Corilagin alleviates liver fibrosis in zebrafish and mice by repressing IDO1-mediated M2 macrophage repolarization.

BACKGROUND: Liver fibrosis caused by chronic liver injury, eventually develops into liver cirrhosis and hepatocellular carcinoma. Currently, there are no effective drugs to relieve liver fibrosis due to the lack of molecular pathogenesis characteristics. Former research demonstrates that the hepatic immune microenvironment plays a key role in the pathogenesis of liver fibrosis, thus macrophages are important immune cells in the liver. Our previous study has found that IDO1 plays an important role in the liver immune microenvironment. CRG is a gallic acid tannin found in medicinal plants of many ethnicities that protects against inflammation, tumors and chronic liver disease. However, the mechanism of by which CRG mediates the interaction of IDO1 with macrophages during hepatic immune maturation is not clear. PURPOSE: To investigate the regulatory mechanism of CRG in liver fibrosis and the intrinsic relationship between IDO1 and macrophage differentiation. METHODS: Zebrafish, RAW264.7 cells and mice were used in the study. IDO1 overexpression and knockdown cell lines were constructed using lentiviral techniques. RESULTS: We discovered that CRG remarkably reduced the AST and ALT serum levels. Histological examination revealed that CRG ameliorates CCL4-induced liver fibrosis and depressed the expression of α-SMA, Lamimin, Collagen-Ι and fibronectin. Besides, we found that CRG promoted increased MerTK expression on partly macrophages. Interestingly, in vitro, we found that CRG suppressed IDO1 expression and regulated macrophage differentiation by upregulating CD86, CD80 and iNOS, while downregulating CD206, CD163, IL-4 and IL-10 expression. Additionally, we found that CRG could inhibit hepatic stellate cell activation by direct or indirect action. CONCLUSION: Our findings suggest that CRG alleviates liver fibrosis by mediating IDO1-mediated M2 macrophage repolarization.

Improved NLMS-based adaptive denoising method for ECG signals.

BACKGROUND: Traditional least mean square algorithm (LMS) tends to converge faster and thus the larger the steady-state error of the algorithm. OBJECTIVE: In order to solve this issue, an improved adaptive normalized least mean square (NLMS) ECG signal denoising algorithm is proposed through utilizing the NLMS and the least mean square algorithm with added momentum term (MLMS). METHODS: The algorithm firstly performs LMS adaptive filtering on the original ECG signal. Then, the algorithm uses the relative error of the prior error signal and the posterior error signal before and after filtering to adaptively determine the iteration step factor. Finally, the expected error is set to determine whether the denoising meets the expected requirements. This method is applied to the MIT-BIH ECG database established by the Massachusetts Institute of Technology. RESULTS: Experimental results have shown that the proposed algorithm can achieve good denoising for the target signal, and the average signal to noise ratio (SNR) of the proposed method is 17.6016, the RMSE is only 0.0334, and the average smoothness index R is only 0.0325. CONCLUSION: The proposed algorithm effectively removes the original ECG signal noise, and improves the smoothness of the signal the denoising efficiency.

[Real-time forecasting model for monitoring pollutant with differential optical absorption spectroscopy].

For real-time and on-line monitoring DOAS (differential optical absorption spectroscopy) system, a model based on an improved Elman network for monitoring pollutant concentrations was proposed. In order to reduce the systematical complexity, the forecasting factors have been obtained based on the step-wise regression method. The forecasting factors were current concentrations, temperature and relative humidity, and wind speed and wind direction. The dynamic back propagation (BP) algorithm was used for creating training set. The experiment results show that the predicted value follows the real well. So the modified Elman network can meet the demand of DOAS system's real time forecasting.