Evaluation of Anti-Fatigue Activity of Flavonoids from Tartary Buckwheat in Mice

Background: Flavonoids are the major biological activities components of tartary buckwheat which has multifunctional bioactivities. However, there are a limited number of studies on the effect of flavonoids from tartary buckwheat (TBF) on physical fatigue at present. This study aimed to investigate the anti-fatigue activity of TBF in mice. Materials and Methods: The mice were divided into four groups: control (C), low-dose TBF-treated (LFT), middle-dose TBF-treated (MFT) and high-dose TBF-treated (HFT). The treated groups received TBF (100, 200 and 400 mg/kg), while the control group received physiological saline. After 28 days' treatment, the mice performed exhaustive running exercise on the treadmill, along with the measure of exhaustive running times, blood lactic acid (BLA), serum urea nitrogen (SUN), serum creatine kinase (SCK), liver glycogen, superoxide dismutase (SOD), glutathione peroxidase (GPx) and catalase (CAT). Results: TBF prolonged the exhaustive running time of the mice. It sub-served to remove the accumulated products of metabolism by decreasing the levels of BLA and SUN. It ameliorated the muscle damage by decreasing the SCK levels. It improved the metabolic control of exercise and activated the energy metabolism by increasing the liver glycogen contents, as well as improving endogenous cellular antioxidant enzymes in mice by increasing the SOD, GPx and CAT activities. Conclusion: TBF has significant anti‑fatigue activity.Key words: anti-fatigue, flavonoids, tartary buckwheat, exhaustive running exercise, mic

EVALUATION OF ANTI-FATIGUE ACTIVITY OF FLAVONOIDS FROM TARTARY BUCKWHEAT IN MICE

Background: Flavonoids are the major biological activities components of tartary buckwheat which has multifunctional bioactivities. However, there are a limited number of studies on the effect of flavonoids from tartary buckwheat (TBF) on physical fatigue at present. This study aimed to investigate the anti-fatigue activity of TBF in mice. Materials and Methods: The mice were divided into four groups: control (C), low-dose TBF-treated (LFT), middle-dose TBF-treated (MFT) and high-dose TBF-treated (HFT). The treated groups received TBF (100, 200 and 400 mg/kg), while the control group received physiological saline. After 28 days' treatment, the mice performed exhaustive running exercise on the treadmill, along with the measure of exhaustive running times, blood lactic acid (BLA), serum urea nitrogen (SUN), serum creatine kinase (SCK), liver glycogen, superoxide dismutase (SOD), glutathione peroxidase (GPx) and catalase (CAT). Results: TBF prolonged the exhaustive running time of the mice. It sub-served to remove the accumulated products of metabolism by decreasing the levels of BLA and SUN. It ameliorated the muscle damage by decreasing the SCK levels. It improved the metabolic control of exercise and activated the energy metabolism by increasing the liver glycogen contents, as well as improving endogenous cellular antioxidant enzymes in mice by increasing the SOD, GPx and CAT activities. Conclusion: TBF has significant anti‑fatigue activity

Obtaining Human Experience for Intelligent Dredger Control: A Reinforcement Learning Approach

This work presents a reinforcement learning approach for intelligent decision-making of a Cutter Suction Dredger (CSD), which is a special type of vessel for deepening harbors, constructing ports or navigational channels, and reclaiming landfills. Currently, CSDs are usually controlled by human operators, and the production rate is mainly determined by the so-called cutting process (i.e., cutting the underwater soil into fragments). Long-term manual operation is likely to cause driving fatigue, resulting in operational accidents and inefficiencies. To reduce the labor intensity of the operator, we seek an intelligent controller the can manipulate the cutting process to replace human operators. To this end, our proposed reinforcement learning approach consists of two parts. In the first part, we employ a neural network model to construct a virtual environment based on the historical dredging data. In the second part, we develop a reinforcement learning model that can lean the optimal control policy by interacting with the virtual environment to obtain human experience. The results show that the proposed learning approach can successfully imitate the dredging behavior of an experienced human operator. Moreover, the learning approach can outperform the operator in a way that can make quick responses to the change in uncertain environments

Profiling, clinicopathological correlation and functional validation of specific long non-coding RNAs for hepatocellular carcinoma

Abstract Background Hepatocellular carcinoma (HCC) is one of the most prevalent and aggressive malignancies worldwide. Studies seeking to advance the overall understanding of lncRNA profiling in HCC remain rare. Methods The transcriptomic profiling of 12 HCC tissues and paired adjacent normal tissues was determined using high-throughput RNA sequencing. Fifty differentially expressed mRNAs (DEGs) and lncRNAs (DELs) were validated in 21 paired HCC tissues via quantitative real-time PCR. The correlation between the expression of DELs and various clinicopathological characteristics was analyzed using Student’s t-test or linear regression. Co-expression networks between DEGs and DELs were constructed through Pearson correlation co-efficient and enrichment analysis. Validation of DELs’ functions including proliferation and migration was performed via loss-of-function RNAi assays. Results In this study, we identified 439 DEGs and 214 DELs, respectively, in HCC. Furthermore, we revealed that multiple DELs, including NONHSAT003823, NONHSAT056213, NONHSAT015386 and especially NONHSAT122051, were remarkably correlated with tumor cell differentiation, portal vein tumor thrombosis, and serum or tissue alpha fetoprotein levels. In addition, the co-expression network analysis between DEGs and DELs showed that DELs were involved with metabolic, cell cycle, chemical carcinogenesis, and complement and coagulation cascade-related pathways. The silencing of the endogenous level of NONHSAT122051 or NONHSAT003826 could significantly attenuate the mobility of both SK-HEP-1 and SMMC-7721 HCC cells. Conclusion These findings not only add knowledge to the understanding of genome-wide transcriptional evaluation of HCC but also provide promising targets for the future diagnosis and treatment of HCC