Maternal ozone exposure lowers infant's birthweight: A nationwide cohort of over 4 million livebirths in Iran.

BACKGROUND: Nationwide evidence linking maternal ozone exposure with fetal growth restriction (FGR) was extensively scarce, especially in the Middle East with dry climate and distinct religious culture. METHODS: We carried out a national retrospective birth cohort study using registry-based records from 749 hospitals across 31 provinces in Iran from 2013 to 2018. Monthly concentrations of maximum daily average 8-hour (MDA8) ozone at 0.125° × 0.125° resolution were extracted from well-validated spatiotemporal grid dataset. Linear and logistic regression models were employed to evaluate associations of maternal MDA8 ozone exposure with birthweight outcomes. Assuming causality, the comparative risk assessment framework was utilized to estimate the burden of low birthweight (LBW), small for gestational age (SGA), and birthweight loss per livebirth (BLL) attributable to ambient ozone pollution. RESULTS: Of 4030383 livebirths included in the study, 264304 (6.6%) were LBW and 484405 (12.0%) were SGA. Each 10-ppb increase in MDA8 ozone exposure was associated with an odds ratio of 1.123 (95% confidence interval [CI]: 1.104 to 1.142) for LBW and 1.210 (95% CI: 1.197 to 1.223) for SGA, and a 30.5-g (95% CI: 29.0 to 32.0) reduction in birthweight. We observed approximately linear exposure-response relationships of maternal MDA8 ozone exposure with LBW (Pnonlinear= 0.786), SGA (Pnonlinear= 0.156), and birthweight reduction (Pnonlinear= 0.104). Under the premise of causal association, we estimated 6.6% (95% CI: 5.7 to 7.5) of LBW, 10.1% (95% CI: 9.6 to 10.6) of SGA, and 18.8 g (95% CI: 17.9 to 19.7) of BLL could be attributable to maternal ozone exposure in Iran. Considerably greater risk and burden of ozone-related FGR were observed among younger, less-educated, and rural-dwelling mothers. CONCLUSIONS: Our study provided compelling evidence that maternal ozone exposure was associated with heightened FGR risk and burden, particularly among socioeconomically disadvantaged mothers. These findings underscored the urgent need for government to incorporate socioeconomic factors into future ozone-related health policies, not only to mitigate pollution, but also minimize inequality.

Using machine learning to predict the risk of short-term and long-term death in acute kidney injury patients after commencing CRRT.

BACKGROUND: The mortality rate and prognosis of short-term and long-term acute kidney injury (AKI) patients who undergo continuous renal replacement therapy (CRRT) are different. Setting up risk stratification tools for both short-term and long-term deaths is highly important for clinicians. METHOD: A total of 1535 AKI patients receiving CRRT were included in this study, with 1144 from the training set (the Dryad database) and 391 from the validation set (MIMIC IV database). A model for predicting mortality within 10 and 90 days was built using nine different machine learning (ML) algorithms. AUROC, F1-score, accuracy, sensitivity, specificity, precision, and calibration curves were used to assess the predictive performance of various ML models. RESULTS: A total of 420 (31.1%) deaths occurred within 10 days, and 1080 (68.8%) deaths occurred within 90 days. The random forest (RF) model performed best in both predicting 10-day (AUROC: 0.80, 95% CI: 0.74-0.84; accuracy: 0.72, 95% CI: 0.67-0.76; F1-score: 0.59) and 90-day mortality (AUROC: 0.78, 95% CI: 0.73-0.83; accuracy: 0.73, 95% CI: 0.69-0.78; F1-score: 0.80). The importance of the feature shows that SOFA scores are rated as the most important risk factor for both 10-day and 90-day mortality. CONCLUSION: Our study, utilizing multiple machine learning models, estimates the risk of short-term and long-term mortality among AKI patients who commence CRRT. The results demonstrated that the prognostic factors for short-term and long-term mortality are different. The RF model has the best prediction performance and has valuable potential for clinical application.

Short-term ozone exposure and cancer mortality in Brazil: A nationwide case-crossover study.

