Objectives: The aim is to identify exposures associated with lung cancer mortality and mortality disparities by race and gender using an exposome database coupled to a graph-theoretical toolchain. Methods: Graph-theoretical algorithms were employed to extract paracliques from correlation graphs using associations between 2162 environmental exposures and lung cancer mortality rates in 2067 counties, with clique-doubling applied to compute an absolute threshold of significance. Factor analysis and multiple linear regressions then were used to analyze differences in exposures associated with lung cancer mortality and mortality disparities by race and gender. Results: While cigarette consumption was highly correlated with rates of lung cancer mortality for both white men and women, previously unidentified novel exposures were more closely associated with lung cancer mortality and mortality disparities for blacks, particularly black women. Conclusions: Exposures beyond smoking moderate lung cancer mortality and mortality disparities by race and gender. Policy Implications: An exposome approach and database coupled with scalable combinatorial analytics provides a powerful new approach for analyzing relationships between multiple environmental exposures, pathways and health outcomes. An assessment of multiple exposures is needed to appropriately translate research findings into environmental public health practice and policy.

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Background: Evidence has emerged which suggests that indoor air pollution resulting from biomass fuel combustion in developing countries may, apart from chronic bronchitis, chronic obstructive pulmonary disease, and lung cancer, also increase the risk of asthma, middle ear infection in children, and tuberculosis, nasopharyngeal and laryngeal cancer, and cataract in adults. Significant findings, although through fewer studies, are being observed recently regarding the association of low birth weight, neonatal mortality with biomass fuel use. Biomass provides 32% of all the primary energy use in India at present, which may bring significant adverse impacts on human health. In this backdrop, the present study was initiated to explore the effect of biomass fuel use on adverse neonatal outcome. Methods: This hospital-based prospective study was carried out during March 2014–December 2015 in Medical College and Hospital, Kolkata, India. This study included 609 subjects and compared adverse neonatal outcome with normal outcome in relation to fuel use characteristics. Results: This study observed that low birth weight, lesser head circumference, neonatal death, less developed genitalia, and need to stay at nursery was more frequent with mothers using biomass fuel. Significantly increased risk of “low birth weight” (risk ratio [RR] 1.78, 95% confidence interval [CI]; 1.11–3.64) and “need of newborn to stay in neonatal care unit” (RR 1.82, 95% CI; 1.08–4.06) was observed in biomass fuel users after adjusting for age of mother, type of residence, age at marriage, and hemoglobin level of the mother at last trimester. Conclusions: This study observed a significant association between biomass fuel use and adverse neonatal outcomes such as low birth weight and stay in neonatal care unit. Observation of the study not only highlighted the need of a proper preventive measure in the form of an intervention device but also pointed out the fact that elevating the level of education among women may suitably contribute in effective control of the problem.

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Context: Fetal alcohol spectrum disorders are a continuum of defects including cognitive and behavioral impairments. Ethanol exposure causes increased apoptosis in striatum of wild-type (WT) mice within 4 h of exposure, an effect that is exacerbated in mice lacking adenylyl cyclases 1/8 (double knockout [DKO]). Aims: To further understand the effects of neonatal ethanol exposure on striatal neurons, the current study focused on the acute expression of postsynaptic density-95 (PSD-95) and synaptophysin. Subjects and Methods: WT and DKO mice were treated with a single dose of saline or 2.5 g/kg ethanol at postnatal days 5–7. At various time points after ethanol exposure, striatal tissues were collected for protein and mRNA analysis. Statistical Analysis: Independent two-way ANOVAs for each time point were performed using SigmaPlot 12. Results: Genetic deletion of AC1/8 alone significantly increased PSD-95 expression at all time points analyzed compared to saline-treated WT controls. Neonatal ethanol increased PSD-95 protein expression in WT mice 2–6 h after exposure, with no effect in DKO mice. By 24 and 48 h, ethanol exposure had no effect on PSD-95 protein expression in WT mice but resulted in a significant reduction in DKO mice. Neither PSD-95 mRNA nor synaptophysin protein expression was affected by ethanol and/or AC1/8 knockout. Conclusions: Acute ethanol exposure in WT mice elicits a postsynaptic effect which may be designed to combat the detrimental effects of ethanol exposure. The lack of this acute increase in PSD-95 protein expression in DKO mice may reflect the increased striatal neurodegeneration reported in these mice 4 h after neonatal ethanol treatment compared to WT mice, further evidenced by the delayed reduction in PSD-95 levels 24–48 h postexposure.

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Background: Overweight and obesity are risk factors for human colorectal cancer. Growing evidence suggests that the gut microbiome affects both obesity and cancer. In this study, we examined how the murine microbiota composition correlated with obesity, intestinal tumorigenesis, glucose regulation, and inflammation. Materials and Methods: We used 16S ribosomal RNA gene analyses of feces and data obtained from a double-mutant mouse model; multiple intestinal neoplasia (Min), mice, which spontaneously develop intestinal tumors, crossed with obesity (ob), mice, which develop obesity, fed 10% or 45% fat diet. Results: We found that diet and genotypes imposed a major impact on the gut microbiota composition. Likewise, we found strong associations of the microbiota composition with obesity, number of small intestinal tumors, and blood glucose levels. Specifically, bacteria related to Clostridium perfringens and Lactobacillus showed strong positive associations with both dietary induced and genetically induced obesity, while Bacteroidales showed strong negative associations. Representatives of Lachnospiraceae and Peptostreptococcaceae only showed significant negative associations with genetically induced obesity and no associations with dietary induced obesity. Conclusions: We found complex associations between the microbiota and genetic background, diet, obesity, glucose levels, inflammation, and intestinal tumorigenesis. This could contribute to the lack of consensus between the results in previous studies regarding correlations of microbiota with obesity and cancer.

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