Isomer of per- and polyfluoroalkyl substances and red blood cell indices in adults: The Isomers of C8 Health Project in China.

This study aimed to explore the isomer-specific, sex-specific, and joint associations of PFAS and red blood cell indices. We used data of 1,238 adults from the Isomers of C8 Health Project in China. Associations of PFAS isomers and red blood cell indices were explored using multiple linear regression models, Bayesian Kernel Machine Regression models and subgroup analysis across sex. We found that serum concentration of linear (n-) and branched (Br-) isomers of perfluorooctane sulfonate (PFOS) and perfluorohexanesulfonic acid (PFHxS) were significantly associated with red blood cell indices in single-pollutant models, with stronger associations observed for n-PFHxS than Br-PFHxS, in women than in men. For instance, the estimated percentage change in hemoglobin concentration for n-PFHxS (3.65%; 95% CI: 2.95%, 4.34%) was larger than that for Br-PFHxS (0.96%; 95% CI: 0.52%, 1.40%). The estimated percentage change in red blood cell count for n-PFHxS in women (2.55%; 95% CI: 1.81%, 3.28%) was significantly higher than that in men (0.12%; 95% CI: -1.04%, 1.29%) (Pinter < 0.001). Similarly, sex-specific positive association of PFAS mixture and outcomes was observed. Therefore, the structure, susceptive population, and joint effect of PFAS isomers should be taken into consideration when evaluating the health risk of chemicals.

Outdoor light at night is a modifiable environmental factor for metabolic syndrome: The 33 Communities Chinese Health Study (33CCHS).

Metabolic syndrome (MetS) is a significant public health problem and presents an escalating clinical challenge globally. To combat this problem effectively, urgent measures including identify some modifiable environmental factors are necessary. Outdoor artificial light at night (LAN) exposure garnered much attention due to its impact on circadian rhythms and metabolic process. However, epidemiological evidence on the association between outdoor LAN exposure and MetS remains limited. To determine the relationship between outdoor LAN exposure and MetS, 15,477 adults participated the 33 Communities Chinese Health Study (33CCHS) in 2009 were evaluated. Annual levels of outdoor LAN exposure at participants' residential addresses were assessed using satellite data from the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS). Generalized linear mixed effect models were utilized to assess the association of LAN exposure with MetS and its components, including elevated waist circumference (WC), triglycerides (TG), blood pressure (BP), fasting blood glucose (FBG), and reduced high-density lipoprotein cholesterol (HDL-C). Effect modification by various social demographic and behavior factors was also examined. Overall, 4701 (30.37 %) participants were defined as MetS. The LAN exposure ranged from 6.03 to 175.00 nW/cm2/sr. The adjusted odds ratio (OR) of MetS each quartile increment of LAN exposure were 1.43 (95 % CI: 1.21-1.69), 1.44 (95 % CI: 1.19-1.74) and 1.52 (95 % CI: 1.11-2.08), respectively from Q2-Q4. Similar adverse associations were also found for the components of MetS, especially for elevated BP, TG and FBG. Interaction analyses indicated that the above associations were stronger in participants without habitual exercise compared with those with habitual exercise (e.g. OR were 1.52 [95 % CI: 1.28-1.82] vs. 1.27 [95 % CI, 1.04-1.55], P-interaction = 0.042 for MetS). These findings suggest that long-term exposure to LAN can have a significant deleterious effect on MetS, potentially making LAN an important modifiable environmental factor to target in future preventive strategies.

Exposure to greenspaces sourced soils improves mice gut microbiota.