Exposure to ambient ozone (O3) is linked to increased mortality risks from various diseases, but epidemiological investigations delving into its potential implications for cancer mortality are limited. We aimed to examine the association between short-term O3 exposure and site-specific cancer mortality and investigate vulnerable subgroups in Brazil. In total 3,459,826 cancer death records from 5570 Brazilian municipalities between 2000 and 2019, were included. Municipal average daily O3 concentration was calculated from a global estimation at 0.25°×0.25° spatial resolution. The time-stratified case-crossover design was applied to assess the O3-cancer mortality association. Subgroup analyses by age, sex, season, time-period, region, urban hierarchy, climate classification, quantiles of GDP per capita and illiteracy rates were performed. A linear and non-threshold exposure-response relationship was observed for short-term exposure to O3 with cancer mortality, with a 1.00% (95% CI: 0.79%-1.20%) increase in all-cancer mortality risks for each 10-µg/m3 increment of three-day average O3. Kidney cancer was most strongly with O3 exposure, followed by cancers of the prostate, stomach, breast, lymphoma, brain and lung. The associated cancer risks were relatively higher in the warm season and in southern Brazil, with a decreasing trend over time. When restricting O3 concentration to the national minimum value during 2000-2019, a total of 147,074 (116,690-177,451) cancer deaths could be avoided in Brazil, which included 17,836 (7014-28,653) lung cancer deaths. Notably, these associations persisted despite observed adaptation within the Brazilian population, highlighting the need for a focus on incorporating specific measures to mitigate O3 exposure into cancer care recommendations.

Convolutional Neural Networks Facilitate Process Understanding of Megacity Ozone Temporal Variability.

Ozone pollution is profoundly modulated by meteorological features such as temperature, air pressure, wind, and humidity. While many studies have developed empirical models to elucidate the effects of meteorology on ozone variability, they predominantly focus on local weather conditions, overlooking the influences from high-altitude and broader regional meteorological patterns. Here, we employ convolutional neural networks (CNNs), a technique typically applied to image recognition, to investigate the influence of three-dimensional spatial variations in meteorological fields on the daily, seasonal, and interannual dynamics of ozone in Shenzhen, a major coastal urban center in China. Our optimized CNNs model, covering a 13° × 13° spatial domain, effectively explains over 70% of daily ozone variability, outperforming alternative empirical approaches by 7 to 62%. Model interpretations reveal the crucial roles of 2-m temperature and humidity as primary drivers, contributing 16% and 15% to daily ozone fluctuations, respectively. Regional wind fields account for up to 40% of ozone changes during the episodes. CNNs successfully replicate observed ozone temporal patterns, attributing -5-6 µg·m-3 of interannual ozone variability to weather anomalies. Our interpretable CNNs framework enables quantitative attribution of historical ozone fluctuations to nonlinear meteorological effects across spatiotemporal scales, offering vital process-based insights for managing megacity air quality amidst changing climate regimes.

Environmentally relevant exposure to cotinine induces neurobehavioral toxicity in zebrafish (Danio rerio): A study using neurobehavioral and metabolomic approaches.

As an important psychoactive substance, cotinine is ubiquitous in aquatic environment and poses a threat to aquatic organisms. However, the mechanism of its adverse health impacts remains unclear. We evaluated the effects of cotinine exposure at environmentally relevant concentrations on the development and locomotor behavior of zebrafish (Danio rerio) larvae using neurotransmitters and whole endogenous metabolism. Mild developmental toxicity and significant neurobehavior disorder, such as spontaneous movement (1-1000 µg/L), 48 hpf tactile response (50, 100, and 1000 µg/L), and 144 hpf swimming speed (1, 10, 100, 500, and 1000 µg/L), were observed in zebrafish. Exposure to cotinine led to significant alterations in 11 neurotransmitters, including homogentisic acid, serotonin, glutamic acid and aspartic acid, etc. 298 metabolites were identified and two pathways - linoleic acid metabolism and taurine and hypotaurine metabolism - were delineated. In addition, amino acid neurotransmitters were significantly correlated with metabolites such as arachidonic acid as well as its derivatives, steroidal compounds, and amino acids. Serotonin demonstrates a noteworthy correlation with 31 out of 40 differentially expressed neurotransmitters, encompassing lipids, amino acids, and other compounds. These novel findings contribute to a comprehensive understanding of the ecological risks associated with cotinine contamination in surface waters.

