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Search Results: 1 - 10 of 75450 matches for " James Hua Zhou "
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Hepatoprotective Activity of Yigan Mingmu Oral Liquid against Isoniazid/Rifampicin-Induced Liver Injuries in Rats  [PDF]
Yuxin Chen, Qigui Mo, Baibo Xie, Bingxin Ma, Xinyu Zang, Gao Zhou, Linyou Cheng, James Hua Zhou, Youwei Wang
Chinese Medicine (CM) , 2018, DOI: 10.4236/cm.2018.94010

Background: To explore the hepatoprotective effect of Yigan mingmu oral liquid (YGMM) on isoniazid-rifampicin induced liver injury in rats. Methods: Total 38 SD rats were randomly divided into 6 groups including control group, model group, silymarin positive control group, and three YGMM treatment groups. Model group was administered intragastrically with INH (100 mg/kg) and RIF (100 mg/kg) for 14 days. Silymarin group and YGMM treatment groups were administered intragastrically with silymarin (100 mg/kg) and different doses of YGMM (1, 2.5, 5 mg/kg) 2 hours before INH and RIF administration from day 4 to day 14.Results: Rats were sacrificed 16 hours after the last day treatment to determine the activities of serum alanine transaminase (ALT), aspartate transaminase (AST) and alkaline phosphatase (ALP), as well as total bilirubin (TB) content. Oxidative stress was evaluated by measuring total superoxide dismutase (T-SOD) and malondialdehyde (MDA) levels. Histopathological changes in liver tissues were observed under an optical microscope by using hematoxylin and eosin staining. The mice?in model groups showed significantly (p < 0.05) increased levels in AST, ALT, ALP, TB and MDA compared to their control groups; and showed significantly (p < 0.05) decreased level in T-SOD. These changes were significantly (p < 0.05) reversed by the YGMM treatments in a dose-dependent manner. Hepatic pathological changes were attenuated or even reversed by silymarin or YGMM treatments. Conclusions: YGMM has a good hepatoprotective activity on isoniazid-rifampicin induced liver

Convex and Scalable Weakly Labeled SVMs
Yu-Feng Li,Ivor W. Tsang,James T. Kwok,Zhi-Hua Zhou
Computer Science , 2013,
Abstract: In this paper, we study the problem of learning from weakly labeled data, where labels of the training examples are incomplete. This includes, for example, (i) semi-supervised learning where labels are partially known; (ii) multi-instance learning where labels are implicitly known; and (iii) clustering where labels are completely unknown. Unlike supervised learning, learning with weak labels involves a difficult Mixed-Integer Programming (MIP) problem. Therefore, it can suffer from poor scalability and may also get stuck in local minimum. In this paper, we focus on SVMs and propose the WellSVM via a novel label generation strategy. This leads to a convex relaxation of the original MIP, which is at least as tight as existing convex Semi-Definite Programming (SDP) relaxations. Moreover, the WellSVM can be solved via a sequence of SVM subproblems that are much more scalable than previous convex SDP relaxations. Experiments on three weakly labeled learning tasks, namely, (i) semi-supervised learning; (ii) multi-instance learning for locating regions of interest in content-based information retrieval; and (iii) clustering, clearly demonstrate improved performance, and WellSVM is also readily applicable on large data sets.
Pyrvinium Targets the Unfolded Protein Response to Hypoglycemia and Its Anti-Tumor Activity Is Enhanced by Combination Therapy
De-Hua Yu, James Macdonald, Guohong Liu, Amy S. Lee, Mimi Ly, Timothy Davis, Ning Ke, Demin Zhou, Flossie Wong-Staal, Qi-Xiang Li
PLOS ONE , 2008, DOI: 10.1371/journal.pone.0003951
Abstract: We identified pyrvinium pamoate, an old anthelminthic medicine, which preferentially inhibits anchorage-independent growth of cancer cells over anchorage-dependent growth (~10 fold). It was also reported by others to have anti-tumor activity in vivo and selective toxicity against cancer cells under glucose starvation in vitro, but with unknown mechanism. Here, we provide evidence that pyrvinium suppresses the transcriptional activation of GRP78 and GRP94 induced by glucose deprivation or 2-deoxyglucose (2DG, a glycolysis inhibitor), but not by tunicamycin or A23187. Other UPR pathways induced by glucose starvation, e.g. XBP-1, ATF4, were also found suppressed by pyrvinium. Constitutive expression of GRP78 via transgene partially protected cells from pyrvinium induced cell death under glucose starvation, suggesting that suppression of the UPR is involved in pyrvinium mediated cytotoxicity under glucose starvation. Xenograft experiments showed rather marginal overall anti-tumor activity for pyrvinium as a monotherapy. However, the combination of pyrvinium and Doxorubicin demonstrated significantly enhanced efficacy in vivo, supporting a mechanistic treatment concept based on tumor hypoglycemia and UPR.
Combining Gene-Phenotype Association Matrix with KEGG Pathways to Mine Gene Modules Using Data Set in GAW17  [PDF]
Hua Lin, Yang Zheng, Ping Zhou
Engineering (ENG) , 2013, DOI: 10.4236/eng.2013.510B067

