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China is now confronting the intertwined challenges of air pollution and climate change. Given the high synergies between air pollution abatement and climate change mitigation, the Chinese government is actively promoting synergetic control of these two issues. The Synergetic Roadmap project was launched in 2021 to track and analyze the progress of synergetic control in China by developing and monitoring key indicators. The Synergetic Roadmap 2022 report is the first annual update, featuring 20 indicators across five aspects: synergetic governance system and practices, progress in structural transition, air pollution and associated weather-climate interactions, sources, sinks, and mitigation pathway of atmospheric composition, and health impacts and benefits of coordinated control. Compared to the comprehensive review presented in the 2021 report, the Synergetic Roadmap 2022 report places particular emphasis on progress in 2021 with highlights on actions in key sectors and the relevant milestones. These milestones include the proportion of non-fossil power generation capacity surpassing coal-fired capacity for the first time, a decline in the production of crude steel and cement after years of growth, and the surging penetration of electric vehicles. Additionally, in 2022, China issued the first national policy that synergizes abatements of pollution and carbon emissions, marking a new era for China's pollution-carbon co-control. These changes highlight China's efforts to reshape its energy, economic, and transportation structures to meet the demand for synergetic control and sustainable development. Consequently, the country has witnessed a slowdown in carbon emission growth, improved air quality, and increased health benefits in recent years.

Abstract Autosomal recessive (AR) disorders pose a significant burden for public health. However, despite their clinical importance, epidemiology and molecular genetics of many AR diseases remain poorly characterized. Here, we analyzed the genetic variability of 508 genes associated with AR disorders based on sequencing data from 141,456 individuals across seven ethnogeographic groups by integrating variants with documented pathogenicity from ClinVar, with stringent functionality predictions for variants with unknown pathogenicity. We first validated our model using 85 diseases for which population-specific prevalence data were available and found that our estimates strongly correlated with the respective clinically observed disease frequencies (r = 0.68; p 25 additional population-specific founder mutations. The presented analyses reveal the molecular genetics of AR diseases with unprecedented resolution and provide insights into epidemiology, complexity, and population-specific founder effects. These data can serve as a powerful resource for clinical geneticists to inform population-adjusted genetic screening programs, particularly in otherwise understudied ethnogeographic groups.

Abstract Background The biological network is highly dynamic. Functional relations between genes can be activated or deactivated depending on the biological conditions. On the genome-scale network, subnetworks that gain or lose local expression consistency may shed light on the regulatory mechanisms related to the changing biological conditions, such as disease status or tissue developmental stages. Results In this study, we develop a new method to select genes and modules on the existing biological network, in which local expression consistency changes significantly between clinical conditions. The method is called DNLC: Differential Network Local Consistency. In simulations, our algorithm detected artificially created local consistency changes effectively. We applied the method on two publicly available datasets, and the method detected novel genes and network modules that were biologically plausible. Conclusions The new method is effective in finding modules in which the gene expression consistency change between clinical conditions. It is a useful tool that complements traditional differential expression analyses to make discoveries from gene expression data. The R package is available at https://cran.r-project.org/web/packages/DNLC.

Background: Previous studies have reported inverse associations between urban greenness and mortality. However, findings regarding contemporaneous and cumulative average greenness exposure are inconsistent. A potential explanation is the weak effects of greenness among the general population. This study assessed the associations between contemporaneous and cumulative average greenness exposure and survival in lung cancer patients. Methods: An open cohort consisting of lung cancer patients enrolled from 1 January 2001 was studied. The cohort was followed up until 31 December 2018. We evaluated contemporaneous and cumulative greenness exposure using the normalized difference vegetation index (NDVI) within a 250 m buffer of each patient’s geocoded residential address. The association between NDVI and mortality was evaluated using both time-fixed and time-varying Cox models. Their difference was compared either. Results: In time-fixed Cox models, a 0.1-unit increment in contemporaneous and cumulative average NDVI was associated with 17% (95% confidence interval [CI], 15–18%) and 7% (95% CI, 5–8%) reductions in mortality rate, respectively. Time-varying Cox models consistently revealed significant associations, but their magnitudes were lower, at 2% (95% CI, 1–3%) for both contemporaneous and cumulative average NDVI. Compared to the time-fixed models, the time-varying ones exhibited better fit for the proportional hazard assumption in Cox regressions with more conservative results. Conclusion: Urban greenness is positively associated with an increased chance of survival in lung cancer patients. Compared to time-fixed Cox models, the results of time-varying Cox models were more conservative. This study confirms the beneficial health effects of urban greenness, which may facilitate the improvement of public health by urban green space planning.

