The Effect of Exposure to Neighborhood Violence on Glucocorticoid Receptor Signaling in Lung Tumors.

Despite lower rates and intensity of smoking, Black men experience a higher incidence of lung cancer compared to white men. The racial disparity in lung cancer is particularly pronounced in Chicago, a highly segregated urban city. Neighborhood conditions, particularly social stress, may play a role in lung tumorigenesis. Preliminary studies indicate that Black men residing in neighborhoods with higher rates of violent crime have significantly higher levels of hair cortisol, an indicator of stress response. To examine the relationship between social stress exposure and gene expression in lung tumors, we investigated glucocorticoid receptor (GR) binding in 15 lung tumor samples in relation to GR target gene expression levels and zip code level residential violent crime rates. Spatial transcriptomics and a version of ChIP sequencing known as CUT&RUN were used. Heatmap of genes, pathway analysis, and motif analysis were conducted at the statistical significance of P < 0.05. GR recruitment to chromatin was correlated with zip code level residential violent crime rate and overall GR binding increased with higher violent crime rates. Our findings suggest that exposure to residential violent crime may influence tumor biology via reprogramming GR recruitment. Prioritizing lung cancer screening in neighborhoods with increased social stress, such as high levels of violent crime, may reduce racial disparities in lung cancer. SIGNIFICANCE: Exposure to neighborhood violent crime is correlated with glucocorticoid signaling and lung tumor gene expression changes associated with increased tumor aggressiveness, suggesting social conditions have downstream biophysical consequences that contribute to lung cancer disparities.

Assessment of Iron Biosorption Potential by Live and Dead Biomass of Bacillus subtilis (MN093305) from Aqueous Solution.

Heavy metals polluted aquatic ecosystems and become a global environmental issue due to their toxic effect on all forms of ecosystems and further on all forms of life. Heavy metals are non- degradable and accumulated in different life forms by accumulating in the food chain; this increases the need for the development of a sustainable method for the removal of these metals. Biosorption is an eco-friendly and cost-effective convenient technique of heavy metal bioremediation from the contaminated aquatic ecosystem. The current investigation involves biosorption of iron using Bacillus subtilis strain (MN093305) isolated from Ganga river at different physical parameters with the highest rate of biosorption was 96.64%, 98.91%, 97.88%, and 99.44% at pH 5, 60 min incubation period, 35 °C temperature and 2.5 mg/ml of biomass respectively for dead biomass. Living biomass biosorption rate was 87.32%, 96.74%, 96.94% and 95.02% at pH 7, 72 h, 35 °C and 2.5 mg/ml respectively. Functional groups involved in the biosorption of iron by Bacillus subtilis were fitted to a second-order kinetic model. Langmuir and Freundlich's isotherm are used to evaluate data; both isotherms indicate iron absorption as a favorable process.