Molecular hydrogen has been shown to have neuroprotective effects in mouse models of acute neurodegeneration. The effect was suggested to be mediated by its free-radical scavenger properties. However, it has been shown recently that molecular hydrogen alters gene expression and protein phosphorylation. The aim of this study was to test whether chronic ad libitum consumption of molecular hydrogen-enriched electrochemically reduced water (H-ERW) improves the outcome of lipopolysaccharide (LPS)-induced neuroinflammation. Seven days after the initiation of H-ERW treatment, C57Bl/6 mice received a single injection of LPS (0.33 mg/kg i.p.) or an equivalent volume of vehicle. The LPS-induced sickness behaviour was assessed 2 h after the injection, and recovery was assessed by monitoring the spontaneous locomotor activity in the homecage for 72 h after the administration of LPS. The mice were killed in the acute or recovery phase, and the expression of pro- and antiinflammatory cytokines in the hippocampus was assessed by real-time PCR. We found that molecular hydrogen reduces the LPS-induced sickness behaviour and promotes recovery. These effects are associated with a shift towards anti-inflammatory gene expression profile at baseline (downregulation of TNF- α and upregulation of IL-10). In addition, molecular hydrogen increases the amplitude, but shortens the duration and promotes the extinction of neuroinflammation. Consistently, molecular hydrogen modulates the activation and gene expression in a similar fashion in immortalized murine microglia (BV-2 cell line), suggesting that the effects observed in vivo may involve the modulation of microglial activation. Taken together, our data point to the regulation of cytokine expression being an additional critical mechanism underlying the beneficial effects of molecular hydrogen.

To analyze the relationship of different COD concentration, sediment pollutants with hydrodynamic. Taking a polluted river as the research object, the data of flow velocity, water temperature, COD concentration, sediment OM content, sediment TN content and sediment TP content at nine sampling points were analyzed by stepwise regression and SPSS 25 data analysis software. Construct linear regression model of COD concentration Y, river flow velocity X1, water temperature X2, sediment OM content X3, sediment TN content X4, sediment TP content X5. The regression equation Y=106.172-64.304X4 + 0.065X5 with correlation coefficient R=0.954 and determination coefficient R2=0.91 was obtained by stepwise regression method. The results showed that the concentration of COD in water was correlated with the content of nitrogen and phosphorus in river sediments, and negatively correlated with the content of TN and positively correlated with the content of TP. The model can be used to estimate COD load of water body by analyzing the nitrogen and phosphorus content in river sediments.