Early-life noise exposure causes cognitive impairment in a sex-dependent manner by disrupting homeostasis of the microbiota-gut-brain axis.

Epidemiological investigations show that noise exposure in early life is associated with health and cognitive impairment. The gut microbiome established in early life plays a crucial role in modulating developmental processes that subsequently affect brain function and behavior. Here, we examined the impact of early-life exposure to noise on cognitive function in adolescent rats by analyzing the gut microbiome and metabolome to elucidate the underlying mechanisms. Chronic noise exposure during early life led to cognitive deficits, hippocampal injury, and neuroinflammation. Early-life noise exposure showed significant difference on the composition and function of the gut microbiome throughout adolescence, subsequently causing axis-series changes in fecal short-chain fatty acid (SCFA) metabolism and serum metabolome profiles, as well as dysregulation of endothelial tight junction proteins, in both intestine and brain. We also observed sex-dependent effects of microbiota depletion on SCFA-related beneficial bacteria in adolescence. Experiments on microbiota transplantation and SCFA supplementation further confirmed the role of intestinal bacteria and related SCFAs in early-life noise-exposure-induced impairments in cognition, epithelial integrity, and neuroinflammation. Overall, these results highlight the homeostatic imbalance of microbiota-gut-brain axis as an important physiological response toward environmental noise during early life and reveals subtle differences in molecular signaling processes between male and female rats.

Scenario analysis of COVID-19 dynamical variations by different social environmental factors: a case study in Xinjiang.

Background: With the rapid advancement of the One Health approach, the transmission of human infectious diseases is generally related to environmental and animal health. Coronavirus disease (COVID-19) has been largely impacted by environmental factors regionally and globally and has significantly disrupted human society, especially in low-income regions that border many countries. However, few research studies have explored the impact of environmental factors on disease transmission in these regions. Methods: We used the Xinjiang Uygur Autonomous Region as the study area to investigate the impact of environmental factors on COVID-19 variation using a dynamic disease model. Given the special control and prevention strategies against COVID-19 in Xinjiang, the focus was on social and environmental factors, including population mobility, quarantine rates, and return rates. The model performance was evaluated using the statistical metrics of correlation coefficient (CC), normalized absolute error (NAE), root mean square error (RMSE), and distance between the simulation and observation (DISO) indices. Scenario analyses of COVID-19 in Xinjiang encompassed three aspects: different population mobilities, quarantine rates, and return rates. Results: The results suggest that the established dynamic disease model can accurately simulate and predict COVID-19 variations with high accuracy. This model had a CC value of 0.96 and a DISO value of less than 0.35. According to the scenario analysis results, population mobilities have a large impact on COVID-19 variations, with quarantine rates having a stronger impact than return rates. Conclusion: These results provide scientific insight into the control and prevention of COVID-19 in Xinjiang, considering the influence of social and environmental factors on COVID-19 variation. The control and prevention strategies for COVID-19 examined in this study may also be useful for the control of other infectious diseases, especially in low-income regions that are bordered by many countries.