Greenspaces are important components of our living environment and have been linked to various human health. However, the mechanisms underlying the linkages remain unclear. Enriching microbiota has emerged as a novel mechanism, but the corresponding evidence is still limited. We collected soil samples from forest land, grassland, and barren land in Zunyi City, southwestern China and prepared soil solutions. A total of 40 BALB/c mice were evenly divided into normal control group, model control group, forest soil group, grassland soil group, and barren land soil group. After establishing the pseudo germ-free mouse model, different soil solutions were administered through gavage, lasting for seven weeks. Fecal samples were collected and a 16S rRNA high-throughput sequencing analysis was performed. Then, alpha- and beta-diversity were calculated and employed to estimate the effects of soil exposures on mice gut microbial diversity and composition. Further, Linear Discriminant Analysis Effect Size (LEfSe) analysis was carried out to evaluate the effects of soil exposures on gut microbiota specific genera abundances and functional pathways. Compared to mice exposed to barren land soils, those exposed to soils sourced from forest land showed an increase of 0.43 and 70.63 units in the Shannon index and the Observed ASVs, respectively. In addition, exposure to soils sourced from forest land and grassland resulted in healthier changes (i.e., more short-chain fatty acids (SCFAs)-producing bacteria) in gut microbiota than those from barren land. Furthermore, mice exposed to forest soil and grassland soil showed enrichment in 5 and 3 pathways (e.g., butanoate metabolism) compared to those exposed to barren land soil, respectively. In conclusion, exposure to various greenspaces soils may modify the gut microbial communities of mice, potentially fostering a more beneficial microbiota profile. Further better-designed studies are needed to validate the current findings and to explore the effects of greenspace related gut microbiota on human health.

Spatial regulation of NMN supplementation on brain lipid metabolism upon subacute and sub-chronic PM exposure in C57BL/6 mice.

BACKGROUND: Atmospheric particulate matter (PM) exposure-induced neuroinflammation is critical in mediating nervous system impairment. However, effective intervention is yet to be developed. RESULTS: In this study, we examine the effect of ß-nicotinamide mononucleotide (NMN) supplementation on nervous system damage upon PM exposure and the mechanism of spatial regulation of lipid metabolism. 120 C57BL/6 male mice were exposed to real ambient PM for 11 days (subacute) or 16 weeks (sub-chronic). NMN supplementation boosted the level of nicotinamide adenine dinucleotide (NAD+) in the mouse brain by 2.04 times. This augmentation effectively reduced neuroinflammation, as evidenced by a marked decrease in activated microglia levels across various brain regions, ranging from 29.29 to 85.96%. Whole brain lipidomics analysis revealed that NMN intervention resulted in an less increased levels of ceramide (Cer) and lysophospholipid in the brain following subacute PM exposure, and reversed triglyceride (TG) and glycerophospholipids (GP) following sub-chronic PM exposure, which conferred mice with anti-neuroinflammation response, improved immune function, and enhanced membrane stability. In addition, we demonstrated that the hippocampus and hypothalamus might be the most sensitive brain regions in response to PM exposure and NMN supplementation. Particularly, the alteration of TG (60:10, 56:2, 60:7), diacylglycerol (DG, 42:6), and lysophosphatidylcholine (LPC, 18:3) are the most profound, which correlated with the changes in functional annotation and perturbation of pathways including oxidative stress, inflammation, and membrane instability unveiled by spatial transcriptomic analysis. CONCLUSIONS: This study demonstrates that NMN intervention effectively reduces neuroinflammation in the hippocampus and hypothalamus after PM exposure by modulating spatial lipid metabolism. Strategies targeting the improvement of lipid homeostasis may provide significant protection against brain injury associated with air pollutant exposure.

Metabolic pathways altered by air pollutant exposure in association with coagulation function among the rural elderly.

Air pollution exposure has been linked with coagulation function. However, evidence is limited for the relationships between air pollution, coagulation function and metabolomics in humans. We recruited a panel of 130 rural elderly from the Chayashan township in China, all of whom were free of pre-existing cardiovascular diseases and had provided residential address information. We conducted clinical examinations and collected blood samples from these rural elderly for the detection of coagulation biomarkers (e.g, activated partial thromboplastin time, fibrinogen, thrombin time, and prothrombin time) and untargeted metabolites in both December 2021 and August 2022. We used mini ambient air quality monitor to measure the mean levels of five air pollutants (e.g., PM2.5, SO2, NO2, CO and O3) during 1 to 2 weeks before blood sample collection. The Mummichog pathway analysis was used to identified potential metabolic features and pathways. In this study, we identified 5 pathways associated with both air pollution and coagulation function, and further pinpointed eight metabolic features within these pathways. The majority of these features were lipids, including arachidonic acid and linoleic acid. Overall, the findings of this study offer insights into potential mechanisms, particularly lipid metabolism, that may underlie the association between air pollution and coagulation function.