Air quality improvements can strengthen China's food security.

Air pollution exerts crucial influence on crop yields and impacts regional and global food supplies. Here we employ a statistical model using satellite-based observations and flexible functional forms to analyse the synergistic effects of reductions in ozone and aerosols on China's food security. The model consistently shows that ozone is detrimental to crops, whereas aerosol has variable effects. China's maize, rice and wheat yields are projected to increase by 7.84%, 4.10% and 3.43%, respectively, upon reaching two air quality targets (60 µg m-3 for peak-season ozone and 35 µg m-3 for annual fine particulate matter). Average calories produced from these crops would surge by 4.51%, potentially allowing China to attain grain self-sufficiency 2 years earlier than previously estimated. These results show that ozone pollution control should be a high priority to increase staple crop edible calories, and future stringent air pollution regulations would enhance China's food security.

A Chinese longitudinal maternity cohort study (2013-2021) on intrahepatic cholestasis phenotypes: Risk associations from environmental exposure to adverse pregnancy outcomes.

Intrahepatic cholestasis of pregnancy (ICP) is an idiopathic disease that occurs during mid-to-late pregnancy and is associated with various adverse pregnancy outcomes, including intrauterine fetal demise. However, since the underlying cause of ICP remains unclear, there is an ongoing debate on the phenotyping criteria used in the diagnostic process. Here, we identified single- and multi-symptomatic ICP (ICP-S and ICP-M) in 104,221 Chinese females from the ZEBRA maternity cohort, with the objective of exploring the risk implications of the two phenotypes on pregnancy outcomes and from environmental exposures. We employed multivariate binary logistic regression to estimate confounder-adjusted odds ratios and found that ICP-M was more strongly associated with preterm birth and low birth weight compared to ICP-S. Throughout pregnancy, incremental exposure to PM2.5, O3, and greenness could alter ICP risks by 17.3%, 12.5%, and -2.3%, respectively, with more substantial associations observed with ICP-M than with ICP-S. The major scientific advancements lie in the elucidation of synergistic risk interactions between pollutants and the protective antagonistic effects of greenness, as well as highlighting the risk impact of preconceptional environmental exposures. Our study, conducted in the context of the "three-child policy" in China, provides epidemiological evidence for policy-making to safeguard maternal and neonatal health.

Investigation of Plant-Level Volatile Organic Compound Emissions from Chemical Industry Highlights the Importance of Differentiated Control in China.

The chemical industry is a significant source of nonmethane volatile organic compounds (NMVOCs), pivotal precursors to ambient ozone (O3), and secondary organic aerosol (SOA). Despite their importance, precise estimation of these emissions remains challenging, impeding the implementation of NMVOC controls. Here, we present the first comprehensive plant-level assessment of NMVOC emissions from the chemical industry in China, encompassing 3461 plants, 127 products, and 50 NMVOC compounds from 2010 to 2019. Our findings revealed that the chemical industry in China emitted a total of 3105 (interquartile range: 1179-8113) Gg of NMVOCs in 2019, with a few specific products accounting for the majority of the emissions. Generally, plants engaged in chemical fibers production or situated in eastern China pose a greater risk to public health due to their higher formation potentials of O3 and SOA or their proximity to residential areas or both. We demonstrated that targeting these high-risk plants for emission reduction could enhance health benefits by 7-37% per unit of emission reduction on average compared to the current situation. Consequently, this study provides essential insights for developing effective plant-specific NMVOC control strategies within China's chemical industry.

Iron and Steel Industry Emissions: A Global Analysis of Trends and Drivers.

The iron and steel industry (ISI) is important for socio-economic progress but emits greenhouse gases and air pollutants detrimental to climate and human health. Understanding its historical emission trends and drivers is crucial for future warming and pollution interventions. Here, we offer an exhaustive analysis of global ISI emissions over the past 60 years, forecasting up to 2050. We evaluate emissions of carbon dioxide and conventional and unconventional air pollutants, including heavy metals and polychlorinated dibenzodioxins and dibenzofurans. Based on this newly established inventory, we dissect the determinants of past emission trends and future trajectories. Results show varied trends for different pollutants. Specifically, PM2.5 emissions decreased consistently during the period 1970 to 2000, attributed to adoption of advanced production technologies. Conversely, NOx and SO2 began declining recently due to stringent controls in major contributors such as China, a trend expected to persist. Currently, end-of-pipe abatement technologies are key to PM2.5 reduction, whereas process modifications are central to CO2 mitigation. Projections suggest that by 2050, developing nations (excluding China) will contribute 52-54% of global ISI PM2.5 emissions, a rise from 29% in 2019. Long-term emission curtailment will necessitate the innovation and widespread adoption of new production and abatement technologies in emerging economies worldwide.

