Satellite Images Show the Movement of Floating _Sargassum_ in the Gulf of Mexico and Atlantic Ocean

The question of the origin, distribution and fate of the floating seaweed _Sargassum_ has fascinated sailors and scientists from the time of Columbus. Observations from ships are hampered by the large and variable area over which _Sargassum_ is dispersed. Here we use satellite imagery to present the first mapping of the full distribution and movement of the population of _Sargassum_ in the Gulf of Mexico and western Atlantic in the years 2002 to 2008. For the first time, we show a seasonal pattern in which _Sargassum_ originates in the northwest Gulf of Mexico in spring of each year, is advected into the Atlantic in about July, appearing east of Cape Hatteras as a "Sargassum jet", and ending northeast of the Bahamas in February of the following year. This pattern appears consistent with historical surveys. Future satellite observations will show whether this pattern repeats in all or most years

Developing Evidence-Based Health Policy in a Changing Climate

This article outlines the necessary research and societal supports necessary to ensure thatevidence-based climate adaptation policy to protect society's most vulnerable  members is developed an a comprehensive and timely manner

A Computer-Based Decision Tool for Prioritizing the Reduction of Airborne Chemical Emissions from Canadian Oil Refineries Using Estimated Health Impacts

Petroleum refineries emit a variety of airborne substances which may be harmful to human health. HEIDI II (Health Effects Indicators Decision Index II) is a computer-based decision analysis tool which assesses airborne emissions from Canada's oil refineries for reduction, based on ordinal ranking of estimated health impacts. The model was designed by a project team within NERAM (Network for Environmental Risk Assessment and Management) and assembled with significant stakeholder consultation. HEIDI II is publicly available as a deterministic Excel-based tool which ranks 31 air pollutants based on predicted disease incidence or estimated DALYS (disability adjusted life years). The model includes calculations to account for average annual emissions, ambient concentrations, stack height, meteorology/dispersion, photodegradation, and the population distribution around each refinery. Different formulations of continuous dose-response functions were applied to nonthreshold-acting air toxics, threshold-acting air toxics, and nonthreshold-acting CACs (criteria air contaminants). An updated probabilistic version of HEIDI II was developed using Matlab code to account for parameter uncertainty and identify key leverage variables. Sensitivity analyses indicate that parameter uncertainty in the model variables for annual emissions and for concentration-response/toxicological slopes have the greatest leverage on predicted health impacts. Scenario analyses suggest that the geographic distribution of population density around a refinery site is an important predictor of total health impact. Several ranking metrics (predicted case incidence, simple DALY, and complex DALY) and ordinal ranking approaches (deterministic model, average from Monte Carlo simulation, test of stochastic dominance) were used to identify priority substances for reduction; the results were similar in each case. The predicted impacts of primary and secondary particulate matter (PM) consistently outweighed those of the air toxics. Nickel, PAH (polycyclic aromatic hydrocarbons), BTEX (benzene, toluene, ethylbenzene and xylene), sulphuric acid, and vanadium were consistently identified as priority air toxics at refineries where they were reported emissions. For many substances, the difference in rank order is indeterminate when parametric uncertainty and variability are considered

Concentration-Dependent Effects of a Dietary Ketone Ester on Components of Energy Balance in Mice

Objectives: Exogenous ketones may provide therapeutic benefit in treatment of obesity. Administration of the ketone ester (KE) R,S-1,3-butanediol acetoacetate diester (BD-AcAc2) decreases body weight in mice, but effects on energy balance have not been extensively characterized. The purpose of this investigation was to explore concentration-dependent effects of BD-AcAc2 on energy intake and expenditure in mice.Methods: Forty-two male C57BL/6J mice were randomly assigned to one of seven isocaloric diets (n = 6 per group): (1) Control (CON, 0% KE by kcals); (2) KE5 (5% KE); (3) KE10 (10% KE); (4) KE15 (15% KE); (5) KE20 (20% KE); (6) KE25 (25% KE); and (7) KE30 (30% KE) for 3 weeks. Energy intake and body weight were measured daily. Fat mass (FM), lean body mass (LBM), and energy expenditure (EE) were measured at completion of the study. Differences among groups were compared to CON using ANOVA and ANCOVA.Results: Mean energy intake was similar between CON and each concentration of KE, except KE30 which was 12% lower than CON (P < 0.01). KE25 and KE30 had lower body weight and FM compared to CON, while only KE30 had lower LBM (P < 0.03). Adjusted resting and total EE were lower in KE30 compared to CON (P < 0.03), but similar for all other groups.Conclusions: A diet comprised of 30% energy from BD-AcAc2 results in lower energy intake, coincident with lower body weight and whole animal adiposity; while KE20 and KE25 have significantly lower body weight and adiposity effects independent of changes in energy intake or expenditure

Concentration-Dependent Effects of a Dietary Ketone Ester on Components of Energy Balance in Mice