Background: Active commuting as a contributor to daily physical activity is beneficial for cardiovascular health, but leads to more chances of exposure to ambient air pollution. This study aimed to investigate associations between active commuting to work with cardiovascular disease (CVD), mortality and life expectancy among general Chinese adults, and to further evaluate the modification effect of fine particulate matter (PM2.5) exposure on these associations. Methods: We included 76,176 Chinese adults without CVD from three large cohorts of the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project. Information about commuting mode and physical activity were collected by unified questionnaire. Satellite-based PM2.5 concentrations at 1-km spatial resolution was used for estimating PM2.5 exposure of participants. Hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD incidence, mortality and all-cause mortality were estimated using Cox proportional hazards regression models. Multiplicative interaction term of commuting mode and PM2.5 level was tested to investigate potential effect modification. Results: During 448,499 person-years of follow-up, 2230 CVD events and 2777 all-cause deaths were recorded. Compared with the non-active commuters, the multivariable-adjusted HRs (95% CIs) of CVD incidence and all-cause mortality were 0.95(0.85–1.05) and 0.79(0.72–0.87) for walking commuters, respectively. Corresponding HRs (95% CIs) for cycling commuters were 0.71(0.62–0.82) and 0.67(0.59–0.76). Active commuters over 45 years old were estimated to have more CVD-free years and life expectancy than non-active commuters under lower PM2.5 concentration. However, these beneficial effects of active commuting were alleviated or counteracted by long-term exposure to high PM2.5 concentration. Significant multiplicative interaction of commuting mode and PM2.5 level was showed in all-cause mortality, with the lowest risk observed in cycling participants exposed to lower level of PM2.5. Conclusions: Active commuting was associated with lower risk of CVD, all-cause mortality, and longer life expectancy among Chinese adults under ambient settings with lower PM2.5 level. It will be valuable to encourage active commuting among adults and develop stringent strategies on ambient PM2.5 pollution control for prevention of CVD and prolongation of life expectancy.

Background: Diabetes caused substantial economic and health burden worldwide. However, the associations between air pollution and diabetes incidence were rarely reported in the developing countries, especially in China with relatively high PM2.5 concentrations. Objectives: A cohort-based study was conducted to assess the diabetes incidence associated with long-term exposure to ambient PM2.5. Methods: We collected individual health data and risk factors from the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR Project) from 15 provinces over China. Diabetes was defined as fasting glucose levels ≥7.0 mmol/L at the follow-ups and/or the use of insulin or oral hypoglycemic agents and/or diagnosed medical history of diabetes during 2004 to 2015. Individual-level PM2.5 exposures were estimated from satellite-based PM2.5 concentrations (10 km spatial resolution) during the study period. Cox proportional hazards models with random intercepts of each cohort and region were employed to estimate the diabetes incidence attributable to PM2.5, after the adjustment for age, gender, body mass index, smoking status, education, work-related physical activity level, hypertension, urbanicity, county-level averaged years of education, and long-term levels of temperature and relative humidity. Results: A total of 88,397 subjects were analyzed with 580,928 person-years of follow-up after 2004, among which 6439 new cases of diabetes were observed. The mean age of the subjects was 51.7 years at baseline. For an increase of 10 μg/m3 in long-term PM2.5 exposure, the multivariable-adjusted percent increase in the diabetes incidence was estimated to be 15.66% (95% confidence interval: 6.42%, 25.70%). The adverse effects of PM2.5 were larger among females, rural subjects, non-smokers, normotensives, subjects younger than 65 years and subjects with body mass index

