysed. Results Clinically observed concentration-time profiles of all investigated antiretrovirals were generally within the 95% confidence interval of the PBPK simulations, demonstrating the predictive power of the modelling approach used. The predicted decline in drug clearance drove age-related pharmacokinetic changes of antiretrovirals, resulting in a maximal 70% [95% confidence interval 40%, 120%] increase in antiretrovirals exposure across adulthood. Peak concentration, time to peak concentration and apparent volume of distribution were predicted to be unaltered by ageing. There was no statistically significant difference of age-related pharmacokinetic changes between studied ethnicities. Conclusion Dose adjustment for antiretrovirals based on the age of male and female PLWH is a priori not necessary in the absence of severe comorbidities considering the large safety margin of the current first-line HIV treatments.Diabetes is a well-established risk factor for both ischemic and hemorrhagic stroke. Individuals with diabetes not only have a higher risk of stroke, they also have worse clinical outcomes after stroke, including poorer neurological recovery, higher rates of stroke recurrence and mortality. In addition to optimizing glycemia, control of cardiovascular risk factors like hypertension and dyslipidemia is crucial in stroke prevention in subjects with diabetes.Background Diabetes mellitus, a metabolic disorder characterised by hyperglycaemia and associated with a heavy burden of microvascular and macrovascular complications, frequently remains undiagnosed. Screening of apparently healthy individuals may lead to early detection and treatment of type 2 diabetes mellitus and may prevent or delay the development of related complications. Objectives To assess the effects of screening for type 2 diabetes mellitus. ON123300 Search methods We searched CENTRAL, MEDLINE, LILACS, the WHO ICTRP, and ClinicalTrials.gov from inception. The date of the last search was May 2019 for all databases. We applied no language restrictions. Selection criteria We included randomised controlled trials involving adults and children without known diabetes mellitus, conducted over at least three months, that assessed the effect of diabetes screening (mass, targeted, or opportunistic) compared to no diabetes screening. Data collection and analysis Two review authors independently screened titles and abslycosylated haemoglobin A1c (HbA1c), and socioeconomic effects. Authors' conclusions We are uncertain about the effects of screening for type 2 diabetes on all-cause mortality and diabetes-related mortality. Evidence was available from one study only. We are therefore unable to draw any firm conclusions relating to the health outcomes of early type 2 diabetes mellitus screening. Furthermore, the included study did not assess all of the outcomes prespecified in the review (diabetes-related morbidity, incidence of type 2 diabetes, health-related quality of life, adverse events, socioeconomic effects).