Long-term ambient ozone exposure and childhood asthma, rhinitis, eczema, and conjunctivitis: A multi-city study in China.

Evidence on the link of long-term exposure to ozone (O3) with childhood asthma, rhinitis, conjunctivitis and eczema is inconclusive. We did a population-based cross-sectional survey, including 177,888 children from 173 primary and middle schools in 14 Chinese cities. A satellite-based spatiotemporal model was employed to assess four-year average O3 exposure at both residential and school locations. Information on asthma, allergic rhinitis, eczema and conjunctivitis was collected by a standard questionnaire developed by the American Thoracic Society. We used generalized non-linear and linear mixed models to test the associations. We observed linear exposure-response associations between O3 and all outcomes. The odds ratios of doctor-diagnosed asthma, rhinitis, eczema, and conjunctivitis associated with per interquartile increment in home-school O3 concentration were 1.31 (95 % confidence interval [CI]: 1.28, 1.34), 1.25 (95 %CI: 1.23, 1.28), 1.19 (95 %CI: 1.16, 1.21), and 1.28 (95 %CI: 1.21, 1.34), respectively. Similar associations were observed for asthma-related outcomes including current asthma, wheeze, current wheeze, persistent phlegm, and persistent cough. Moreover, stronger associations were observed among children who were aged > 12 years, physically inactive, and exposed to higher temperature. In conclusion, long-term O3 exposure was associated with higher risks of asthma, allergic rhinitis, conjunctivitis and eczema in children.

Association of Air Quality Improvement and Frailty Progression: A National Study across China.

Accumulating evidence strongly suggests that exposure to ambient air pollution is linked with increased frailty. However, little is known about the effect of improved air quality on frailty progression. We aimed to investigate whether improvements in air quality (PM1, PM2.5, PM10, NO2, and O3) can alleviate frailty progression, particularly in the aftermath of implementation of the "Clean Air Action" policy in China. The study involved 12,891 participants with geocoded environmental data from the nationwide China Health and Retirement Longitudinal Study (CHARLS) during the period from May 2011 to August 2015. Multivariate logistic regression models were used to analyze the association of air pollution improvements and frailty progression. The protective effects were noted for PM1, PM2.5, PM10, and NO2 indices, with an aOR (adjusted odds ratio) ranging from 0.72 to 0.79. Air quality improvement in PM1, PM2.5, PM10, and NO2 could alleviate the progression of frailty. The study is the first to examine the association between the improvement of air quality and the progression of frailty, setting a precedent for the importance of a nationwide clean air policy and its impact on healthy ageing.

Associations between urinary rare Earth elements with renal function: Findings from a cross-sectional study in Guangxi, China.

BACKGROUND: With increased applications of rare earth elements (REEs) across various industries, evaluating the relationship between REEs exposure and potential health effects has become a public concern. In vivo experiments have established that REEs impact renal function. However, relevant epidemiological evidence on this relationship remains scarce. The objective of this study is to examine the impact of exposure to REEs on renal function. METHODS: In this cross-sectional study, 1052 participants were recruited from Guangxi, China. We measured urinary concentrations of 12 REEs using an inductively coupled plasma-mass spectrometer (ICP-MS). Multiple linear regression models were developed to explore the relationship between a single REEs exposure and the estimated glomerular filtration rate (eGFR), a marker of renal function. Weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR) were used to examine the combined effects of REE co-exposure on eGFR. RESULTS: In the multiple linear regression analysis, increasing the concentrations of lanthanum (La, ß: 8.22, 95% CI: 5.67-10.77), cerium (Ce, ß:6.61, 95% CI: 3.80-9.43), praseodymium (Pr, ß: 8.46, 95% CI: 5.85-11.07), neodymium (Nd, ß:8.75, 95% CI: 6.10-11.41), and dysprosium (Dy, ß:7.38, 95% CI: 4.85-9.91) significantly increased the eGFR. In the WQS regression model, the WQS index was significantly associated with eGFR (ß: 4.03, 95% CI: 2.46-5.60), with Pr having the strongest correlation with eGFR. Similar results were obtained in the BKMR model. Additionally, interactions between Pr and La, and Pr and Nd were observed. CONCLUSIONS: Co-exposure to REEs is positively associated with elevated eGFR. Pr is likely to have the most significant influence on increased eGFRs and this might be exacerbated when interacting with La and Nd. Mixed exposure to low doses of REEs had a protective effect on renal function, which can provide some evidence for the exposure threshold of REEs in the environment. TRIAL REGISTRATION: The study has been approved by the Guangxi Medical University Medical Ethics Committee (#20170206-1), and all participants provided written informed consent.

