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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Associations of Ambient Particulate Matter with Maternal Thyroid Autoimmunity and Thyroid Function in Early Pregnancy.

This prospective birth cohort study evaluated the association of exposure to PM2.5 (diameter ≤2.5 µm), PM1-2.5 (1-2.5 µm), and PM1 (≤1 µm) with maternal thyroid autoimmunity and function during early pregnancy. A total of 15,664 pregnant women were included at 6 to 13+6 gestation weeks in China from 2018 to 2020. Single-pollutant models using generalized linear models (GLMs) showed that each 10 µg/m3 increase in PM2.5 and PM1-2.5 was related with 6% (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.01, 1.12) and 15% (OR = 1.15, 95% CI: 1.08, 1.22) increases in the risk of thyroid autoimmunity, respectively. The odds of thyroid autoimmunity significantly increased with each interquartile range increase in PM2.5 and PM1-2.5 exposure (P for trend <0.001). PM1 exposure was not significantly associated with thyroid autoimmunity. GLM with natural cubic splines demonstrated that increases in PM2.5 and PM1-2.5 exposure were associated with lower maternal FT4 levels, while a negative association between PM1 and FT4 levels was found when exposure exceeded 32.13 µg/m3. Only PM2.5 exposure was positively associated with thyrotropin (TSH) levels. Our findings suggest that high PM exposure is associated with maternal thyroid disruption during the early pregnancy.

Placental inflammatory injury induced by chlorinated polyfluorinated ether sulfonate (F-53B) through NLRP3 inflammasome activation.

Chlorinated polyfluorinated ether sulfonate, commercially known as F-53B, has been associated with adverse birth outcomes. However, the reproductive toxicology of F-53B on the placenta remains poorly understood. To address this gap, we examined the impact of F-53B on placental injury and its underlying molecular mechanisms in vivo. Pregnant C57BL/6 J female mice were randomly allocated to three groups: the control group, F-53B 0.8 µg/kg/day group, and F-53B 8 µg/kg/day group. After F-53B exposure through free drinking water from gestational day (GD) 0.5-14.5, the F-53B 8 µg/kg/day group exhibited significant increases in placental weights and distinctive histopathological alterations, including inflammatory cell infiltration, heightened syncytiotrophoblast knots, and a loosened trophoblastic basement membrane. Within the F-53B 8 µg/kg/day group, placental tissue exhibited increased apoptosis, as indicated by increased caspase3 activation. Furthermore, F-53B potentially induced the NF-κB signaling pathway activation through IκB-α phosphorylation. Subsequently, this activation upregulated the expression of inflammatory cytokines and components of the NLRP3 inflammasome, including activated caspase1, IL-1ß, IL-18, and cleaved gasdermin D (GSDMD), ultimately leading to pyroptosis in the mouse placenta. Our findings reveal a pronounced inflammatory injury in the placenta due to F-53B exposure, suggesting potential reproductive toxicity at concentrations relevant to the human population. Further toxicological and epidemiological investigations are warranted to conclusively assess the reproductive health risks posed by F-53B.

Caspase-8 promotes NLRP3 inflammasome activation mediates eye development defects in zebrafish larvae exposed to perfulorooctane sulfonate (PFOS).

Epidemiological evidence showed that serum high perfluorooctane sulfonate (PFOS) levels are associated with multiple eye related diseases, but the potential underlying molecular mechanisms remain poorly understood. Zebrafish and photoreceptor cell (661w) models were used to investigate the molecular mechanism of PFOS induced eye development defects. Our results showed a novel molecular mechanism of PFOS-induced inflammation response-mediated photoreceptor cell death associated with eye development defects. Inhibition of Caspase-8 activation significantly decreased photoreceptor cell death in PFOS exposure. Mechanistically, Toll-like receptor 4 (TLR4) mediates activation of Caspase-8 promote activation of NLR family pyrin domain-containing 3 (NLRP3) inflammasome to elicit maturation of interleukin-1 beta (IL-1ß) via Caspase-1 activation, facilitating photoreceptor cell inflammation damage in PFOS exposure. In addition, we also made a novel finding that Caspase-3 activation was increased via Caspase-8 activation and directly intensified cell death. Our results show the important role of Caspase-8 activation in PFOS induced eye development defects and highlight Caspase-8 mediated activation of the NLRP3 inflammation triggers activation of Caspase-1 and promote the maturation of IL-1ß in retinal inflammatory injury.

Human molybdenum exposure risk in industrial regions of China: New critical effect indicators and reference dose.

