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Objective Xindening oral liquid (Xin) is a widely used traditional Chinese medicine for the treatment of chronic heart failure (CHF). However, the exact mechanisms related to its therapeutic effects against CHF remain unclear. In the present study, we investigate the effects of Xin on cardiac function in CHF rats and the possible mechanisms involved. Methods Transverse aortic constriction (TAC) was conducted to induce a CHF rat model in this study. Sixty male Wistar rats were randomly assigned to six groups 28 days after TAC: sham; CHF model; Xin at concentrations of 5 ml/kg, 10 mL/kg, and 20 mL/kg; and QiLi 0.6 g/kg. After four weeks, the rats were treated with Xin (5, 10, or 20 mL/kg/d) for six weeks consecutively. At the end of the study, the cardiac function, heart weight index (HWI) and left ventricular mass index (LVMI), serum level of LDH, B-type natriuretic peptide (BNP), cTnI and CK-MB, and collagen volume fraction were studied. The expression of transforming growth factor-s1 (TGF-s1), drosophila mothers against decapentaplegic protein 3 (Smad3), and p38 mitogen activated protein kinase (p38 MAPK) were detected. Results The results showed that Xin treatment significantly improved cardiac function but decreased the serum level of LDH, BNP, cTnI, and CKMB of CHF rats. In addition, it reduced the HWI, LVMI, and collagen volume fraction compared with the model group. Xin treatment significantly improved cardiac function and attenuated cardiac fibrosis by suppressing the p38 MAPK and TGF-s1/Smad3 signaling pathway in CHF rats. Conclusion These results suggested that Xin might be a promising complementary treatment for CHF. More detailed experimental studies will be carried out in our subsequent research.

This paper analyzes the existing decision tree classification algorithms and finds that these algorithms based on variable precision rough set VPRS have better classification accuracy and can tolerate the noise data. But when constructing decision tree based on variable precision rough set, these algorithms have the following shortcomings: the choice of attribute is difficult and the decision tree classification accuracy is not high. Therefore, this paper proposes a new variable precision rough set based decision tree algorithm IVPRSDT. This algorithm uses a new standard of attribute selection which considers comprehensively the classification accuracy and number of attribute values, that is, weighted roughness and complexity. At the same time support and confidence are introduced in the conditions of the corresponding node to stop splitting, and they can improve the algorithm's generalization ability. To reduce the impact of noise data and missing values, IVPRSDT uses the label predicted method based on match. The comparing experiments on twelve different data sets from the UCI Machine Learning Repository show that IVPRSDT can effectively improve the classification accuracy.

Purpose: To investigate the effects of Kangshen oral liquid (KSOL) on gentamicin sulfate (GS)-induced acute kidney injury (AKI) in rats. Methods: The rats were randomly divided into seven groups and treated with normal saline (NS), GS, furosemide, uremic clearance granule, or one of three different doses of KSOL. Several AKI-related indices were monitored, including renal index (RI), urine protein (UP) level, B-N-acetyl-glucosaminidase (NAG) activity in the urine, serum creatinine (SCr) level, blood urea nitrogen (BUN) level in the serum, malondialdehyde (MDA) level, and superoxide dismutase (SOD) activity in the kidney tissue. Histopathological changes in the kidney tissue of each group were monitored using light microscopy. Results: After treatment with KSOL (20, 10, or 5 mL/kg), the RI, activity of NAG and levels of UP, SCr, BUN, and MDA were significantly decreased by 6.66 - 41.47 %, and the activity of SOD was significantly increased by 15.85 - 20.27 %, compared with the GS group (p < 0.05 or 0.01). The histopathological studies showed that KSOL notably improved GS-induced atrophy of the glomeruli, lymphocytic infiltration in the interstitium of the cortex, protein deposits in the collecting tubules, and hyperemia of the renal interstitium. Conclusion: KSOL improves GS-induced AKI at biochemical and histopathological levels, and thus has a potential to be developed into a therapeutic drug for AKI. Keywords: Kangshen oral liquid, Gentamicin, Acute kidney injury, Furosemide, Uremic clearance granule, Biochemical parameters

This paper analyzes the existing decision tree classification algorithms and finds that these algorithms based on variable precision rough set (VPRS) have better classification accuracies and can tolerate the noise data. But when constructing decision tree based on variable precision rough set, these algorithms have the following shortcomings: the choice of attribute is difficult and the decision tree classification accuracy is not high. Therefore, this paper proposes a new variable precision rough set based decision tree algorithm (IVPRSDT). This algorithm uses a new standard of attribute selection which considers comprehensively the classification accuracy and number of attribute values, that is, weighted roughness and complexity. At the same time support and confidence are introduced in the conditions of the corresponding node to stop splitting, and they can improve the algorithm's generalization ability. To reduce the impact of noise data and missing values, IVPRSDT uses the label predicted method based on match. The comparing experiments on twelve different data sets from the UCI Machine Learning Repository show that IVPRSDT can effectively improve the classification accuracy.