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BACKGROUND: Evidence linking gaseous air pollution to late-life brain health is mixed. OBJECTIVE: We explored associations between exposure to gaseous pollutants and brain magnetic resonance imaging (MRI) markers among Atherosclerosis Risk in Communities (ARIC) Study participants, with attention to the influence of exposure estimation method and confounding by site. METHODS: We considered data from 1,665 eligible ARIC participants recruited from four US sites in the period 1987-1989 with valid brain MRI data from Visit 5 (2011-2013). We estimated 10-y (2001-2010) mean carbon monoxide (CO), nitrogen dioxide (N[O.sub.2]), nitrogen oxides (N[O.sub.x]), and 8-and 24-h ozone ([O.sub.3]) concentrations at participant addresses, using multiple exposure estimation methods. We estimated site-specific associations between pollutant exposures and brain MRI outcomes (total and regional volumes; presence of microhemorrhages, infarcts, lacunes, and severe white matter hyperintensities), using adjusted linear and logistic regression models. We compared meta-analytically combined site-specific associations to analyses that did not account for site. RESULTS: Within-site exposure distributions varied across exposure estimation methods. Meta-analytic associations were generally not statistically significant regardless of exposure, outcome, or exposure estimation method; point estimates often suggested associations between higher N[O.sub.2] and N[O.sub.x] and smaller temporal lobe, deep gray, hippocampal, frontal lobe, and Alzheimer disease signature region of interest volumes and between higher CO and smaller temporal and frontal lobe volumes. Analyses that did not account for study site more often yielded significant associations and sometimes different direction of associations. DISCUSSION: Patterns of local variation in estimated air pollution concentrations differ by estimation method. Although we did not find strong evidence supporting impact of gaseous pollutants on brain changes detectable by MRI, point estimates suggested associations between higher exposure to CO, N[O.sub.x], and N[O.sub.2] and smaller regional brain volumes. Analyses of air pollution and dementia-related outcomes that do not adjust for location likely underestimate uncertainty and may be susceptible to confounding bias. https://doi.org/10.1289/EHP13906, Introduction Growing evidence links air pollution to late-life cognitive health. Currently, the strongest evidence supports an effect of particulate matter (PM) air pollution. (1) In comparison with PM, fewer studies [...]

Objective To highlight the impact of behavioral and non-behavioral factors on cardiovascular health, disease prevention and management. Methods Cox regression and forest plots were used to assess and demonstrate the relationship between their behavioral and non-behavioral factors and cardiovascular disease (CVD) risk in a study population of 20 745 people at high cardiovascular risk from Zhejing province. Apriori algorithm was used to analyze the correlation between behavioral factors and non-behavioral factors for people with at least one of the greatest risk behavioral factors. Results The incidence of cardiovascular risk in Zhejiang province was positively related to age and inversely related to education level of target population. The higher risk was identified in in male and population in urban citities as compared to female and the people in rural areas; The risk was positively related to smoking intensity and showed a U-shaped association with alcohol intake; The incidence was lowest in those who were mainly standing during routine work; The risk was lower in those who had a clear distinction between busy and idle farming activity in farmers; Men who were engaged in general physical labor and never smoked nor drank high dose of alcohol; Women who never smoked and drank, but did not work and at home were important factors related to the higher cardiovascular risk rate. Conclusions There are a wide range of factors affecting the high-risk population of cardiovascular disease, and there is a certain correlation among these factors.

Background: Many approaches to quantifying air pollution exposures have been developed. However, the impact of choice of approach on air pollution estimates and health-effects associations remains unclear. Objectives: Our objective is to compare particulate matter with aerodynamic diameter [less than or equal to]2.5 [micro]m (P[M.sub.2.5]) concentrations and resulting health effects associations using multiple estimation approaches previously used in epidemiologic analyses. Methods: We assigned annual P[M.sub.2.5] exposure estimates from 1999 to 2004 derived from 11 different approaches to Women's Health Initiative Memory Study (WHIMS) participant addresses within the contiguous US. Approaches included geostatistical interpolation approaches, land-use regression or spatiotemporal models, satellite-derived approaches, air dispersion and chemical transport models, and hybrid models. We used descriptive statistics and plots to assess relative and absolute agreement among exposure estimates and examined the impact of approach on associations between P[M.sub.2.5] and death due to natural causes, cardiovascular disease (CVD) mortality, and incident CVD events, adjusting for individual-level covariates and climate-based region. Results: With a few exceptions, relative agreement of approach-specific P[M.sub.2.5] exposure estimates was high for P[M.sub.2.5] concentrations across the contiguous US. Agreement among approach-specific exposure estimates was stronger near P[M.sub.2.5] monitors, in certain regions of the country, and in 2004 vs. 1999. Collectively, our results suggest but do not quantify lower agreement at local spatial scales for P[M.sub.2.5]. There was no evidence of large differences in health effects associations with P[M.sub.2.5] among estimation approaches in analyses adjusted for climate region. Conclusions: Different estimation approaches produced similar spatial patterns of P[M.sub.2.5] concentrations across the contiguous US and in areas with dense monitoring data, and P[M.sub.2.5]-health effects associations were similar among estimation approaches. P[M.sub.2.5] estimates and P[M.sub.2.5]-health effects associations may differ more in samples drawn from smaller areas or areas without substantial monitoring data, or in analyses with finer adjustment for participant location. Our results can inform decisions about P[M.sub.2.5] estimation approach in epidemiologic studies, as investigators balance concerns about bias, efficiency, and resource allocation. Future work is needed to understand whether these conclusions also apply in the context of other air pollutants of interest. https://doi.org/10.1289/EHP12995, Introduction Routine air pollution monitoring is primarily conducted for regulatory purposes. While existing monitor networks provide useful information on air pollution exposures, they do not necessarily provide the spatial resolution [...]

Diamond color centers have been widely studied in the field of quantum optics. The negatively charged silicon vacancy (SiV−) center exhibits a narrow emission linewidth at the wavelength of 738 nm, a high Debye–Waller factor, and unique spin properties, making it a promising emitter for quantum information technologies, biological imaging, and sensing. In particular, nanodiamond (ND)-based SiV− centers can be heterogeneously integrated with plasmonic and photonic nanostructures and serve as in vivo biomarkers and intracellular thermometers. Out of all methods to produce NDs with SiV− centers, ion implantation offers the unique potential to create controllable numbers of color centers in preselected individual NDs. However, the formation of single color centers in NDs with this technique has not been realized. We report the creation of single SiV− centers featuring stable high-purity single-photon emission through Si implantation into NDs with an average size of ∼20 nm. We observe room temperature emission, with zero-phonon line wavelengths in the range of 730–800 nm and linewidths below 10 nm. Our results offer new opportunities for the controlled production of group-IV diamond color centers with applications in quantum photonics, sensing, and biomedicine.