Gastrodia elata Blume extract ameliorates exercise-induced fatigue

To investigate the effect of Gastrodia elata Blume (GEB) extract on exercise-induced fatigue recovery, 120 mice were divided at random into four experimental groups (3 GEB administered groups and the normal control group). The normal control group were gavaged with distilled water and the GEB administered groups were gavaged with GEB extract (1000, 500 and 200 mg/kg) for seven consecutive days. The effect of GEB extract on the performance of forced swimming time and blood biochemical parameters related to fatigue blood urea nitrogen (BUN) and blood lactate were measured after forced swimming test (FST). The results indicated that the administration of GEB extract could elevate the endurance of the mice, lower the blood lactate produced and prevent the increase of serum BUN of mice after swimming. GEB extract ameliorates exercise-induced fatigue.Keywords: Gastrodia elata Blume, exercise, fatigueAfrican Journal of Biotechnology Vol. 9(36), pp. 5978-5982, 6 September, 201

Chinese older, middle-aged, and young participants' stereotypes of young adults

Permissions were not obtained for sharing the full text of this article.This study examined stereotype traits of Chinese young adults generated by 180 older, middle-aged, and young Chinese participants. Trait lists were compared across age groups and to Western traits reported in earlier research. Results indicated a considerable overlap between stereotype traits generated by the Chinese participants and those from earlier studies with Western participants (e.g., energetic, ambitious, and reckless). Unique Chinese traits (e.g., filial, hedonistic, and individualistic) associated with young adults were also identified. Whereas the middle-aged and older participants listed an equal number of positive and negative traits, the young participants generated significantly more negative traits than positive ones. Discussion focuses on the impact of modernization and cultural change on perceptions of young adults in the Chinese society

A Mutual Attraction Model for Both Assortative and Disassortative Weighted Networks

In most networks, the connection between a pair of nodes is the result of their mutual affinity and attachment. In this letter, we will propose a Mutual Attraction Model to characterize weighted evolving networks. By introducing the initial attractiveness $A$ and the general mechanism of mutual attraction (controlled by parameter $m$), the model can naturally reproduce scale-free distributions of degree, weight and strength, as found in many real systems. Simulation results are in consistent with theoretical predictions. Interestingly, we also obtain nontrivial clustering coefficient C and tunable degree assortativity r, depending on $m$ and A. Our weighted model appears as the first one that unifies the characterization of both assortative and disassortative weighted networks.Comment: 4 pages, 3 figure