Exposure to ozone (O3) is associated with stroke incidence and mortality. However, whether long-term exposure to O3 is associated with post-stroke neurological disability remains unknown. This study investigated the relationship based on the longitudinal analysis of China National Stroke Screening Survey (CNSSS), which included 65,778 records of stroke patients. All of the analyzed patients were followed-up at least twice. Stroke disability was assessed using the modified Rankin scale (mRS). Long-term exposure was assessed by the peak-season or annual mean of maximum 8-h O3 concentrations for 365 days before the mRS measurement. We used fixed-effect models to evaluate the associations between O3 and mRS score, with adjustment for multiple confounders, and found a 10 µg/m3 increase in peak-season O3 concentration was associated with a 0.0186 (95% confidence interval [CI] 0.0115–0.0256) increment in the mRS score. The association was robust in various subpopulations. For secondary outcomes, for each 10 µg/m3 increment in peak-season O3, the odds ratio of an increased mRS score (vs. unchanged or decreased mRS score) increased by 23% (95% CI 9–37%). A nonlinear analysis showed a sublinear association between O3 exposure and risk for post-stroke disability. A saturation effect was observed at an O3 concentration of more than ~120 μg/m3. Our study adds to evidence that long-term exposure to O3 increases the risk of neurological disability after stroke.

Resistance to Immune Checkpoint Blockade (ICB) constitutes the current limiting factor for the optimal implementation of this novel therapy, which otherwise demonstrates durable responses with acceptable toxicity scores. This limitation is exacerbated by a lack of robust biomarkers. In this study, we have dissected the basal TME composition at the gene expression and cellular levels that predict response to Nivolumab and prognosis. BCR, TCR and HLA profiling were employed for further characterization of the molecular variables associated with response. The findings were validated using a single-cell RNA-seq data of metastatic melanoma patients treated with ICB, and by multispectral immunofluorescence. Finally, machine learning was employed to construct a prediction algorithm that was validated across eight metastatic melanoma cohorts treated with ICB. Using this strategy, we have unmasked a major role played by basal intratumoral Plasma cells expressing high levels of IGKC in efficacy. IGKC, differentially expressed in good responders, was also identified within the Top response-related BCR clonotypes, together with IGK variants. These results were validated at gene, cellular and protein levels; CD138+ Plasma-like and Plasma cells were more abundant in good responders and correlated with the same RNA-seq-defined fraction. Finally, we generated a 15-gene prediction model that outperformed the current reference score in eight ICB-treated metastatic melanoma cohorts. The evidenced major contribution of basal intratumoral IGKC and Plasma cells in good response and outcome in ICB in metastatic melanoma is a groundbreaking finding in the field beyond the role of T lymphocytes.

To improve air quality, China has been implementing strict clean air policies since 2013. These policies not only substantially improved air quality but may also modify the spatial distribution of air pollution, since urban emission sources were under stricter control and some were moved to rural regions with lower air quality improvement targets and lacking of monitoring. Here, we predicted satellite-based monthly PM2.5 concentrations during 2000–2018 at a 1-km resolution with complete spatial-temporal coverage to analyze changes in the spatial pattern of PM2.5 pollution in China. We found that the PM2.5 concentration in urban regions was higher than that in rural regions of the same city by an average of 3.3 μg/m3 during 2000–2018. This urban-rural disparity in PM2.5 concentration significantly increased from 2.5 μg/m3 in 2000 and peaked in 2007 of 3.8 μg/m3, then it sharply declined by 49% during 2013–2018 with the implementation of clean air policies. This shrinkage in the urban-rural PM2.5 gap was partly due to the 1.3 μg/m3 greater average decrease in the PM2.5 level in the urban region than in the rural region of the same town during 2013–2018 on average. We also observed that cities that started monitoring earlier experienced greater decreases in the urban-rural PM2.5 difference, and regions surrounding monitor showed significantly greater PM2.5 decrease than regions far away from monitor during 2013–2018. Additionally, clean air policies modified the relationship between PM2.5 concentrations and per capita gross domestic product (GDP), leading to a lower PM2.5 level with the same per capita GDP after 2013. Emissions in rural and suburban regions should be considered to further improve air quality in China.