Hybrid CNN-Transformer Network for Electricity Theft Detection in Smart Grids.

Illicitly obtaining electricity, commonly referred to as electricity theft, is a prominent contributor to power loss. In recent years, there has been growing recognition of the significance of neural network models in electrical theft detection (ETD). Nevertheless, the existing approaches have a restricted capacity to acquire profound characteristics, posing a persistent challenge in reliably and effectively detecting anomalies in power consumption data. Hence, the present study puts forth a hybrid model that amalgamates a convolutional neural network (CNN) and a transformer network as a means to tackle this concern. The CNN model with a dual-scale dual-branch (DSDB) structure incorporates inter- and intra-periodic convolutional blocks to conduct shallow feature extraction of sequences from varying dimensions. This enables the model to capture multi-scale features in a local-to-global fashion. The transformer module with Gaussian weighting (GWT) effectively captures the overall temporal dependencies present in the electricity consumption data, enabling the extraction of sequence features at a deep level. Numerous studies have demonstrated that the proposed method exhibits enhanced efficiency in feature extraction, yielding high F1 scores and AUC values, while also exhibiting notable robustness.

Antagonism between ambient ozone increase and urbanization-oriented population migration on Chinese cardiopulmonary mortality.

Ever-increasing ambient ozone (O3) pollution in China has been exacerbating cardiopulmonary premature deaths. However, the urban-rural exposure inequity has seldom been explored. Here, we assess population-scale O3 exposure and mortality burdens between 1990 and 2019 based on integrated pollution tracking and epidemiological evidence. We find Chinese population have been suffering from climbing O3 exposure by 4.3 ± 2.8 ppb per decade as a result of rapid urbanization and growing prosperity of socioeconomic activities. Rural residents are broadly exposed to 9.8 ± 4.1 ppb higher ambient O3 than the adjacent urban citizens, and thus urbanization-oriented migration compromises the exposure-associated mortality on total population. Cardiopulmonary excess premature deaths attributable to long-term O3 exposure, 373,500 (95% uncertainty interval [UI]: 240,600-510,900) in 2019, is underestimated in previous studies due to ignorance of cardiovascular causes. Future O3 pollution policy should focus more on rural population who are facing an aggravating threat of mortality risks to ameliorate environmental health injustice.

Correction: WeChat-Based HIV e-Report, a New Approach for HIV Serostatus Requests and Disclosures Among Men Who Have Sex With Men: Prospective Subgroup Analysis of a Randomized Controlled Trial.

[This corrects the article DOI: 10.2196/44513.].

WeChat-Based HIV e-Report, a New Approach for HIV Serostatus Requests and Disclosures Among Men Who Have Sex With Men: Prospective Subgroup Analysis of a Randomized Controlled Trial

