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In the current study, schisandrin B(SchB)-loaded F127 modified lipid-polymer hybrid nanoparticles(SchB-F-LPNs) were developed to improve the inhibition of breast cancer lung metastasis. Modified nanoprecipitation method was used to prepare SchB-F-LPNs. The nanoparticles were spherical in shape with shell-core structure by TEM observation. SchB-F-LPNs showed a mean particle size of(234.60±6.11) nm with zeta potential of(-5.88±0.49) mV. XRD results indicated that SchB existed in the nanoparticles in an amorphous state. The apparent permeability coefficient through porcine mucus of F-LPNs was 1.43-fold of that of LPNs as shown in the in vitro mucus penetration study. The pharmacokinetics study showed that the C_(max) of SchB was(369.06±146.94) μg·L~(-1),(1 121.34±91.65) μg·L~(-1) and(2 951.91±360.53) μg·L~(-1) respectively in SchB suspensions group, SchB-LPNs group and SchB-F-LPNs group after oral administration in rats. With SchB suspensions as the reference formulation, the relative bioavailability of SchB-F-LPNs was 568.60%. SchB-F-LPNs inhibited the morphological change during transforming growth factor-β1(TGF-β1)-induced epithelial-mesenchymal transition. In addition, SchB-F-LPNs significantly decreased the number of metastatic pulmonary nodules in 4 T1 tumor-bearing mice, suggesting that SchB-F-LPNs may inhibit the metastasis of breast cancer. These results reveal the promising potential of SchB-F-LPNs in treatment of breast cancer lung metastasis.

The optimal treatment (liver transplantation [LT] vs surgical resection [SR]) for early-stage hepatocellular carcinoma (HCC) remains controversial. A total of 209 SR patients and 129 LT patients were identified at our institution. After eliminating 27 patients with Child–Pugh C, the data from 209 SR patients and 102 LT patients were analyzed using a propensity score matching (PSM) model. Forty-six pairs were generated. A subgroup analysis was conducted based on the alpha-fetoprotein (AFP) level or platelet count (PLT). A survival analysis was performed using the Kaplan–Meier method. Gender, satellite lesions, and the treatment method were predictors of HCC recurrence. The Ishak score and treatment methods were associated with long-term survival after surgery. Before PSM, LT patients had a better prognosis than those treated by SR. Among HCC patients with childhood A/B cirrhosis, after PSM, SR achieved similar overall survival outcomes compared with LT. LT and SR resulted in comparable long-term survival for patients with or without thrombocytopenia. Patients with an AFP ≥ 400 ng/mL might achieve more survival benefits from LT. Our propensity score model provided evidence that, compared with transplantation, surgical resection could result in comparable long-term survival for resectable early-stage HCC patients, except for the AFP ≥ 400 ng/mL HCC subgroup. Surgical resection might not be a contraindication for early-stage HCC patients with thrombocytopenia due to their similar prognosis after transplantation.

The paper analysed the mobile node, home agent, and foreign agent of mobile IP network firstly, some key technique, such as mobile IP network basical principle, protocol work principle, agent discovery, registration, and IP packet transmission, were discussed. Then a network simulation model was designed, validating the characteristic of mobile IP network, and some advantages, which were brought by mobile network, were testified. Finally, the conclusion is gained: mobile IP network could realize the expectation of consumer that they can communicate with others anywhere.

QoS is essential for selecting an appropriate service from a set of services that match user’s functionality requirements. To enable this, a QoS Ontology for semantic service discovery, which provide the uniform model for QoS, is proposed in this article. With this ontology, the algorithms for QoS matchmaking and service ranking are presented. And an expanded service discovery framework is also presented.

This paper proposed an incremental textclustering algorithm based on semantic sequence. Using similarity relation of semantic sequences and calculating the cover of similarity semantic sequences set, the candidate cluster with minimum entropy overlap value was selected as a result cluster every time in this algorithm. The comparison of experimental results shows that the precision of the algorithm is higher than other algorithms under same conditions and this is obvious especially on long documents set.

Aiming at the characteristic of the dependency between the application components and the application server platform, a rejuvenation strategy with two different levels of rejuvenation granularities is put forward in this paper including the application component rejuvenation and the application server system rejuvenation. The availability and maintenance cost functions are obtained by means of establishing the application server aging model and the boundary condition of the optimal rejuvenation time is analyzed. Theory analysis indicates that the two-level rejuvenation strategy is superior to the traditional single level one. Finally, evaluation experiments are carried out and numerical result shows that compared with the traditional rejuvenation policy, the rejuvenation strategy proposed in this paper can further increase availability of the application server and reduce maintenance cost.

With the explosive growth of data available, there is an urgent need to develop continuous data mining which reduces manual interaction evidently. A novel model for data mining is proposed in evolving environment. First, some valid mining task schedules are generated, and then autonomous and local mining are executed periodically, finally, previous results are merged and refined. The framework based on the model creates a communication mechanism to incorporate domain knowledge into continuous process through ontology service. The local and merge mining are transparent to the end user and heterogeneous data source by ontology. Experiments suggest that the framework should be useful in guiding the continous mining process.

With the development of middleware technology, there are some new features to be adopted on demand in middleware platform based on container component. Aiming at the adaptation of middleware platform, from the nature of component container, this paper begins with behaviors features of EJB (Enterprise Java Bean) container, extracts general behaviors protocol of container, and defines its formal behaviors specification. In the end, the interactive relationship of components is described by WRIGHT language, and the configuration of whole system is shown. The method proposed in this paper mines the hidden features of framework of component container, and applies to refactor middleware platform in reflection and aspect-oriented programming technology.

Requests distribution is an key technology for Web cluster server. This paper presents a throughput-driven scheduling algorithm (TDSA). The algorithm adopts the throughput of cluster back-ends to evaluate their load and employs the neural network model to predict the future load so that the scheduling system features a self-learning capability and good adaptability to the change of load. Moreover, it separates static requests from dynamic requests to make full use of the CPU resources and takes the locality of requests into account to improve the cache hit ratio. Experimental results from the testing tool of WebBenchTM show better performance for Web cluster server with TDSA than that with traditional scheduling algorithms.