Glycitin exerts anticancer effect on human lung cancer cells through induction of apoptosis, cell cycle arrest, and inhibition of PI3K/AKT signal pathway

Purpose: To determine the effect of glycitin on PI3K/AKT signaling, migration, invasion, apoptosis, and cell cycle in A549 lung cancer cells.Methods: 3-[4,5-Dimethylthiazole-2-yl]-2,5-diphenyltetrazolium bromide (MTT) and clonogenic assays were used to determine the proliferation and colony generation potency of A549 cells, respectively, after treatment with glycitin (0 - 120 μM). Apoptosis in A549 cells was measured using DAPI and Annexin V/PI-FITC assays. Cell cycle arrest was assessed byflow cytometry, while the effect of glycitin on migration and invasion of A549 cells was determined by Transwell assay. The effect of glycitin on expressions of proteins associated with PI3K/AKT signaling in A549 cells was measured using western blotting.Results: Glycitin significantly inhibited the proliferation and colony generation potential of A549 cells (p < 0.05). The antiproliferative effects of glycitin on A549 cells were mediated through stimulation of apoptosis and cell cycle arrest at G0/G1-phase. The compound also distorted normal cellular morphology by causing membrane damage and nuclear fragmentation. The proportion of cells in the G0/G1-phase increased after glycitin treatment, when compared to the other two phases, demonstrating cell cycle arrest (p < 0.05). Glycitin suppressed the migration and invasion of A549 cells. However, Western blotting results showed that glycitin down-regulated the expressions of PI3K/AKT signaling proteins in A549 cells (p < 0.05).Conclusion: Glycitin produced significant anticancer effect on A549 cells via enhanced apoptosis, induction of cell cycle arrest, and inhibition of PI3K/AKT signalling. Moreover, it suppressed the migration and invasion of A549 cells. Therefore, glycitin is a potential lead molecule for the development of a therapeutic agent for invasive lung cancer

Modified cotton fabrics for improved ultraviolet protection performance and reactive dyeing property

Reactive quaternary ammonium cationic compound, [2,3-epoxypropyl-1-methy imidazole ammonium chloride (EPMI)] has been synthesized with 1-methylimidazole and epoxy chloropropane to improve the dyeing property of cotton fabrics and the cationic cotton fabrics combined Fe3+ to obtain UV protective property. The dye fixation (F%) of three reactive dyes is found to be 84.5-89.7% on modified cotton fabrics. Ultraviolet protection factor (UPF) value of modified cotton fabric is increased to 137.47 from 7.57 of untreated cotton fabric. The breaking strength of modified cotton fabrics is well retained. The hue (h) of dyed samples before and after modification shows a little change. The UPF of modified cotton fabric shows excellent durability. After 50 laundering cycles, the UPF values decrease to 12.47%. Scanning electron microscopy observations and XRD patterns show that the modified cotton fibres are left nearly undamaged by the modification. The FTIR spectra suggest that the EPMI and Fe3+ are combined on the cotton fibres

PhysarumSpreader: a new bio-Inspired methodology for identifying influential spreaders in complex networks

Identifying influential spreaders in networks, which contributes to optimizing the use of available resources and efficient spreading of information, is of great theoretical significance and practical value. A random-walk-based algorithm LeaderRank has been shown as an effective and efficient method in recognizing leaders in social network, which even outperforms the well-known PageRank method. As LeaderRank is initially developed for binary directed networks, further extensions should be studied in weighted networks. In this paper, a generalized algorithm PhysarumSpreader is proposed by combining LeaderRank with a positive feedback mechanism inspired from an amoeboid organism called Physarum Polycephalum. By taking edge weights into consideration and adding the positive feedback mechanism, PhysarumSpreader is applicable in both directed and undirected networks with weights. By taking two real networks for examples, the effectiveness of the proposed method is demonstrated by comparing with other standard centrality measures

Reasearch on Shared Intelligent Test Paper Generating Algorithm Based on Multi Branches Tree

AbstractThe study first summarizes the characteristics of various intelligent algorithms such as improved genetic algorithm, differential evolution algorithm and ant colony algorithm adopted in test paper generation, and then proposes the parallel evolution of swarm based on ideas of shared intelligent algorithm and dynamic multi branches tree algorithm, so as to improve searching speed and achieve the effect of short-time optimization. During forming optimal individuals, classified training and repeated recognition by virtue of dynamic multi branches tree can not only avoid premature appearance but also get strong convergence. In addition, when the constraints change, the existing knowledge can be inherited. Facts have shown that this algorithm has certain theoretical significance and reference value to the development of intelligent test paper generation algorithm