Remote sensing image products (e.g. brightness of nighttime lights and land cover/land use types) have been widely used to disaggregate census data to produce gridded population maps for large ...geographic areas. The advent of the geospatial big data revolution has created additional opportunities to map population distributions at fine resolutions with high accuracy. A considerable proportion of the geospatial data contains semantic information that indicates different categories of human activities occurring at exact geographic locations. Such information is often lacking in remote sensing data. In addition, the remarkable progress in machine learning provides toolkits for demographers to model complex nonlinear correlations between population and heterogeneous geographic covariates. In this study, a typical type of geospatial big data, points-of-interest (POIs), was combined with multi-source remote sensing data in a random forests model to disaggregate the 2010 county-level census population data to 100 × 100 m grids. Compared with the WorldPop population dataset, our population map showed higher accuracy. The root mean square error for population estimates in Beijing, Shanghai, Guangzhou, and Chongqing for this method and WorldPop were 27,829 and 34,193, respectively. The large under-allocation of the population in urban areas and over-allocation in rural areas in the WorldPop dataset was greatly reduced in this new population map. Apart from revealing the effectiveness of POIs in improving population mapping, this study promises the potential of geospatial big data for mapping other socioeconomic parameters in the future.
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•A population map for China at 100-m spatial resolution was produced by random forests.•Remote sensing and POI data were jointly used to disaggregate census population.•The new population map showed higher accuracy than the Worldop dataset.•The use of POI reduced under-allocation in urban and over-allocation in rural areas.•POIs have more strengths than brightness of nighttime lights for population estimation.
Successful cancer therapy requires drugs being precisely delivered to tumors. Nanosized drugs have attracted considerable recent attention, but their toxicity and high immunogenicity are important ...obstacles hampering their clinical translation. Here we report a novel “cocktail therapy” strategy based on excess natural killer cell-derived exosomes (NKEXOs) in combination with their biomimetic core–shell nanoparticles (NNs) for tumor-targeted therapy. The NNs were self- assembled with a dendrimer core loading therapeutic miRNA and a hydrophilic NKEXOs shell. Their successful fabrication was confirmed by transmission electron microscopy (TEM) and confocal laser scanning microscopy (CLSM). The resulting NN/NKEXO cocktail showed highly efficient targeting and therapeutic miRNA delivery to neuroblastoma cells in vivo, as demonstrated by two-photon excited scanning fluorescence imaging (TPEFI) and with an IVIS Spectrum in vivo imaging system (IVIS), leading to dual inhibition of tumor growth. With unique biocompatibility, we propose this NN/NKEXO cocktail as a new avenue for tumor therapy, with potential prospects for clinical applications.
Abstract
The purpose of this study was to examine the changes in severity of anxiety and depression symptoms, stress and sleeping quality after three months of mass quarantine for COVID-19 among ...undergraduate fresh students compared to their pre-COVID-19 measures. We used participants from the Chinese Undergraduate Cohort (CUC), a national prospective longitudinal study to examine the changes in anxiety and depression symptoms severity, stress and sleep quality after being under mass quarantine for three months. Wilcoxon matched pair signed-rank test was used to compare the lifestyle indicators. Severity of anxiety, depression symptoms, stress and sleep quality were compared with Wilcoxon signed-rank test. We used generalized estimating equation (GEE) to further quantify the change in mental health indicators and sleep quality after the COVID-19 mass quarantine compared to baseline. This study found that there was no deterioration in mental health status among Chinese new undergraduate students in 2020 after COVID-19 mass quarantine compared with the baseline measures in 2019. There was an improvement in sleep quality and anxiety symptoms. After adjusting for age, sex, exercise habit, time spent on mobile gadgets, and time spent outdoors, year 2020 was significantly associated with severity of depression symptoms in males (OR:1.52. 95%CI:1.05–2.20,
p
-value = 0.027). Year 2020 was significantly associated with the improvement of sleeping quality in total (OR:0.45, 95%CI:0.38–0.52,
p
< 0.001) and in all the subgroups. This longitudinal study found no deterioration in mental health status among Chinese new undergraduate students after three months of mass quarantine for COVID-19.
Limited evidence is available on the health effects of particulate matter with an aerodynamic diameter of <1 μm (PM1), mainly due to the lack of its ground measurement worldwide.
To identify and ...examine the mortality risks and mortality burdens associated with PM1, PM2.5, and PM10 in Zhejiang province, China.