Evidence increasingly suggests molybdenum exposure at environmental levels is still associated with adverse human health, emphasizing the necessity to establish a more protective reference dose (RfD). Herein, we conducted a study measuring 15 urinary metals and 30 clinical health indicators in 2267 participants residing near chemical enterprises across 11 Chinese provinces to investigate their relationships. The kidney and cystatin-C emerged as the most sensitive organ and critical effect indicator of molybdenum exposure, respectively. Odds of cystatin-C-defined chronic kidney disease (CKD) in the highest quantile of molybdenum exposure significantly increased by 133.5% (odds ratio [OR]: 2.34, 95% CI: 1.78, 3.11) and 75.8% (OR: 1.76, 95% CI: 1.24, 2.49) before and after adjusting for urinary 14 metals, respectively. Intriguingly, cystatin-C significantly mediated 15.9-89.5% of molybdenum's impacts on liver and lung function, suggesting nephrotoxicity from molybdenum exposure may trigger hepatotoxicity and pulmonary toxicity. We derived a new RfD for molybdenum exposure (0.87 µg/kg-day) based on cystatin-C-defined estimated glomerular filtration rate by employing Bayesian Benchmark Dose modeling analysis. This RfD is significantly lower than current exposure guidance values (5-30 µg/kg-day). Remarkably, >90% of participants exceeded the new RfD, underscoring the significant health impacts of environmental molybdenum exposure on populations in industrial regions of China.

Long-term exposure to major constituents of fine particulate matter and neurodegenerative diseases: A population-based survey in the Pearl River Delta Region, China.

BACKGROUND: Exposure to PM2.5 has been linked to neurodegenerative diseases, with limited understanding of constituent-specific contributions. OBJECTIVES: To explore the associations between long-term exposure to PM2.5 constituents and neurodegenerative diseases. METHODS: We recruited 148,274 individuals aged ≥ 60 from four cities in the Pearl River Delta region, China (2020 to 2021). We calculated twenty-year average air pollutant concentrations (PM2.5 mass, black carbon (BC), organic matter (OM), ammonium (NH4+), nitrate (NO3-) and sulfate (SO42-)) at the individuals' home addresses. Neurodegenerative diseases were determined by self-reported doctor-diagnosed Alzheimer's disease (AD) and Parkinson's disease (PD). Generalized linear mixed models were employed to explore associations between pollutants and neurodegenerative disease prevalence. RESULTS: PM2.5 and all five constituents were significantly associated with a higher prevalence of AD and PD. The observed associations generally exhibited a non-linear pattern. For example, compared with the lowest quartile, higher quartiles of BC were associated with greater odds for AD prevalence (i.e., the adjusted odds ratios were 1.81; 95% CI, 1.45-2.27; 1.78; 95% CI, 1.37-2.32; and 1.99; 95% CI, 1.54-2.57 for the second, third, and fourth quartiles, respectively). CONCLUSIONS: Long-term exposure to PM2.5 and its constituents, particularly combustion-related BC, OM, and SO42-, was significantly associated with higher prevalence of AD and PD in Chinese individuals. ENVIRONMENTAL IMPLICATION: PM2.5 is a routinely regulated mixture of multiple hazardous constituents that can lead to diverse adverse health outcomes. However, current evidence on the specific contributions of PM2.5 constituents to health effects is scarce. This study firstly investigated the association between PM2.5 constituents and neurodegenerative diseases in the moderately to highly polluted Pearl River Delta region in China, and identified hazardous constituents within PM2.5 that have significant impacts. This study provides important implications for the development of targeted PM2.5 prevention and control policies to reduce specific hazardous PM2.5 constituents.

8-OHdG mediates the association of co-exposure to fifty-five typical endocrine-disrupting chemicals with renal function: a cross-section investigation in Southern Chinese adults.

Individual typical endocrine-disrupting chemicals (EDCs), including organophosphate triesters (OPEs), parabens, triclosan (TCS), bisphenols, benzophenones (BPs), phthalates (PAEs), and synthetic phenolic antioxidants (SPAs), are associated with renal dysfunction. However, the combined effects and underlying mechanisms of mixed EDC exposure on renal function remain unclear. Two hundred ninety-nine adult participants were enrolled in the cross-sectional survey conducted in Guangzhou, China. Urinary levels of 7 OPEs, 6 parabens, TCS, 14 bisphenols, 8 BPs, 15 PAEs, 4 SPAs, and 8-hydroxy-2'-deoxyguanosine (8-OHdG) were determined, and estimated glomerular filtration rate (eGFR) was served as the outcome index. We found elevated levels of diphenyl phosphate (DPP), bisphenol A (BPA), mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), and mono-butyl phthalate (MBP) showed dose-responsive associations with eGFR decline, However, nonlinear associations were observed for bis(2-butoxyethyl) hydrogen phosphate (BBOEP), TCS, 4-hydroxybenzophenone (HBP), mono-n-pentyl phthalate (MnPP), and mono-benzyl phthalate (MBzP). The quantile-based g-computation model demonstrated that a quartile increase in the EDC mixture corresponded to a 0.383-SD decrease (95% CI - 0.658 ~ - 0.108, P = 0.007) in eGFR. Notably, BPA was identified as the primary contributor to this effect. Moreover, 8-OHdG mediated the eGFR decline associated with EDC mixtures with a mediation proportion of 25.49%. A sex-modified effect was also observed (P = 0.004), indicating that exposure to the mixture of EDC was linked to more pronounced renal dysfunction in females. Our novel findings suggest that exposure to a typical mixture of EDCs is associated with renal dysfunction in the general adult population of Southern China. Furthermore, 8-OHdG may play a role in the pathogenesis of EDC mixture-related renal dysfunction.