Long-Term Exposure to Silica Dust and Risk of Total and Cause-Specific Mortality in Chinese Workers: A Cohort Study

A retro-prospective cohort study by Weihong Chen and colleagues provides new estimates for the risk of total and cause-specific mortality due to long-term silica dust exposure among Chinese workers

Synthesis and Properties of pH-, Thermo-, and Salt-Sensitive Modified Poly(aspartic acid)/Poly(vinyl alcohol) IPN Hydrogel and Its Drug Controlled Release

Modified poly(aspartic acid)/poly(vinyl alcohol) interpenetrating polymer network (KPAsp/PVA IPN) hydrogel for drug controlled release was synthesized by a simple one-step method in aqueous system using poly(aspartic acid) grafting 3-aminopropyltriethoxysilane (KH-550) and poly(vinyl alcohol) (PVA) as materials. The hydrogel surface morphology and composition were characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The thermal stability was analyzed by thermogravimetric analysis (TGA). The swelling properties and pH, temperature, and salt sensitivities of KPAsp, KPAsp/PVA semi-interpenetrating polymer network (semi-IPN), and KPAsp/PVA IPN hydrogels were also investigated. All of the three hydrogels showed ampholytic pH-responsive properties, and swelling behavior was also extremely sensitive to the temperature, ionic strength, and cationic species. Finally, the drug controlled release properties of the three hydrogels were evaluated and results indicated that three hydrogels could control drug release by external surroundings stimuli. The drug controlled release properties of KPAsp/PVA IPN hydrogel are the most outstanding, and the correlative measured release profiles of salicylic acid at 37°C were 32.6 wt% at pH = 1.2 (simulated gastric fluid) and 62.5 wt% at pH = 7.4 (simulated intestinal fluid), respectively. These results indicated that KPAsp/PVA IPN hydrogels are a promising carrier system for controlled drug delivery

Estimated HRs for total and cause-specific mortality associated with a continuous CDE variable in nested case–control samples from workers with detailed data on historical silica exposure and smoking, 1960–2003.

<p>HRs and 95% CIs were derived from penalized spline regression models to examine the nonlinear relation of CDE to mortality. The vertical solid line in each panel represents the 95th percentile of CDE. Dashed lines represent the point estimate of the HR adjusted for duration of follow-up (time-dependent, continuous) and calendar time (time-dependent, continuous); solid lines represent HR further adjusted for smoking (never smoked/ever smoked), with dotted lines indicating the 95% CI; the rug plots along the horizontal axes give the distribution of CDE values. For simplicity of presentation, the reference value of CDE was set to 0 mg/m³-y (0.01 mg/m³-y for pneumoconiosis).</p

Annual silica dust concentrations, average of all job titles in different mines/factories in China, 1950–2003.

<p>Annual silica dust concentrations, average of all job titles in different mines/factories in China, 1950–2003.</p

Description of the cohort (<i>n</i> = 74,040) based on different types of mine/factory, 1960–2003.

<p>Description of the cohort (<i>n</i> = 74,040) based on different types of mine/factory, 1960–2003.</p

Estimated SMRs for underlying cause of death of silica-dust-exposed workers in the cohort (<i>n</i> = 72,248), 1970–2003.

<p>SMRs were estimated based on Chinese national mortality rates (not available before 1970).</p

Characteristics of the cohort (<i>n</i> = 74,040) based on CDE, 1960–2003.

<p>Values expressed as mean ± standard deviation, unless otherwise indicated. Percentages may not total 100 due to rounding.</p>a<p>Levels are tertiles of CDE of all the workers with exposure to silica dust: low, 0.01–1.23 mg/m³-y; medium, 1.24–4.46 mg/m³-y; and high, >4.46 mg/m³-y.</p>b<p>Data were available for the sub-cohorts that had been followed through the end of 2003. Smokers were defined as those who had smoked regularly for over 1 y. Smokers who stopped smoking within 1 y before the end of follow-up were defined as current smokers.</p>c<p>These characteristics were calculated among workers exposed to silica dust. Mean silica dust concentration was calculated as CDE divided by duration of silica dust exposure.</p>d<p>These characteristics were calculated among workers diagnosed with pneumoconiosis. Latency of pneumoconiosis was defined as the period between the year of first exposure to dust and the year of first diagnosis of pneumoconiosis.</p><p>NA, not applicable.</p

Estimated HRs for total and cause-specific mortality associated with CDE in the cohort (<i>n</i> = 74,040), 1960–2003.

<p>All Cox proportional hazards models included age as the time variable. Categorical analyses were based on levels of CDE, including unexposed, low, medium, and high; the unexposed level was used as the reference category (low level for pneumoconiosis). In all models, the HRs associated with CDE were adjusted for gender, year of hire (five categories: 1955 or earlier, 1956–1960, 1961–1965, 1966–1970, and 1970 or later), age at hire (continuous), and type of mine/factory (four categories: tungsten, iron/copper, tin, and pottery).</p>a<p>Levels were tertiles of CDE of all the workers with exposure to silica dust: low, 0.01–1.23 mg/m³-y; medium, 1.24–4.46 mg/m³-y; and high, >4.46 mg/m³-y.</p>b<p>Assessed by including the median values of exposure within each category as a continuous variable in the model, including the reference category.</p

Spatially-explicit modelling of grassland classes - an improved method of integrating a climate-based classification model with interpolated climate surfaces

Spatially-explicit modelling of grassland classes is important to site-specific planning for improving grassland and environmental management over large areas. In this study, a climate-based grassland classification model, the Comprehensive and Sequential Classification System (CSCS) was integrated with spatially interpolated climate data to classify grassland in Gansu province, China. The study area is characterized by complex topographic features imposed by plateaus, high mountains, basins and deserts. To improve the quality of the interpolated climate data and the quality of the spatial classification over this complex topography, three linear regression methods, namely an analytic method based on multiple regression and residues (AMMRR), a modification of the AMMRR method through adding the effect of slope and aspect to the interpolation analysis (M-AMMRR) and a method which replaces the IDW approach for residue interpolation in M-AMMRR with an ordinary kriging approach (I-AMMRR), for interpolating climate variables were evaluated. The interpolation outcomes from the best interpolation method were then used in the CSCS model to classify the grassland in the study area. Climate variables interpolated included the annual cumulative temperature and annual total precipitation. The results indicated that the AMMRR and M-AMMRR methods generated acceptable climate surfaces but the best model fit and cross validation result were achieved by the I-AMMRR method. Twenty-six grassland classes were classified for the study area. The four grassland vegetation classes that covered more than half of the total study area were "cool temperate-arid temperate zonal semi-desert", "cool temperate-humid forest steppe and deciduous broad-leaved forest", "temperate-extra-arid temperate zonal desert", and "frigid per-humid rain tundra and alpine meadow". The vegetation classification map generated in this study provides spatial information on the locations and extents of the different grassland classes. This information can be used to facilitate government agencies' decision-making in land-use planning and environmental management, and for vegetation and biodiversity conservation. The information can also be used to assist land managers in the estimation of safe carrying capacities which will help to prevent overgrazing and land degradation