Green space and its types can attenuate the associations of PM2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China.

BACKGROUND: The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces. METHODS: A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations. RESULTS: Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups. CONCLUSION: Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.

Bta-miR-33a affects gene expression and lipid levels in Chinese Holstein mammary epithelial cells.

MicroRNAs (miRNAs) are non-coding single-stranded RNA molecules of about 19-25 nucleotides in length that regulate different biological processes, including lipid metabolism. In this study, we explored the effect of bta-miR-33a on lipid metabolism in bovine mammary epithelial cells (BMECs) of Chinese Holstein for the first time. For this purpose, the plasmids of bta-miR-33a mimic, bta-miR-33a inhibitor and bta-miR-33a negative control were constructed to overexpress or repress bta-miR-33a in BMECs. The effects of plasmid transfection were analysed by examining the mRNA and protein expression levels of ELOVL6 and the intracellular triglycerides. The results showed that bta-miR-33a directly inhibited the expression of ELOVL6 in BMECs; decreased the mRNA levels of ELOVL5, HACD2, CPT1A and MSMO1; and increased the mRNA level of ALOX15. Sequence bta-miR-33a also increased the contents of triglycerides in the cells, presumably as a consequence of these gene expression changes. In summary, the results of the present study suggest that bta-miR-33a regulates lipid metabolism by targeting ELOVL6, which might be a potential molecular marker of milk fat composition.