Spatial Analysis of Time of Flight−Secondary Ion Mass Spectrometric Images by Ordinary Kriging and Inverse Distance Weighted Interpolation Techniques

A water quality assessment model involving novel fluorescence technology

The reasonable utilization of water resources and real-time monitoring of water pollution are the core tasks of current world hydrological and water conservancy work. Novel technologies and methods for monitoring water pollution are important means to ensure water health. However, the absence of intuitive and simple analysis methods for the assessment of regional pollution in large-scale water bodies has prevented scientists from quickly grasping the overall situation of water pollution. In this study, we propose a strategy based on the unique combination of fluorescence technology and simple kriging (SK) interpolation (FL-SK) for the first time. This strategy could present the relative magnitude and distribution of the physicochemical indicators of a whole natural lake intuitively and accurately. The unique FL-SK model firstly offers a simple and effective water quality method that provides the pollution index of different sampling points in lakes. The macroscopic evaluation of large-scale water bodies by the FL-SK model primarily relies on the fluorescence response of the RDM-TPE to the comprehensive indicators of the water body, as experimental results have revealed a good correlation between fluorescent responses and six normalized physicochemical indicators. Multiple linear regression and fluorescence response experiments on RDM-TPE indicate that to some extent, the fluorescence signals of the FL-SK model may originate from a certain type of sulfide in the water body. Pattern discovery could enable the analysis of pollution levels in other ecosystems and promote early pollution assessment in the future.

PM2.5-derived exosomal long noncoding RNA PAET participates in childhood asthma by enhancing DNA damage via m6A-dependent OXPHOS regulation

Fine particulate matter (PM2.5) is known to enhance DNA damage levels and is involved in respiratory diseases. Exosomes can carry noncoding RNAs, especially long noncoding RNAs (lncRNAs), as regulators of DNA damage, which participate in diseases. However, their role in PM2.5-induced childhood asthma remains unclear. We performed RNA-seq to profile aberrantly expressed exosomal lncRNAs derived from PM2.5-treated human bronchial epithelial (HBE) cell models. The role of exosomal lncRNAs in childhood asthma was determined in a case-control study. The intercellular communication mechanisms of exosomal lncRNA on DNA damage were determined in vitro. Exosomes secreted by PM2.5-treated HBE cells (PM2.5-Exos) could increase the DNA damage levels of recipient HBE cells and promote the expression levels of airway remodeling-related markers in sensitive human bronchial smooth muscle cells (HBSMCs). LncRNA PM2.5-associated exosomal transcript (PAET) was highly expressed in PM2.5-Exos and was associated with PM2.5 exposure in childhood asthma. Mechanistically, exosomal lncRNA PAET promoted methyltransferase-like 3 (METTL3) accumulation by increasing its stability, which stimulated N6-methyladenosine (m6A) modification of cytochrome c oxidase subunit 4I1 (COX4I1), and COX4I1 levels were decreased in a mechanism dependent on the m6A "reader" YTH domain family 3 (YTHDF3). COX4I1 deficiency subsequently disrupted oxidative phosphorylation (OXPHOS), resulting in attenuated adenosine triphosphate (ATP) production and accumulation of reactive oxygen species (ROS), which increased DNA damage levels. This comprehensive study extends the understanding of PM2.5-induced childhood asthma via DNA damage and identifies exosomal lncRNA PAET as a potential target for childhood asthma.

The impact of prolonged exposure to air pollution on the incidence of chronic non-communicable disease based on a cohort in Tianjin

