Carbon Nitride-Based siRNA Vectors with Self-Produced O2 Effects for Targeting Combination Therapy of Liver Fibrosis via HIF-1α-Mediated TGF-ß1/Smad Pathway.

Hypoxia is an important feature, which can upregulate the hypoxia-inducible factor-1α (HIF-1α) expression and promote the activation of hepatic stellate cells (HSCs), leading to liver fibrosis. Currently, effective treatment for liver fibrosis is extremely lacking. Herein, a safe and effective method is established to downregulate the expression of HIF-1α in HSCs via targeted delivery of VA-PEG-modified CNs-based nanosheets-encapsulated (VA-PEG-CN@GQDs) HIF-1α small interfering RNA (HIF-1α-siRNA). Due to the presence of lipase in the liver, the reversible release of siRNA can be promoted to complete the transfection process. Simultaneously, VA-PEG-CN@GQD nanosheets enable trigger the water splitting process to produce O2 under near-infrared (NIR) irradiation, thereby improving the hypoxic environment of the liver fibrosis site and maximizing the downregulation of HIF-1α expression to improve the therapeutic effect, as demonstrated in liver fibrosis mice. Such combination therapy can inhibit the activation of HSCs via HIF-1α-mediated TGF-ß1/Smad pathway, achieving outstanding therapeutic effects in liver fibrosis mice. In conclusion, this study proposes a novel strategy for the treatment of liver fibrosis by regulating the hypoxic environment and the expression of HIF-1α at lesion site.

Analyzing the effects of public interventions on reducing public gatherings in China during the COVID-19 epidemic via mobile terminals positioning data.

At the beginning of 2020, the novel coronavirus disease (COVID-19) became an outbreak in China. On January 23, China raised its national public health response to the highest level. As part of the emergency response, a series of public social distancing interventions were implemented to reduce the transmission rate of COVID-19. In this article, we explored the feasibility of using mobile terminal positioning data to study the impact of some nonpharmaceutical public health interventions implemented by China. First, this article introduced a hybrid method for measuring the number of people in public places based on anonymized mobile terminal positioning data. Additionally, the difference-in-difference (DID) model was used to estimate the effect of the interventions on reducing public gatherings in different provinces and during different stages. The data-driven experimental results showed that the interventions that China implemented reduced the number of people in public places by approximately 60% between January 24 and February 28. Among the 31 provinces in the Chinese mainland, some provinces, such as Tianjin and Chongqing, were more affected by the interventions, while other provinces, such as Gansu, were less affected. In terms of the stages, the phase with the greatest intervention effect was from February 3 to 14, during which the number of daily confirmed cases in China showed a turning point. In conclusion, the interventions significantly reduced public gatherings, and the effects of interventions varied with provinces and time.