Background: The concentration-response relationship between mortality and long-term exposure to fine particulate matter (PM2.5) has not been fully elucidated, especially at high levels of PM2.5 concentrations. Objective: We aimed to evaluate chronic effects of ambient PM2.5 exposure on deaths among Chinese adults in high-exposure settings. Methods: Participants of the Prediction for Atherosclerotic cardiovascular disease Risk in China (China-PAR) project were included from four prospective cohorts among Chinese adults aged ≥18 years old. The overall follow-up rate of the four cohorts was 93.4% until the recent follow-up survey that ended in 2015. The average of satellite-based PM2.5 concentrations during 2000–2015 at 1-km spatial resolution was assigned to each participant according to individual residence addresses. Based on the pooled analysis of individual data from the four cohorts, a Cox proportional hazards model was used to estimate the hazard ratio (HR) and corresponding 95% confidence intervals (95% CIs) for the association of PM2.5 exposure with mortality after multivariate adjustment. Results: A total of 116,821 participants were eligible in the final analysis. During a mean of 7.7 years of follow-up, 6,395 non-accidental deaths and 2,507 cardio-metabolic deaths occurred. The mean of PM2.5 concentration was 64.9 μg/m3 ranging from 31.2 μg/m3 to 97.0 μg/m3. For each 10 μg/m3 increment in PM2.5, the HR was 1.11 (95% CI: 1.08–1.14) for non-accidental mortality and 1.22 (95% CI: 1.16–1.27) for cardio-metabolic mortality. In addition, a weak exponential curve for the concentration-response association between mortality and PM2.5 was observed among Chinese adults. Conclusions: Our study provided important evidence of the long-term effects of PM2.5 exposure on deaths among Chinese adults. The findings expand our knowledge on concentration-response relationship in high-exposure environments, which is essential to address the urgent challenge of reducing the disease burden attributable to PM2.5 exposure in rapidly industrializing countries such as China. Keywords: Satellite-based PM2.5, Long-term exposure, Cohort study, Mortality, Concentration-response relationship

Previous studies have reported that intra-urban variability of NO2 concentrations is even higher than inter-urban variability. In recent years, an increasing number of studies have developed satellite-derived land use regression (LUR) models to predict ground-level NO2 concentrations, though only a few have been conducted at a city scale. In this study, we developed a satellite-derived LUR model to predict seasonal NO2 concentrations at a city scale by including satellite-retrieved NO2 tropospheric column density, population density, traffic indicators, and NOx emission data. The R2 of model fitting and 10-fold cross validation were 0.70 and 0.61 for the satellite-derived seasonal LUR model, respectively. The satellite-based LUR model captured seasonal patterns and fine gradients of NO2 variations at a 100 m × 100 m resolution and demonstrated that NO2 pollution in winter is 1.46 times higher than that in summer. NO2 concentrations declined significantly with increasing distance from roads and with increasing distance from the city center. In Suzhou, 84% of the total population lived in areas with NO2 concentrations exceeding the annual-mean standard at 40 μg/m3 in 2014. This study demonstrated that satellite-retrieved data could help increase the accuracy and temporal resolution of the traditional LUR models at a city scale. This application could support exposure assessment at a high resolution for future epidemiological studies and policy development pertaining to air quality control.

