Air pollution and upper respiratory diseases: an examination among medically insured populations in Wuhan, China.

Multiple evidence has supported that air pollution exposure has detrimental effects on the cardiovascular and respiratory systems. However, most investigations focus on the general population, with limited research conducted on medically insured populations. To address this gap, the current research was designed to examine the acute effects of inhalable particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ground-level ozone (O3), and sulfur dioxide (SO2) on the incidence of upper respiratory tract infections (URTI), utilizing medical insurance data in Wuhan, China. Data on URTI were collected from the China Medical Insurance Basic Database for Wuhan covering the period from 2014 to 2018, while air pollutant data was gathered from ten national monitoring stations situated in Wuhan city. Statistical analysis was performed using generalized additive models for quasi-Poisson distribution with a log link function. The analysis indicated that except for ozone, higher exposure to four other pollutants (NO2, SO2, PM2.5, and PM10) were significantly linked to an elevated risk of URTI, particularly during the previous 0-3 days and previous 0-4 days. Additionally, NO2 and SO2 were found to be positively linked with laryngitis. Furthermore, the effects of air pollutants on the risk of URTI were more pronounced during cold seasons than hot seasons. Notably, females and the employed population were more susceptible to infection than males and non-employed individuals. Our findings gave solid proof of the link between ambient air pollution exposure and the risk of URTI in medically insured populations.

Temporal and spatial variations and the relationships of land use pattern and ecosystem services in Qinghai-Tibet Plateau, China.

The Qinghai-Tibet Plateau is the key and largest ecological hotspot globally with enormous multiple ecosystem services. The vast and unique alpine ecosystems in this area have been subjected to the increased human disturbances, such as intensified land use. To explore the magnitude, spatiotemporal pattern and transformation process of land use in the Qinghai-Tibet Plateau and their impacts on the major ecosystem services during 1980-2020, we used the Integrated Valuation of Ecosystem Services and Trade-offs model to simulate the spatiotemporal variations of three types of ecosystem services, including habitat quality, carbon storage, and water yield. We analyzed the impacts of land use change on ecosystem services. The findings revealed that land use pattern remained generally stable from 1980 to 2020, with alpine grassland and desert as the dominant land use types. Habitat quality had generally enhanced, while carbon storage and water yield increased firstly and then declined. The magnitudes of three services gradually increased from the northwest to the southeast, corresponding to the spatial transformation pattern from desert via grassland to forest. The correlation between land use intensity and ecosystem services showed significant spatial heterogeneity, particulaly in counties greatly affected by land use intensity which concentrated predominantly in the mid-west, southern, and mid-east regions of the Qinghai-Tibet Plateau. The results have certain guiding significance for formulating land use policy and regulating land use pattern of alpine ecosystems in the Qinghai-Tibet Plateau.

Metformin inhibits ovarian granular cell pyroptosis through the miR-670-3p/NOX2/ROS pathway.

Recent studies have demonstrated that ovarian granular cells (OGCs) pyroptosis is present in the ovaries of polycystic ovary syndrome (PCOS) mice and that NLRP3 activation destroys follicular functions. Metformin has been shown to protect against PCOS by reducing insulin resistance in women, whereas its role in OGC pyroptosis is unknown. This study aimed to investigate the impact of metformin on OGC pyroptosis and the underlying mechanisms. The results showed that treating a human granulosa-like tumor cell line (KGN) with metformin significantly decreased LPS-induced expression of miR-670-3p, NOX2, NLRP3, ASC, cleaved caspase-1, and GSDMD-N. Cellular caspase-1 activity; ROS production; oxidative stress; and the secretion of IL-1ß, IL-6, IL-18, and TNF-α were also diminished. These effects were amplified by adding N-acetyl-L-cysteine (NAC), a pharmacological inhibitor of ROS. In contrast, metformin's anti-pyroptosis and anti-inflammatory effects were robustly ameliorated by NOX2 overexpression in KGN cells. Moreover, bioinformatic analyses, RT-PCR, and Western blotting showed that miR-670-3p could directly bind to the NOX2 (encoded by the CYBB gene in humans) 3'UTR and decrease NOX2 expression. Metformin-induced suppression of NOX2 expression, ROS production, oxidative stress, and pyroptosis was significantly alleviated by transfection with the miR-670-3p inhibitor. These findings suggest that metformin inhibits KGN cell pyroptosis via the miR-670-3p/NOX2/ROS pathway.

Evaluation of Model-Based PM2.5 Estimates for Exposure Assessment during Wildfire Smoke Episodes in the Western U.S.