We collected daily data regarding all-cause (stratified by age and gender), cardiovascular, stroke, respiratory, and chronic obstructive pulmonary disease (COPD) mortality, and PM1, PM2.5, and PM10, from 11 cities in Zhejiang province, China during 2013 and 2017. We used a quasi-Poisson regression model to estimate city-specific associations between mortality and PM concentrations. Then we used a random-effect meta-analysis to pool the provincial estimates. To show the mortality burdens of PM1, PM2.5, and PM10, we calculated the mortality fractions and deaths attributable to these PMs.
Daily concentrations of PM1, PM2.5, and PM10 ranged between 0–199 μg/m3, 0–218 μg/m3, and 0–254 μg/m3, respectively; Mortality effects were significant in lag 0–2 days. The relative risks for all-cause mortality were 1.0064 (95% CI: 1.0034, 1.0094), 1.0061 (95% CI: 1.0034, 1.0089), and 1.0060 (95% CI: 1.0038, 1.0083) associated with a 10 μg/m3 increase in PM1, PM2.5, and PM10, respectively. Age- and gender-stratified analysis shows that elderly people (aged 65+) and females are more sensitive to PMs. The mortality fractions of all-cause mortality were estimated to be 2.39% (95% CI: 1.28, 3.48) attributable to PM1, 2.53% (95% CI: 1.42, 3.63) attributable to PM2.5, and 3.08% (95% CI: 1.95, 4.19) attributable to PM10. The ratios of attributable cause-specific deaths for PM1/PM2.5, PM1/PM10, and PM2.5/PM10 were higher than the ratios of their respective concentrations.
PM1, PM2.5 and PM10 are risk factors of all-cause, cardiovascular, stroke, respiratory, and COPD mortality. PM1 accounts for the vast majority of short-term PM2.5- and PM10-induced mortality. Our analyses support the notion that smaller size fractions of PM have a more toxic mortality impacts, which suggests to develop strategies to prevent and control PM1 in China, such as to foster strict regulations for automobile and industrial emissions.
•PM1, PM2.5 and PM10 are risk factors of all-cause, cardiovascular, stroke, respiratory, and COPD mortality.•PM1 accounts for the vast majority of short-term PM2.5- and PM10-induced mortality.•Smaller size fractions of PM have a more toxic mortality impacts.•PM1 has stronger effects on all-cause, cardiovascular, and stroke mortality in the warm season than in the cold season.
Temperature-related mortality risks have mostly been studied in urban areas, with limited evidence for urban-rural differences in the temperature impacts on health outcomes.
We investigated whether ...temperature-mortality relationships vary between urban and rural counties in China.
We collected daily data on 1 km gridded temperature and mortality in 89 counties of Zhejiang Province, China, for 2009 and 2015. We first performed a two-stage analysis to estimate the temperature effects on mortality in urban and rural counties. Second, we performed meta-regression to investigate the modifying effect of the urbanization level. Stratified analyses were performed by all-cause, nonaccidental (stratified by age and sex), cardiopulmonary, cardiovascular, and respiratory mortality. We also calculated the fraction of mortality and number of deaths attributable to nonoptimum temperatures associated with both cold and heat components. The potential sources of the urban-rural differences were explored using meta-regression with county-level characteristics.
Increased mortality risks were associated with low and high temperatures in both rural and urban areas, but rural counties had higher relative risks (RRs), attributable fractions of mortality, and attributable death counts than urban counties. The urban-rural disparity was apparent for cold (first percentile relative to minimum mortality temperature), with an RR of 1.47 95% confidence interval (CI): 1.32, 1.62 associated with all-cause mortality for urban counties, and 1.98 (95% CI: 1.87, 2.10) for rural counties. Among the potential sources of the urban-rural disparity are age structure, education, GDP, health care services, air conditioners, and occupation types.
Rural residents are more sensitive to both cold and hot temperatures than urban residents in Zhejiang Province, China, particularly the elderly. The findings suggest past studies using exposure-response functions derived from urban areas may underestimate the mortality burden for the population as a whole. The public health agencies aimed at controlling temperature-related mortality should develop area-specific strategies, such as to reduce the urban-rural gaps in access to health care and awareness of risk prevention. Future projections on climate health impacts should consider the urban-rural disparity in mortality risks. https://doi.org/10.1289/EHP3556.
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•This study estimated the spatiotemporal trends of joint events from city, province and country scales in China.•Henan, Xinjiang, and Chongqing were the most influenced areas by joint ...events across China.•Socioeconomic indicators were the significant factors to explain the variation of joint events between cities.