It is well recognized that exposure to fine particulate matter (PM2.5) affects health adversely, yet few studies from South America have documented such associations due to the sparsity of PM2.5 measurements. Lima’s topography and aging vehicular fleet results in severe air pollution with limited amounts of monitors to effectively quantify PM2.5 levels for epidemiologic studies. We developed an advanced machine learning model to estimate daily PM2.5 concentrations at a 1 km2 spatial resolution in Lima, Peru from 2010 to 2016. We combined aerosol optical depth (AOD), meteorological fields from the European Centre for Medium-Range Weather Forecasts (ECMWF), parameters from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), and land use variables to fit a random forest model against ground measurements from 16 monitoring stations. Overall cross-validation R2 (and root mean square prediction error, RMSE) for the random forest model was 0.70 (5.97 μg/m3). Mean PM2.5 for ground measurements was 24.7 μg/m3 while mean estimated PM2.5 was 24.9 μg/m3 in the cross-validation dataset. The mean difference between ground and predicted measurements was −0.09 μg/m3 (Std.Dev. = 5.97 μg/m3), with 94.5% of observations falling within 2 standard deviations of the difference indicating good agreement between ground measurements and predicted estimates. Surface downwards solar radiation, temperature, relative humidity, and AOD were the most important predictors, while percent urbanization, albedo, and cloud fraction were the least important predictors. Comparison of monthly mean measurements between ground and predicted PM2.5 shows good precision and accuracy from our model. Furthermore, mean annual maps of PM2.5 show consistent lower concentrations in the coast and higher concentrations in the mountains, resulting from prevailing coastal winds blown from the Pacific Ocean in the west. Our model allows for construction of long-term historical daily PM2.5 measurements at 1 km2 spatial resolution to support future epidemiological studies.

BACKGROUND:Pulmonary arterial hypertension, also known as Ascites syndrome (AS), remains a clinically challenging disease with a large impact on both humans and broiler chickens. Pulmonary arterial remodeling presents a key step in the development of AS. The precise molecular mechanism of pulmonary artery remodeling regulating AS progression remains unclear. METHODOLOGY/PRINCIPAL FINDINGS:We obtained pulmonary arteries from two positive AS and two normal broilers for RNA sequencing (RNA-seq) analysis and pathological observation. RNA-seq analysis revealed a total of 895 significantly differentially expressed genes (DEGs) with 437 up-regulated and 458 down-regulated genes, which were significantly enriched to 12 GO (Gene Ontology) terms and 4 KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways (Padj

Fossil-fuel combustion related winter heating has become a major air quality and public health concern in northern China recently. We analyzed the impact of winter heating on aerosol loadings over China using the MODIS-Aqua Collection 6 aerosol product from 2004-2012. Absolute humidity (AH) and planetary boundary layer height (PBL) -adjusted aerosol optical depth (AOD*) was constructed to reflect ground-level PM2.5 concentrations. GIS analysis, standard statistical tests, and statistical modeling indicate that winter heating is an important factor causing increased PM2.5 levels in more than three-quarters of central and eastern China. The heating season AOD* was more than five times higher as the non-heating season AOD*, and the increase in AOD* in the heating areas was greater than in the non-heating areas. Finally, central heating tend to contribute less to air pollution relative to other means of household heating.

Deadly heat waves are increasing with climate change. Public forecasts and warnings are a primary public health strategy for dealing with such extreme weather events; however, temperatures can vary widely within the administrative units used to issue warnings, particularly across urban landscapes. The emergence of more frequent and widely distributed sources of urban temperature data provide the opportunity to investigate the specificity of the current National Weather Service (NWS) warnings and to improve their accuracy and precision. In this work, temperatures from distributed public weather stations, NWS heat advisories and warnings, and land surface temperature imagery throughout two large metropolitan areas, Atlanta and Chicago, during the 2006–2012 summers are considered. We investigate the spatial variability of hazardous temperatures and their agreement against NWS advisories. Second, we examine the potential for thermal imagery to replicate National Weather Service heat warnings. Observations from weather stations exhibit varying degrees of agreement with NWS advisories. The level of agreement varied by station and was not found to be associated with the station’s proximate land cover. Air temperatures estimated from satellite imagery correspond with NWS Advisory status regionally and may enable creating more refined public warnings regarding hazardous temperatures and protective actions