Investigating the health impacts of wildfire smoke requires data on people's exposure to fine particulate matter (PM2.5) across space and time. In recent years, it has become common to use machine learning models to fill gaps in monitoring data. However, it remains unclear how well these models are able to capture spikes in PM2.5 during and across wildfire events. Here, we evaluate the accuracy of two sets of high-coverage and high-resolution machine learning-derived PM2.5 data sets created by Di et al. and Reid et al. In general, the Reid estimates are more accurate than the Di estimates when compared to independent validation data from mobile smoke monitors deployed by the US Forest Service. However, both models tend to severely under-predict PM2.5 on high-pollution days. Our findings complement other recent studies calling for increased air pollution monitoring in the western US and support the inclusion of wildfire-specific monitoring observations and predictor variables in model-based estimates of PM2.5. Lastly, we call for more rigorous error quantification of machine-learning derived exposure data sets, with special attention to extreme events.

Association between ambient air pollution and daily hospital visits for cardiovascular diseases in Wuhan, China: a time-series analysis based on medical insurance data.

Although evidence showed the adverse effects of air pollution on cardiovascular disease (CVDs), few studies were based on medically insured populations. We applied a generalized additive Poisson model (GAM) to estimate the short-term effects of ambient air pollution on a group of medically insured population in Wuhan, China. We extracted daily air pollution data, meteorological data, and daily hospital visits for CVDs. We found that the ambient air pollutants sulfur dioxide (SO2), nitrogen dioxide (NO2), ground-level ozone (O3) particulate matter (PM) with an aerodynamic diameter ≤10 µm (PM10), and those ≤2.5 µm (PM2.5) all increased the risk of daily hospital visits for CVDs. We also found that the effect of air pollution on daily hospital visits for CVDs is greater in the cold season than in the warm season. Our findings can be used as evidence that supports the formulation of policies for air pollution and CVDs.

Long-term hexavalent chromium exposure disturbs the gut microbial homeostasis of chickens.

Industrial production, ore smelting and sewage disposal plant can discharge large amounts of heavy metals every year, which may contaminate soil, water and air, posing a great threat to ecological environment and animal production. Hexavalent chromium [Cr (VI)], a recognized metallic contaminant, has been shown to impair kidney, liver and gastrointestinal tract of many species, but little is known about the gut microbial characteristics of chickens exposed to Cr (VI). Herein, this study characterized the gut microbial alternations of chickens exposed to Cr (VI). Results indicated that the gut microbial alpha-diversity in chickens exposed to Cr (VI) decreased significantly, accompanied by a distinct shifts in taxonomic composition. Microbial taxonomic analysis demonstrated that the preponderant phyla (Firmicutes, Bacteroidetes, Proteobacteria and Epsilonbacteraeota) were the same in both groups, but different in types and relative abundances of dominant genera. Moreover, some bacterial taxa including 2 phyla and 47 genera significantly decreased, whereas 3 phyla and 17 genera significantly increased during Cr (VI) exposure. Among decreased taxa, 9 genera (Coprobacter, Ruminococcus_1, Faecalicoccus, Eubacterium_nodatum_group, Parasutterella, Slackia, Barnesiella, Family_XIII_UCG-001 and Collinsella) even cannot be detected. In conclusion, this study revealed that Cr (VI) exposure dramatically decrased the gut microbial diversity and altered microbial composition of chickens. Additionally, this study also provided a theoretical basis for relieving Cr (VI) poisoning from the perspective of gut microbiota.

Short-term impact of ambient temperature on the incidence of influenza in Wuhan, China.

Few studies have estimated the nonlinear association of ambient temperature with the risk of influenza. We therefore applied a time-series analysis to explore the short-term effect of ambient temperature on the incidence of influenza in Wuhan, China. Daily influenza cases were collected from Hubei Provincial Center for Disease Control and Prevention (Hubei CDC) from January 1, 2014, to December 31, 2017. The meteorological and daily pollutant data was obtained from the Hubei Meteorological Service Center and National Air Quality Monitoring Stations, respectively. We used a generalized additive model (GAM) coupled with the distributed lag nonlinear model (DLNM) to explore the exposure-lag-response relationship between the short-term risk of influenza and daily average ambient temperature. Analyses were also performed to assess the extreme cold and hot temperature effects. We observed that the ambient temperature was statistically significant, and the exposure-response curve is approximately S-shaped, with a peak observed at 23.57 ℃. The single-day lag curve showed that extreme hot and cold temperatures were both significantly associated with influenza. The extreme hot temperature has an acute effect on influenza, with the most significant effect observed at lag 0-1. The extreme cold temperature has a relatively smaller effect but lasts longer, with the effect exerted continuously during a lag of 2-4 days. Our study found significant nonlinear and delayed associations between ambient temperature and the incidence of influenza. Our finding contributes to the establishment of an early warning system for airborne infectious diseases.