Climate change triggered more environmental extremes. The joint events of air pollution wave and cold wave showed higher health risks than independent events, but little evidence is available for the spatiotemporal features of their co-occurrence. To better understand and forecast the joint events, a method framework was developed in this study. The temporal trend and spatial distribution of count and duration for joint events were measured at each grid cell (0.5°×0.5°) by integrating the PM2.5 air pollution wave and cold wave. The generalized linear mixed model was used to screen influencing variables that took into account socioeconomic characteristics, meteorological variables, and annual PM2.5 levels. During 2000 and 2018, the average annual count of joint events was 4.1 ± 6.8 days and the average duration ranged from 1.0 to 9.7 days. High spatial heterogeneity was observed throughout China, with a significant increase in joint events observed in Xinjiang area (the largest province in China). The most average count of joint events was observed in Henan province (one of the most populous provinces), while the longest duration was in Chongqing (a municipality, one of the megacities). Areas with higher PM2.5 levels, prolonged air pollution wave, and cold wave durations would experience more joint events. These findings can assist China in locating vulnerable areas and establishing effective local early warning systems. The method framework offers broader perspectives on mitigating health risks associated with extreme events in other countries and regions.
Graphene oxide (GO) prepared by modified hummers method was used as adsorbent for removal of heavy metal ions. The oxygenous functional groups on the surface of GO were primarily responsible for the ...sorption of metal ions. The effects of the parameters of pH value, contact time, Cu(II) concentration, and adsorbent dosage on adsorption were examined. The sorption process conformed to the Freundlich isotherm, and the maximum sorption capacity of 117.5 mg g
−1
was observed at an initial pH value of 5.3 after agitating for 150 min. It was also found that Cu-pretreated GO could be desorbed by HCl and the reusability of GO could still maintain above 90 % of its initial capability after ten cycles. The results suggest that GO is an effective adsorbent for copper ions removal in water treatment.
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•First study on the risk of preterm birth/term low birth weight associated with wildfire-specific PM2.5 in New South Wales, Australia.•14.30% preterm births and 8.04% term low birth ...weight cases attributable to maternal exposure to wildfire-specific PM2.5.•Susceptibility higher in male infants and mothers > 40 years, suffering medical conditions, temperature extremes, conceived in spring or from inner region for preterm birth.•Vulnerability greater in male infants and mothers < 20 years, smoking, experiencing heat, conceived in spring or from very remote areas for term low birth weight.
Exposure to wildfire smoke has been linked with a range of health outcomes. However, to date, evidence is limited for the association between wildfire-specific PM2.5, a primary emission of wildfire smoke, and adverse birth outcomes.
We aimed to estimate the risk and burden of preterm birth/term low birth weight, associated with maternal exposure to wildfire-specific PM2.5.
A total of 330,884 birth records with maternal information were collected from the New South Wales Australia from 2015 to 2019, covering 523 residential communities. Daily wildfire-specific PM2.5 at a 0.25° × 0.25° (≈ 25 km × 25 km) resolution was estimated by a machine learning method combining 3-D chemical transport model (GEOS-Chem) and reanalysis meteorological data. Cox proportional hazards models were implemented to evaluate the association between wildfire-specific PM2.5 and preterm birth/term low birth weight. Number and fraction of preterm birth/term low birth weight attributable to wildfire-specific PM2.5 during pregnancy were calculated.
Per one interquartile-range rise in wildfire-specific PM2.5 was found to be associated with 6.9% (HR: 1.069, 95% CI: 1.058–1.081) increased risk of preterm birth and 3.6% (HR: 1.036, 95% CI: 1.014–1.058) higher risk of term low birth weight. The most susceptible gestational window was the 2nd trimester for preterm birth whereas the 1st for term low birth weight. We estimated that 14.30% preterm births and 8.04% term low birth weight cases were attributable to maternal exposure to wildfire-specific PM2.5 during the whole pregnancy. Male infants and mothers aged ≥ 40, experiencing temperature extremes or living in the inner region, and concepted during spring had higher risks of preterm birth/term low birth weight associated with wildfire-specific PM2.5. Comparatively, mothers with advanced age have a higher risk of preterm birth while younger mothers were more likely to deliver term newborns with low birth weight, when being exposed to wildfire-specific PM2.5. Pregnancy-induced hypertension enhanced the risk of preterm birth associated with wildfire-specific PM2.5.
