1,511 research outputs found

    Lactobacillus rhamnosus confers protection against colorectal cancer in rats

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    Purpose: To investigate the protective effect and mechanism of action of Lactobacillus rhamnosus against colorectal cancer (CRC). Methods: A total of 40 healthy female Sprague Dawley rats weighing 100 – 140 g (mean weight = 120 ± 20 g) were used for this study. The rats were randomly assigned to four groups of 10 rats each: normal control group, L. rhamnosus group; 1, 2-dimethylhydrazine (DMH) group and treatment group. Rats in L. rhamnosus group were inoculated with L. rhamnosus (1 x 108 CFU/mL) orally for 20 weeks, while rats in DMH group received 35 mg DMH/kg /week intraperitoneally for 10 weeks for induction of CRC. Treatment group rats received 35 mg DMH/kg bwt intraperitoneally for 10 weeks for induction of CRC, and were treated with L. rhamnosus (1 x 108 CFU/mL) orally for 20 weeks. After 20 weeks, the rats were euthanized using ether anesthesia. Expressions of inflammatory, angiogenesis and proapoptotic genes were determined using Western blotting and real-time quantitative polymerase chain reaction (qRT-PCR). Results: Treatment with L. rhamnosus significantly reduced the incidence of CRC in the rats (p < 0.05). The incidence of multiple tumors in the treatment group was also significantly reduced, when compared to DMH group (p < 0.05). The protein expressions of inducible nitric oxide synthase (iNOS), tumor necrosis factor α (TNF-α), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-kB), cyclooxygenase-2 (COX-2), bcl-2 and vascular endothelial growth factor α (VEGF-α) were significantly upregulated in DMH group, when compared with normal control group (p < 0.05). However, treatment with L. rhamnosus significantly down-regulated the expressions of these proteins (p < 0.05). DMH treatment also significantly upregulated the expressions of iNOS, TNF-α, VEGF-α, NF-kB, ÎČ-catenin and bax genes (p < 0.05). However, L. rhamnosus significantly reversed the effects of DMH on the expression levels of these genes (p < 0.05). Conclusion: These results show that L. rhamnosus prevents CRC via suppression of expressions of inflammatory and angiogenesis genes, and upregulation of apoptotic gene expression

    Multiple Model Rao-Blackwellized Particle Filter for Manoeuvring Target Tracking

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    Particle filters can become quite inefficient when applied to a high-dimensional state space since a prohibitively large number of samples may be required to approximate the underlying density functions with desired accuracy. In this paper, a novel multiple model Rao-Blackwellized particle filter (MMRBPF)-based algorithm has been proposed for manoeuvring target tracking in a cluttered environment. The advantage of the proposed approach is that the Rao-Blackwellization allows the algorithm to be partitioned into target tracking and model selection sub-problems, where the target tracking can be solved by the probabilistic data association filter, and the model selection by sequential importance sampling. The analytical relationship between target state and model is exploited to improve the efficiency and accuracy of the proposed algorithm. Moreover, to reduce the particle-degeneracy problem, the resampling approach is selectively carried out. Finally, experiment results, show that the proposed algorithm, has advantages over the conventional IMM-PDAF algorithm in terms of robust and  efficiency.Defence Science Journal, 2009, 59(3), pp.197-204, DOI:http://dx.doi.org/10.14429/dsj.59.151

    Goal-Driven Process Navigation for Individualized Learning Activities in Ubiquitous Networking and IoT Environments

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    Abstract: In the study, we propose an integrated adaptive framework to support and facilitate individualized learning through sharing the successful process of learning activities based on similar learning patterns in the ubiquitous learning environments empowered by Internet of Things (IoT). This framework is based on a dynamic Bayesian network that gradually adapts to a target student's needs and information access behaviours. By analysing the log data of learning activities and extracting students' learning patterns, our analysis results show that most of students often use their preferred learning patterns in their learning activities, and the learning achievement is affected by the learning process. Based on these findings, we try to optimise the process of learning activities using the extracted learning patterns, infer the learning goal of target students, and provide a goal-driven navigation of individualized learning process according to the similarity of the extracted learning patterns

    Organizational factors influencing for the success of ERP implementation

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    Enterprise Resource Planning (ERP) systems link together entire organization's operations. The success of ERP implementation depends not only on the technology but also on many organizational factors. This study identifies the organizational factors influencing the success of ERP system. The study found that the success of ERP implementation depends on several organizational elements. According to research findings, these can be categorized into three main elements: Alignment of ERP with the business process, Transferring ERP know-how to end users and Promoting ERP acceptance in the user organizatio

    Microfluidic chip-based valveless flow injection analysis system with gravity-driven flows

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    In this work, a microfluidic chip-based valveless flow injection analysis (FIA) system with gravity-driven flows and liquid-core waveguide (LCW) spectrometric detection was developed. Automated sample injection in the 0.3-6.4 nL range under gated injection mode was achieved by controlling the vertical position of the waste reservoir fixed on a moving platform and the residence time of the reservoir in each position, without the requirement of microvalves or electrokinetic manipulation. An integrated LCW spectrometric detection system was built on the chip by coupling a 20 mm-long Teflon AF 2400 capillary with the microchannel to function as a LCW flow cell, using a green LED as light source and a photodiode as detector. The performance of the system was demonstrated in the determination o

    Effects of Sangu Decoction on Osteoclast Activity in a Rat Model of Breast Cancer Bone Metastasis

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    Bone metastasis (BM) is a major clinical problem for which current treatments lack full efficacy. The Traditional Chinese Medicine (TCM) Sangu Decoction (SGD) has been widely used to treat BM in China. However, no in vivo experiments to date have investigated the effects of TCM on osteoclast activity in BM. In this study, the protective effect and probable mechanism of SGD were evaluated. The model was established using the breast cancer MRMT-1 cells injected into the tibia of rat. SGD was administrated, compared with Zoledronic acid as a positive control. The development of the bone tumor and osteoclast activity was monitored by radiological analysis. TRAP stain was used to identify osteoclasts quantity and activity. TRAP-5b in serum or bone tumor and TRAP mRNA were also quantified. Radiological examination showed that SGD inhibited tumor proliferation and preserved the cortical and trabecular bone structure. In addition, a dramatic reduction of TRAP positive osteoclasts was observed and TRAP-5b levels in serum and bone tumor decreased significantly. It also reduced the mRNA expression of TRAP. The results indicated that SGD exerted potent antiosteoclast property that could be directly related to its TRAP inhibited activity. In addition it prevented bone tumor proliferation in BM model

    LSMR: An iterative algorithm for sparse least-squares problems

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    An iterative method LSMR is presented for solving linear systems Ax=bAx=b and least-squares problem \min \norm{Ax-b}_2, with AA being sparse or a fast linear operator. LSMR is based on the Golub-Kahan bidiagonalization process. It is analytically equivalent to the MINRES method applied to the normal equation A\T Ax = A\T b, so that the quantities \norm{A\T r_k} are monotonically decreasing (where rk=b−Axkr_k = b - Ax_k is the residual for the current iterate xkx_k). In practice we observe that \norm{r_k} also decreases monotonically. Compared to LSQR, for which only \norm{r_k} is monotonic, it is safer to terminate LSMR early. Improvements for the new iterative method in the presence of extra available memory are also explored.Comment: 21 page
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