BACKGROUND: Requesting and disclosing HIV serostatus is associated with a reduction in HIV transmission among men who have sex with men (MSM). However, the reliability of common methods for HIV serostatus request and disclosure is inadequate. Validated approaches for requesting and disclosing HIV serostatus are necessary. OBJECTIVE: The objective of this study was to investigate the use of the HIV e-report as authentic evidence of HIV serostatus among the MSM community in Guangzhou, China. Additionally, the study aimed to explore its correlation with HIV serostatus requesting and disclosure receiving behavior. METHODS: This study is a subgroup analysis of a cluster randomized controlled trial (RCT) that enrolled 357 participants during the first year. Participants in this RCT were recruited from the WeChat-based HIV testing service miniprogram developed by Guangzhou Center for Disease Control and Prevention, China. Participants completed web-based questionnaires at baseline and at the month 3 follow-up, which covered sociodemographic characteristics, HIV-related information, HIV serostatus requests, receiving HIV serostatus disclosures, and HIV e-report usage. Univariate and multivariate logistic regressions were used for data analysis. RESULTS: The WeChat-based HIV e-report was available in Guangzhou when the RCT project started. At the month 3 follow-up, 32.2% (115/357) of participants had their own HIV e-reports, and 37.8% (135/357) of them had received others' HIV e-reports. In all, 13.1% (27/205) and 10.5% (16/153) of participants started to use HIV e-reports to request the HIV serostatus from regular and casual male sex partners, respectively. Moreover, 27.3% (42/154) and 16.5% (18/109) of the regular and casual male sex partners, respectively, chose HIV e-reports to disclose their HIV serostatus. Compared to MSM who did not have HIV e-reports, those who had HIV e-reports and stated, "I had had my own HIV e-report(s) but hadn't sent to others" (multivariate odds ratio 2.71, 95% CI 1.19-6.86; P=.02) and "I had had my own HIV e-reports and had sent to others" (multivariate odds ratio 2.67, 95% CI 1.07-7.73; P=.048) were more likely to request HIV serostatus from their partners. However, no factor was associated with receiving an HIV serostatus disclosure from partners. CONCLUSIONS: The HIV e-report has been accepted by the MSM community in Guangzhou and could be applied as a new optional approach for HIV serostatus requests and disclosures. This innovative intervention could be effective in promoting infectious disease serostatus disclosure among the related high-risk population. TRIAL REGISTRATION: ClinicalTrials.gov NCT03984136; https://clinicaltrials.gov/show/NCT03984136. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12879-021-06484-y.

Ambient PM2.5, ozone and mortality in Chinese older adults: A nationwide cohort analysis (2005-2018).

BACKGROUND: Cohort evidence linking long-term survival with exposure to multiple air pollutants (e.g., fine particulate matter [PM2.5] and ozone) was extensively sparse in low- and middle-income countries, especially among older adults. This study aimed to investigate potential associations of long-term exposures to PM2.5 and ozone with all-cause mortality in Chinese older adults. METHODS: A dynamic nationwide prospective cohort comprising 20,352 adults aged ≥65 years were enrolled from the Chinese Longitudinal Healthy Longevity Study and followed up through 2005-2018. Participants' annual exposures to warm-season ozone and year-round PM2.5 were assigned using satellite-derived spatiotemporal estimates. A directed acyclic graph (DAG) was developed to identify confounding variables. Associations of annual mean exposures to PM2.5 and ozone with mortality were evaluated using single- and two-pollutant Cox proportional hazards models, adjusting for time-dependent individual risk factors and ambient temperature. RESULTS: During 100 thousand person-years of follow-up (median: 3.6 years), a total of 14,313 death events occurred. The participants were averagely aged 87.1 years at baseline and exposed to a wide range of annual average concentrations of warm-season maximum 8-hour ozone (mean, 54.4 ppb; range, 23.3-81.6 ppb) and year-round PM2.5 (mean, 65.5 µg/m3; range, 10.1-162.9 µg/m3). Approximately linear concentration-response relationship was identified for ozone, whereas significant increases in PM2.5-associated mortality risks were observed only when concentrations were above 60 µg/m3. Rises of 10 ppb in ozone and 10 µg/m3 in PM2.5 above 60 µg/m3 were associated with increases in all-cause mortality of 13.2% (95% confidence interval [CI]: 10.2-16.2%) and 6.2% (95% CI: 4.6-7.7%) in DAG-based single-pollutant model, and of 9.7% (95% CI: 6.6-13.0%) and 5.3% (95% CI: 3.7-6.9%) in DAG-based two-pollutant model, respectively. We detected significant effect modification by temperature in associations of mortality with ozone (P <0.001 for interaction), suggesting greater ozone-related risks among participants in warmer locations. CONCLUSIONS: This study provided longitudinal evidence that long-term exposure to ambient PM2.5 and ozone significantly and independently contributed to elevated risks of all-cause mortality among older adults in China.

Excess mortality associated with high ozone exposure: A national cohort study in China.

