Chen Shanguang

The memory enhancement effect of Kai Xin San on cognitive deficit induced by simulated weightlessness in rats.

ETHNOPHARMACOLOGICAL RELEVANCE It is vital for astronauts to develop effective countermeasures to prevent their decline of cognitive performance in microgravity to make space-flight missions successful. The traditional Chinese herbal formula Kai Xin San (KXS) has been used to treat amnesia for thousands years. It is a traditional complex prescription comprising of ginseng (Panax ginseng C. A. Meyer), hoelen (Poria cocos (Schw.) Wolf), polygala (Polygala tenaifolia Willd), and acorus (Acorus tatarinowii Schott). Previous study showed KXS could improve CMS-induced memory impairment in rats. MATERIAL AND METHODS In this paper, a unique environmental factor-microgravity (weightlessness) was simulated as hindlimb suspension (HLS) by tail in rats for two weeks as the HLS animal model. The KXS at the doses of 0.3 or 0.6g/kg p.o. daily was administrated to HLS rats for two weeks at the same time of HLS, the memory behavior tests were investigated with Morris water maze (MWM) and Shuttle Box (SB) test. The levels of ROS, 8-OHdG and 3-nitrotyrosine (3-NT) in the serum, and AChE and ChAT activity in the brain of rats were determined by ELISA or biochemical analysis. RESULTS After HLS for two weeks, the escape latency and the swimming distance were significantly increased in the MWM test in rats in the HLS group, compared with control group. The percent of swimming distance in target quadrant and the number of target crossing was significantly decreased in rats in the HLS group compared with the control group. Performance in the SB test showed, the numbers and the distance of active avoidance was decreased from day 4 to day 7, the time spent in electric area was increased in rats in the HLS group compared with the control group. Administration of KXS 0.3 or 0.6g/kg to the HLS rats for two weeks significantly reduced the escape latency and the swimming distance, increased the percentage of swimming distance in target quadrant and the number of target crossings (P<0.01, compared with the HLS group) in the MWM test. Similar treatment with KXS increased the numbers and the distance of active avoidance (P<0.01, compared with the HLS group) and reduced the time spent in electric area after training 3 days in the SB test (P<0.01, compared with the HLS group). The HLS induced the increase of the ROS, 8-OHdG and 3-NT in the serum of rats, but has little influence on the AChE, ChAT activity in the brain. Only the AChE activity in the cortex and the ChAT activity in the hippocampus had some changes in rats in the HLS model group. After administration of KXS 0.6g/kg for two weeks, the abnormal levels of ROS, 8-OHdG, 3-NT were found reversed in the serum of rats (P<0.05, compared with HLS model group). And KXS 0.3g/kg was found reversed the increased AChE activity in the cortex. CONCLUSIONS Experimental results from this study show that KXS may improve memory deficiency induced by HLS, its mechanisms are major related to antioxidant activities, rather than the central cholinergic system.

Comparison of the Prognostic Utility of the Diverse Molecular Data among lncRNA, DNA Methylation, microRNA, and mRNA across Five Human Cancers.

Introduction Advances in high-throughput technologies have generated diverse informative molecular markers for cancer outcome prediction. Long non-coding RNA (lncRNA) and DNA methylation as new classes of promising markers are emerging as key molecules in human cancers; however, the prognostic utility of such diverse molecular data remains to be explored. Materials and Methods We proposed a computational pipeline (IDFO) to predict patient survival by identifying prognosis-related biomarkers using multi-type molecular data (mRNA, microRNA, DNA methylation, and lncRNA) from 3198 samples of five cancer types. We assessed the predictive performance of both single molecular data and integrated multi-type molecular data in patient survival stratification, and compared their relative importance in each type of cancer, respectively. Survival analysis using multivariate Cox regression was performed to investigate the impact of the IDFO-identified markers and traditional variables on clinical outcome. Results Using the IDFO approach, we obtained good predictive performance of the molecular datasets (bootstrap accuracy: 0.71–0.97) in five cancer types. Impressively, lncRNA was identified as the best prognostic predictor in the validated cohorts of four cancer types, followed by DNA methylation, mRNA, and then microRNA. We found the incorporating of multi-type molecular data showed similar predictive power to single-type molecular data, but with the exception of the lncRNA + DNA methylation combinations in two cancers. Survival analysis of proportional hazard models confirmed a high robustness for lncRNA and DNA methylation as prognosis factors independent of traditional clinical variables. Conclusion Our study provides insight into systematically understanding the prognostic performance of diverse molecular data in both single and aggregate patterns, which may have specific reference to subsequent related studies.