Neurotoxicity of fine and ultrafine particulate matter: A comprehensive review using a toxicity pathway-oriented adverse outcome pathway framework.

Fine particulate matter (PM2.5) can cause brain damage and diseases. Of note, ultrafine particles (UFPs) with an aerodynamic diameter less than or equal to 100 nm are a growing concern. Evidence has suggested toxic effects of PM2.5 and UFPs on the brain and links to neurological diseases. However, the underlying mechanism has not yet been fully illustrated due to the variety of the study models, different endpoints, etc. The adverse outcome pathway (AOP) framework is a pathway-based approach that could systematize mechanistic knowledge to assist health risk assessment of pollutants. Here, we constructed AOPs by collecting molecular mechanisms in PM-induced neurotoxicity assessments. We chose particulate matter (PM) as a stressor in the Comparative Toxicogenomics Database (CTD) and identified the critical toxicity pathways based on Ingenuity Pathway Analysis (IPA). We found 65 studies investigating the potential mechanisms linking PM2.5 and UFPs to neurotoxicity, which contained 2, 675 genes in all. IPA analysis showed that neuroinflammation signaling and glucocorticoid receptor signaling were the common toxicity pathways. The upstream regulator analysis (URA) of PM2.5 and UFPs demonstrated that the neuroinflammation signaling was the most initially triggered upstream event. Therefore, neuroinflammation was recognized as the MIE. Strikingly, there is a clear sequence of activation of downstream signaling pathways with UFPs, but not with PM2.5. Moreover, we found that inflammation response and homeostasis imbalance were key cellular events in PM2.5 and emphasized lipid metabolism and mitochondrial dysfunction, and blood-brain barrier (BBB) impairment in UFPs. Previous AOPs, which only focused on phenotypic changes in neurotoxicity upon PM exposure, we for the first time propose AOP framework in which PM2.5 and UFPs may activate pathway cascade reactions, resulting in adverse outcomes associated with neurotoxicity. Our toxicity pathway-based approach not only advances risk assessment for PM-induced neurotoxicity but shines a spotlight on constructing AOP frameworks for new chemicals.

Intrauterine exposure to long-chain perfluorocarboxylic acids (PFCAs) were associated with reduced primary bile acids in three-year-old children: Findings from a prospective birth cohort study.

Bile acids (BAs) play a crucial role in lipid metabolism of children. However, the association between per- and polyfluoroalkyl substance (PFAS) exposure and BAs in children is scarce. To address this need, we selected 252 children from the Maoming Birth Cohort and measured 32 PFAS, encompassing short- and long-chain perfluorocarboxylic acids (PFCAs) and perfluorosulfonic acids (PFSAs) in the cord blood. Additionally, we analyzed nine primary and eight secondary BAs in the serum of three-year-old children. Generalized linear models with FDR-adjusted and Bayesian kernel machine regression (BKMR) were used to explore the associations of individual and mixture effects of PFAS and BAs. We found negative associations between cord blood long-chain PFCAs exposure and serum primary BAs in three-year-old children. For example, one ln-unit (ng/mL) increase of perfluoro-n-tridecanoic acid (PFTrDA), perfluoro-n-undecanoic acid (PFUnDA) and perfluoro-n-decanoic acid (PFDA) were associated with decreased taurochenodeoxycholic acid, with estimated percentage change of -24.28% [95% confidence interval (CI): -36.75%, -9.35%], -25.84% (95% CI: -39.67%, -8.83%), and -22.97% (95% CI: -34.45%, -9.47%) respectively. Notably, the observed associations were more pronounced in children with lower vegetable intake. Additionally, the BKMR model also demonstrated a monotonical decline in primary BAs as the PFAS mixture increased. We provided the first evidence of the association between intrauterine exposure to PFAS and its mixture with BAs in children. Further large-sample-size studies are needed to verify this finding.

