Clobetasol Propionate Cream Versus Halcinonide Cream in Psoriasis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66420/1/j.1365-4362.1986.tb02261.x.pd

Riječ uredništva

BACKGROUND: Methods for estimating air pollutant exposures for epidemiological studies are becoming more complex in an effort to minimise exposure error and its associated bias. While land use regression (LUR) modelling is now an established method, there has been little comparison between LUR and other recent, more complex estimation methods. Our aim was to develop a LUR model to estimate intra-city exposures to nitrogen dioxide (NO2) for a Sydney cohort, and to compare those with estimates from a national satellite-based LUR model (Sat-LUR) and a regional Bayesian Maximum Entropy (BME) model. METHODS: Satellite-based LUR and BME estimates were obtained using existing models. We used methods consistent with the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to develop LUR models for NO2 and NOx. We deployed 46 Ogawa passive samplers across western Sydney during 2013/2014 and acquired data on land use, population density, and traffic volumes for the study area. Annual average NO2 concentrations for 2013 were estimated for 947 addresses in the study area using the three models: standard LUR, Sat-LUR and a BME model. Agreement between the estimates from the three models was assessed using interclass correlation coefficient (ICC), Bland-Altman methods and correlation analysis (CC). RESULTS: The NO2 LUR model predicted 84% of spatial variability in annual mean NO2 (RMSE: 1.2 ppb; cross-validated R2: 0.82) with predictors of major roads, population and dwelling density, heavy traffic and commercial land use. A separate model was developed that captured 92% of variability in NOx (RMSE 2.3 ppb; cross-validated R2: 0.90). The annual average NO2 concentrations were 7.31 ppb (SD: 1.91), 7.01 ppb (SD: 1.92) and 7.90 ppb (SD: 1.85), for the LUR, Sat-LUR and BME models respectively. Comparing the standard LUR with Sat-LUR NO2 cohort estimates, the mean estimates from the LUR were 4% higher than the Sat-LUR estimates, and the ICC was 0.73. The Pearson's correlation coefficients (CC) for the LUR vs Sat-LUR values were r = 0.73 (log-transformed data) and r = 0.69 (untransformed data). Comparison of the NO2 cohort estimates from the LUR model with the BME blended model indicated that the LUR mean estimates were 8% lower than the BME estimates. The ICC for the LUR vs BME estimates was 0.73. The CC for the logged LUR vs BME estimates was r = 0.73 and for the unlogged estimates was r = 0.69. CONCLUSIONS: Our LUR models explained a high degree of spatial variability in annual mean NO2 and NOx in western Sydney. The results indicate very good agreement between the intra-city LUR, national-scale sat-LUR, and regional BME models for estimating NO2 for a cohort of children residing in Sydney, despite the different data inputs and differences in spatial scales of the models, providing confidence in their use in epidemiological studies

Avoidable mortality attributable to anthropogenic fine particulate matter (Pm2.5) in Australia

Ambient fine particulate matter 2.5) air pollution increases premature mortalityglobally. Some PM2.5 is natural, but anthropogenic PM2.5 is comparatively avoidable. We determinedthe impact of long-term exposures to the anthropogenic PM component on mortality in Australia.PM2.5-attributable deaths were calculated for all Australian Statistical Area 2 (SA2; n = 2310) regions.All-cause death rates from Australian mortality and population databases were combined withannual anthropogenic PM2.5 exposures for the years 2006–2016. Relative risk estimates were derivedfrom the literature. Population-weighted average PM2.5 concentrations were estimated in eachSA2 using a satellite and land use regression model for Australia. PM2.5-attributable mortality wascalculated using a health-impact assessment methodology with life tables and all-cause death rates.The changes in life expectancy (LE) from birth, years of life lost (YLL), and economic cost of lostlife years were calculated using the 2019 value of a statistical life. Nationally, long-term populationweighted average total and anthropogenic PM2.5 concentrations were 6.5 µg/m3(min 1.2–max 14.2)and 3.2 µg/m3(min 0–max 9.5), respectively. Annually, anthropogenic PM2.5-pollution is associatedwith 2616 (95% confidence intervals 1712, 3455) deaths, corresponding to a 0.2-year (95% CI 0.14, 0.28)reduction in LE for children aged 0–4 years, 38,962 (95%CI 25,391, 51,669) YLL and an average annualeconomic burden of $6.2 billion (95$4.0 billion, $8.1 billion). We conclude that the anthropogenicPM2.5-related costs of mortality in Australia are higher than community standards should allow,and reductions in emissions are recommended to achieve avoidable mortality

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases

Identifying Shopping Problems and Improving Retail Patronage Among Urban Filipino Customers

This paper describes the common problems that urban Filipinos encounter while shopping for groceries in supermarkets. Store exit interviews with 500 customers were conducted to elicit reasons for retail patronage and shopping difficulties. Typical Filipino shopping problems are not markedly different from their Western counterparts. Implications on how to improve the shopping experience and retail patronage are identified for Filipino retailers