Currently, genome-wide association studies have been proved to be a powerful approach to identify risk loci. However, the molecular regulatory mechanisms of complex diseases are still not clearly understood. It is therefore important to consider the interplay between genetic factors and biological networks in elucidating the mechanisms of complex disease pathogenesis. In this paper, we first conducted a genome-wide association analysis by using the SNP genotype data and phenotype data provided by Genetic Analysis Workshop 17, in order to filter significant SNPs associated with the diseases. Second, we conducted a bioinformatics analysis of gene-phenotype association matrix to identify gene modules (biclusters). Third, we performed a KEGG enrichment test of genes involved in biclusters to find evidence to support their functional consensus. This method can be used for better understanding complex diseases.

Generating large non-singular matrices over an arbitrary field with blocks of full rank
James Xiao,Yongxin Zhou
Mathematics , 2002,
Abstract: This note describes a technique for generating large non-singular matrices with blocks of full rank. Our motivation to construct such matrices arises in the white-box implementation of cryptographic algorithms with S-boxes.
Machine Learning in China
Zhi-Hua Zhou
Asian Journal of Information Technology , 2012,
Abstract: NA
Positive solutions of four-point boundary-value problems for higher-order with $p$-Laplacian operator
Yunming Zhou,Hua Su
Electronic Journal of Differential Equations , 2007,
Abstract: In this paper, we study the existence of positive solutions for nonlinear four-point singular boundary-value problems for higher-order equation with the $p$-Laplacian operator. Using the fixed-point index theory, we find conditions for the existence of one solution, and of multiple solutions.
Predicting Protein-Protein Interaction by the Mirrortree Method: Possibilities and Limitations
Hua Zhou, Eric Jakobsson
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0081100
Abstract: Molecular co-evolution analysis as a sequence-only based method has been used to predict protein-protein interactions. In co-evolution analysis, Pearson's correlation within the mirrortree method is a well-known way of quantifying the correlation between protein pairs. Here we studied the mirrortree method on both known interacting protein pairs and sets of presumed non-interacting protein pairs, to evaluate the utility of this correlation analysis method for predicting protein-protein interactions within eukaryotes. We varied metrics for computing evolutionary distance and evolutionary span of the species analyzed. We found the differences between co-evolutionary correlation scores of the interacting and non-interacting proteins, normalized for evolutionary span, to be significantly predictive for proteins conserved over a wide range of eukaryotic clades (from mammals to fungi). On the other hand, for narrower ranges of evolutionary span, the predictive power was much weaker.
Rates of convergence of some multivariate Markov chains with polynomial eigenfunctions
Kshitij Khare,Hua Zhou
Mathematics , 2009, DOI: 10.1214/08-AAP562
Abstract: We provide a sharp nonasymptotic analysis of the rates of convergence for some standard multivariate Markov chains using spectral techniques. All chains under consideration have multivariate orthogonal polynomial as eigenfunctions. Our examples include the Moran model in population genetics and its variants in community ecology, the Dirichlet-multinomial Gibbs sampler, a class of generalized Bernoulli--Laplace processes, a generalized Ehrenfest urn model and the multivariate normal autoregressive process.
MM Algorithms for Geometric and Signomial Programming
Kenneth Lange,Hua Zhou
Mathematics , 2010, DOI: 10.1007/s10107-012-0612-1
Abstract: This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-arithmetic mean inequality and a supporting hyperplane inequality to create a surrogate function with parameters separated. Thus, unconstrained signomial programming reduces to a sequence of one-dimensional minimization problems. Simple examples demonstrate that the MM algorithm derived can converge to a boundary point or to one point of a continuum of minimum points. Conditions under which the minimum point is unique or occurs in the interior of parameter space are proved for geometric programming. Convergence to an interior point occurs at a linear rate. Finally, the MM framework easily accommodates equality and inequality constraints of signomial type. For the most important special case, constrained quadratic programming, the MM algorithm involves very simple updates.
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