Evidence on the associations of prolonged ambient pollutants exposure with chronic non-communicable diseases among middle-aged and elderly residents is still limited. This prospective cohort study intends to investigate the long-term effects of ambient pollution on hypertension and diabetes incidence among relatively older residents in China. Individual particulate matter exposure levels were estimated by satellite-based model. Individual gaseous pollutants exposure levels were estimated by Inverse Distance Weighted model. A Cox regression model was employed to assess the risks of hypertension and diabetes morbidity linked to air pollutants exposures. The cross-product term of ambient pollutants exposure and covariates was further added into the regression model to test whether covariates would modify these air pollution-morbidity associations. During the period from 2014 to 2018, a total of 97,982 subjects completed follow-up. 12,371 incidents of hypertension and 2034 of diabetes occurred. In the multi-covariates model, the hazard ratios (HR) and 95% confidence interval (CI) were 1.49 (1.45-1.52), 1.28 (1.26-1.30), 1.17 (1.15-1.18), 1.21 (1.17-1.25) and 1.33 (1.31-1.35) for hypertension morbidity per 10 μg/m³ increment in PM₁, PM_2.5, PM₁₀, NO₂ and SO₂, respectively. For diabetes onsets, the HR (95% CI) were 1.17 (1.11-1.23), 1.09 (1.04-1.13), 1.06 (1.02-1.09), 1.02 (0.95-1.10), and 1.24 (1.19-1.29), respectively. In addition, for hypertension analyses, the effect estimates were more pronounced in the participants with age <60 years old, BMI ≥24 kg/m², and frequent alcohol drinking. These findings provided the evidence on elevated risks of morbidity of hypertension and diabetes associated with prolonged ambient pollutants exposure at relatively high levels.

Fine Particulate Matter Induces Childhood Asthma Attacks via Extracellular Vesicle-Packaged Let-7i-5p-Mediated Modulation of the MAPK Signaling Pathway

Fine particulate matter less than 2.5 µm in diameter (PM_2.5 ) is a major risk factor for acute asthma attacks in children. However, the biological mechanism underlying this association remains unclear. In the present study, PM_2.5 -treated HBE cells-secreted extracellular vesicles (PM_2.5 -EVs) caused cytotoxicity in "horizontal" HBE cells and increased the contractility of "longitudinal" sensitive human bronchial smooth muscle cells (HBSMCs). RNA sequencing showed that let-7i-5p is significantly overexpressed in PM_2.5 -EVs and asthmatic plasma; additionally, its level is correlated with PM_2.5 exposure in children with asthma. The combination of EV-packaged let-7i-5p and the traditional clinical biomarker IgE exhibits the best diagnostic performance (area under the curve [AUC] = 0.855, 95% CI = 0.786-0.923). Mechanistically, let-7i-5p is packaged into PM_2.5 -EVs by interacting with ELAVL1 and internalized by both "horizontal" recipient HBE cells and "longitudinal" recipient-sensitive HBSMCs, with subsequent activation of the MAPK signaling pathway via suppression of its target DUSP1. Furthermore, an injection of EV-packaged let-7i-5p into PM_2.5 -treated juvenile mice aggravated asthma symptoms. This comprehensive study deciphered the remodeling of the extracellular environment mediated by the secretion of let-7i-5p-enriched EVs during PM_2.5 -induced asthma attacks and identified plasma EV-packaged let-7i-5p as a novel predictor of childhood asthma.

Does underweight amplify the relationship between short-term particulate matter exposure and blood pressure in children and adolescents: a large cross-sectional study in a metropolis of China

Overweight/obesity modified the effects of ambient particulate matter (PM) exposure on blood pressure (BP). This study aims to assess whether interaction of underweight and short-term PM exposure on BP exists in Chinese children. A cross-sectional analysis including 144,513 children aged 6 to 17 years in 2016 Health Promotion Program for Children and Adolescents of Suzhou, China, was performed. Daily concentrations of inhalable PM (PM₁₀) and fine PM (PM_2.5) were extracted from air monitoring stations close to students' schools. We applied generalized linear mixed-effects models to estimate the interactions. Estimated changes (95% confidence intervals (CIs)) of systolic BP (SBP), diastolic BP (DBP), and odds ratios (ORs) (95% CIs) for prevalence of HBP were calculated. Significant interactions between PM and underweight on BP and prevalence of high BP (HBP) were observed. For example, at lag 6, the ORs (95% CIs) for HBP by each 10 μg/m³ changes of PM_2.5 were 1.066 (1.039, 1.093) and 1.036 (1.028, 1.043) among underweight and normal weight subjects, respectively; these values for PM₁₀ were 1.048 (1.031, 1.065) and 1.025 (1.021, 1.030). At lag 5, the increases of SBP for PM_2.5 were 0.32 (95% CI 0.22, 0.43) mmHg and 0.23 (95% CI 0.29, 0.26) mmHg, while changes of DBP were 0.27 (95% CI 0.18, 0.35) mmHg and 0.19 (95% CI 0.16, 0.21) mmHg among underweight and normal weight subjects, respectively. Stratified analyses demonstrated that these interactions were only obtained in males. Effects of short-term PM exposure on BP and prevalence of HBP are enhanced in underweight children and adolescents.