Abstract Objective: To evaluate the safety and feasibility of a novel stent-graft for thoracic endovascular aortic repair (TEVAR) in a canine model, 9 adult hybrid dogs were used for the experiment. Methods: All animals were implanted with a novel thoracic aortic stent-graft via femoral artery. Blood sample was collected at pre-operation and 1, 2, 4, 8 and 12 weeks after implantation for hematological examination. Moreover, tissues from randomly selected 4 dogs were subjected to histopathological analysis with the optical microscope after stent-grafts were implanted for 3, 6, 9, and 12 months respectively. The experimental period lasted for more than 2 years. Results: A total of 9 stent-grafts were successfully implanted in the canine thoracic aortas and no migration or deformation occurred. Related indicators of blood routine, inflammatory factors, and immunology changes were not significantly (P>0.05), except the white blood cell (WBC) counts in the first week. Moreover, abnormal morphology was not found in all thoracic aortas via histopathological examination. Additionally, all stent-grafts were patent and did not migrate, and there was no thrombus in the lumens of stent-grafts. Conclusion: The novel thoracic aortic stent-graft made in China was safe and feasible for thoracic endovascular aortic repair in a canine model.

Rationale: Limited cohort studies have evaluated chronic effects of high fine particulate matter (particulate matter with an aerodynamic diameter ≤2.5 μm [PM2.5]) exposure on lung cancer.Objectives: To investigate the response pattern of lung cancer associated with high PM2.5 exposure.Methods: A Chinese cohort of 118,551 participants was followed up from 1992 to 2015. By incorporating PM2.5 exposure at 1 km spatial resolution generated using the satellite-based model during 2000-2015, we estimated the association between lung cancer and time-weighted average PM2.5 concentration using Cox proportional hazard models.Measurements and Main Results: A total of 844 incident lung cancer cases were identified during 915,053 person-years of follow-up. Among them, 701 lung cancer deaths occurred later. The exposure-response curves for lung cancer associated with PM2.5 exposure were nonlinear, with steeper slopes at the higher concentrations. Adjusted for age, sex, geographical region, urbanization, education level, smoking status, alcohol consumption, work-related physical activity, and body mass index, participants exposed to the second-fifth quintiles of PM2.5 had higher risk for lung cancer incidence than those exposed to the first quintile, with hazard ratios of 1.44 (95% confidence interval [CI], 1.10-1.88), 1.49 (95% CI, 1.12-1.99), 2.08 (95% CI, 1.42-3.04), and 2.45 (95% CI, 1.83-3.29), respectively. The corresponding hazard ratios for lung cancer mortality were 1.83 (95% CI, 1.33-2.50), 1.80 (95% CI, 1.29-2.53), 2.50 (95% CI, 1.62-3.86), and 2.95 (95% CI, 2.09-4.17), respectively.Conclusions: We provide strong evidence that high PM2.5 exposure leads to an elevated risk of lung cancer incidence and mortality, highlighting that remarkable public health benefits could be obtained from the improvement of air quality in highly polluted regions. [ABSTRACT FROM AUTHOR]

