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Aims: This multicenter, open‐label, randomized study (Registration No. ChiCTR‐OCH‐14004528) aimed to compare the efficacy and effects of oxcarbazepine (OXC) with levetiracetam (LEV) as monotherapies on patient quality of life and mental health for patients with newly diagnosed focal epilepsy from China. Methods: Patients with newly diagnosed focal epilepsy who had experienced 2 or more unprovoked seizures at greater than a 24‐h interval during the previous year were recruited. Participants were randomly assigned to the OXC group or LEV group. Efficacy, safety, quality of life, and mental health were evaluated over 12‐week and 24‐week periods. Results: In total, we recruited 271 newly diagnosed patients from 23 centers. Forty‐four patients were excluded before treatment for reasons. The rate of seizure freedom of OXC was significantly superior to that of LEV at 12 weeks and 24 weeks (p < 0.05). The quality of life (except for the seizure worry subsection) and anxiety scale scores also showed significant differences from before to after treatment in the OXC and LEV groups. Conclusions: OXC monotherapy may be more effective than LEV monotherapy in patients with newly diagnosed focal epilepsy. Both OXC and LEV could improve the quality of life and anxiety state in adult patients with focal epilepsy. [ABSTRACT FROM AUTHOR]

Gynostemma pentaphyllum, a member of family Cucurbitaceae, is a perennial creeping herb used as a traditional medicinal plant in China. In this study, six polymorphic nSSR and four EST‐SSR primers were used to genotype 1,020 individuals in 72 wild populations of G. pentaphyllum. The genetic diversity and population structure were investigated, and ecological niche modeling was performed to reveal the evolution and demographic history of its natural populations. The results show that G. pentaphyllum has a low level of genetic diversity and high level of variation among populations because of pervasive asexual propagation, genetic drift, and long‐term habitat isolation. Results of the Mantel test demonstrate that the genetic distance and geographic distance are significantly correlated among G. pentaphyllum natural populations. The populations can be divided into two clusters on the basis of genetic structure. Asymmetrical patterns of historical gene flow were observed among the clusters. For the contemporary, almost all the bidirectional gene flow of the related pairs was symmetrical with slight differences. Recent bottlenecks were experienced by 34.72% of the studied populations. The geographic range of G. pentaphyllum continues to expand northward and eastward from Hengduan Mountains. The present distribution of G. pentaphyllum is a consequence of its complex evolution. Polyploidy in G. pentaphyllum is inferred to be polygenetic. Finally, G. pentaphyllum is a species in need of protection, so in situ and ex situ measures should be considered in the future. [ABSTRACT FROM AUTHOR]

Background and aims: Research into the variability of fine‐root decomposition and nutrient cycling processes in arid and semiarid ecosystems is highly significant not only for investigations of regional and global carbon and nitrogen cycling but also for offering a theoretical basis for vegetation restoration and reconstruction. In particular, information is limited on fine‐root decomposition processes and nutrient releasing characteristics in the high‐altitude Qinghai Gonghe basin, which has different tree species and variable fine‐root diameters. Materials and methods: Four types of Salicaceae and Caragana shrubs were selected at the Qinghai Gonghe desert ecosystem research station. The litterbag method was adopted to measure decomposition rates of fine‐roots with three diameter classes (1–2 mm, 0.5–1 mm, and 0–0.5 mm). Chemical analysis was performed to determine nutrient (C, N, P, and K) concentrations of fine‐root, and nutrient release rates were compared among fine‐roots with different diameters during different decomposition periods. The differences in mass residual ratio and nutrient release rate among different diameter classes were studied with one‐way ANOVA. Results: Fine‐root decomposition rates were in the order Caragana intermedia > Caragana korshinskii > Salix psammophila > Salix cheilophila. Fine‐root decomposition showed a trend of "fast‐slow‐fast" variation, and decomposition rate increased as the diameter of fine‐roots increased, irrespective of tree species. During the decomposition process, the nutrients C, N, and P of fine‐root were in a release state for the four shrubs with different fine‐root diameters, and the corresponding release rates of Caragana shrubs were higher than those of Salicaceae shrubs. Release rates of nutrients C and N accelerated as fine‐root diameter increased, whereas release rates of nutrients P and K had no observed relation with fine‐root diameter. Fine‐root decomposition ratio was significantly correlated with initial values of N, P, C/N, C/P, and N/P of fine‐root. Fine‐root mass loss ratio was significantly correlated with initial concentration of soil nutrient K, and the correlation was positive for fine‐roots with diameters of 0–0.5 mm and 0.5–1 mm; however, no other significant correlation was observed between fine‐root mass loss ratio and initial soil environmental factors within this study. Conclusions: Our study showed that tree species and fine‐root diameter strongly affected decomposition rates, whereas diameter class exerted little effect on nutrient release rates. [ABSTRACT FROM AUTHOR]

Mappings of the stimuli effects and the input and output estimates of artificial neural networks (ANN) are obtained via combinations of nonlinear functions. This approach offers the advantages of self-learning, self-organization, self-adaptation, and fault tolerance as well as the potential for use in flood forecasting applications. Furthermore, the ANN technology allows the use of multiple variables in both the input and output layers. This capability is very important for flood calculation because the stage, discharge, and other hydrological variables often are functions of many influential variables. Herein, we propose a flood forecasting system with related application, based on ANN. This method offers better performance and efficiency. [ABSTRACT FROM AUTHOR]