Exogenous ketones may provide therapeutic benefit in treatment of obesity. Administration of the ketone ester (KE) R,S-1,3-butanediol acetoacetate diester (BD-AcAc) decreases body weight in mice, but effects on energy balance have not been extensively characterized. The purpose of this investigation was to explore concentration-dependent effects of BD-AcAc on energy intake and expenditure in mice. Forty-two male C57BL/6J mice were randomly assigned to one of seven isocaloric diets ( = 6 per group): (1) Control (CON, 0% KE by kcals); (2) KE5 (5% KE); (3) KE10 (10% KE); (4) KE15 (15% KE); (5) KE20 (20% KE); (6) KE25 (25% KE); and (7) KE30 (30% KE) for 3 weeks. Energy intake and body weight were measured daily. Fat mass (FM), lean body mass (LBM), and energy expenditure (EE) were measured at completion of the study. Differences among groups were compared to CON using ANOVA and ANCOVA. Mean energy intake was similar between CON and each concentration of KE, except KE30 which was 12% lower than CON ( \u3c 0.01). KE25 and KE30 had lower body weight and FM compared to CON, while only KE30 had lower LBM ( \u3c 0.03). Adjusted resting and total EE were lower in KE30 compared to CON ( \u3c 0.03), but similar for all other groups. A diet comprised of 30% energy from BD-AcAc results in lower energy intake, coincident with lower body weight and whole animal adiposity; while KE20 and KE25 have significantly lower body weight and adiposity effects independent of changes in energy intake or expenditure

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution.

The early detection of relapse following primary surgery for non-small-cell lung cancer and the characterization of emerging subclones, which seed metastatic sites, might offer new therapeutic approaches for limiting tumour recurrence. The ability to track the evolutionary dynamics of early-stage lung cancer non-invasively in circulating tumour DNA (ctDNA) has not yet been demonstrated. Here we use a tumour-specific phylogenetic approach to profile the ctDNA of the first 100 TRACERx (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy (Rx)) study participants, including one patient who was also recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release and analyse the tumour-volume detection limit. Through blinded profiling of postoperative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients who are very likely to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastasis, providing a new approach for ctDNA-driven therapeutic studies

Tropical Data: Approach and Methodology as Applied to Trachoma Prevalence Surveys

PURPOSE: Population-based prevalence surveys are essential for decision-making on interventions to achieve trachoma elimination as a public health problem. This paper outlines the methodologies of Tropical Data, which supports work to undertake those surveys. METHODS: Tropical Data is a consortium of partners that supports health ministries worldwide to conduct globally standardised prevalence surveys that conform to World Health Organization recommendations. Founding principles are health ministry ownership, partnership and collaboration, and quality assurance and quality control at every step of the survey process. Support covers survey planning, survey design, training, electronic data collection and fieldwork, and data management, analysis and dissemination. Methods are adapted to meet local context and needs. Customisations, operational research and integration of other diseases into routine trachoma surveys have also been supported. RESULTS: Between 29th February 2016 and 24th April 2023, 3373 trachoma surveys across 50 countries have been supported, resulting in 10,818,502 people being examined for trachoma. CONCLUSION: This health ministry-led, standardised approach, with support from the start to the end of the survey process, has helped all trachoma elimination stakeholders to know where interventions are needed, where interventions can be stopped, and when elimination as a public health problem has been achieved. Flexibility to meet specific country contexts, adaptation to changes in global guidance and adjustments in response to user feedback have facilitated innovation in evidence-based methodologies, and supported health ministries to strive for global disease control targets

Identifying inequitable exposure to toxic air pollution in racialized and low-income neighbourhoods to support pollution prevention

Numerous environmental justice studies have confirmed a relationship between population characteristics such as low-income or minority status and the location of environmental health hazards. However, studies of the health risks from exposure to harmful substances often do not consider their toxicological characteristics. We used two different methods, the unit-hazard and the distance-based approach, to evaluate demographic and socio-economic characteristics of the population residing near industrial facilities in the City of Toronto, Canada. In addition to the mass of air emissions obtained from the national pollutant release inventory (NPRI), we also considered their toxicity using toxic equivalency potential (TEP) scores. Results from the unit-hazard approach indicate no significant difference in the proportion of low-income individuals living in host versus non-host census tracts (t(107) = 0.3, P = 0.735). However, using the distance-based approach, the proportion of low-income individuals was significantly higher (+5.1%, t(522) = 6.0, P <0.001) in host tracts, while the indicator for “racialized” communities (“visible minority”) was 16.1% greater (t(521) = 7.2, P <0.001) within 2 km of a NPRI facility. When the most toxic facilities by non-carcinogenic TEP score were selected, the rate of visible minorities living near the most toxic NPRI facilities was significantly higher (+12.9%, t(352) = 3.5, P = 0.001) than near all other NPRI facilities. TEP scores were also used to identify areas in Toronto that face a double burden of poverty and air toxics exposure in order to prioritise pollution prevention