Investigations on the chronic health effects of fine particulate matter (PM2.5) exposure in China are limited due to the lack of long-term exposure data. Using satellite-driven models to generate spatiotemporally resolved PM2.5 levels, we aimed to estimate high-resolution, long-term PM2.5 and associated mortality burden in China. The multiangle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD) at 1-km resolution was employed as a primary predictor to estimate PM2.5 concentrations. Imputation techniques were adopted to fill in the missing AOD retrievals and provide accurate long-term AOD aggregations. Monthly PM2.5 concentrations in China from 2000 to 2016 were estimated using machine-learning approaches and used to analyze spatiotemporal trends of adult mortality attributable to PM2.5 exposure. Mean coverage of AOD increased from 56 to 100% over the 17-y period, with the accuracy of long-term averages enhanced after gap filling. Machine-learning models performed well with a random cross-validation R² of 0.93 at the monthly level. For the time period outside the model training window, prediction R² values were estimated to be 0.67 and 0.80 at the monthly and annual levels. Across the adult population in China, long-term PM2.5 exposures accounted for a total number of 30.8 (95% confidence interval [CI]: 28.6, 33.2) million premature deaths over the 17-y period, with an annual burden ranging from 1.5 (95% CI: 1.3, 1.6) to 2.2 (95% CI: 2.1, 2.4) million. Our satellite-based techniques provide reliable long-term PM2.5 estimates at a high spatial resolution, enhancing the assessment of adverse health effects and disease burden in China. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the safety and feasibility of a novel stent-graft for thoracic endovascular aortic repair (TEVAR) in a canine model, 9 adult hybrid dogs were used for the experiment. Methods: All animals were implanted with a novel thoracic aortic stent-graft via femoral artery. Blood sample was collected at pre-operation and 1, 2, 4, 8 and 12 weeks after implantation for hematological examination. Moreover, tissues from randomly selected 4 dogs were subjected to histopathological analysis with the optical microscope after stent-grafts were implanted for 3, 6, 9, and 12 months respectively. The experimental period lasted for more than 2 years. Results: A total of 9 stent-grafts were successfully implanted in the canine thoracic aortas and no migration or deformation occurred. Related indicators of blood routine, inflammatory factors, and immunology changes were not significantly (P>0.05), except the white blood cell (WBC) counts in the first week. Moreover, abnormal morphology was not found in all thoracic aortas via histopathological examination. Additionally, all stent-grafts were patent and did not migrate, and there was no thrombus in the lumens of stent-grafts. Conclusion: The novel thoracic aortic stent-graft made in China was safe and feasible for thoracic endovascular aortic repair in a canine model. [ABSTRACT FROM AUTHOR]

Background: Estimating the health effects of ambient air pollutant mixtures is necessary to understand the risk of real-life air pollution exposures. Methods: Pediatric Emergency Department (ED) visit records for asthma or wheeze (n = 148,256), bronchitis (n = 84,597), pneumonia (n = 90,063), otitis media (n = 422,268) and upper respiratory tract infection (URI) (n = 744,942) were obtained from Georgia hospitals during 2002-2008. Spatially-contiguous daily concentrations of 11 ambient air pollutants were estimated from CMAQ model simulations that were fused with ground-based measurements. Using a case-crossover study design, odds ratios for 3-day moving average air pollutant concentrations were estimated using conditional logistic regression, matching on ZIP code, day-of-week, month, and year. Results: In multipollutant models, the association of highest magnitude observed for the asthma/wheeze outcome was with "oxidant gases" (O3, NO2, and SO2); the joint effect estimate for an IQR increase of this mixture was OR: 1.068 (95% CI: 1.040, 1.097). The group of "secondary pollutants" (O3 and the PM2.5 components SO4 2-, NO3-, and NH4+) was strongly associated with bronchitis (OR: 1.090, 95% CI: 1.050, 1.132), pneumonia (OR: 1.085, 95% CI: 1.047, 1.125), and otitis media (OR: 1.059, 95% CI: 1.042, 1.077). ED visits for URI were strongly associated with "oxidant gases," "secondary pollutants," and the "criteria pollutants" (O3, NO2, CO, SO2, and PM2.5). Conclusions: Short-term exposures to air pollution mixtures were associated with ED visits for several different pediatric respiratory diseases. [ABSTRACT FROM AUTHOR]