Emerging epidemiological studies suggest that long-term ozone (O3) exposure may increase the risk of mortality, while pre-existing evidence is mixed and has been generated predominantly in North America and Europe. In this study, we investigated the impact of long-term O3 exposure on all-cause mortality in a national cohort in China. A dynamic cohort of 20882 participants aged ≥40 years was recruited between 2011 and 2018 from four waves of the China Health and Retirement Longitudinal Study. A Cox proportional hazard regression model with time-varying exposures on an annual scale was used to estimate the mortality risk associated with warm-season (April-September) O3 exposure. The annual average level of participant exposure to warm-season O3 concentrations was 100 µg m-3 (range: 61-142 µg m-3). An increase of 10 µg m-3 in O3 was associated with a hazard ratio (HR) of 1.18 (95% confidence interval [CI]: 1.13-1.23) for all-cause mortality. Compared with the first exposure quartile of O3, HRs of mortality associated with the second, third, and highest exposure quartiles were 1.09 (95% CI: 0.95-1.25), 1.02 (95% CI: 0.88-1.19), and 1.56 (95% CI: 1.34-1.82), respectively. A J-shaped concentration-response association was observed, revealing a non-significant increase in risk below a concentration of approximately 110 µg m-3. Low-temperature-exposure residents had a higher risk of mortality associated with long-term O3 exposure. This study expands current epidemiological evidence from China and reveals that high-concentration O3 exposure curtails the long-term survival of middle-aged and older adults.

Validity of using ambient concentrations as surrogate exposures at the individual level for fine particle and black carbon: A systematic review and meta-analysis.

Exposure measurement error is an important source of bias in epidemiological studies. We assessed the validity of employing ambient (outdoor) measurements as proxies of personal exposures at individual levels focusing on fine particles (PM2.5) and black carbon (BC)/elemental carbon (EC) on a global scale. We conducted a systematic review and meta-analysis and searched databases (ISI Web of Science, Scopus, PubMed, Ovid MEDLINE®, Ovid Embase, and Ovid BIOSIS) to retrieve observational studies in English language published from 1 January 2006 until 5 May 2021. Correlation coefficients (r) between paired ambient (outdoor) concentration and personal exposure for PM2.5 or BC/EC were standardized as effect size. We used random-effects meta-analyses to pool the correlation coefficients and investigated the causes of heterogeneity and publication bias. Furthermore, we employed subgroup and meta-regression analyses to evaluate the modification of pooled estimates by potential mediators. This systematic review identified thirty-two observational studies involving 1744 subjects from ten countries, with 28 studies for PM2.5 and 11 studies for BC/EC. Personal PM2.5 exposure is more strongly correlated with ambient (outdoor) concentrations (0.63, 95% confidence interval [CI]: 0.57-0.68) than personal BC/EC exposure (0.49, 95% CI: 0.38-0.59), with significant differences in r (0.14, 95% CI: 0.03-0.25; p < 0.05). The results demonstrated that the health status of participants was a significant modifier of pooled correlations. In addition, the personal to ambient (P/A) ratio for PM2.5 and average ambient BC/EC levels were potential effect moderators of the pooled r. The funnel plots and Egger's regression test indicated inevident publication bias. The pooled estimates were robust through sensitivity analyses. The results support the growing consensus that the validity coefficient of proxy measures should be addressed when interpreting results from epidemiological studies to better understand how strong health outcomes are affected by different levels of PM2.5 and their components.

Cohort-based long-term ozone exposure-associated mortality risks with adjusted metrics: A systematic review and meta-analysis.

