Astragaloside IV exerts anti-inflammatory role in endometriosis by downregulating TLR4/NF-κB pathway

Purpose: To investigate the effect of astragaloside IV administration on the inflammatory response in endometriosis and the underlying mechanism of action. Methods: Mice were divided into two groups: endometriosis (EMs) mice and control mice (n = 12). EMs induction in mice was achieved by transplantation of mouse uterine tissue. The same procedure was performed in control mice except that a separate suture was inserted instead of endometrial tissue. After 5 weeks, EMs mice were treated with or without astragaloside IV (AIV). The tissue lesions in EMs and control mice were stained with hematoxylin and eosin staining. The activation of toll-like receptor 4 (TLR4) and nuclear factor-κB (NF-κB) p65 signaling was evaluated by western blot, while expression of inflammatory cytokines was evaluated by quantitative real-time-polymerase chain reaction (qRT-PCR), and enzyme-linked immunosorbent assay (ELISA). Results: Astragaloside IV repressed the inflammation of murine Ems lesions, and also dampened the activation of TLR4/NF-κB signaling in vivo and vitro (p < 0.01 and p < 0.001, respectively). In addition, the expression levels of inflammatory cytokines (IL-1β, IL-6, Ccl-2, and TNF-α) decreased following AIV treatment in vivo. Conclusion: The results indicate that TLR4/NF-κB signaling pathways are closely related to the inhibition of Ems inflammation by astragaloside IV. Thus, astragaloside IV may be a novel drug for the prevention and treatment of endometrioses

Managing urban development could halve nitrogen pollution in China

Halving nitrogen pollution is crucial for achieving Sustainable Development Goals (SDGs). However, how to reduce nitrogen pollution from multiple sources remains challenging. Here we show that reactive nitrogen (Nr) pollution could be roughly halved by managed urban development in China by 2050, with NH3, NOx and N2O atmospheric emissions declining by 44%, 30% and 33%, respectively, and Nr to water bodies by 53%. While rural-urban migration increases point-source nitrogen emissions in metropolitan areas, it promotes large-scale farming, reducing rural sewage and agricultural non-point-source pollution, potentially improving national air and water quality. An investment of approximately US$61 billion in waste treatment, land consolidation, and livestock relocation yields an overall benefit of US$ 245 billion. This underscores the feasibility and cost-effectiveness of halving Nr pollution through urbanization, contributing significantly to SDG1 (No poverty), SDG2 (Zero hunger), SDG6 (Clean water), SDG12 (Responsible consumption and production), SDG14 (Climate Action), and so on

Knockdown of ARHGAP30 inhibits ovarian cancer cell proliferation, migration, and invasiveness by suppressing the PI3K/AKT/mTOR signaling pathway

The mortality and morbidity rates of ovarian cancer (OC) are high, but the underlying mechanisms of OC have not been characterized. In this study, we determined the role of Rho GTPase Activating Protein 30 (ARHGAP30) in OC progression. We measured ARHGAP30 abundance in OC tissue samples and cells using immunohistochemistry (IHC) and RT-qPCR. EdU, transwell, and annexin V/PI apoptosis assays were used to evaluate proliferation, invasiveness, and apoptosis of OC cells, respectively. The results showed that ARHGAP30 was overexpressed in OC tissue samples and cells. Inhibition of ARHGAP30 suppressed growth and metastasis of OC cells, and enhanced apoptosis. Knockdown of ARHGAP30 in OC cells significantly inhibited the PI3K/AKT/mTOR pathway. Treatment with the PI3K/AKT/mTOR pathway inhibitor buparlisib simulated the effects of ARHGAP30 knockdown on growth, invasiveness, and apoptosis of OC cells. Following buparlisib treatment, the expression levels of p-PI3K, p-AKT, and p-mTOR were significantly decreased. Furthermore, buparlisib inhibited the effects of ARHGAP30 upregulation on OC cell growth and invasiveness. In conclusion, ARHGAP30 regulated the PI3K/AKT/mTOR pathway to promote progression of OC

Spatially Explicit Reconstruction of Cropland Using the Random Forest: A Case Study of the Tuojiang River Basin, China from 1911 to 2010

A long-term, high-resolution cropland dataset plays an essential part in accurately and systematically understanding the mechanisms that drive cropland change and its effect on biogeochemical processes. However, current widely used spatially explicit cropland databases are developed according to a simple downscaling model and are associated with low resolution. By combining historical county-level cropland archive data with natural and anthropogenic variables, we developed a random forest model to spatialize the cropland distribution in the Tuojiang River Basin (TRB) during 1911–2010, using a resolution of 30 m. The reconstruction results showed that the cropland in the TRB increased from 1.13 × 104 km2 in 1911 to 1.81 × 104 km2. In comparison with satellite-based data for 1980, the reconstructed dataset approximated the remotely sensed cropland distribution. Our cropland map could capture cropland distribution details better than three widely used public cropland datasets, due to its high spatial heterogeneity and improved spatial resolution. The most critical factors driving the distribution of TRB cropland include nearby-cropland, elevation, and climatic conditions. This newly reconstructed cropland dataset can be used for long-term, accurate regional ecological simulation, and future policymaking. This novel reconstruction approach has the potential to be applied to other land use and cover types via its flexible framework and modifiable parameters

Spatially Explicit Reconstruction of Cropland Using the Random Forest: A Case Study of the Tuojiang River Basin, China from 1911 to 2010

A long-term, high-resolution cropland dataset plays an essential part in accurately and systematically understanding the mechanisms that drive cropland change and its effect on biogeochemical processes. However, current widely used spatially explicit cropland databases are developed according to a simple downscaling model and are associated with low resolution. By combining historical county-level cropland archive data with natural and anthropogenic variables, we developed a random forest model to spatialize the cropland distribution in the Tuojiang River Basin (TRB) during 1911–2010, using a resolution of 30 m. The reconstruction results showed that the cropland in the TRB increased from 1.13 × 104 km2 in 1911 to 1.81 × 104 km2. In comparison with satellite-based data for 1980, the reconstructed dataset approximated the remotely sensed cropland distribution. Our cropland map could capture cropland distribution details better than three widely used public cropland datasets, due to its high spatial heterogeneity and improved spatial resolution. The most critical factors driving the distribution of TRB cropland include nearby-cropland, elevation, and climatic conditions. This newly reconstructed cropland dataset can be used for long-term, accurate regional ecological simulation, and future policymaking. This novel reconstruction approach has the potential to be applied to other land use and cover types via its flexible framework and modifiable parameters