Transcriptome sequencing identified the ceRNA network associated with recurrent spontaneous abortion.

BACKGROUND: Recurrent spontaneous abortion (RSA) is one of the common complication of pregnancy, bringing heavy burden to the patients and their families. The study aimed to explore the lncRNA-miRNA-mRNA network associated with recurrent spontaneous abortion. METHODS: By transcriptome sequencing, we detected differences in lncRNA, miRNA and mRNA expression in villus tissue samples collected from 3 patients with RSA and 3 normal abortion patients. Differentially expressed lncRNAs, miRNAs and genes (DELs, DEMs and DEGs, respectively) were identified, and Geno Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to determine the functions of DELs and DEGs, which were analysed by Fisher's test. We also observed the regulatory relationships between miRNA-mRNA and lncRNA-miRNA by Cytoscape 3.6.1. RESULTS: The results showed that 1008 DELs (523 upregulated and 485 downregulated), 475 DEGs (201 upregulated and 274 downregulated) and 37 DEMs (15 upregulated and 22 downregulated) were identified. And we also constructed a novel lncRNA-related ceRNA network containing 31 lncRNAs, 1 miRNA (hsa-miR-210-5p) and 3 genes (NTNG2, GRIA1 and AQP1). CONCLUSIONS: lncRNA-related ceRNA network containing 31 lncRNAs, 1 miRNA (hsa-miR-210-5p) and 3 mRNAs (NTNG2, GRIA1 and AQP1) was constructed. The results may provide a basic theory for elucidating the mechanism underlying RSA.

Characterization of cooking-related ultrafine particles in a US residence and impacts of various intervention strategies.

Interventions that improve air exchange or filter the air have the potential to reduce particle exposures from residential cooking. In this study, we evaluated the effect of using a range hood, opening kitchen windows, and using portable air cleaners (PACs) in various home locations on the concentrations of ultrafine particles (UFPs) at different times and in different rooms during and after cooking. All experiments were conducted using a standardized cooking protocol in a real-world naturally-ventilated apartment located in the northwest United States. Real-time UFP measurements collected from the kitchen, living room, and bedroom locations were used to estimate parameters of a dynamic model, which included time-varying particle emission rates from cooking and particle decay. We found that 1-min mean UFP number concentrations in the kitchen and living room mostly peaked within 0-10 min after cooking ended at levels of 150,000-500,000 particles/cm3. In contrast, the bedroom UFP concentrations were consistently low except for the window-open scenario. While varying considerably with time, the 1-min UFP emission rates were comparable during and within 5-min after cooking, with means (standard deviations) of 0.8 (1.1) × 1012 and 1.1 (1.2) × 1012 particles/min, respectively. Compared with the no-intervention scenario, keeping the kitchen windows open and using a kitchen range hood reduced the mean indoor average UFP concentrations during and 1 h after cooking by ~70% and ~35%, respectively. Along with the range hood on, utilizing a PAC in the kitchen during and after cooking further reduced the mean indoor average UFP levels during and 1 h after cooking by an additional 53%. In contrast, placing the PAC in the living room or bedroom resulted in worse efficacy, with additional 2-13% reductions. These findings provide useful information on how to reduce cooking-related UFP exposure via readily accessible intervention strategies.

Residential cooking-related PM2.5: Spatial-temporal variations under various intervention scenarios.

Some cooking events can generate high levels of hazardous PM2.5. This study assesses the dispersion of cooking-related PM2.5 throughout a naturally-ventilated apartment in the US, examines the dynamic process of cooking-related emissions, and demonstrates the impact of different indoor PM2.5 mitigating strategies. We conducted experiments with a standardized pan-frying cooking procedure under seven scenarios, involving opening kitchen windows, using a range hood, and utilizing a portable air cleaner (PAC) in various indoor locations. Real-time PM2.5 concentrations were measured in the open kitchen, living room, bedroom (door closed), and outdoor environments. Decay-related parameters were estimated, and time-resolved PM2.5 emission rates for each experiment were determined using a dynamic model. Results show that the 1-min mean PM2.5 concentrations in the kitchen and living room peaked 1-7 min after cooking at levels of 200-1400 µg/m3, which were more than 9 times higher than the peak bedroom levels. Mean (standard deviation) kt for the kitchen, ranging from 0.58 (0.02) to 6.62 (0.34) h-1, was generally comparable to that of the living room (relative difference < 20%), but was 1-5 times larger than that of the bedroom. The range of PM2.5 full-decay time was between 1-10 h for the kitchen and living room, and from 0 to > 6 h for the bedroom. The PM2.5 emission rates during and 5 min after cooking were 2.3 (3.4) and 5.1 (3.9) mg/min, respectively. Intervention strategies, including opening kitchen windows and using PACs either in the kitchen or living room, can substantially reduce indoor PM2.5 levels and the related full-decay time. For scenarios involving a PAC, placing it in the kitchen (closer to the source) resulted in better efficacy.

