Diurnal Floc Generation from Neuston Biofilms in Two Contrasting Freshwater Lakes

Selective adaptation of biofilm-forming bacteria to the nutrient-rich but environmentally challenging conditions of the surface microlayer (SML) or neuston layer was evident in littoral regions of two physically and geochemically contrasting freshwater lakes. SML bacterial communities (bacterioneuston) in these systems were depleted in <i>Actinobacteria</i>, enriched in either <i>Betaproteobacteria</i> or <i>Gammaproteobacteria</i>, and either unicellular <i>Cyanobacteria</i> were absent or microbial mat forming <i>Cyanobacteria</i> enriched relative to communities in the underlying shallow water column (0.5 m depth). Consistent with the occurrence of biofilm-hosted, geochemically distinct microhabitats, As-, Fe-, and S-metabolizing bacteria including anaerobic taxa were detected only in the SML in both systems. Over diurnal time scales, higher wind speeds resulted in the generation of floc from SML biofilms, identifying a transport mechanism entraining SML accumulated microorganisms, nutrients, and contaminants into the underlying water column. The energy regime experienced by the SML was more important to floc generation as larger flocs were more abundant in the larger, oligotrophic lake (higher relative energy regime) compared to the sheltered, smaller lake, despite relatively higher concentrations of bacteria, organic carbon, Fe, and PO₄^3– in the latter system

An approach to estimating the environmental burden of cancer from known and probable carcinogens: application to Ontario, Canada

Background: Quantifying the potential cancer cases associated with environmental carcinogen exposure can help inform efforts to improve population health. This study developed an approach to estimate the environmental burden of cancer and applied it to Ontario, Canada. The purpose was to identify environmental carcinogens with the greatest impact on cancer burden to support evidence-based decision making. Methods: We conducted a probabilistic assessment of the environmental burden of cancer in Ontario. We selected 23 carcinogens that we defined as “environmental” (e.g., pollutants) and were relevant to the province, based on select classifications provided by the International Agency for Research on Cancer. We evaluated population exposure to the carcinogens through inhalation of indoor/outdoor air; ingestion of food, water, and dust; and exposure to radiation. We obtained or calculated concentration-response functions relating carcinogen exposure and the risk of developing cancer. Using both human health risk assessment and population attributable fraction models in a Monte Carlo simulation, we estimated the annual cancer cases associated with each environmental carcinogen, reporting the simulation summary (e.g., mean and percentiles). Results: We estimated between 3540 and 6510 annual cancer cases attributable to exposure to 23 environmental carcinogens in Ontario. Three carcinogens were responsible for over 90% of the environmental burden of cancer: solar ultraviolet (UV) radiation, radon in homes, and fine particulate matter (PM2.5) in outdoor air. Eight other carcinogens had an estimated mean burden of at least 10 annual cancer cases: acrylamide, arsenic, asbestos, chromium, diesel engine exhaust particulate matter, dioxins, formaldehyde, and second-hand smoke. The remaining 12 carcinogens had an estimated mean burden of less than 10 annual cancer cases in Ontario. Conclusions: We found the environmental burden of cancer in Ontario to fall between previously estimated burdens of alcohol and tobacco use. These results allow for a comparative assessment across carcinogens and offer insights into strategies to reduce the environmental burden of cancer. Our analysis could be adopted by other jurisdictions and repeated in the future for Ontario to track progress in reducing cancer burden, assess newly classified environmental carcinogens, and identify top burden contributors.Population and Public Health (SPPH), School ofReviewedFacult

Comparative efficacy of therapies for relapsing multiple sclerosis: a systematic review and network meta-analysis

Aim: To assess the relative efficacy of disease-modifying therapies (DMTs) for relapsing multiple sclerosis (RMS) including newer therapies (ozanimod, ponesimod, ublituximab) using network meta-analysis (NMA). Materials & methods: Bayesian NMAs for annualised relapse rate (ARR) and time to 3-month and 6- month confirmed disability progression (3mCDP and 6mCDP) were conducted. Results: For each outcome, the three most efficacious treatments versus placebo were monoclonal antibody (mAb) therapies: alemtuzumab, ofatumumab, and ublituximab for ARR; alemtuzumab, ocrelizumab, and ofatumumab for 3mCDP; and alemtuzumab, natalizumab, and either ocrelizumab or ofatumumab (depending on the CDP definition used for included ofatumumab trials) for 6mCDP. Conclusion: The most efficacious DMTs for RMS were mAb therapies. Of the newer therapies, only ublituximab ranked among the three most efficacious treatments (for ARR)

Exploring nighttime road traffic noise: A comprehensive predictive surface for Toronto, Canada

<p>Road traffic noise can adversely impact the health of city residents, particularly when it occurs at night. The objective of this study was to evaluate nighttime traffic ambient noise in Toronto, Canada using measured and model-estimated noise levels. Road traffic noise was measured at 767 locations over 3 seasonal sampling campaigns between June 2012 and October 2013 to fully capture noise variability in Toronto. Temporal and campaign-specific spatial models, developed using the noise measurements, were used to build a final predictive surface. The surface was capable of estimating noise across the city over a 24-hr time frame. Measured and surface-estimated noise levels were compared with guidelines from the World Health Organization and the Province of Ontario to identify areas where noise may pose a health risk. Measured mean nighttime noise in Toronto exceeded World Health Organization (40 dBA) guidelines and mean daytime noise exceeded provincial (55 dBA) guidelines. The final predictive surface, incorporating spatial variables and daily cycles in noise levels, provides noise estimates geocoded for the entire study area. This tool could be used for epidemiological studies and to inform noise mitigation efforts. Based on surface-estimated noise levels during the quietest time of night (2 a.m.–2:30 a.m.), 100% of Toronto has nighttime noise exceeding 40 dBA (mean = 57 dBA, range = 49–110 dBA). A predictive surface was developed to estimate geocoded noise levels and facilitate further study of noise in Toronto. This tool can be used to assess road traffic noise, particularly at night, as an environmental health hazard.</p

Adaptation de la famille et des proches

info:eu-repo/semantics/publishe