The induction of apoptosis by azadirachtin, a well-known botanical tetranortriterpenoid isolated from the neem tree (Azadirachta indica A. Juss) and other members of the Meliaceae, was investigated in Spodoptera frugiperda cultured cell line (Sf9). Morphological changes in Sf9 cells treated by various concentrations of azadirachtin were observed at different times under light microscopy. Morphological and biochemical analysis indicated that Sf9 cells treated by 1.5 μg/mL azadirachtin showed typical morphological changes, which were indicative of apoptosis and a clear DNA ladder. The flow cytometry analysis showed the apoptosis rate reached a maximum value of 32.66% at 24 h with 1.5 μg/mL azadirachtin in Sf9 cells. The inhibition of Sf9 cell proliferation suggested that the effect of azadirachtin was dose dependent and the EC50 at 48 and 72 h was 2.727 × 10(-6) and 6.348 × 10(-9) μg/mL, respectively. The treatment of azadirachtin in Sf9 cells could significantly increase the activity of Sf caspase-1, but showed no effect on the activity of Topo I, suggesting that the apoptosis induced by azadirachtinin Sf9 cells is through caspase-dependent pathway. These results provided not only a series of morphological, biochemical, and toxicological comprehensive evidences for induction of apoptosis by azadirachtin, but also a reference model for screening insect cell apoptosis inducers from natural compounds.

Learning of the information diffusion model is a fundamental problem in the study of information diffusion in social networks. Existing approaches learn the diffusion models from events in social networks. However, events in social networks may have different underlying reasons. Some of them may be caused by the social influence inside the network, while others may reflect external trends in the "real world". Most existing work on the learning of diffusion models does not distinguish the events caused by the social influence from those caused by external trends. In this paper, we extract social events from data streams in social networks, and then use the extracted social events to improve the learning of information diffusion models. We propose a LADP (Latent Action Diffusion Path) model to incorporate the information diffusion model with the model of external trends, and then design an EM-based algorithm to infer the diffusion probabilities, the external trends and the sources of events efficiently.

In the social network research, the studies on social influence maximization and entity similarity are two important and orthogonal tasks. On homogeneous networks, social influence maximization research tries to identify an initial influential set that maximizes the spread of the information, while similarity studies focus on designing meaningful ways to quantify entities' similarities. When heterogeneous networks are becoming ubiquitous and entities of different types are related to each other, we observe the possibility of merging the two directions together to improve the performance for both of them. In fact, we found that influence values among one type of nodes and similarity scores among the other type of nodes reinforce each other towards better and more meaningful results.Therefore, we introduce a framework that computes social influence for one type of nodes and simultaneously measures similarity of the other type of nodes in a heterogeneous network. First, we decouple the target heterogeneous network (or we call it Influence Similarity (IS) network) into three different parts: Influence network, Similarity network and information tunnels (IT) between them. Through IT, we exchange the influence scores and the similarity scores to calculate more precise similarity and influence scores in order to improve both of their qualities. The experiment results on real world data shows that our framework enables influence maximization framework to identify more influential seeds in Influence network and similarity measures to produce more meaningful similarity scores in Similarity network simultaneously.

To explore the related factors on the clinical pregnancy outcome in intrauterine insemination, a retrospective study was conducted on the clinical data of 580 cycles for 301 infertile couples who were treated with intrauterine insemination. The female age, male age, duration of infertility, treatment protocols, endometrial thickness and sperm parameters were compared between pregnant group and non-pregnant group. The results showed that there were statistical differences in female age, duration of infertility and endometrial thickness between the two groups. The pregnancy rate was 19.34% in Group A (female age ≤ 30 y) compared with 10.91% in Group B (female age > 30 y). The pregnancy rate was 18.44% when the duration of infertility ≤ 2 years, which was higher than another group 10.73% when the duration of infertility > 2 years. Group analysis according to endometrial thickness (Group1: < 8 mm; Group 2: ≥ 8 mm and ≤ 12 mm; Group 3: > 12 mm) demonstrated significant differences in clinical pregnancy rate (7.41%, 18.00% and 11.48% respectively). For those infertile female without ovulation failure, the higher clinical pregnancy rates were observed in patients undergoing intrauterine insemination in natural cycle 16.12% when compared with the patients in ovarian stimulated cycles 10.48%. Thus, we demonstrate that the pregnancy rate is related with female age, duration of infertility and endometrial thickness. The ovarian stimulated cycle couldn’t improve the pregnancy outcome for those women without ovulation disorder in intrauterine insemination.

The failure modes of ZnO nanowires (NWs) with hexagonal cross section subjected to a uniaxial load are systematically investigated by using molecular dynamics (MD) simulations and two theoretical models considering the surface effect. Our results show that two different failure modes of the phase transition and buckling are triggered when the NWs are under uniaxial compression along the [0001] direction, in which the transformation between the two modes is related to the slenderness ratios of the NWs. Such slenderness-ratio-dependent mode transformation is mainly attributed to the competition between the critical stresses of phase transition and buckling. The Euler and Timoshenko models considering surface effect are further proposed to derive the critical slenderness for such mode transformation. The obtained analytical threshold values agree well with those of present MD simulations. Our results should be of great help for shedding some light on the design and application of functional devices based on ZnO NWs.