Credibility of the evidence on green space and human health: an overview of meta-analyses using evidence grading approaches.

BACKGROUND: Green space is an important part of the human living environment, with many epidemiological studies estimating its impact on human health. However, no study has quantitatively assessed the credibility of the existing evidence, impeding their translations into policy decisions and hindering researchers from identifying new research gaps. This overview aims to evaluate and rank such evidence credibility. METHODS: Following the PRISMA guideline, we systematically searched PubMed, Web of Science, and Embase databases for systematic reviews with meta-analyses concerning green spaces and health outcomes published up to January 15, 2024. We categorized the credibility of meta-analytical evidence from interventional studies into four levels (i.e., high, moderate, low, and very low) using the Grading of Recommendation, Assessment, Development and Evaluations framework, based on five domains including risk of bias, inconsistency, indirectness, imprecision, and publication bias. Further, we recalculated all the meta-analyses from observational studies and classified evidence into five levels (i.e., convincing, highly suggestive, suggestive, weak, and non-significant) by considering stringent thresholds for P-values, sample size, robustness, heterogeneity, and testing for biases. FINDINGS: In total, 154 meta-analysed associations (interventional = 44, observational = 110) between green spaces and health outcomes were graded. Among meta-analyses from interventional studies, zero, four (wellbeing, systolic blood pressure, negative affect, and positive affect), 20, and 20 associations between green spaces and health outcomes were graded as high, moderate, low, and very low credibility evidence, respectively. Among meta-analyses from observational studies, one (cardiovascular disease mortality), four (prevalence/incidence of diabetes mellitus, preterm birth, and small for gestational age infant, and all-cause mortality), 12, 22, and 71 associations were categorized as convincing, highly suggestive, suggestive, weak, and non-significant evidence, respectively. INTERPRETATION: The current evidence largely confirms beneficial associations between green spaces and human health. However, only a small subset of these associations can be deemed to have a high or convincing credibility. Hence, future better designed primary studies and meta-analyses are still needed to provide higher quality evidence for informing health promotion strategies. FUNDING: The National Natural Science Foundation of China of China; the Guangzhou Science and Technology Program; the Guangdong Medical Science and Technology Research Fund; the Research Grant Council of the Hong Kong SAR; and Sino-German mobility program.

Long-term exposure to ozone and sleep disorders in children: A multicity study in China.

Evidence regarding the link between long-term ambient ozone (O3) exposure and childhood sleep disorders is little. This study aims to examine the associations between long-term exposure to O3 and sleep disorders in children. We conducted a population-based cross-sectional survey, including 185,428 children aged 6-18 years in 173 schools across 14 Chinese cities during 2012 and 2018. Parents or guardians completed a checklist using Sleep Disturbance Scale for Children, and O3 exposure at residential and school addresses was estimated using a satellite-based spatiotemporal model. We used generalized linear mixed models to test the associations with adjustment for factors including socio-demographic variables, lifestyle, meteorology and multiple pollutants. Mean concentrations of O3, particulate matter with diameters ≤2.5 mm (PM2.5) and nitrogen dioxide (NO2) were 89.0 µg/m3, 42.5 µg/m3 and 34.4 µg/m3, respectively. O3 and NO2 concentrations were similar among provinces, while PM2.5 concentration varied significantly among provinces. Overall, 19.4% of children had at least one sleep disorder. Long-term exposure to O3 was positively associated with odds of sleep disorders for all subtypes. For example, each interquartile increment in home-school O3 concentrations was associated with a higher odds ratio for global sleep disorder, at 1.22 (95% confidence interval: 1.18, 1.26). Similar associations were observed for sleep disorder subtypes. The associations remained similar after adjustment for PM2.5 and NO2. Moreover, these associations were heterogeneous regionally, with more prominent associations among children residing in southeast region than in northeast and northwest regions in China. We concluded that long-term exposure to O3 is positively associated with risks of childhood sleep disorders. These associations varied by geographical region of China.