Long-term ozone (O3) exposure may lead to non-communicable diseases and increase mortality risk. However, cohort-based studies are relatively rare, and inconsistent exposure metrics impair the credibility of epidemiological evidence synthetization. To provide more accurate meta-estimations, this study updates existing systematic reviews by including recent studies and summarizing the quantitative associations between O3 exposure and cause-specific mortality risks, based on unified exposure metrics. Cross-metric conversion factors were estimated linearly by decadal observations during 1990-2019. The Hunter-Schmidt random-effects estimator was applied to pool the relative risks. A total of 25 studies involving 226,453,067 participants (14 unique cohorts covering 99,855,611 participants) were included in the systematic review. After linearly unifying the inconsistent O3 exposure metrics , the pooled relative risks associated with every 10 nmol mol-1 (ppbV) incremental O3 exposure, by mean of the warm-season daily maximum 8-h average metric, were as follows: 1.014 with 95% confidence interval (CI) ranging 1.009-1.019 for all-cause mortality; 1.025 (95% CI: 1.010-1.040) for respiratory mortality; 1.056 (95% CI: 1.029-1.084) for COPD mortality; 1.019 (95% CI: 1.004-1.035) for cardiovascular mortality; and 1.074 (95% CI: 1.054-1.093) for congestive heart failure mortality. Insignificant mortality risk associations were found for ischemic heart disease, cerebrovascular diseases, and lung cancer. Adjustment for exposure metrics laid a solid foundation for multi-study meta-analysis, and widening coverage of surface O3 observations is expected to strengthen the cross-metric conversion in the future. Ever-growing numbers of epidemiological studies supported the evidence for considerable cardiopulmonary hazards and all-cause mortality risks from long-term O3 exposure. However, evidence of long-term O3 exposure-associated health effects was still scarce, so more relevant studies are needed to cover more populations with regional diversity.

Spatial Resolved Surface Ozone with Urban and Rural Differentiation during 1990-2019: A Space-Time Bayesian Neural Network Downscaler.

Long-term exposure to ambient ozone (O3) can lead to a series of chronic diseases and associated premature deaths, and thus population-level environmental health studies hanker after the high-resolution surface O3 concentration database. In response to this demand, we innovatively construct a space-time Bayesian neural network parametric regressor to fuse TOAR historical observations, CMIP6 multimodel simulation ensemble, population distributions, land cover properties, and emission inventories altogether and downscale to 10 km × 10 km spatial resolution with high methodological reliability (R2 = 0.89-0.97, RMSE = 1.97-3.42 ppbV), fair prediction accuracy (R2 = 0.69-0.77, RMSE = 5.63-7.97 ppbV), and commendable spatiotemporal extrapolation capabilities (R2 = 0.62-0.76, RMSE = 5.38-11.7 ppbV). Based on our predictions in 8-h maximum daily average metric, the rural-site surface O3 are 15.1±7.4 ppbV higher than urban globally averaged across 30 historical years during 1990-2019, with developing countries being of the most evident differences. The globe-wide urban surface O3 are climbing by 1.9±2.3 ppbV per decade, except for the decreasing trends in eastern United States. On the other hand, the global rural surface O3 tend to be relatively stable, except for the rising tendencies in China and India. Using CMIP6 model simulations directly without urban-rural differentiation will lead to underestimations of population O3 exposure by 2.0±0.8 ppbV averaged over each historical year. Our original Bayesian neural network framework contributes to the deep-learning-driven environmental studies methodologically by providing a brand-new feasible way to realize data fusion and downscaling, which maintains high interpretability by conforming to the principles of spatial statistics without compromising the prediction accuracy. Moreover, the 30-year highly spatial resolved monthly surface O3 database with multiple metrics fills in the literature gap for long-term surface O3 exposure tracing.

Low Expression of GLIS2 Gene Might Associate with Radiosensitivity of Gastric Cancer.

Human gene GLIS family zinc finger 2 (GLIS2) is a member of GLI-similar zinc finger protein family. Previous studies indicated GLIS2 gene involved in tumorigenesis mechanisms. However, the association between GLIS2 expression and radiosensitivity of gastric cancer has not been well understood. In this study, we used the gastric cancer database in TCGA, and significant association was observed between the low expression of GLIS2 and radiosensitivity of patients with gastric cancer. The adjusted HR values for radiotherapy were 0.162(0.035-0.756) and 0.089(0.014-0.564), with p values 0.021 and 0.010, respectively, in training and testing data, for these patients with low expression of GLIS2, while for patients with high expression of GLIS2, there was no significant survival difference between radiotherapy and nonradiotherapy groups. The adjusted HR were 0.676(0.288-1.586) and 0.508(0.178-1.450), with p values 0.368 and 0.206 in training and testing data, respectively. Further study showed that, for low expression patients, radiotherapy did not significantly increase new tumor event rate and disease progression rate, which partially supported our assumption. These results suggested that low expression of GLIS2 might significantly associate with the radiosensitivity of patients with gastric cancer. The GLIS2 gene might be a potential effective molecular marker of gastric cancer for precise radiotherapy.