Inflammatory bowel disease (IBD) is a chronic and relapsing disorder for many people associated with poor health. Although there are some clinical drugs for IBD treatment, the development of effective therapeutics on IBD patients has always been necessary. Here, we show that externalized phosphatidylserine (PS) is observed on the surface of colonic capillaries. Annexin A5 (ANXA5) with high affinity for PS has a good targeting to the colon and effectively alleviates experimental colitis. In contrast, ANXA5 mutant (A5m) lacking the PS-binding ability, has no accumulation in the colon and no therapeutic effects on colitis. Mechanistic investigations indicate that ANXA5 reduces the inflammatory cell infiltration by inhibiting endothelial cell activation dependent on PS-binding ability. With the increasing of PS exposure on activated HUVECs (human umbilical vein endothelial cells), ANXA5 binding induces the internalization of TLR4 via PS-dependent endocytosis. We provide new insights on the molecular mechanism of ANXA5 for its anti-inflammatory effect. Our data suggest that PS-externalization is a potential target of ANXA5 aiming at targeted drug delivery (TDD) for IBD treatment.

Floods caused by heavy rainfall events associated with landfalling tropical cyclones (TCs) represent a major risk for the Yangtze River Delta (YRD) region of China. Accurate extreme precipitation forecasting, at long lead times, is crucial for the improvement of flood prevention and warning. However, accurate prediction of timing, location, and intensity of the heavy rainfall events is a major challenge for the Numerical Weather Prediction (NWP). In this study, high-resolution satellite precipitation products like Global Precipitation Measurement (GPM) are evaluated at the hourly timescale, and the optimal Integrated Multi-satellite Retrievals for GPM (IMERG) precipitation product is selected and applied to directly assimilate into the Weather Research and Forecasting (WRF) model via the four-dimensional variational (4D-Var) method. The TC Jondari and Rumbia events of August 2018 are evaluated to analyze the performance of the WRF model with the 4D-Var method assimilated IMERG precipitation product (DA-IMERG) and the conventional observation (DA-CONV) for real-time heavy rainfall forecasting. The results indicate that (1) IMERG precipitation products were larger and wetter than the observed precipitation values over YRD. By comparison, the performance of “late” run precipitation product (IMERG-L) was the closest to the observation data with lower deviation and higher detection capability; (2) DA-IMERG experiment substantially affected the magnitude of the WRF model primary variables, which changed the precipitation pattern of the TC heavy rain. (3) DA-IMERG experiment further improved the forecast of heavy rainbands and relatively reduced erroneous detection rate than CTL and DA-CONV experiments at the grid scale. Meanwhile, the DA-IMERG experiment has a better fractions skill score (FSS) value (especially in the threshold of 10 mm/h) than DA-CONV for TC Jondari and Rumbia at the spatial scale, while it shows a lower performance than CTL and DA-CONV experiments when the threshold is lower than the 5 mm/h for the TC Rumbia.

Extreme precipitation events and their triggered flood disasters have received increasing attention owing to their severe threats to human lives and socioeconomic development. However, there is still a lack of research on their evolutionary characteristics and driving factors from a three-dimensional (3D) event-based perspective. Here, we developed a 3D automatic recognition algorithm based on the connected component 3D algorithm. This method was applied to investigate the 3D characteristics of 632 flood-causing precipitation (FCP) events in China from 2000 to 2023. The associated flood disasters and their underlying driving factors were further analysed. The FCP events with larger accumulated magnitudes and affected areas are mainly distributed in the center of Southern China (SC) and Northern China (NC), mostly moving eastward with longer distances and lifespans. FCP-induced flood disasters are more severe in the SC and parts of the NC, while a relatively higher proportion of flood disaster losses are concentrated in the southeastern fringe of the Qinghai-Tibetan Plateau (TP) and southwestern China (SWC). In other words, flood disasters caused by FCP in China exhibit the changing characteristics of "high impact-low losses ratio" in SC and NC and "low impact-high losses ratio" in TP and SWC. Notably, despite the increase in 3D characteristics of FCP events over the past two decades, flood disasters have shown a significant reduction, except for the direct economic losses. Driving factor analysis indicates that the combination of precipitation and environmental factors have the greatest explanatory power for most flood disasters in China, while human activities have a prominent impact on the flood disasters in the center of SC and NC. These findings provide new insights into the characteristics of FCP events and their associated flood disasters from a 3D event-based perspective.

Extreme precipitation events and their triggered flood disasters have received increasing attention owing to their severe threats to human lives and socioeconomic development. However, there is still a lack of research on their evolutionary characteristics and driving factors from a three-dimensional (3D) event-based perspective. Here, we developed a 3D automatic recognition algorithm based on the connected component 3D algorithm. This method was applied to investigate the 3D characteristics of 632 flood-causing precipitation (FCP) events in China from 2000 to 2023. The associated flood disasters and their underlying driving factors were further analysed. The FCP events with larger accumulated magnitudes and affected areas are mainly distributed in the center of Southern China (SC) and Northern China (NC), mostly moving eastward with longer distances and lifespans. FCP-induced flood disasters are more severe in the SC and parts of the NC, while a relatively higher proportion of flood disaster losses are concentrated in the southeastern fringe of the Qinghai-Tibetan Plateau (TP) and southwestern China (SWC). In other words, flood disasters caused by FCP in China exhibit the changing characteristics of "high impact-low losses ratio" in SC and NC and "low impact-high losses ratio" in TP and SWC. Notably, despite the increase in 3D characteristics of FCP events over the past two decades, flood disasters have shown a significant reduction, except for the direct economic losses. Driving factor analysis indicates that the combination of precipitation and environmental factors have the greatest explanatory power for most flood disasters in China, while human activities have a prominent impact on the flood disasters in the center of SC and NC. These findings provide new insights into the characteristics of FCP events and their associated flood disasters from a 3D event-based perspective.