The effect of residential greenness on cardiovascular mortality from a large cohort in South China: An in-depth analysis of effect modification by multiple demographic and lifestyle characteristics.

BACKGROUND: The potential for residential greenness to improve cardiovascular health through both physical and psychological mechanisms is well recognized. However, evidence from rapidly urbanizing developing countries and cohort-based causal inference approaches, remains limited. We aim to examine the effect of residential greenness and time to cardiovascular mortality in South China. METHODS: We utilized data from a community-based population survey involving 748,209 participants at baseline from 2009 to 2015, followed up until 2020. Residential greenness exposure was assessed by the annual Normalized Difference Vegetation Index (NDVI) in the 500 m radius of each participant's residence. We used time-varying proportional hazard Cox models coupled with inverse probability weighting to fit marginal structural models and obtain hazard ratios (HRs) for cardiovascular disease (CVD) mortality after adjusting for confounders. Multiple effect modifiers on both additive and multiplicative scales were further explored. RESULTS: A total of 15,139 CVD-related deaths were identified during a median of 7.9 years of follow-up. A protective effect was found between higher greenness exposure and reduced CVD mortality, with a 9.3 % lower rate of total CVD mortality (HR 0.907, 95 % CI 0.859-0.957) based on a 0.1 increase in annual average NDVI. Demographic (age, marital status) and lifestyle factors (smoking, drinking status) were found to modify the association between residential greenness and CVD mortality (all P interaction values < 0.05 or 95 %CI for RERI excluded the value 0). Notably, this effect was more pronounced among older adults, married, and individuals having healthier lifestyles, indicating a greater benefit from greenness for these subgroups. CONCLUSIONS: Our findings support a causal link between increased residential greenness exposure and a reduced risk of CVD mortality in South China with marked heterogenous effects, which has public health implications for cultivating greener urban environments to mitigate the impact of CVD within the context of rapid urbanization.

Quantitative studies on charcoalification: Physical and chemical changes of charring wood.

Charcoal is commonly preserved in both natural and artificial sediments, and is intensively used in paleontological, paleoenvironmental, and archaeological studies due to the abundant bio-information it contains. The biochemical properties of charcoal are also used for paleoclimatic reconstruction; however, the reliability of this approach has been challenged due to a lack of clarity on how physicochemical properties change during the charring process, as well as the temperatures required for charcoalification. To address this lack, in this study, Qinghai spruce and Chinese pine wood samples from the northeastern Tibetan Plateau were heated at different temperatures and for different lengths of time under restricted oxygen conditions. The reflectance; carbon, nitrogen, and oxygen content; and tracheid morphology were quantified before and after heating to assess changes related to the charring process. Archaeological charcoal remains were then evaluated to determine the charcoalification temperatures by comparing with the experimental results. The minimum temperature required for wood charcoalification was ∼300 °C, while temperatures recorded by archaeological charcoal were concentrated at 400-500 °C. During the charring experiments, the tracheid cell walls gradually homogenized, and tracheid cell wall thickness and lumen area decreased by ∼20%. On average, 50% mass losses were observed; the carbon and oxygen content (% wt.) approximately changed from 47% to 60% and 48% to 35% respectively, while the nitrogen content (% wt.) fluctuated around 0.2%. The reflectance increased slightly from 0% to 0.5%. We propose that the charcoalification of wood tissue refers to charring (in restricted air) and carbonization (in the almost absence of air) when the wood is exposed to a heat source, which then finally transforms into a black, inert solid. This quantitative study provided valuable data and a thorough assessment of the process of wood charcoalification, as well as accurately estimated the feasibility of using charcoal physicochemical properties in paleoclimatic research.

Exposures to particulate matters and childhood sleep disorders-A large study in three provinces in China.

