Odonnellmcmillan8955

Metals may affect adversely cardiovascular system, but epidemiological evidence on the associations of priority-controlled metals including antimony (Sb), arsenic (As), cadmium, lead, and thallium with children's blood pressure (BP) was scarce and inconsistent. We conducted two panel studies with 3 surveys across 3 seasons among 144 and 142 children aged 4-12 years in Guangzhou and Weinan, respectively. During each seasonal survey, urine samples were collected for 4 consecutive days and BP was measured on the 4th day. We obtained 786 BP values and urinary metals measurements at least once within 4 days, while 773, 596, 612, and 754 urinary metals measurements were effective on the health examination day (Lag 0), and the 1st, 2nd, and 3rd day preceding BP measurement (Lag 1, lag 2 and lag 3), respectively. We used linear mixed-effect models, generalized estimating equations and multiple informant models to assess the associations of individual metal at each lag day and accumulated lag day (4 days averaged, lag 0-3) with BP and hypertension, and Bayesian Kernel Machine Regression to evaluate the relations of metals mixture at lag 0-3 and BP outcomes. We found Sb was positively and consistently related to systolic BP (SBP), mean arterial pressure (MAP), and odds of having hypertension within 4 days, which were the strongest at lag 0 and declined over time. And such relationships at lag 0-3 showed in a dose-response manner. Meanwhile, Sb was the only contributor to the relations of mixture with SBP, MAP, and odds of having hypertension. Also, synergistic interaction between Sb and As was significant. In addition, modification effect of passive smoking status on the association of Sb and SBP was more evident in passive smokers. Accordingly, urinary Sb was consistently and dose-responsively associated with increased BP and hypertension, of which Sb was the major contributor among children.This study aimed to evaluate the impact factors and effectiveness of management policies on the presence of polybrominated diphenyl ethers (PBDEs) in sediment samples in Taiwan from the last 10 years. Twenty-four PBDE congeners were detected in 838 sediment samples collected from 4 stages (2006-2019) in 30 principal rivers, based on the national project for background monitoring of the environmental distribution of chemical substances. The ΣPBDE concentrations in the 4 stages ranged from 30.00 to 147.10 ng/g dw, 6.03-15.30 ng/g dw, 4.99-7.00 ng/g dw, and 1.20-2.10 ng/g dw in the northern, southern, central, and eastern areas, respectively. The concentrations of PBDEs (e.g., penta-BDE and octa-BDE) in sediment samples notably decreased (-6 to -73%) as the Taiwan Environmental Protection Administration implemented policies banning PBDEs (except deca-BDE). The PBDEs levels of the sediment samples collected in the dry season were higher than those collected in the wet season. The levels of ΣPBDEs in sediment samples were affected by season, the amount of general waste present, and nearby PBDE-related factories and e-waste recycling facilities. Reducing the release of PBDEs, especially deca-BDE, through sound waste management and recycling practices is still needed to improve environmental sustainability in Taiwan.Chemically intensive crop production depletes wildlife food resources, hinders animal development, health, survival, and reproduction, and it suppresses wildlife immune systems, facilitating emergence of infectious diseases with excessive mortality rates. Gut microbiota is crucial for wildlife's response to environmental stressors. Its composition and functionality are sensitive to diet changes and environmental pollution associated with modern crop production. In this study we use shotgun metagenomics (median 8,326,092 sequences/sample) to demonstrate that exposure to modern crop production detrimentally affects cecal microbiota of sharp-tailed grouse (Tympanuchus phasianellus 9 exposed, 18 unexposed and greater prairie chickens (T. cupido; 11, 11). Exposure to crop production had greater effect on microbiota richness (t = 6.675, P less then 0.001) and composition (PERMANOVA r2 = 0.212, P = 0.001) than did the host species (t = 4.762, P less then 0.001; r2 = 0.070, P = 0.001) or their interaction (t = 3.449; r2 = 0.072, both P = 0.001), whereas sex and age had no effect. Although microbiota richness was greater in exposed (T. cupido chao1 = 152.8 ± 20.5; T. phasianellus 115.3 ± 17.1) than in unexposed (102.9 ± 15.1 and 101.1 ± 17.2, respectively) birds, some beneficial bacteria dropped out of exposed birds' microbiota or declined and were replaced by potential pathogens. Exposed birds also had higher richness and load of virulome (mean ± standard deviation; T. cupido 24.8 ± 10.0 and 10.1 ± 5.5, respectively; T. phasianellus 13.4 ± 6.8/4.9 ± 2.8) and resistome (T. cupido 46.8 ± 11.7/28.9 ± 10.2, T. phasianellus 38.3 ± 16.7/18.9 ± 14.2) than unexposed birds (T. cupido virulome 14.2 ± 13.5, 4.5 ± 4.2; T. cupido resistome 31.6 ± 20.2 and 13.1 ± 12.0; T. phasianellus virulome 5.2 ± 4.7 and 1.4 ± 1.5; T. phasianellus resistome 13.7 ± 16.1 and 4.0 ± 6.4).China was seriously affected by air pollution in the past decade, especially for particulate matter (PM) and emerging ozone pollution recently. In this study, we systematically examined the spatiotemporal variations of six air pollutants and conducted ozone prediction using machine learning (ML) algorithms in the Beijing-Tianjin-Hebei (BTH) region. The annual-average concentrations of CO, PM10, PM2.5 and SO2 decreased at a rate of 141, 11.0, 6.6 and 5.6 μg/m3/year, while a pattern of initial increase and later decrease was observed for NO2 and O3_8 h. The concentration