Short-term effects of ambient particulate matter on blood pressure among children and adolescents:A cross-sectional study in a city of Yangtze River delta, China

Several studies have demonstrated associations between short-term exposure to particulate matter (PM) and blood pressure (BP) among various adults groups, but evidence in children and adolescents is still rare. In 2016, a cross-sectional survey was conducted among 194 104 participants aged 6-17 years in Suzhou, China. Daily concentrations of particulate matters with an aerodynamic diameter of ≤10 μg/m³ (PM₁₀) and aerodynamic diameter ≤2.5 μg/m³ (PM_2.5) on 0-6 days preceding BP examination were collected from nearby air monitoring stations. Using generalized linear mixed-effects models, short-term effects of PM on personal BP were estimated. A 10 μg/m³ increment in the 0-6 day mean of PM_2.5 was significantly associated with elevation of 0.20 mmHg [95% confidence interval (95% CI) 0.16-0.23] in systolic BP (SBP), 0.49 mmHg (95% CI 0.45-0.53) in diastolic BP (DBP), respectively. Similarly, 0.14 mmHg (95% CI 0.12-0.16) higher SBP and 0.32 mmHg (95% CI 0.30-0.34) higher DBP were found for each 10 μg/m³ increase in 0-6 day mean of PM₁₀. More apparent associations were observed in females than in males. Odds ratio (95%CI) of for PM_2.5 exposure at 0-6 d mean was 1.06 (1.03-1.08) in females, while it was 1.01 (0.99-1.03) in males. Participants with young ages, underweight and obesity were also associated with increased susceptibility to PM-induced BP effects. Short-term exposure in PM was significantly associated with elevated BP in children, indicating a need to control PM levels and protect children from PM exposure in China.

Comparison of the accuracy of kriging and IDW interpolations in estimating groundwater arsenic concentrations in Texas

Exposure to arsenic causes many diseases. Most Americans in rural areas use groundwater for drinking, which may contain arsenic above the currently allowable level, 10µg/L. It is cost-effective to estimate groundwater arsenic levels based on data from wells with known arsenic concentrations. We compared the accuracy of several commonly used interpolation methods in estimating arsenic concentrations in >8000 wells in Texas by the leave-one-out-cross-validation technique. Correlation coefficient between measured and estimated arsenic levels was greater with inverse distance weighted (IDW) than kriging Gaussian, kriging spherical or cokriging interpolations when analyzing data from wells in the entire Texas (p<0.0001). Correlation coefficient was significantly lower with cokriging than any other methods (p<0.006) for wells in Texas, east Texas or the Edwards aquifer. Correlation coefficient was significantly greater for wells in southwestern Texas Panhandle than in east Texas, and was higher for wells in Ogallala aquifer than in Edwards aquifer (p<0.0001) regardless of interpolation methods. In regression analysis, the best models are when well depth and/or elevation were entered into the model as covariates regardless of area/aquifer or interpolation methods, and models with IDW are better than kriging in any area/aquifer. In conclusion, the accuracy in estimating groundwater arsenic level depends on both interpolation methods and wells' geographic distributions and characteristics in Texas. Taking well depth and elevation into regression analysis as covariates significantly increases the accuracy in estimating groundwater arsenic level in Texas with IDW in particular.