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Inflammation is one of the key injury factors for spinal cord injury (SCI). Exosomes (Exos) derived from M2 macrophages have been shown to inhibit inflammation and be beneficial in SCI animal models. However, lacking targetability restricts their application prospects. Considering that chemokine receptors increase dramatically after SCI, viral macrophage inflammatory protein II (vMIP-II) is a broad-spectrum chemokine receptor binding peptide, and lysosomal associated membrane protein 2b (Lamp2b) is the key membrane component of Exos, we speculated that vMIP-II-Lamp2b gene-modified M2 macrophage-derived Exos (vMIP-II-Lamp2b-M2-Exo) not only have anti-inflammatory properties, but also can target the injured area by vMIP-II. In this study, using a murine contusive SCI model, we revealed that vMIP-II-Lamp2b-M2-Exo could target the chemokine receptors which highly expressed in the injured spinal cords, inhibit some key chemokine receptor signaling pathways (such as MAPK and Akt), further inhibit proinflammatory factors (such as IL-1β, IL-6, IL-17, IL-18, TNF-α, and iNOS), and promote anti-inflammatory factors (such as IL-4 and Arg1) productions, and the transformation of microglia/macrophages from M1 into M2. Moreover, the improved histological and functional recoveries were also found. Collectively, our results suggest that vMIP-II-Lamp2b-M2-Exo may provide neuroprotection by targeting the injured spinal cord, inhibiting some chemokine signals, reducing proinflammatory factor production and modulating microglia/macrophage polarization. [Display omitted] • vMIP-II-Lamp2b-M2-Exo can target the injured spinal cord by vMIP-II. • vMIP-II-Lamp2b-M2-Exo can inhibit MAPK and AKT signaling pathways. • vMIP-II-Lamp2b-M2-Exo can reduce proinflammatory factor production. • vMIP-II-Lamp2b-M2-Exo can inhibit M1 microglia/macrophage polarization. • The early administration of vMIP-II-Lamp2b-M2-Exo is a promising strategy for SCI. [ABSTRACT FROM AUTHOR]

Predicting the groundwater level of karst aquifers in North China Coalfield is essential for early warning of mine water hazards and regional water resources management. However, the dynamic changes of strata structure and hydrogeological parameters driven by coal mining activity cause challenges to the process-oriented groundwater model. In order to achieve accurate prediction of groundwater level in large mining areas, this study was the first to use the data-driven Nonlinear Autoregressive with External Input (NARX) model to predict the groundwater level of six karst aquifer observation wells in Pingshuo Mining Area. Three variable input scenarios were set up, solely considering meteorological factors, anthropogenic disturbance factors, and considering both meteorological and anthropogenic disturbance factors. The novel partial mutual information (PMI) screening algorithm was adopted to determine optimized input variables in each scenario. The input and feedback delay coefficients of NARX model were determined by using Seasonal-trend Decomposition Procedure Based on Loess (STL) algorithm and auto- and cross-correlation functions. The results showed that PMI algorithm can effectively screen out the optimal input variables for predicting groundwater level, the NSE coefficients of the PMI-NARX models under the three scenarios were 38.81%, 4.26% and 41.46% higher than those of the corresponding control experiments, respectively. In addition, the prediction performance of the PMI-NARX built on the basis of meteorological factors is poor (NSE <0.63). However, in scenarios which solely use anthropogenic disturbance factors and both use meteorological and anthropogenic disturbance factors, the PMI-NARX coupling models exhibit good prediction performance (NSE and R 2 are all greater than 0.8). Especially under solely considering anthropogenic disturbance factors scenario, the model still exhibited good prediction accuracy with a negligible number of input variables. The results can provide technical and theoretical support for the prediction of groundwater level in other mining areas. [ABSTRACT FROM AUTHOR]