of SO2, CO and NO2 was higher in Tangshan and Xingtai, while northern BTH region has lower levels of CO, NO2 and PM. Spatial variations of ozone were relatively small in the BTH region. Monthly variations of PM10 displayed an increase in March probably due to wind-blown dusts from Northwest China. A seasonal and diurnal pattern with summer and afternoon peaks was found for ozone, which was contrast with other pollutants. Further ML algorithms such as Random Forest (RF) model and Decision tree (DT) regression showed good ozone prediction performance (daily R2 = 0.83 and 0.73, RMSE = 30.0 and 37.3 μg/m3, respectively; monthly R2 = 0.93 and 0.88, RMSE = 12.1 and 15.8 μg/m3, respectively) based on 10-fold cross-validation. Both RF model and DT regression relied more on the spatial trend as higher temporal prediction performance was achieved. Solar radiation- and temperature-related variables presented high importance at daily level, whereas sea level pressure dominated at monthly level. The spatiotemporal heterogeneity in variable importance was further confirmed using case studies based on RF model. In addition, variable importance was possibly influenced by the emission reductions due to COVID-19 pandemic. Despite its possible weakness to capture ozone extremes, RF model was beneficial and suggested for predicting spatiotemporal variations of ozone in future studies.Micoroplastics (MPs) can be transported through atmospheric circulations, and have caused global attentions due to their potential risk to the environment. In this study, MPs in snowpit samples collected from Demula (DML) glacier in southeast Tibetan Plateau were investigated. The results showed that the average abundance of MPs in snow was 9.55 ± 0.9 items L-1, with dominant shapes of plastic fibers and films. MPs size was dominated by MPs less then 200 μm, with detected minimum size of 48 μm from the DML glacier. MPs in snowpit indicated seasonal variations, showing relatively higher abundance during the monsoon season than that during the non-monsoon season. The chemical composition of MPs and backward air mass trajectory modeling revealed that MPs in DML snowpit mostly originated from the atmospheric long-range transport, suggesting the glacier in southeast Tibetan Plateau can be a temporal sink of atmospheric MPs. The surface structure of the MPs was rough and adhered to a large amount of mineral dust and metallic particles, revealed that these MPs have undergone severe weathering during transportation and after deposition. Based on the MPs data, multi-year average precipitation, and glacier mass balance of DML glacier, the deposition flux of MPs on DML glacier was estimated to be about 7640 ± 720 to 9550 ± 900 items m-2 yr-1 and the export from melting water was about 5.9 ± 1.3 × 109 to 6.6 ± 1.4 × 109 items yr-1, indicating the glacier may be also an important source of MPs to the downstream ecosystems. These results provided the current status of MPs pollution on the Tibetan Plateau glaciers and new data to the study of MPs in typical cryospheric regions.In this report, we describe the characterization of a new monoclonal antibody, named 4H5CR4, against porcine CD9. see more Its use in combination with antibodies to CD4, CD8α, and 2E3 allows to distinguish at least five main CD4+ T cell subsets. Analysis on these subsets of CD45RA, CD27, CD29, CD95, CCR7, and SLA-DR markers depicts a progressive model of CD4+ T cell development. CD4+ 2E3+ CD8α- CD9- cells are the least differentiated population of naïve cells, whereas the CD4+ 2E3- CD8α+CD9+ and CD4+ 2E3- CD8α+ CD9- cells display phenotypic features of central and effector memory T helper cells, respectively. The latter subsets were able to produce IFN-γ after polyclonal activation with PMA/Ionomycin; however, in vitro virus-specific IFN-γ production of PBMCs collected at 38-44 days after pseudorabies virus vaccination was dominated by cells with a CD9+ phenotype. Therefore, CD9 appears to be a useful marker to investigate CD4+ T cell heterogeneity in swine.Climate change is one of the major challenges to the current conservation of biodiversity. Here, by using the brown bear, Ursus arctos, in the southernmost limit of its global distribution as a model species, we assessed the impact of climate change on the species distribution in western Iran. The mountainous forests of Iran are inhabited by small and isolated populations of brown bears that are prone to extinction in the near future. We modeled the potential impact of climate change on brown bear distribution and habitat connectivity by the years 2050 and 2070 under four representative concentration pathways (RCPs) of two general circulation models (GCMs) BCC-CSM1-1 and MRI-CGCM3. Our projections revealed that the current species' range, which encompasses 6749.8 km2 (40.8%) of the landscape, will decline by 10% (2050 RCP2.6, MRI-CGCM3) to 45% (2070 RCP8.5, BCC-CSM1-1). About 1850 km2 (27.4%) of the current range is covered by a network of conservation (CAs) and no-hunting (NHAs) areas which are predicted to decline by 0.64% (2050 RCP2.6, MRI-CGCM3) to 15.56% (2070 RCP8.5, BCC-CSM1-1) due to climate change. The loss of suitable habitats falling within the network of CAs and NHAs is a conservation challenge for brown bears because it may lead to bears moving outside the CAs and NHAs and result in subsequent increases in the levels of bear-human conflict. Thus, re-evaluation of the network of CAs and NHAs, establishing more protected areas in suitable landscapes, and conserving vital linkages between habitat patches under future climate change scenarios are crucial strategies to conserve and manage endangered populations of the brown bear.