Ruellia tuberosa L. (RTL) has been used as a folk medicine for curing diabetes mellitus in East Asia decades. This study investigated the effect of RTL on hepatic detoxification enzyme expression in diabetic rats. Male Wistar rats were fed a high fat diet (HFD) and intraperitoneally injected with streptozotocin (STZ) to induce diabetes. Subsequently, rats received oral administrations of 100 or 400 mg kg À1 body weight RTL extract, in either water (RTLW) or ethanol (RTLE), once a day for 4 weeks. The real-time PCR analyses showed that abnormality of hepatic phase I and II detoxification enzyme expression was observed in diabetic rats. However, both RTLW and RTLE significantly normalized the expression of hepatic phase I detoxification enzymes such as CYP 2E1, and expression of phase II detoxification enzymes such as UGT 1A7 and GST M1 in diabetic rats. Furthermore, we found that fasting serum glucose, hemoglobin A1C (HbA1C) and the area under the curve of oral glucose tolerance test (AUC OGTT ) levels were significantly reduced in both RTLW and RTLE treated diabetic rats.Moreover, both RTLW and RTLE significantly increased the activity of hepatic anti-oxidative enzymes such as superoxide dismutase (SOD) in diabetic rats. The present study suggests that RTL may ameliorate abnormal hepatic detoxification function via alleviating hyperglycemia and enhancing hepatic antioxidant capacity in HFD/STZ-induced diabetic rats.

Nonalcoholic fatty liver disease (NAFLD) has been associated with obesity, insulin resistance, type 2 diabetes mellitus (T2DM), and cardiovascular disease (Browning et al., 2004). Defined as the presence of macrovesicular steatosis by more than 5% in liver of individuals without alcohol intake (Loomba & Sanya, 2013), NAFLD develops when the rate of fatty acid uptake and de novo lipogenesis (DNL) exceeds the rate of fatty acid output such as fatty acid oxidation and secretion of very-low-density lipoprotein (VLDL) (Fabbrini, Sullivan, & Klein, 2010). De novo lipogenesis is the main metabolic pathway for converting excess carbohydrate

-This paper proposes a novel environmental monitoring mechanism to integrate recentlyestablished development of an Unmanned Aerial System (UAS) with WSNs for remote monitoring.The high mobility of UASs can solve the limitations associated with using WSNs in hazardous areas. In this paper, the WSN node, the Wireless Environmental Monitoring Station (WEMS), is based onZigBee protocol for long-duration monitoring. Furthermore, to ensure the integrity of collected environmental data, an algorithm is designed in WEMS for verification. Finally, a detailed analysis of packet transmission efficiency based on ranges of flight distance is proposed to examine the effect of environmental monitoring.

Health-related physical fitness has decreased with age; this is od immense concern to adolescents. School-based health intervention programs can be classified as either population-wide or high-risk approach. Although the population-wide and risk-based approaches adopt different healthcare angles, they all need to focus resources on risk evaluation. In this paper, we describe an exploratory application of cluster analysis and the tree model to collaborative evaluation of students' health- related physical fitness from a high school sample in Taiwan (n=742). Cluster analysis show that physical fitness can be divided into relatively good, moderate and poor subgroups. There are significant differences in biochemical measurements among these three groups. For the tree model, we used 2004 school-year students as an experimental group and 2005 school-year students as a validation group. The results indicate that if sit-and-reach is shorter than 33 cm, BMI is >25.46 kg/m2, and 1600 m run/walk is >534 s, the predicted probability for the number of metabolic risk factors ≥2 is 100% and the population is 41, both results are the highest. From the risk-based healthcare viewpoint, the cluster analysis can sort out students' physical fitness data in a short time and then narrow down the scope to recognize the subgroups. A classification tree model specifically shows the discrimination paths between the measurements of physical fitness for metabolic risk and would be helpful for self-management or proper healthcare education targeting different groups. Applying both methods to specific adolescents' health issues could provide different angles in planning health promotion projects.