Maternal PM2.5 exposure triggers preterm birth: a cross-sectional study in Wuhan, China.

Background: Most of the studies regarding air pollution and preterm birth (PTB) in highly polluted areas have estimated the exposure level based on fixed-site monitoring. However, exposure assessment methods relying on monitors have the potential to cause exposure misclassification due to a lack of spatial variation. In this study, we utilized a land use regression (LUR) model to assess individual exposure, and explored the association between PM2.5 exposure during each time window and the risk of preterm birth in Wuhan city, China. Methods: Information on 2101 singleton births, which were ≥ 20 weeks of gestation and born between November 1, 2013 and May 31, 2014; between January 1, 2015 and August 31, 2015, was obtained from the Obstetrics Department in one 3A hospital in Wuhan. Air quality index (AQI) data were accessed from the Wuhan Environmental Protection Bureau website. Individual exposure during pregnancy was assessed by LUR models and Kriging interpolation. Logistic regression analyses were conducted to determine the association between women exposure to PM2.5 and the risk of different subtypes of PTB. Results: During the study period, the average individual exposure concentration of PM2.5 during the entire pregnancy was 84.54 µg/m3. A 10 µg/m3 increase of PM2.5 exposure in the first trimester (OR: 1.169; 95% CI: 1.077, 1.262), the second trimester (OR: 1.056; 95% CI: 1.015, 1.097), the third trimester (OR: 1.052; 95% CI: 1.002, 1.101), and the entire pregnancy (OR: 1.263; 95% CI: 1.158, 1.368) was significantly associated with an increased risk of PTB. For the PTB subgroup, the hazard of PM2.5 exposure during pregnancy was stronger for very preterm births (VPTB) than moderate preterm births (MPTB). The first trimester was the most susceptible exposure window. Moreover, women who had less than 9 years of education or who conceived during the cold season tended to be more susceptible to the PM2.5 exposure during pregnancy. Conclusions: Maternal exposure to PM2.5 increased the risk of PTB, and this risk was stronger for VPTB than for MPTB, especially during the first trimester.

Impact of Ambient Temperature and Relative Humidity on the Incidence of Hand-Foot-Mouth Disease in Wuhan, China.

Background: Few studies have previously explored the relationship between hand, foot, and mouth disease (HFMD) and meteorological factors with the effect modification of air pollution, and these studies had inconsistent findings. We therefore applied a time-series analysis assessing the effects of temperature and humidity on the incidence of HFMD in Wuhan, China to deepen our understanding of the relationship between meteorological factors and the risk of HFMD. Methods: Daily HFMD cases were retrieved from Hubei Provincial Center for Disease Control and Prevention from 1 February 2013 to 31 January 2017. Daily meteorological data including 24 h average temperature, relative humidity, wind velocity, and atmospheric pressure were obtained from Hubei Meteorological Bureau. Data on Air pollution was collected from 10 national air-monitoring stations in Wuhan city. We adopted a distributed lag non-linear model (DLNM) combined with Poisson regression and time-series analysis to estimate the effects of temperature and relative humidity on the incidence HFMD. Results: We found that the association between temperature and HFMD incidence was non-linear, exhibiting an approximate "M" shape with two peaks occurring at 2.3 °C (RR = 1.760, 95% CI: 1.218-2.542) and 27.9 °C (RR = 1.945, 95% CI: 1.570-2.408), respectively. We observed an inverted "V" shape between relative humidity and HFMD. The risk of HFMD reached a maximum value at a relative humidity of 89.2% (RR = 1.553, 95% CI: 1.322-1.824). The largest delayed cumulative effects occurred at lag 6 for temperature and lag 13 for relative humidity. Conclusions: The non-linear relationship between meteorological factors and the incidence of HFMD on different lag days could be used in the early targeted warning system of infectious diseases, reducing the possible outbreaks and burdens of HFMD among sensitive populations.

Association between ambient air pollution exposure and infants small for gestational age in Huangshi, China: a cross-sectional study.