OBJECTIVES: Evidence on the link between long-term ambient particulate matter (PM) exposures and childhood sleep disorders were scarce. We examined the associations between long-term exposures to PM2.5 and PM1 (PM with an aerodynamic equivalent diameter <2.5 µm and <1 µm, respectively) with sleep disorders in children. METHODS: We performed a population-based cross-sectional survey in 177,263 children aged 6 to 18 years in 14 Chinese cities during 2012-2018. A satellite-based spatiotemporal model was employed to estimate four-year annual average PM2.5 and PM1 exposures at residential and school addresses. Parents or guardians completed a checklist using the Sleep Disturbance Scale for Children. We estimated the associations using generalized linear mixed models with adjustment for characteristics of children, parents, and indoor environments. RESULTS: Long-term PM2.5 and PM1 exposures were positively associated with odds of sleep disorders for almost all domains. For example, increments in PM2.5 and PM1 per 10 µg/m3 were associated with odds ratios of global sleep disorder of 1.24 (95 % confidence interval [CI]: 1.14, 1.35) and 1.31 (95 %CI: 1.18, 1.46), respectively. Similar results were observed for subtypes of sleep disorder. These associations were heterogeneous regionally, with stronger associations among children residing in southeast region than in northeast and northwest regions. Moreover, larger estimates of PM1 were found than that of PM2.5 in southeast region. CONCLUSION: Long-term PM2.5 and PM1 exposures are independently associated with higher risks of childhood sleep disorders, and these associations vary by geographical region.

Association between outdoor light at night exposure and executive function in Chinese children.

BACKGROUND: Recent evidences highlight the potential impact of outdoor Light at Night (LAN) on executive function. However, few studies have investigated the association between outdoor LAN exposure and executive function. METHODS: We employed data from 48,502 Chinese children aged 5-12 years in a cross-sectional study conducted in Guangdong province during 2020-2021, to examine the association between outdoor LAN and executive function assessed using the validated parent-completed Behavior Rating Inventory of Executive Function. We assessed children's outdoor LAN exposure using the night-time satellite images based on the residential addresses. We used generalized linear mixed models to estimate the association between outdoor LAN exposure and executive function scores and executive dysfunction. RESULTS: After adjusting for potential covariates, higher quintiles of outdoor LAN exposure were associated with poorer executive function. Compared to the lowest quintile (Q1), all higher quintiles of exposure showed a significant increased global executive composite (GEC) score with ß (95% confidence intervals, CI) of 0.58 (0.28, 0.88) in Q2, 0.59 (0.28, 0.9) in Q3, 0.85 (0.54, 1.16) in Q4, and 0.76 (0.43, 1.09) in Q5. Higher quintiles of exposure were also associated with higher risks for GEC dysfunction with odd ratios (ORs) (95% CI) of 1.34 (1.18, 1.52) in Q2, 1.40 (1.24, 1.59) in Q3, 1.40 (1.23, 1.59) in Q4, and 1.39 (1.22, 1.58) in Q5. And stronger associations were observed in children aged 10-12 years. CONCLUSIONS: Our study suggested that high outdoor LAN exposure was associated with poor executive function in children. These findings suggested that future studies should determine whether interventions to reduce outdoor LAN exposure can have a positive effect on executive function.

Long-term exposure to ambient fine particulate matter (PM2.5) and attributable pulmonary tuberculosis notifications in Ningxia Hui Autonomous Region, China: a health impact assessment.

