Epithelial-Mesenchymal Transition and its Regulation in Tumor Metastasis

Epithelial-mesenchymal transition (EMT) plays a key role in cancer metastasis. This process is a complex, multi-functional, and tightly regulated developmental program. EMT has been extensively investigated, but the molecular regulation of its signaling pathway is highly complex. In this study, the different elements of EMT cascades that could be targeted were determined. Difficulties in translating the preclinical findings in routine clinic were also distinguished. Future research will provide insights into the activation and regulation of various EMT programs in different tumor types and at distinct stages of tumor development. These results will likely facilitate the development of early detection strategies and improve the therapeutic targeting of malignant solid tumors

Efficient callus induction and indirect plant regeneration from various tissues of Jatropha curcas

The Jatropha curcas is considered as an important energy plant due to the fact that its seed contains high oil content. Nowadays focus is being placed on J. curcas callus induction and plant regeneration. In this study, explants epicotyl, hypocotyl, petiole and cotyledon of 8-day-old seedlings of J. curcas were utilized for callus induction on media supplied with 1 mg/L 2,4-dichlorophenoxyacetic acid (2,4-D), naphthyl acetic acid (NAA) or indolebutyric acid (IBA) and 0.1 mg/L kinetin (Kin), and the results demonstrated that the combination of 1 mg/L NAA and 0.1 mg/L Kin was the best medium for callus induction and growth. In addition, induced calli were transferred to regeneration medium containing different combination of auxins and cytokinins, and the data showed that the medium containing 1 mg/L thidiazuron (TDZ) and 1 mg/L Kin combined with 0.1 mg/L IBA was propitious to plant regeneration compared with other combinations.Keywords: Callus induction, indolebutyric acid, Jatropha curcas, kinetin, naphthyl acetic acid, plant regeneration, thidiazuro

Antitumor Effect of Natural Product Molecules against Lung Cancer

Lung cancer treatment remains difficult because of multidrug resistance and adverse effects, and natural product molecules show powerful activity in lung cancer with few side effects. The molecular targets and efficacy of natural product molecules remain unclear. We described the molecular regulation of natural product molecules with antitumor activities, the antilung cancer activities and the clinical trials for lung cancer treatment of natural product molecules. The results support the updated systemic information on the use of natural product molecules to prevent cancer progression and their constituents for lung cancer treatment

The Improvement of Chord Protocol about Structured P2P System

Chord protocol is one of the most classical protocols in structured P2P system, with the good effect, reliability, high query efficiency, and many other advantages. However, Chord agreement remains two main shortcomings the one that the searching speed of resources is slower, and the other that the detention of routing is higher. This paper in view of these shortcomings, combination with modification, then put forward the new Chord structure that super nodes and common nodes coexist, super nodes management general nodes. The new structure using Zipf-law determines the proportion of super nodes and ordinary nodes. The last, the new structure is simulated by simulation software, and the improved Chord protocol make better the previous shortcoming through the new structure compares with the Chord protocol

Efficient Content Location Using Semantic Small World in Peer-to-Peer Networks

        Locating content in unstructured peer-to-peer networks is a challenging problem. This paper presents a novel semantic small world resource search mechanism to address the problem. By using vector space model to compute the semantic relevance and applying small world properties such as low average hop distance and high clustering coefficient to construct a cluster overlay. In semantic small world system, the search mechanism is divided into two parts, searching at cluster and outside cluster through inner link and short link, so that it can achieve the incremental research. It significantly reduces the average path length and query cost. Meanwhile, the simulation results show that semantic small world scheme outperforms K-random walks and flooding scheme than higher query hit rate and lower query latency

Deep learning assisted jet tomography for the study of Mach cones in QGP

Mach cones are expected to form in the expanding quark-gluon plasma (QGP) when energetic quarks and gluons (called jets) traverse the hot medium at a velocity faster than the speed of sound in high-energy heavy-ion collisions. The shape of the Mach cone and the associated diffusion wake are sensitive to the initial jet production location and the jet propagation direction relative to the radial flow because of the distortion by the collective expansion of the QGP and large density gradient. The shape of jet-induced Mach cones and their distortions in heavy-ion collisions provide a unique and direct probe of the dynamical evolution and the equation of state of QGP. However, it is difficult to identify the Mach cone and the diffusion wake in current experimental measurements of final hadron distributions because they are averaged over all possible initial jet production locations and propagation directions. To overcome this difficulty, we develop a deep learning assisted jet tomography which uses the full information of the final hadrons from jets to localize the initial jet production positions. This method can help to constrain the initial regions of jet production in heavy-ion collisions and enable a differential study of Mach-cones with different jet path length and orientation relative to the radial flow of the QGP in heavy-ion collisions