Small for gestational age (SGA) is defined as intrauterine growth retardation or small sample, referring to the 10th percentile of birth weight lower or two standard deviations less than the average weight at the same gestational age. SGA infants bring great economic and psychological burdens to families and society. The association between exposure to air pollution and SGA in underdeveloped cities with poor air quality remains unclear. Thus, this study is conducted to estimate the effects of maternal exposure to air pollutants on SGA numbers. Birth information was collected from the Huangshi Maternity and Children's Health Hospital from January 1st to December 31st in 2017. Data of pregnancy exposure were accessed using stationary monitors. These data included particulate matter less than or equal to 10 µm in aerodynamic diameter (PM10), particulate matter less than or equal to 2.5 µm in aerodynamic diameter (PM2.5), nitrogen dioxide (NO2), and sulfur dioxide (SO2). Multivariate logistic regression models were performed to estimate the association between ambient air pollution and the risk of SGA during different exposure windows. It was found that a 1 µg/m3 increase in air pollution concentrations during the entire pregnancy was associated with a higher risk of SGA, with an adjusted odds ratio (OR) and 95% confidence interval (CI) of 1.055 (1.035-1.076), 1.084 (1.053-1.116), 1.000 (0.953-1.049), and 1.051 (0.968-1.141) for PM10, PM2.5, NO2, and SO2, respectively. Thus, it is suggested that exposure to air pollution is associated with an increased risk of SGA. The effects of PM10 and PM2.5 were more stable than NO2 and SO2.

The association between short-term exposure to ambient air pollution and the incidence of mumps in Wuhan, China: A time-series study.

BACKGROUND: Previous studies have estimated the association between meteorological factors and mumps outbreaks without assessing the influence of air pollution. In this research, we explored the effects of short-term exposure to air pollution on the incidence of mumps. METHODS: Our time-series analysis was conducted using data collected in Wuhan, China from 2015 to 2017. Daily number of mumps cases was obtained from Disease Reporting System in Hubei Provincial Center for Disease Control and Prevention. Data on air pollution was obtained from 10 national air quality monitoring stations, including nitrogen dioxide (NO2), sulfur dioxide (SO2), ground-level ozone (O3), particulate matter less than or equal to 10 µm in aerodynamic diameter (PM10), and particulate matter less than or equal to 2.5 µm in aerodynamic diameter (PM2.5). Daily meteorological data including temperature and relative humidity were obtained from Hubei Meteorological Bureau. We performed a Poisson regression in generalized additive models (GAM) to explore the association between the incidence of mumps and exposure to air pollution. RESULTS: We observed that the effects of air pollutants were statistically significant mainly in two periods, lag 0 to lag 5 and lag 20 to lag 25, with the strongest effects appearing at lag 2 and lag 23. The cumulative effects were stronger than single-day lag effects. The stratified analysis showed the effect of pollutants during the hot season was stronger than that during the cold season, especially for NO2 and SO2. CONCLUSIONS: We found that exposure to NO2 and SO2 was significantly associated with higher risk of developing mumps. Our findings could help deepen the understanding of how air pollution exposure affects the incidence of mumps.

Effects of female and male body mass indices on the treatment outcomes and neonatal birth weights associated with in vitro fertilization/intracytoplasmic sperm injection treatment in China.

OBJECTIVE: To investigate the combined effects of Chinese couples' body mass indices (BMIs) on the outcomes of IVF or intracytoplasmic sperm injection (ICSI) and the clinical characteristics of their neonates. DESIGN: Retrospective cohort study. SETTING: University-affiliated reproductive medicine center. PATIENT(S): A total of 12,061 first fresh IVF/ICSI cycles with autologous oocytes from September 1, 2009 to December 31, 2014. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): The primary treatment outcome was live birth, and the primary outcome for the neonates was neonatal birth weight (NBW). RESULT(S): After adjusting for confounders, our study showed that in IVF cycles, couples with a female BMI ≥25 kg/m(2) had a significantly higher odds of abortion and a significantly lower odds of live birth than couples with both male and female BMIs <25 kg/m(2). Regarding ICSI cycles, no significant relationship was found between the couples' BMIs and the live birth rate. The NBWs of singletons conceived via IVF/ICSI cycles was significantly higher when their parents' BMIs were greater; however, no significant differences were observed in the NBWs of twins conceived via IVF/ICSI cycles. CONCLUSION(S): Increased female BMI negatively affected live births conceived via IVF. Regarding ICSI, no significant differences were found in the outcomes in terms of parental BMI. The singleton neonates' NBWs increased with parental BMI conceived via IVF/ICSI. However, parental BMI did not significantly affect the NBWs of twins conceived via IVF/ICSI.