This study strengthened robust evidence on the enhanced risk of preterm birth/term low birth weight associated with maternal exposure to wildfire-specific PM2.5. In light of higher frequency and intensity of wildfire occurrences globally, more special attention should be paid to pregnant women by policy makers.
Accurate estimates of the causal effect of air pollution on health outcomes, are critical when calculating attributable disease burdens. Brazil has a large population exposed to fast-growing ...emissions of air pollutants, however no national level studies have been conducted to examine the causal effect of PM2.5 exposure on health outcomes. This study proposes a novel approach, to accurately estimate the causal relationship between daily PM2.5 exposure and hospitalisations, across 1,814 Brazilian cities during 2000–2015. A variant of the difference-in-differences (DID) approach was applied under a counterfactual framework. Daily time series data were divided into panels. Seasonality and long-term trend were controlled using indicators for the panel. Variables which do not change within a short-period were controlled using a dummy variable for the day. Controls for variables which vary day by day, were included in the model. We found the proposed model exhibited competitive power performance in detecting causal associations between short-term PM2.5 exposure and hospitalisations in Brazil. A 10 μg/m3 increase in PM2.5 concentrations over four days (lag 0–3) was associated with a 1.06 % (95 % CI: 0.94 to 1.17) increase in all-cause hospitalisations and accounted for 1.26 % (95 % CI: 1.12–1.39) of total hospitalisations. Larger effects were found for children aged 0–4 years and the elderly aged 80+ years, suggesting policies should be developed to minimise the exposure of these age groups.
Background
Long-term exposure to fine particles ≤2.5 μm in diameter (PM
2.5
) has been linked to cancer mortality. However, the effect of wildfire-related PM
2.5
exposure on cancer mortality risk is ...unknown. This study evaluates the association between wildfire-related PM
2.5
and site-specific cancer mortality in Brazil, from 2010 to 2016.
Methods and findings
Nationwide cancer death records were collected during 2010–2016 from the Brazilian Mortality Information System. Death records were linked with municipal-level wildfire- and non-wildfire-related PM
2.5
concentrations, at a resolution of 2.0° latitude by 2.5° longitude. We applied a variant difference-in-differences approach with quasi-Poisson regression, adjusting for seasonal temperature and gross domestic product (GDP) per capita. Relative risks (RRs) and 95% confidence intervals (CIs) for the exposure for specific cancer sites were estimated. Attributable fractions and cancer deaths were also calculated. In total, 1,332,526 adult cancer deaths (age ≥ 20 years), from 5,565 Brazilian municipalities, covering 136 million adults were included. The mean annual wildfire-related PM
2.5
concentration was 2.38 μg/m
3
, and the annual non-wildfire-related PM
2.5
concentration was 8.20 μg/m
3
. The RR for mortality from all cancers was 1.02 (95% CI 1.01–1.03,
p
< 0.001) per 1-μg/m
3
increase of wildfire-related PM
2.5
concentration, which was higher than the RR per 1-μg/m
3
increase of non-wildfire-related PM
2.5
(1.01 95% CI 1.00–1.01,
p =
0.007, with
p
for difference = 0.003). Wildfire-related PM
2.5
was associated with mortality from cancers of the nasopharynx (1.10 95% CI 1.04–1.16,
p =
0.002), esophagus (1.05 95% CI 1.01–1.08,
p =
0.012), stomach (1.03 95% CI 1.01–1.06,
p =
0.017), colon/rectum (1.08 95% CI 1.05–1.11,
p <
0.001), larynx (1.06 95% CI 1.02–1.11,
p =
0.003), skin (1.06 95% CI 1.00–1.12,
p =
0.003), breast (1.04 95% CI 1.01–1.06,
p =
0.007), prostate (1.03 95% CI 1.01–1.06,
p =
0.019), and testis (1.10 95% CI 1.03–1.17,
p =
0.002). For all cancers combined, the attributable deaths were 37 per 100,000 population and ranged from 18/100,000 in the Northeast Region of Brazil to 71/100,000 in the Central-West Region. Study limitations included a potential lack of assessment of the joint effects of gaseous pollutants, an inability to capture the migration of residents, and an inability to adjust for some potential confounders.
Conclusions
Exposure to wildfire-related PM
2.5
can increase the risks of cancer mortality for many cancer sites, and the effect for wildfire-related PM
2.5
was higher than for PM
2.5
from non-wildfire sources.
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