INTRODUCTION: Long-term exposure to fine particulate matter (≤2.5 µm (PM2.5)) has been associated with pulmonary tuberculosis (TB) notifications or incidence in recent publications. Studies quantifying the relative contribution of long-term PM2.5 on TB notifications have not been documented. We sought to perform a health impact assessment to estimate the PM2.5- attributable TB notifications during 2007-2017 in Ningxia Hui Autonomous Region (NHAR), China. METHODS: PM2.5 attributable TB notifications were estimated at township level (n=358), stratified by age group and summed across NHAR. PM2.5-associated TB-notifications were estimated for total and anthropogenic PM2.5 mass and expressed as population attributable fractions (PAFs). The main analysis used effect and uncertainty estimates from our previous study in NHAR, defining a counterfactual of the lowest annual PM2.5 (30 µg/m3) level, above which we assumed excess TB notifications. Sensitivity analyses included counterfactuals based on the 5th (31 µg/m3) and 25th percentiles (38 µg/m3), and substituting effect estimates from a recent meta-analysis. We estimated the influence of PM2.5 concentrations, population growth and baseline TB-notification rates on PM2.5 attributable TB notifications. RESULTS: Over 2007-2017, annual PM2.5 had an estimated average PAF of 31.2% (95% CI 22.4% to 38.7%) of TB notifications while the anthropogenic PAF was 12.2% (95% CI 9.2% to 14.5%). With 31 and 38 µg/m3 as counterfactuals, the PAFs were 29.2% (95% CI 20.9% to 36.3%) and 15.4% (95% CI 10.9% to 19.6%), respectively. PAF estimates under other assumptions ranged between 6.5% (95% CI 2.9% to 9.6%) and 13.7% (95% CI 6.2% to 19.9%) for total PM2.5, and 2.6% (95% CI 1.2% to 3.8%) to 5.8% (95% CI 2.7% to 8.2%) for anthropogenic PM2.5. Relative to 2007, overall changes in PM2.5 attributable TB notifications were due to reduced TB-notification rates (-23.8%), followed by decreasing PM2.5 (-6.2%), and population growth (+4.9%). CONCLUSION: We have demonstrated how the potential impact of historical or hypothetical air pollution reduction scenarios on TB notifications can be estimated, using public domain, PM2.5 and population data. The method may be transferrable to other settings where comparable TB-notification data are available.

scZAG: Integrating ZINB-Based Autoencoder with Adaptive Data Augmentation Graph Contrastive Learning for scRNA-seq Clustering.

Single-cell RNA sequencing (scRNA-seq) is widely used to interpret cellular states, detect cell subpopulations, and study disease mechanisms. In scRNA-seq data analysis, cell clustering is a key step that can identify cell types. However, scRNA-seq data are characterized by high dimensionality and significant sparsity, presenting considerable challenges for clustering. In the high-dimensional gene expression space, cells may form complex topological structures. Many conventional scRNA-seq data analysis methods focus on identifying cell subgroups rather than exploring these potential high-dimensional structures in detail. Although some methods have begun to consider the topological structures within the data, many still overlook the continuity and complex topology present in single-cell data. We propose a deep learning framework that begins by employing a zero-inflated negative binomial (ZINB) model to denoise the highly sparse and over-dispersed scRNA-seq data. Next, scZAG uses an adaptive graph contrastive representation learning approach that combines approximate personalized propagation of neural predictions graph convolution (APPNPGCN) with graph contrastive learning methods. By using APPNPGCN as the encoder for graph contrastive learning, we ensure that each cell's representation reflects not only its own features but also its position in the graph and its relationships with other cells. Graph contrastive learning exploits the relationships between nodes to capture the similarity among cells, better representing the data's underlying continuity and complex topology. Finally, the learned low-dimensional latent representations are clustered using Kullback-Leibler divergence. We validated the superior clustering performance of scZAG on 10 common scRNA-seq datasets in comparison to existing state-of-the-art clustering methods.

Hierarchical multimodal self-attention-based graph neural network for DTI prediction.

Drug-target interactions (DTIs) are a key part of drug development process and their accurate and efficient prediction can significantly boost development efficiency and reduce development time. Recent years have witnessed the rapid advancement of deep learning, resulting in an abundance of deep learning-based models for DTI prediction. However, most of these models used a single representation of drugs and proteins, making it difficult to comprehensively represent their characteristics. Multimodal data fusion can effectively compensate for the limitations of single-modal data. However, existing multimodal models for DTI prediction do not take into account both intra- and inter-modal interactions simultaneously, resulting in limited presentation capabilities of fused features and a reduction in DTI prediction accuracy. A hierarchical multimodal self-attention-based graph neural network for DTI prediction, called HMSA-DTI, is proposed to address multimodal feature fusion. Our proposed HMSA-DTI takes drug SMILES, drug molecular graphs, protein sequences and protein 2-mer sequences as inputs, and utilizes a hierarchical multimodal self-attention mechanism to achieve deep fusion of multimodal features of drugs and proteins, enabling the capture of intra- and inter-modal interactions between drugs and proteins. It is demonstrated that our proposed HMSA-DTI has significant advantages over other baseline methods on multiple evaluation metrics across five benchmark datasets.